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Implementation of microsurgery simulation in an ophthalmology clerkship in Germany: a prospective, exploratory study | 1582a110-09be-4a57-9fdd-17098fdacbf4 | 9351152 | Ophthalmology[mh] | Microscopic surgery is becoming more prevalent across a wide variety of medical specialties. The finessed technique required to successfully perform microscopic and often minimally invasive surgeries is a learned skill, but some individuals are better suited to the task than others. During their medical education, it is important for students be exposed to a variety of medical specialties so that they are able to choose a residency that suits both their interests and abilities. Practical experiences such as clinical rotations and simulated patient interactions can help to guide students in their decision making. The Eyesi Surgical simulator from Haag-Streit Simulation is a virtual reality simulation tool that enables trainees to practice microscopic intraocular surgery in a realistic simulated environment. The curriculum included with the device begins with basic skills practice and progressively advances users through anterior or posterior segment surgical tasks as skills and comfort increase. Eyesi Surgical allows individuals to improve their surgical skills and confidence without the risk of injuring a real patient. Eyesi utilizes a binocular operating microscope, surgical instruments, a patient with mechanical eye, and foot pedals for operating equipment (microscope, phaco, vitrectomy machine, and laser) to create the simulated surgical environment (Fig. ). Trainees begin with abstract Basic Navigation training and progress through different levels on the simulator, ending with more complex clinical skill modules. Our team has assisted in the development of simulators in ophthalmology, including diagnostic simulators for ophthalmoscopic and slit lamp examinations (Eyesi Direct, Indirect, Slit Lamp) and surgical simulators for cataract and vitreoretinal surgery (Eyesi Surgical). In recent publications, we assessed the introduction of the Eyesi Direct and Indirect ophthalmoscopy virtual reality simulators in the medical school curriculum . Virtual reality training of direct and indirect ophthalmoscopy is important from a teaching and learning standpoint. Even if an institution has enough real ophthalmoscope devices for all pupils, the option to examine each other assumes that all students are willing to have at least one pupil dilated. These peer examinations are generally performed on healthy eyes, which does not allow students to examine typical pathologies routinely. The Eyesi Surgical simulator is a useful tool for ophthalmology residents and surgeons, and is currently utilized as a training device for surgeons and residents who are systematically learning cataract and vitreoretinal surgery. Training on the device prior to beginning live intraocular surgery is essential and has been proven to reduce intraoperative complication rates . The validity of both vitreoretinal and cataract modules on Eyesi Surgical has been analyzed and simulator metrics confirmed . Novice surgeons also show improvement in their intraoperative skills after training with Eyesi Surgical . Basic abstract skill levels on the Eyesi Surgical platform, such as Navigation Training and Anti-Tremor Training, are not only valuable for ophthalmic surgery training. These skills can be transferred to a variety of microsurgical fields. The precision movements required for all types microsurgery can be practiced and repeated in the controlled, simulated environment. The ability to practice these types of transferrable skills gives medical trainees insight into microsurgical fields of medicine and provides a preview of what a residency and future career in a microsurgical field might look like. To our knowledge, Eyesi Surgical has not been widely implemented in medical school curriculums. Feedback received after briefly introducing the simulator to other cohorts of students showed that simulator training was valuable hands-on experience. The students appreciated the opportunity to try out devices which allowed them to determine whether surgical interventions – mostly controlled on a microscope – are an option for them in their future career. The combination of feedback from the instructor as well as the simulator helped to provide students with real-time feedback about what subspecialties might be appropriate options for them to consider pursuing after medical school. Based on this feedback, we chose to implement simulator training in a more structured way and adapted the training to be more generalized and applicable to student needs at their current learning stage. The purpose of this study was to assess the inclusion of microsurgical simulation training in the medical school ophthalmology clerkship curriculum and determine the student response by means of subjective feedback from participating students.
Study design and investigation methods This prospective, monocentric, exploratory study was approved by the ethics committee of the medical department of the Goethe University Frankfurt (resolution number E 205/19, transaction number 19–327) and was conducted at the Ophthalmology Department of the Goethe University Hospital Frankfurt. Participation in the study was voluntary. A total of 115 medical students in their 10th semester who had already attended ophthalmology lectures and were beginning their ophthalmology clerkship were included. Declarations of consent were obtained from all study participants before inclusion in the study. Students were given the opportunity to attend two sessions with the Eyesi Surgical simulator (software version 3.4), on the first and last day of their ophthalmology clerkship. On the first day, students received an introductory lecture about the simulator technology and were given a short demonstration of how to work with it. This introduction was followed by a practical simulator training. Students began with a basic skills targeting task (level 1 of the Eyesi module ‘Navigation Training’) and progressed through a maximum of 5 additional modules over the course of the two sessions. As the levels advanced, they became more specific to ophthalmologic surgical technique. After completion of simulator levels, students were able to review a summary of their performance and results on the simulator, an example of which is shown in Supplementary material . A survey tool consisting out of a ‘pre-simulation’ and ‘post-simulation’ – questionnaire (Supplementary Material ) was developed and distributed to students. The survey was developed based on the principles of survey tool development which were discussed in a Medical Didactics course taken by the corresponding author at the Goethe University Frankfurt. Students completed a ‘pre-simulation’ paper-based questionnaire prior to using Eyesi Surgical at the first simulator session. They completed a second paper-based ‘post-simulation’ questionnaire at the end of session 1 or session 2, depending on if they attended one or both sessions. The supervisor of the course assured that each student responded only once and all questionnaires were pseudonymized. Students were asked to assign point values for each question. Questionnaire responses for self-rating of ability were scored on a scale of 0–10. A self-rated score of 0 corresponded with little to no ability and higher scores represented a higher self-perceived ability. Questions relating to the relevance or importance of simulator training were scored on a scale from 1–7. A score of 1 represented ‘strongly disagree’ while a score of 7 represented ‘strongly agree’. Acquisition of results/points from Eyesi Surgical To evaluate the ability of the simulator to be used for general and abstract microsurgical skills, we chose to focus on the results from Navigation Training Level 1. The software module ‘Navigation Training’ consisted of abstract tasks that focused on microsurgical targeting skills in the human eye. Two instruments were available: a light probe and a straight needle. In level 1 of the module, 19 spherical objects were placed within the virtual eye. The spheres were approached with the tip of the needle. When the needle entered the sphere, the color of the sphere slowly changed from red to green. A bright green color signaled that the tip had been positioned for sufficient time inside the eye and the trainee could proceed to the next sphere. The trainee learned to move the tip of the instrument in a controlled and precise way. Rapid or uncontrolled approach with the needle causes the sphere to move away from the instrument and the trainee has to make a new approach attempt. The purpose of the module was to teach the trainee to carefully navigate the instrument to a specific location through a keyhole access within a closed environment under the microscope. For a video example of this task, see Supplementary Material . A total score between 0 and 100 was calculated at the end of the module. Positive points could be acquired in the section Target Achievement. Negative points were awarded in the sections Efficiency, Instrument Handling, Microscope Handling, and Tissue Treatment. It was possible to acquire more than 100 negative points but this was not reflected in the total score which was truncated at 0 points. For each evaluation criterion, value ranges and points were defined to transform the measured value into a score. This was linearly interpolated according to the following formula: [12pt]{minimal}
$$relative\;value=$$ r e l a t i v e v a l u e = v a l u e - s t a r t v a l u e e n d v a l u e - s t a r t v a l u e [12pt]{minimal}
$$points=start\;points+relative\;value(end\;points-start\;points)$$ p o i n t s = s t a r t p o i n t s + r e l a t i v e v a l u e * e n d p o i n t s - s t a r t p o i n t s Depending on the importance of a certain criterion, the range of achievable (positive or negative) points varied. Therefore, a single criterion could affect the total score only to a certain extent. For example, independently of how long a trainee operated out of focus, they got a maximum deduction of 20 points. In this case, it was still possible for them to achieve a total score of 80/100 points if every other task was performed perfectly. Simulator criteria for Navigational Training Level 1 were sorted into 5 categories: Target Achievement, Efficiency, Instrument Handling, Microscope Handling, and Tissue Treatment. Each point earned for each criterion contributed equally to the total score (i.e. it was not weighted by category). Scoring type and range of points for each task, in addition to an example scored task, are listed in Table . Statistics Data was recorded using the Eyesi Surgical platform and evaluated in Excel and in IBM SPSS Statistics v.28. A Spearman rank-order correlation coefficient was used to assess the relationship between simulator performance and self-rating of microsurgical skills. A Wilcoxon-matched-pairs test was used to evaluate the pre and post simulation training self-rating of microsurgical skills. A Kruskal–Wallis-Test was used to determine the relationship between residency specialty interest and simulator performance.
This prospective, monocentric, exploratory study was approved by the ethics committee of the medical department of the Goethe University Frankfurt (resolution number E 205/19, transaction number 19–327) and was conducted at the Ophthalmology Department of the Goethe University Hospital Frankfurt. Participation in the study was voluntary. A total of 115 medical students in their 10th semester who had already attended ophthalmology lectures and were beginning their ophthalmology clerkship were included. Declarations of consent were obtained from all study participants before inclusion in the study. Students were given the opportunity to attend two sessions with the Eyesi Surgical simulator (software version 3.4), on the first and last day of their ophthalmology clerkship. On the first day, students received an introductory lecture about the simulator technology and were given a short demonstration of how to work with it. This introduction was followed by a practical simulator training. Students began with a basic skills targeting task (level 1 of the Eyesi module ‘Navigation Training’) and progressed through a maximum of 5 additional modules over the course of the two sessions. As the levels advanced, they became more specific to ophthalmologic surgical technique. After completion of simulator levels, students were able to review a summary of their performance and results on the simulator, an example of which is shown in Supplementary material . A survey tool consisting out of a ‘pre-simulation’ and ‘post-simulation’ – questionnaire (Supplementary Material ) was developed and distributed to students. The survey was developed based on the principles of survey tool development which were discussed in a Medical Didactics course taken by the corresponding author at the Goethe University Frankfurt. Students completed a ‘pre-simulation’ paper-based questionnaire prior to using Eyesi Surgical at the first simulator session. They completed a second paper-based ‘post-simulation’ questionnaire at the end of session 1 or session 2, depending on if they attended one or both sessions. The supervisor of the course assured that each student responded only once and all questionnaires were pseudonymized. Students were asked to assign point values for each question. Questionnaire responses for self-rating of ability were scored on a scale of 0–10. A self-rated score of 0 corresponded with little to no ability and higher scores represented a higher self-perceived ability. Questions relating to the relevance or importance of simulator training were scored on a scale from 1–7. A score of 1 represented ‘strongly disagree’ while a score of 7 represented ‘strongly agree’.
To evaluate the ability of the simulator to be used for general and abstract microsurgical skills, we chose to focus on the results from Navigation Training Level 1. The software module ‘Navigation Training’ consisted of abstract tasks that focused on microsurgical targeting skills in the human eye. Two instruments were available: a light probe and a straight needle. In level 1 of the module, 19 spherical objects were placed within the virtual eye. The spheres were approached with the tip of the needle. When the needle entered the sphere, the color of the sphere slowly changed from red to green. A bright green color signaled that the tip had been positioned for sufficient time inside the eye and the trainee could proceed to the next sphere. The trainee learned to move the tip of the instrument in a controlled and precise way. Rapid or uncontrolled approach with the needle causes the sphere to move away from the instrument and the trainee has to make a new approach attempt. The purpose of the module was to teach the trainee to carefully navigate the instrument to a specific location through a keyhole access within a closed environment under the microscope. For a video example of this task, see Supplementary Material . A total score between 0 and 100 was calculated at the end of the module. Positive points could be acquired in the section Target Achievement. Negative points were awarded in the sections Efficiency, Instrument Handling, Microscope Handling, and Tissue Treatment. It was possible to acquire more than 100 negative points but this was not reflected in the total score which was truncated at 0 points. For each evaluation criterion, value ranges and points were defined to transform the measured value into a score. This was linearly interpolated according to the following formula: [12pt]{minimal}
$$relative\;value=$$ r e l a t i v e v a l u e = v a l u e - s t a r t v a l u e e n d v a l u e - s t a r t v a l u e [12pt]{minimal}
$$points=start\;points+relative\;value(end\;points-start\;points)$$ p o i n t s = s t a r t p o i n t s + r e l a t i v e v a l u e * e n d p o i n t s - s t a r t p o i n t s Depending on the importance of a certain criterion, the range of achievable (positive or negative) points varied. Therefore, a single criterion could affect the total score only to a certain extent. For example, independently of how long a trainee operated out of focus, they got a maximum deduction of 20 points. In this case, it was still possible for them to achieve a total score of 80/100 points if every other task was performed perfectly. Simulator criteria for Navigational Training Level 1 were sorted into 5 categories: Target Achievement, Efficiency, Instrument Handling, Microscope Handling, and Tissue Treatment. Each point earned for each criterion contributed equally to the total score (i.e. it was not weighted by category). Scoring type and range of points for each task, in addition to an example scored task, are listed in Table .
Data was recorded using the Eyesi Surgical platform and evaluated in Excel and in IBM SPSS Statistics v.28. A Spearman rank-order correlation coefficient was used to assess the relationship between simulator performance and self-rating of microsurgical skills. A Wilcoxon-matched-pairs test was used to evaluate the pre and post simulation training self-rating of microsurgical skills. A Kruskal–Wallis-Test was used to determine the relationship between residency specialty interest and simulator performance.
Statistical evaluation A total of 79 students could be evaluated based on questionnaire responses and simulator performance. 115 students began training with session 1 but 36 out of 115 did not complete both questionnaires and therefore were deemed lost to follow-up. Of the 79 students that completed both questionnaires and simulator training, 62 attended both sessions and 17 attended only one session. Some students were unable to attend both sessions due to scheduling conflicts with other curriculum requirements. Analysis of individual log values, Navigation Training Level 1 The average scores of individual evaluation criteria for Navigation Level 1 is displayed in Table . The mean Total Score was 25.7 (± 17.5) out of a possible 100 points. Target Achievement with Completed Objects was performed on average with relatively few mistakes. Tissue Treatment criteria were also completed with a low average point deduction. In contrast, activities in the Instrument Handling section resulted in a higher number of mistakes and point reductions. “Odometer” is an activity that quantifies instrument movement within the eye. Points are deducted from 0 for unnecessary movement. All students performed extensive instrument movements and therefore reached the saturation value of 20 negative points. Evaluation of questionnaires After evaluating the pre and post simulation questionnaires, it was found that the 73.4% of students self-rated their microsurgical skills higher after completing training with the simulator, when compared to their pre-simulation rating ( p < 0.001) (Fig. ). Mean self-rated score on the pre-simulation score was 3.3 (± 2.3) and mean self-rated score on the post-simulation questionnaire was 5.0 (± 2.4) (possible scores ranged from 0–10). A trend was found ( p = 0.08) in the correlation between self-rated microsurgical ability and Navigation Level 1 total score on the Eyesi Surgical. Students reported on the pre-simulation questionnaire which field they hoped to pursue during residency. Their answers were sorted into 3 categories, surgical specialty, non-surgical specialty, and undecided, based on if the specialty consisted of any surgical training during residency. Surgical specialties included general surgery, ophthalmology, vascular surgery, obstetrics and gynecology, urology, plastic surgery, oral and maxillofacial surgery, neurosurgery, orthopedics, pediatric surgery, trauma surgery, otolaryngology and urology. Non-surgical specialties included general medicine, internal medicine, anesthesiology, pediatrics, psychiatry, hematology, oncology, cardiology, neurology, radiology, forensic medicine, and pathology. 38% of the 10 th semester medical students were interested in a surgical specialty, 43% in a non-surgical specialty and 19% were still undecided. There was no relationship found between students’ Eyesi Surgical performance scores and their pre simulator training specialty interests ( p = 0.8). 92.4% of students reported that training with the Eyesi Surgical was a useful component of an ophthalmology clerkship during medical school, Fig. . 15.2% of students also commented on the questionnaire that they wished that there was more simulator training in the clerkship than was offered.
A total of 79 students could be evaluated based on questionnaire responses and simulator performance. 115 students began training with session 1 but 36 out of 115 did not complete both questionnaires and therefore were deemed lost to follow-up. Of the 79 students that completed both questionnaires and simulator training, 62 attended both sessions and 17 attended only one session. Some students were unable to attend both sessions due to scheduling conflicts with other curriculum requirements.
The average scores of individual evaluation criteria for Navigation Level 1 is displayed in Table . The mean Total Score was 25.7 (± 17.5) out of a possible 100 points. Target Achievement with Completed Objects was performed on average with relatively few mistakes. Tissue Treatment criteria were also completed with a low average point deduction. In contrast, activities in the Instrument Handling section resulted in a higher number of mistakes and point reductions. “Odometer” is an activity that quantifies instrument movement within the eye. Points are deducted from 0 for unnecessary movement. All students performed extensive instrument movements and therefore reached the saturation value of 20 negative points.
After evaluating the pre and post simulation questionnaires, it was found that the 73.4% of students self-rated their microsurgical skills higher after completing training with the simulator, when compared to their pre-simulation rating ( p < 0.001) (Fig. ). Mean self-rated score on the pre-simulation score was 3.3 (± 2.3) and mean self-rated score on the post-simulation questionnaire was 5.0 (± 2.4) (possible scores ranged from 0–10). A trend was found ( p = 0.08) in the correlation between self-rated microsurgical ability and Navigation Level 1 total score on the Eyesi Surgical. Students reported on the pre-simulation questionnaire which field they hoped to pursue during residency. Their answers were sorted into 3 categories, surgical specialty, non-surgical specialty, and undecided, based on if the specialty consisted of any surgical training during residency. Surgical specialties included general surgery, ophthalmology, vascular surgery, obstetrics and gynecology, urology, plastic surgery, oral and maxillofacial surgery, neurosurgery, orthopedics, pediatric surgery, trauma surgery, otolaryngology and urology. Non-surgical specialties included general medicine, internal medicine, anesthesiology, pediatrics, psychiatry, hematology, oncology, cardiology, neurology, radiology, forensic medicine, and pathology. 38% of the 10 th semester medical students were interested in a surgical specialty, 43% in a non-surgical specialty and 19% were still undecided. There was no relationship found between students’ Eyesi Surgical performance scores and their pre simulator training specialty interests ( p = 0.8). 92.4% of students reported that training with the Eyesi Surgical was a useful component of an ophthalmology clerkship during medical school, Fig. . 15.2% of students also commented on the questionnaire that they wished that there was more simulator training in the clerkship than was offered.
This study explored the subjective and objective results of ophthalmological microsurgical training for medical students. The microsurgical skill modules available on the Eyesi Surgical simulator, specifically those that are more abstract in nature, are useful for all medical students, not just those pursuing ophthalmology training. With the Eyesi Simulator, students are able to practice the precise movements that are required for microsurgery and receive immediate feedback. Our results showed that students achieved better scores on tissue treatment tasks than on instrument handling tasks. Students seemed to struggle in particular with the ‘odometer’ and ‘instrument slipped out of sphere’ criteria. These criteria relate directly to basic skills that must be acquired through extensive practice for successful surgery under a microscope. These results are not surprising as precision skills such as instrument handling take time to develop and all students in this study were complete novices. Limitations to this study are the short training interval and a relatively high ( n = 36) loss to follow-up rate. Loss to follow-up was attributed to curriculum conflicts which resulted in some students not attending their second planned simulator training day. These students were required to complete projects for a previous clerkship during their ophthalmology clerkship, which unfortunately resulted in a lower attendance rate on day two of simulator training. Over recent years, there has been a decreased interest in pursuing general surgery residencies in many countries worldwide . Exposing students to surgical skills by means of a simulator such as Eyesi may be helpful in providing a window into a future surgical career and boost interest in surgical subspecialties. The majority of students in this study reported that the Eyesi Surgical simulator was a useful component of their ophthalmology clerkship. Students engagement, how to enhance it and how the result might have an effect onto the acceptance of a curriculum, the creation of innovative curricular changes and also the development of impactful extracurricular projects can be followed up in literature more frequently over the last 10 years. In Germany, students in their 10. th semester of medical school choose which elective specialty they would like to rotate through during their final year. Thus, giving students prior surgical experience with a simulator might help them to decide if they should consider a surgical specialty rotation. As the above results show, a number of students in this study were still undecided about which specialty they hoped to pursue after medical school. Considerations such as talent and enjoyment should not be minimized, and these are two factors that early introduction to basic skills with a simulator can help to clarify. Seo et al. and Yang et al. both reported increased medical student interest in surgical disciplines following a short surgical skills workshop The importance of self-reported confidence in abilities and skills should not be overlooked when considering choice of specialty. Our results showed that a majority of students were more confident in their microsurgical abilities after completing training on the simulator. Similar results were reported by Antiel et al., who developed an intensive pre-clinical surgical experience for medical students. This one-week course, which included a simulation component, resulted in increased confidence in a variety of surgical skills as evidenced by self-reported abilities on pre and post experience surveys . Kahu and Nelson have summarized the understanding of mechanisms of student success and the meaning of student retention for higher education institutions. First, an educational interface adequate for the interaction between students and institutions is required. Second, psychological constructs including self-efficacy, emotions, belonging and well-being are essential for mediating the interaction between both students and institutions. Third, a concept to understand why some students with lower completion rates are retained and do go on to successfully complete their studies and others do not. This could help to explain the lower second session attendance rates in this study, which was mentioned as a limitation, and resulted from a conflict between several clerkships during the medical school curriculum. The design and implementation of curricula and co-curricular initiatives with different subspecialties considerations for each other are essential for a global success of education in medicine. A meticulous debriefing with defined communication content (e.g. advocacy, inquiry, illustration, and confirmation) between debriefers and participants is mentioned by Berger-Estilita et al. to be positively related to learning outcomes. Others, like Peters et al. , give suggestions for enhancing student engagement by maximizing dialogue between students and faculty. Zdravkovic et al. stresses out that peer teaching, school governance and extracurricular activities lead to a high level of student engagement which also can affect innovative curricular changes and enable students to deliver highly impactful extracurricular projects. The number of studies about students engagement potentially facing a shift in the teaching paradigms using simulation has increased over the last 15 years: Okuda et al. summarized in 2009 that simulation had become increasingly prevalent in medical school and resident education and that simulation is proven to be effective in the teaching of basic science and clinical knowledge, procedural skills, teamwork and communication as well as in assessment at the undergraduate and graduate medical education levels. In educational scenarios let by a physical instructor, objective judgment and subjective feelings are united. The virtual trainer is completely free from subjective opinions, and provides clear objective feedback about student performance. As simulator software and technology continues to develop, this will become increasingly more optimized and fine-tuned to fit specific learning objectives. From our personal point of view, the stand-alone function has significant advantages, however the best training procedure includes an additional in-person instructor, who can provide hands-on assistance to the trainee at certain times during the training interval. This leads to the best results in satisfaction of the trainee as well as learning curve during the training process. McGue highlights the modern educational concept of simulation-based medical education. Essential experimental learning opportunities can be offered without risk to patients and simulation devices are differentiated into various categories: low-technology models, standardized “patients”, screen-based computer simulations, complex task trainers, high-fidelity patient simulators, and virtual reality systems. Lu, Cuff and Mansour summarize that because simulation is becoming an important tool in surgical education, faculty is being forced to modify their teaching of technical skill concepts. The authors recommend to concentrate teaching surgical skills ideally in a simulation center. Our personal experiences are that in such simulation centers which bring different medical subspecialties together in one place there are lots of advantages in regard to the infrastructure but we found also an imbalance between subspecialty representation: e.g. ophthalmology is considered to be a “small” subject with less need to be represented in these educational centres.
Inclusion of the Eyesi Surgical Simulator in the medical school curriculum has the potential to bring additional ‘hands-on’ experience to medical students during their clinical rotations. Students have expressed interest in this type of experience, whether it be directly with patients or in a simulated environment. Practice on the simulator allows students to gain a better understanding of microsurgical techniques and additionally boosts self-confidence. Exposing students to surgical techniques early in their medical career can help to reduce the barriers that prevent students from pursuing a career in a surgical specialty. Practical experience and specifically surgical simulator experience should be integrated into the medical school curriculum to help better prepare students and help them find the right discipline that suits both their skills and interests.
Additional file 1: Supplementary Material 1. Example of performance summary following completion of Navigation Training Level 1 on the Eyesi Surgical Simulato. Additional file 2: Supplementary Material 2. ‘pre-simulation’ and ‘post-simulation’ – questionnaire. Additional file 3: Supplementary Material 3. video demonstration of ‘Navigation Training Level 1’ on Eyesi Surgical. Additional file 4: Supplementary Material 4. Eyesi Surgical Navigation training data. Additional file 5: Supplementary Material 5. Eyesi Surgical Questionnaire datasets.
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Implementation of patient-reported outcomes for symptom management in oncology practice through the SIMPRO research consortium: a protocol for a pragmatic type II hybrid effectiveness-implementation multi-center cluster-randomized stepped wedge trial | d9cb523c-ec1b-472f-8214-b7a03c5ca0f7 | 9202326 | Internal Medicine[mh] | Note: the numbers in curly brackets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items (see https://www.equator-network.org/reporting-guidelines/spirit-2013-statement-defining-standard-protocol-items-for-clinical-trials/ ).
Background and rationale {6a} In the USA, nearly 1.9 million people will be diagnosed with cancer in 2022 . In recent years, improved therapies have resulted in decreased mortality, but cancer-related morbidity remains substantial [ – ]. Deficits in symptom management, including sparse patient-clinician communication between clinic visits, contribute to considerable morbidity for cancer patients. Poor symptom control decreases quality of life, increases emergency care needs [ – ], and deters patients from receiving effective therapy . Healthcare in the USA is predominantly structured to be reactive, not proactive, with missed opportunities to optimize symptom control and ineffective strategies to anticipate, prevent and monitor adverse symptoms before they escalate . Growth in internet access and proliferation of smartphones and tablets has created an opportunity to support improved cancer care delivery, particularly symptom control. In 2021, 93% of adults in the USA reported using the internet and 85% owned a smartphone . Even among the elderly and poor, web use is rising for many reasons including managing health needs . Mobile phones and web access create opportunities for patient-clinician communication to optimize symptom management beyond face-to-face encounters . Patient engagement has been called the “blockbuster” drug of the twenty-first century as motivated patients demonstrate improved well-being and health outcomes . Strong theoretical foundations from social cognitive theories of self-efficacy and the chronic care model support the importance of patient engagement [ – ] to minimize toxicities of cancer treatment. Patient-reported outcomes are a patient’s direct report of their health, quality of life, or functional status without interpretation from the clinical care team. Symptom tracking and management via electronic patient-reported outcomes (ePROs) is one promising mechanism by which Internet access may be harnessed to reduce symptom burden among cancer patients through the use of patient portals. In research settings, utilization of ePROs has been shown to decrease symptom burden , improve quality of life, reduce acute care needs , and extend survival . There are two primary mechanisms for these impacts. First, systematic collection of ePROs can support the recognition of problematic symptoms and may encourage self-management . Second, systematic reporting of symptoms can trigger clinical interventions to improve symptom management outside of regularly scheduled clinic visits. Enhanced communication facilitated by technology may make the health care system more responsive to patient needs . Although prior ePRO work is promising , major knowledge gaps persist regarding the optimal implementation of ePROs in routine oncologic care. First, the effectiveness of ePROs has primarily been studied in clinical trials at well-resourced academic cancer centers, leaving less known about their implementation in community settings . Second, existing ePRO platforms have not been integrated into the electronic health record (EHR), requiring patients and clinicians to access separate systems to view symptom reports, thereby introducing inefficiency and barriers to adoption . Third, ePRO systems have rarely integrated effective coaching strategies for enhanced symptom management. Lastly, optimal implementation strategies for integrating ePROs into the standard clinical workflow are unknown. To address these gaps and others identified by the Cancer Moonshot SM , the National Cancer Institute funded the Improving the Management of symPtoms during and following Cancer Treatment (IMPACT) Consortium . Its goals are to improve symptom control for cancer patients through systematic symptom reporting and guideline-based clinical management . IMPACT is made up of three research centers, including the S ymptom Management Im plementation of P atient- R eported Outcomes in O ncology (SIMPRO) Consortium. SIMPRO is led by a multi-disciplinary team of investigators from six US-based health systems (Table ) who are developing, testing, and implementing an EHR-integrated symptom management program in large and small, rural and metropolitan, academic and in community-based clinics for medical oncology and surgical patients. Objectives {7} The research goals of the SIMPRO Consortium are: Create and refine an ePRO-based symptom management system (eSyM) and integrate it into the EHR and routine clinical workflow Determine the effectiveness of eSyM on health outcomes. Specifically, evaluate the impact on: ◦ Healthcare utilization, measured by the use of emergency and acute care ◦ Cancer care delivery, including duration and
delay of medical treatments, and the need for
re-operation ◦ Patient-centered outcomes, including self-efficacy and symptom burden ◦ Patient satisfaction with care 3. Evaluate the facilitators and barriers to implementation of eSyM from the patient, clinician, and organizational perspectives using an implementation science framework A prior manuscript described the eSyM build and design process . The current manuscript outlines the design used to evaluate the effectiveness of eSyM. Detailed methods for describing facilitators and barriers to implementation will be highlighted in a future manuscript. Trial design {8} Overall, the SIMPRO project consists of four key activities (Fig. ). The first three activities focused on building the infrastructure needed to support participating sites, configuring the eSyM program, and pilot testing the intervention. The fourth activity — described in this manuscript — is the conduct of a pragmatic type II hybrid effectiveness-implementation stepped wedge cluster-randomized trial to evaluate the effectiveness of eSyM. The Western Institutional Review Board (WIRB) approved the protocol as a minimal risk research study on November 25, 2018 (protocol #20182593), with a Health Insurance Portability and Accountability Act (HIPAA) waiver. Each healthcare system (referred to as a site) is the unit of randomization. Within each site, two versions of eSyM are deployed — one for medical oncology patients and one for surgery patients. The randomization schema (Fig. ) was constructed to ensure that (a) each site launches the two versions of eSyM during different time periods, (b) three sites launch eSyM-medical oncology first and the other three launch eSyM-surgery first, and (c) sites with similar characteristics (i.e., geographic location and metropolitan/rural setting) deploy eSyM on different schedules. The stepped wedge design includes seven time periods. Consistent with the stepped wedge design , patients are involved in the trial in one of two ways: Eligible patients seen at a participating site before eSyM deployment, and therefore not exposed to the intervention, form a “control group” Eligible patients seen at a participating site after eSyM deployment form the “intervention group.” They are exposed to all aspects of the intervention, including eSyM questionnaires, reminders, symptom self-management tip sheets, and population management tools. Outcomes are collected from control and intervention patients in the following ways: For all patients, automated data extracts from the electronic medical record are used to ascertain demographics, treatments, healthcare service utilization, and outcomes. A subset of eligible patients is randomly selected to complete a one-time research questionnaire asking about their S elf-efficacy, A ttainment of information needs, S ymptom burden, and S atisfaction with care (SASS). Among intervention patients, the SASS questionnaire includes additional questions about eSyM program engagement and use. As a type II hybrid effectiveness-implementation study, facilitators and barriers to implementation are assessed throughout the project (this aspect of the project will be discussed in detail in a future manuscript).
In the USA, nearly 1.9 million people will be diagnosed with cancer in 2022 . In recent years, improved therapies have resulted in decreased mortality, but cancer-related morbidity remains substantial [ – ]. Deficits in symptom management, including sparse patient-clinician communication between clinic visits, contribute to considerable morbidity for cancer patients. Poor symptom control decreases quality of life, increases emergency care needs [ – ], and deters patients from receiving effective therapy . Healthcare in the USA is predominantly structured to be reactive, not proactive, with missed opportunities to optimize symptom control and ineffective strategies to anticipate, prevent and monitor adverse symptoms before they escalate . Growth in internet access and proliferation of smartphones and tablets has created an opportunity to support improved cancer care delivery, particularly symptom control. In 2021, 93% of adults in the USA reported using the internet and 85% owned a smartphone . Even among the elderly and poor, web use is rising for many reasons including managing health needs . Mobile phones and web access create opportunities for patient-clinician communication to optimize symptom management beyond face-to-face encounters . Patient engagement has been called the “blockbuster” drug of the twenty-first century as motivated patients demonstrate improved well-being and health outcomes . Strong theoretical foundations from social cognitive theories of self-efficacy and the chronic care model support the importance of patient engagement [ – ] to minimize toxicities of cancer treatment. Patient-reported outcomes are a patient’s direct report of their health, quality of life, or functional status without interpretation from the clinical care team. Symptom tracking and management via electronic patient-reported outcomes (ePROs) is one promising mechanism by which Internet access may be harnessed to reduce symptom burden among cancer patients through the use of patient portals. In research settings, utilization of ePROs has been shown to decrease symptom burden , improve quality of life, reduce acute care needs , and extend survival . There are two primary mechanisms for these impacts. First, systematic collection of ePROs can support the recognition of problematic symptoms and may encourage self-management . Second, systematic reporting of symptoms can trigger clinical interventions to improve symptom management outside of regularly scheduled clinic visits. Enhanced communication facilitated by technology may make the health care system more responsive to patient needs . Although prior ePRO work is promising , major knowledge gaps persist regarding the optimal implementation of ePROs in routine oncologic care. First, the effectiveness of ePROs has primarily been studied in clinical trials at well-resourced academic cancer centers, leaving less known about their implementation in community settings . Second, existing ePRO platforms have not been integrated into the electronic health record (EHR), requiring patients and clinicians to access separate systems to view symptom reports, thereby introducing inefficiency and barriers to adoption . Third, ePRO systems have rarely integrated effective coaching strategies for enhanced symptom management. Lastly, optimal implementation strategies for integrating ePROs into the standard clinical workflow are unknown. To address these gaps and others identified by the Cancer Moonshot SM , the National Cancer Institute funded the Improving the Management of symPtoms during and following Cancer Treatment (IMPACT) Consortium . Its goals are to improve symptom control for cancer patients through systematic symptom reporting and guideline-based clinical management . IMPACT is made up of three research centers, including the S ymptom Management Im plementation of P atient- R eported Outcomes in O ncology (SIMPRO) Consortium. SIMPRO is led by a multi-disciplinary team of investigators from six US-based health systems (Table ) who are developing, testing, and implementing an EHR-integrated symptom management program in large and small, rural and metropolitan, academic and in community-based clinics for medical oncology and surgical patients.
The research goals of the SIMPRO Consortium are: Create and refine an ePRO-based symptom management system (eSyM) and integrate it into the EHR and routine clinical workflow Determine the effectiveness of eSyM on health outcomes. Specifically, evaluate the impact on: ◦ Healthcare utilization, measured by the use of emergency and acute care ◦ Cancer care delivery, including duration and
delay of medical treatments, and the need for
re-operation ◦ Patient-centered outcomes, including self-efficacy and symptom burden ◦ Patient satisfaction with care 3. Evaluate the facilitators and barriers to implementation of eSyM from the patient, clinician, and organizational perspectives using an implementation science framework A prior manuscript described the eSyM build and design process . The current manuscript outlines the design used to evaluate the effectiveness of eSyM. Detailed methods for describing facilitators and barriers to implementation will be highlighted in a future manuscript.
Overall, the SIMPRO project consists of four key activities (Fig. ). The first three activities focused on building the infrastructure needed to support participating sites, configuring the eSyM program, and pilot testing the intervention. The fourth activity — described in this manuscript — is the conduct of a pragmatic type II hybrid effectiveness-implementation stepped wedge cluster-randomized trial to evaluate the effectiveness of eSyM. The Western Institutional Review Board (WIRB) approved the protocol as a minimal risk research study on November 25, 2018 (protocol #20182593), with a Health Insurance Portability and Accountability Act (HIPAA) waiver. Each healthcare system (referred to as a site) is the unit of randomization. Within each site, two versions of eSyM are deployed — one for medical oncology patients and one for surgery patients. The randomization schema (Fig. ) was constructed to ensure that (a) each site launches the two versions of eSyM during different time periods, (b) three sites launch eSyM-medical oncology first and the other three launch eSyM-surgery first, and (c) sites with similar characteristics (i.e., geographic location and metropolitan/rural setting) deploy eSyM on different schedules. The stepped wedge design includes seven time periods. Consistent with the stepped wedge design , patients are involved in the trial in one of two ways: Eligible patients seen at a participating site before eSyM deployment, and therefore not exposed to the intervention, form a “control group” Eligible patients seen at a participating site after eSyM deployment form the “intervention group.” They are exposed to all aspects of the intervention, including eSyM questionnaires, reminders, symptom self-management tip sheets, and population management tools. Outcomes are collected from control and intervention patients in the following ways: For all patients, automated data extracts from the electronic medical record are used to ascertain demographics, treatments, healthcare service utilization, and outcomes. A subset of eligible patients is randomly selected to complete a one-time research questionnaire asking about their S elf-efficacy, A ttainment of information needs, S ymptom burden, and S atisfaction with care (SASS). Among intervention patients, the SASS questionnaire includes additional questions about eSyM program engagement and use. As a type II hybrid effectiveness-implementation study, facilitators and barriers to implementation are assessed throughout the project (this aspect of the project will be discussed in detail in a future manuscript).
Study setting {9} eSyM is deployed through the SIMPRO Consortium at six US-based healthcare institutions: Baptist Memorial Health Care, Memphis, TN; Dana-Farber Cancer Institute, Boston, MA; Dartmouth Hitchcock Medical Center, Lebanon, NH; Lifespan Health System, Providence, RI; Maine Medical Center, Portland ME; and West Virginia University, Morgantown, WV. These health systems represent a diverse mix of academic/community, rural/metropolitan, North-eastern and Southern community-based cancer centers (Table ). Eligibility criteria {10} Eligible patients are at least 18 years old. Medical oncology patients must be scheduled to receive a new chemotherapy treatment plan in the next 30 days; have a relevant ICD-10 diagnosis code for a thoracic, gastrointestinal, or gynecologic malignancy; and have an encounter at a participating medical oncology site. Surgical patients must be scheduled for surgery commonly used to treat a thoracic, gastrointestinal, or gynecologic malignancy; have a surgery date in the next 30 days; and have an encounter at a participating surgery site. Patients undergoing surgery are considered eligible regardless of whether they have a cancer diagnosis at the time of surgery, as pathologic confirmation of cancer may not be available until several weeks after surgery. We exclude incarcerated individuals as a protected population; pregnant women and cognitively impaired adults are eligible because of the negligible risk of the intervention. Although sites could expand eSyM to populations beyond the above-listed, only the specified patient population is included in research analyses. A subset of eSyM-eligible patients is randomly selected to participate in the SASS sub-study and complete either a control or intervention SASS questionnaire (SASS-control or SASS-intervention, respectively). Selection of SASS questionnaire participants is stratified by cluster and period to ensure even spread. There are no additional eligibility or exclusion criteria for the SASS sub-study other than agreeing to complete a one-time English-language questionnaire. Who will take informed consent? {26a} Since eSyM is implemented and tested for use in routine clinical practice and was deemed standard-of-care and minimal risk, the IRB waived the individual informed consent requirement for both eSyM participation and medical records review. Additional consent provisions for collection and use of participant data and biological specimens {26b} Patients asked to complete a SASS questionnaire are informed of the sub-study’s details by research coordinators and receive a letter outlining the elements of informed consent. The requirement for formal documentation of written informed consent was waived by the IRB. Additionally, this trial does not involve collecting biological specimens for storage.
eSyM is deployed through the SIMPRO Consortium at six US-based healthcare institutions: Baptist Memorial Health Care, Memphis, TN; Dana-Farber Cancer Institute, Boston, MA; Dartmouth Hitchcock Medical Center, Lebanon, NH; Lifespan Health System, Providence, RI; Maine Medical Center, Portland ME; and West Virginia University, Morgantown, WV. These health systems represent a diverse mix of academic/community, rural/metropolitan, North-eastern and Southern community-based cancer centers (Table ).
Eligible patients are at least 18 years old. Medical oncology patients must be scheduled to receive a new chemotherapy treatment plan in the next 30 days; have a relevant ICD-10 diagnosis code for a thoracic, gastrointestinal, or gynecologic malignancy; and have an encounter at a participating medical oncology site. Surgical patients must be scheduled for surgery commonly used to treat a thoracic, gastrointestinal, or gynecologic malignancy; have a surgery date in the next 30 days; and have an encounter at a participating surgery site. Patients undergoing surgery are considered eligible regardless of whether they have a cancer diagnosis at the time of surgery, as pathologic confirmation of cancer may not be available until several weeks after surgery. We exclude incarcerated individuals as a protected population; pregnant women and cognitively impaired adults are eligible because of the negligible risk of the intervention. Although sites could expand eSyM to populations beyond the above-listed, only the specified patient population is included in research analyses. A subset of eSyM-eligible patients is randomly selected to participate in the SASS sub-study and complete either a control or intervention SASS questionnaire (SASS-control or SASS-intervention, respectively). Selection of SASS questionnaire participants is stratified by cluster and period to ensure even spread. There are no additional eligibility or exclusion criteria for the SASS sub-study other than agreeing to complete a one-time English-language questionnaire.
Since eSyM is implemented and tested for use in routine clinical practice and was deemed standard-of-care and minimal risk, the IRB waived the individual informed consent requirement for both eSyM participation and medical records review.
Patients asked to complete a SASS questionnaire are informed of the sub-study’s details by research coordinators and receive a letter outlining the elements of informed consent. The requirement for formal documentation of written informed consent was waived by the IRB. Additionally, this trial does not involve collecting biological specimens for storage.
Explanation for the choice of comparators {6b} We will compare patients who started chemotherapy or had surgery before eSyM deployment (i.e., control episodes) with patients who started chemotherapy or had surgery after eSyM deployment (i.e., intervention episodes). This pre-post design allows each site to provide its own control group and likely reduces the potential for confounding on cluster- and possibly individual-level characteristics. Intervention patients are encouraged, but not required, to use eSyM. Thus, the intervention group is defined by exposure to, not use of, eSyM. Patients who receive multiple chemotherapy treatments or surgeries can contribute multiple episodes to the analysis. For example, a patient who received surgery during the control period and chemotherapy during the intervention period would contribute an episode to the surgery control cohort and a separate episode to the chemotherapy intervention cohort. Intervention description {11a} The eSyM program includes the following core features: (1) EHR registries that automatically identify patients for eSyM activation, (2) patient portal questionnaires that assess symptoms at regular intervals for a defined period after chemotherapy or surgery (the questionnaires are based on the validated Patient Reported Outcome version of the Common Terminology Criteria for Adverse Events [PRO-CTCAE®] plus two pictogram-based questions assessing overall well-being and performance status on a Likert scale), (3) patient self-management symptom tip sheets, (4) patient-facing views of past symptom reports, (5) care-team in-basket alerts for reported severe symptoms, (6) clinician-facing symptom reports and charting tools, and (7) population management reports . Since teams caring for medical oncology and surgery patients may not overlap, and to accommodate differences in hospital system structures and priorities, eSyM was designed with the flexibility to be deployed for both medical oncology and surgery patients, exclusively or in combination. Deploying the medical oncology and surgery versions of eSyM at different time points helps account for co-existing trends that are unrelated to the intervention. The features of eSyM medical oncology and surgery are nearly identical. A patient can only be active on one version of eSyM at a time but can be active on different versions of eSyM sequentially. To use eSyM, patients must either have access to the patient portal (which requires having a smartphone or computer that has internet access) or be provided a tablet during clinic visits (available at two sites). Criteria for discontinuing or modifying allocated interventions {11b} eSyM automatically becomes available to eligible patients via the patient portal 1 day after either chemotherapy starts or hospital discharge after surgery. The program automatically discontinues after 180 days for medical oncology patients and after 60 days for surgical patients. Patients who do not wish to participate can either ignore questionnaire reminders or ask their care team to discontinue them. Strategies to improve adherence to interventions {11c} We use several implementation science strategies to support stakeholder (i.e., patient and clinician) engagement. Educational materials and outreach efforts foster patient use of the program, and training materials and outreach efforts increase care team engagement with the program. Sites routinely employ a coordinator to monitor eSyM patients. Coordinators approach patients to encourage eSyM engagement and assist with program setup, questionnaire submission, technical questions, and care team training. In addition to completing eSyM symptom questions via the patient portal, some sites enable symptom reporting via an internet tablet in clinic. For patients unable to complete questionnaires independently, proxy reporting by a family member or close contact is encouraged. Figure outlines specific implementation strategies recorded to date. Throughout the project, additional implementation strategies are being documented by the site project coordinators in a central database. Relevant concomitant care permitted or prohibited during the trial {11d} eSyM is deployed as a standard-of-care intervention. It neither requires nor precludes concomitant care during the trial. Provisions for post-trial care {30} The trial makes no provisions for post-trial care. After the trial, sites may choose to continue using eSyM with or without modifications, or they may discontinue its use. Outcomes {12} The primary outcome is the occurrence of an emergency department treat-and-release (EDTR) event within 30-days of chemotherapy start or surgical discharge (binary outcome). Secondary clinical outcomes for surgery patients include time to initiation of adjuvant chemotherapy, time to re-operation, time to re-admission, and overall survival. Secondary outcomes for medical oncology patients include time to first chemotherapy treatment, time to delay or dose modification, time to chemotherapy discontinuation, time to admission, and vital status. Patients are followed for 1 year after the treatment start date. Secondary outcomes focus on events through 90, 180 and 360 days. For the SASS sub-study, secondary patient-reported outcomes are evaluated approximately 30–60 days after the treatment initiation date. Participant timeline {13} eSyM becomes available to medical oncology patients the day after the first treatment for a new chemotherapy plan is completed (i.e., cycle 1 day 2). Medical oncology patients can respond to eSyM’s PRO-CTCAE-based symptom questionnaires up to twice per week for 180 days. eSyM becomes available to surgery patients the day after hospital discharge following an eligible surgical procedure. Surgery patients can respond to questionnaires on a tapering schedule, up to 3 times per week for weeks 1–2, up to twice per week for weeks 3–4, and up to once a week for weeks 5–8. If a patient transitions from medical oncology to surgery, or vice versa, then the medical oncology version of eSyM discontinues and the surgery version becomes active. Therefore, only one program is active at a time. There is no limit on the number of times patients may restart the eSyM program for new qualifying treatment plans or surgeries. Sample size {14} We calculated the sample size to have 80% power to detect a difference in the primary outcome of EDTR between the control and invention groups using the stepped wedge clustered randomized design . Thirty-day EDTR rates are estimated to vary between 8 and 15% for the control group. We hypothesized that EDTR rates will be 3–4% lower in the eSyM-intervention group. We based control group rates on EDTR rates derived from HCUP data, institutional data, and early phase analyses from CMMI’s Oncology Care Model (OCM) for Baptist Memorial, the only OCM participant among our six sites. Table shows the required sample size to have 80% power to detect a difference between groups, at two-sided alpha level 0.05, using the stepped wedge cluster-randomized design . Analyses of inter-institutional variation in hospitalization and ED visit rates from AHRQ’s statewide databases indicate low intraclass correlations (ICC) . A low ICC (0.01) is expected for this study because (1) the intervention is deployed with the same technology across hospitals and (2) adjustments are made for variation in baseline risk via generalized linear mixed models such that potential differences in case-mix among hospitals will be negligible. Given these factors, a conservative estimate would suggest that 6048 participants will provide adequate power to evaluate the primary outcome. This equates to a minimum of 504 medical oncology and 504 surgical patients at each of the 6 participating sites. The protocol does not mandate equal distribution of participants among participating sites. Since eSyM is being deployed as a broad-based system-level implementation, it is anticipated that the trial will have a much higher N, allowing for review and analysis of subgroups of interest. Recruitment {15} eSyM-eligible patients are identified automatically using two Epic-based patient registries — one for medical oncology and one for surgery. Thus, patients are not actively recruited. After patients are added to a registry, the system automatically assigns the symptom-based questionnaire series. Patients must have an active patient portal account to use most eSyM features. To increase awareness and engagement, patients receive a welcome message and instructions via their patient portal. Participants may also receive additional program information via pamphlets, telephone calls, emails, and/or personal communications during pre-operative or chemotherapy appointments. During these interactions, study team members assist with patient portal set-up (if needed), eSyM program education, and first questionnaire completion.
We will compare patients who started chemotherapy or had surgery before eSyM deployment (i.e., control episodes) with patients who started chemotherapy or had surgery after eSyM deployment (i.e., intervention episodes). This pre-post design allows each site to provide its own control group and likely reduces the potential for confounding on cluster- and possibly individual-level characteristics. Intervention patients are encouraged, but not required, to use eSyM. Thus, the intervention group is defined by exposure to, not use of, eSyM. Patients who receive multiple chemotherapy treatments or surgeries can contribute multiple episodes to the analysis. For example, a patient who received surgery during the control period and chemotherapy during the intervention period would contribute an episode to the surgery control cohort and a separate episode to the chemotherapy intervention cohort.
The eSyM program includes the following core features: (1) EHR registries that automatically identify patients for eSyM activation, (2) patient portal questionnaires that assess symptoms at regular intervals for a defined period after chemotherapy or surgery (the questionnaires are based on the validated Patient Reported Outcome version of the Common Terminology Criteria for Adverse Events [PRO-CTCAE®] plus two pictogram-based questions assessing overall well-being and performance status on a Likert scale), (3) patient self-management symptom tip sheets, (4) patient-facing views of past symptom reports, (5) care-team in-basket alerts for reported severe symptoms, (6) clinician-facing symptom reports and charting tools, and (7) population management reports . Since teams caring for medical oncology and surgery patients may not overlap, and to accommodate differences in hospital system structures and priorities, eSyM was designed with the flexibility to be deployed for both medical oncology and surgery patients, exclusively or in combination. Deploying the medical oncology and surgery versions of eSyM at different time points helps account for co-existing trends that are unrelated to the intervention. The features of eSyM medical oncology and surgery are nearly identical. A patient can only be active on one version of eSyM at a time but can be active on different versions of eSyM sequentially. To use eSyM, patients must either have access to the patient portal (which requires having a smartphone or computer that has internet access) or be provided a tablet during clinic visits (available at two sites).
eSyM automatically becomes available to eligible patients via the patient portal 1 day after either chemotherapy starts or hospital discharge after surgery. The program automatically discontinues after 180 days for medical oncology patients and after 60 days for surgical patients. Patients who do not wish to participate can either ignore questionnaire reminders or ask their care team to discontinue them.
We use several implementation science strategies to support stakeholder (i.e., patient and clinician) engagement. Educational materials and outreach efforts foster patient use of the program, and training materials and outreach efforts increase care team engagement with the program. Sites routinely employ a coordinator to monitor eSyM patients. Coordinators approach patients to encourage eSyM engagement and assist with program setup, questionnaire submission, technical questions, and care team training. In addition to completing eSyM symptom questions via the patient portal, some sites enable symptom reporting via an internet tablet in clinic. For patients unable to complete questionnaires independently, proxy reporting by a family member or close contact is encouraged. Figure outlines specific implementation strategies recorded to date. Throughout the project, additional implementation strategies are being documented by the site project coordinators in a central database.
eSyM is deployed as a standard-of-care intervention. It neither requires nor precludes concomitant care during the trial.
The trial makes no provisions for post-trial care. After the trial, sites may choose to continue using eSyM with or without modifications, or they may discontinue its use.
The primary outcome is the occurrence of an emergency department treat-and-release (EDTR) event within 30-days of chemotherapy start or surgical discharge (binary outcome). Secondary clinical outcomes for surgery patients include time to initiation of adjuvant chemotherapy, time to re-operation, time to re-admission, and overall survival. Secondary outcomes for medical oncology patients include time to first chemotherapy treatment, time to delay or dose modification, time to chemotherapy discontinuation, time to admission, and vital status. Patients are followed for 1 year after the treatment start date. Secondary outcomes focus on events through 90, 180 and 360 days. For the SASS sub-study, secondary patient-reported outcomes are evaluated approximately 30–60 days after the treatment initiation date.
eSyM becomes available to medical oncology patients the day after the first treatment for a new chemotherapy plan is completed (i.e., cycle 1 day 2). Medical oncology patients can respond to eSyM’s PRO-CTCAE-based symptom questionnaires up to twice per week for 180 days. eSyM becomes available to surgery patients the day after hospital discharge following an eligible surgical procedure. Surgery patients can respond to questionnaires on a tapering schedule, up to 3 times per week for weeks 1–2, up to twice per week for weeks 3–4, and up to once a week for weeks 5–8. If a patient transitions from medical oncology to surgery, or vice versa, then the medical oncology version of eSyM discontinues and the surgery version becomes active. Therefore, only one program is active at a time. There is no limit on the number of times patients may restart the eSyM program for new qualifying treatment plans or surgeries.
We calculated the sample size to have 80% power to detect a difference in the primary outcome of EDTR between the control and invention groups using the stepped wedge clustered randomized design . Thirty-day EDTR rates are estimated to vary between 8 and 15% for the control group. We hypothesized that EDTR rates will be 3–4% lower in the eSyM-intervention group. We based control group rates on EDTR rates derived from HCUP data, institutional data, and early phase analyses from CMMI’s Oncology Care Model (OCM) for Baptist Memorial, the only OCM participant among our six sites. Table shows the required sample size to have 80% power to detect a difference between groups, at two-sided alpha level 0.05, using the stepped wedge cluster-randomized design . Analyses of inter-institutional variation in hospitalization and ED visit rates from AHRQ’s statewide databases indicate low intraclass correlations (ICC) . A low ICC (0.01) is expected for this study because (1) the intervention is deployed with the same technology across hospitals and (2) adjustments are made for variation in baseline risk via generalized linear mixed models such that potential differences in case-mix among hospitals will be negligible. Given these factors, a conservative estimate would suggest that 6048 participants will provide adequate power to evaluate the primary outcome. This equates to a minimum of 504 medical oncology and 504 surgical patients at each of the 6 participating sites. The protocol does not mandate equal distribution of participants among participating sites. Since eSyM is being deployed as a broad-based system-level implementation, it is anticipated that the trial will have a much higher N, allowing for review and analysis of subgroups of interest.
eSyM-eligible patients are identified automatically using two Epic-based patient registries — one for medical oncology and one for surgery. Thus, patients are not actively recruited. After patients are added to a registry, the system automatically assigns the symptom-based questionnaire series. Patients must have an active patient portal account to use most eSyM features. To increase awareness and engagement, patients receive a welcome message and instructions via their patient portal. Participants may also receive additional program information via pamphlets, telephone calls, emails, and/or personal communications during pre-operative or chemotherapy appointments. During these interactions, study team members assist with patient portal set-up (if needed), eSyM program education, and first questionnaire completion.
Sequence generation {16a} To determine the site activation sequence, sites were first categorized into three paired groups: Southern/non-metropolitan (WVU and Baptist), Northern/non-metropolitan (Maine and Dartmouth), or Northern/metropolitan (Dana-Farber and Lifespan). The intention was to ensure that sites with similar characteristics would have different activation sequences. Then, site pairs were randomly assigned to time periods: Southern deploys during the 1st and 6th periods, Northern deploys during the 2nd and 5th periods, and Metropolitan deploys during the 3rd and 4th periods. Finally, within each group, one site was randomly assigned to deploy medical oncology before surgery and the other to deploy surgery before medical oncology (Fig. ). With six participating sites, each deploying eSyM on two separate occasions, there are twelve total deployments (“go-lives”). Initiations were staggered, so that (a) each period includes one medical oncology and one surgery deployment, (b) each site deploys eSyM-medical oncology and eSyM-surgery during different time periods, and (c) each site has the same total time exposed to eSyM. Concealment mechanism {16b} The randomization sequence was not concealed as sites needed to plan for their eSyM deployments with their technical, operational, and clinical teams. Implementation {16c} The allocation sequence was generated randomly by the study statistician at the project coordinating center on November 6, 2018.
To determine the site activation sequence, sites were first categorized into three paired groups: Southern/non-metropolitan (WVU and Baptist), Northern/non-metropolitan (Maine and Dartmouth), or Northern/metropolitan (Dana-Farber and Lifespan). The intention was to ensure that sites with similar characteristics would have different activation sequences. Then, site pairs were randomly assigned to time periods: Southern deploys during the 1st and 6th periods, Northern deploys during the 2nd and 5th periods, and Metropolitan deploys during the 3rd and 4th periods. Finally, within each group, one site was randomly assigned to deploy medical oncology before surgery and the other to deploy surgery before medical oncology (Fig. ). With six participating sites, each deploying eSyM on two separate occasions, there are twelve total deployments (“go-lives”). Initiations were staggered, so that (a) each period includes one medical oncology and one surgery deployment, (b) each site deploys eSyM-medical oncology and eSyM-surgery during different time periods, and (c) each site has the same total time exposed to eSyM.
The randomization sequence was not concealed as sites needed to plan for their eSyM deployments with their technical, operational, and clinical teams.
The allocation sequence was generated randomly by the study statistician at the project coordinating center on November 6, 2018.
Who will be blinded {17a} There is no blinding for patients or sites. eSyM is deployed as a standard-of-care intervention by health systems, such that all patients within a health system have the same intervention exposure, reducing the need for blinding. Post-deployment, all patients are notified of the eSyM program and can choose to participate or not, and all site staff are educated about eSyM to foster successful implementation. Procedure for unblinding if needed {17b} This stepped wedge trial does not require procedures for unblinding because the eSyM intervention is being administered through standard-of-care clinical practice with no blinding for patients or sites. The study design is open label so blinding will not occur.
There is no blinding for patients or sites. eSyM is deployed as a standard-of-care intervention by health systems, such that all patients within a health system have the same intervention exposure, reducing the need for blinding. Post-deployment, all patients are notified of the eSyM program and can choose to participate or not, and all site staff are educated about eSyM to foster successful implementation.
This stepped wedge trial does not require procedures for unblinding because the eSyM intervention is being administered through standard-of-care clinical practice with no blinding for patients or sites. The study design is open label so blinding will not occur.
Plans for assessment and collection of outcomes {18a} Outcomes for control and intervention patients are collected via data extracts from the Epic EHR using custom structured query language (SQL) queries run by each site’s data warehouse team. The primary intervention outcomes include encounters (i.e., ambulatory visits, ED visits, and admissions); chemotherapy treatments, durations, and discontinuations; procedures; and patient portal and eSyM utilization. For the SASS sub-study, patient-reported self-efficacy, symptom burden, and satisfaction with care are assessed through a one-time questionnaire approximately 30–60 days after chemotherapy or surgery. A minimum of 1800 questionnaires are collected across sites, of which 900 are collected before and 900 after eSyM deploys. The SASS questionnaire varies modestly based on the type of treatment (medical oncology vs. surgery), the timing relative to eSyM deployment (before vs. after), and patient use of eSyM’s symptom monitoring questionnaires (responder vs. non-responder). Plans to promote participant retention and complete follow-up {18b} For eSyM patients, an introductory message explaining the program is sent via the patient portal, and automated reminders are sent at pre-defined intervals (approximately twice per week) encouraging symptom questionnaire completion. At some sites, eSyM patients receive additional reminders to engage with the program through phone calls, emails, or in-clinic touch points. The SIMPRO coordinating center regularly updates each site with key performance indicators, including eSyM participation rates, to encourage sites to increase their patients’ use of eSyM. Patients who choose to stop receiving care at a SIMPRO site will have an incomplete follow-up as their encounters will no longer be captured by the site’s EHR system. For patients taking part in the SASS questionnaire, there is no specific retention or follow-up plan. Data management {19} Patient data are collected via Epic and REDCap. Epic, a HIPAA-compliant EHR, is used to deploy eSyM and to capture demographic data, healthcare and patient portal utilization information, and clinical outcomes. REDCap, a HIPAA-compliant and 21 CFR Part 11 application, is used to collect responses to the SASS questionnaire, which asks about patient health information as well as perceptions and behaviors regarding patient portal and ePRO systems. Both systems employ user privileges, password protection and authentication, auto-logout settings, and audit trails. Study-specific procedures to maximize data security include controlled access, use of unique study identification numbers, extensive training, and regular quality checks. Once collected, data are deidentified and shared with the SIMPRO coordinating center via secure file transfer protocols in compliance with a fully executed multi-center data transfer agreement. Data collection and transfer procedures are outlined in Fig. . Confidentiality {27} The study team has taken many steps to protect patient privacy and confidentiality, including training all staff in best practices and regulations, collecting research data using unique identification numbers, and using data collection systems that meet NIH data security standards. In addition, only limited deidentified data are transferred to the coordinating center. Plans for collection, laboratory evaluation, and storage of biological specimens for genetic or molecular analysis in this trial/future use {33} This trial does not include collection, laboratory evaluation, or storage of biological specimens for genetic or molecular analysis.
Outcomes for control and intervention patients are collected via data extracts from the Epic EHR using custom structured query language (SQL) queries run by each site’s data warehouse team. The primary intervention outcomes include encounters (i.e., ambulatory visits, ED visits, and admissions); chemotherapy treatments, durations, and discontinuations; procedures; and patient portal and eSyM utilization. For the SASS sub-study, patient-reported self-efficacy, symptom burden, and satisfaction with care are assessed through a one-time questionnaire approximately 30–60 days after chemotherapy or surgery. A minimum of 1800 questionnaires are collected across sites, of which 900 are collected before and 900 after eSyM deploys. The SASS questionnaire varies modestly based on the type of treatment (medical oncology vs. surgery), the timing relative to eSyM deployment (before vs. after), and patient use of eSyM’s symptom monitoring questionnaires (responder vs. non-responder).
For eSyM patients, an introductory message explaining the program is sent via the patient portal, and automated reminders are sent at pre-defined intervals (approximately twice per week) encouraging symptom questionnaire completion. At some sites, eSyM patients receive additional reminders to engage with the program through phone calls, emails, or in-clinic touch points. The SIMPRO coordinating center regularly updates each site with key performance indicators, including eSyM participation rates, to encourage sites to increase their patients’ use of eSyM. Patients who choose to stop receiving care at a SIMPRO site will have an incomplete follow-up as their encounters will no longer be captured by the site’s EHR system. For patients taking part in the SASS questionnaire, there is no specific retention or follow-up plan.
Patient data are collected via Epic and REDCap. Epic, a HIPAA-compliant EHR, is used to deploy eSyM and to capture demographic data, healthcare and patient portal utilization information, and clinical outcomes. REDCap, a HIPAA-compliant and 21 CFR Part 11 application, is used to collect responses to the SASS questionnaire, which asks about patient health information as well as perceptions and behaviors regarding patient portal and ePRO systems. Both systems employ user privileges, password protection and authentication, auto-logout settings, and audit trails. Study-specific procedures to maximize data security include controlled access, use of unique study identification numbers, extensive training, and regular quality checks. Once collected, data are deidentified and shared with the SIMPRO coordinating center via secure file transfer protocols in compliance with a fully executed multi-center data transfer agreement. Data collection and transfer procedures are outlined in Fig. .
The study team has taken many steps to protect patient privacy and confidentiality, including training all staff in best practices and regulations, collecting research data using unique identification numbers, and using data collection systems that meet NIH data security standards. In addition, only limited deidentified data are transferred to the coordinating center.
This trial does not include collection, laboratory evaluation, or storage of biological specimens for genetic or molecular analysis.
Statistical methods for primary and secondary outcomes {20a} This type II effectiveness-implementation hybrid study will assess the impact of eSyM and describe the facilitators and barriers to eSyM having an impact . The primary analysis will be conducted with the medical oncology and surgical cohorts combined. Descriptive statistics will be used to elucidate characteristics of clusters and participants; multilevel generalized linear regression models will be used to characterize relationships with outcomes controlling for other factors. For each outcome, modification of the intervention effect by cohort (i.e., surgery and medical oncology) will be assessed by including interaction tests. If the observed p -value for the test for interaction is greater than 0.2, the interaction term will be removed from the model and a common intervention effect will be estimated. If the observed p -value is below 0.2, analyses for the medical and surgical cohorts will be conducted separately and intervention effects will be estimated for each cohort. The primary study outcome is the occurrence of an EDTR event within 30 days of chemotherapy start or surgical discharge. This will be classified as a binary outcome: any or no EDTR within 30 days. Events occurring on the first day of chemotherapy infusion or the day of hospital discharge will be excluded, because they could not have been impacted by the eSyM program. Because each patient could experience multiple episodes during the study period (i.e., start more than one chemotherapy region or have more than one surgery), the analysis could include multiple data points from the same patient. Multilevel generalized linear regression with the logit-link will account for within-subject correlations and confounding by known covariates (e.g., age, sex, race/ethnicity, employment status, marital status, socio-economic status, type of cancer, type of surgery or chemotherapy, treating facility, number of co-morbidities). Factors included in the generalized linear regression models will include intervention, time, hospital (fixed effect), subject (random effect), and other potentially relevant predictive factors. The models will include random intercepts; we may explore inclusion of random slopes to assess for temporal changes. If a mixed effect model does not converge, we will use a generalized estimating equation approach instead. Results will be reported as odds ratios with 95% confidence intervals. Key secondary outcomes include the initiation of chemotherapy for surgery patients and the duration of chemotherapy for medical oncology patients. For surgery patients, we will look at the time to initiation of chemotherapy and whether chemotherapy is given within 90 days of discharge. For medical oncology patients, we will assess the time to discontinuation of chemotherapy and the total duration of chemotherapy treatment. For all patients, we will assess response to eSyM questionnaires and utilization of healthcare services. Multilevel generalized linear regression models will be used with an appropriate link function (e.g., logit-link for binary outcomes, log-link for count data, and time-to-event outcomes [e.g., time to admission/re-admission, time to surgery, time to death], and identity-link for continuous outcomes [e.g., self-reported quality of life]), to compare intervention vs. control patients while also controlling for other potential confounding variables. Participants in the SASS sub-study self-report five PROMIS short-form domains: pain, fatigue, depression, anxiety, and physical function. Past studies have reported minimally important difference ranges for these domains, which are approximately 3–5 using a T -score scale or 0.5 using a standard deviation scale [ – ]. To systematically assess patients’ care experience, participants in the SASS sub-study self-report using the Consumer Assessment of Healthcare Providers and Systems (CAHPS) cancer care surveys for drug therapy and surgery . For each of the five PROMIS domains and two CAPHS surveys, we will compare scores for eSyM-intervention versus control patients, adjusting for case-mix and other potential confounding variables. Interim analyses {21b} eSyM utilization is assessed monthly to guide and adapt implementation efforts using two patient-level metrics: (1) response to at least one symptom monitoring questionnaire and (2) response to multiple symptom monitoring questionnaires. We had not planned a formal interim analysis, but the COVID-19 pandemic forced a change in plans. Although eSyM deployments have occurred on schedule, the COVID-19 pandemic has impacted the eSyM project in many ways. Most notably, emergency department visits plummeted during the pandemic . Since the project’s primary outcome is 30-day EDTR, the actual proportion of the event occurrence could be lower than estimated, adversely impacting study power. Therefore, we plan to conduct an interim analysis to estimate the event rate for the intervention cohort, without comparing the intervention and control groups. If needed, we will amend the protocol to extend accrual. Methods for additional analyses (e.g., subgroup analyses) {20b} Analyses to assess for heterogeneity in treatment effects are considered exploratory and will be limited to pre-specified salient domains. Subgroups of interest are (1) computer experience, (2) rurality, (3) age (less than 70 versus greater than or equal to 70), (4) cancer or surgery type, and (5) patient versus patient-proxy reporting. We will also look to see if the intervention has a differential impact over time and by cluster. Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c} Patients exposed to protocol non-adherence will be excluded from the analysis. To evaluate the robustness of the results for the primary analysis, sensitivity analyses will be performed with various approaches to handle missing observations, including best or worst case imputations, mean value imputation, and multiple imputations . For EHR data, substantial missing data is not anticipated but, if needed, multiple imputations will be performed and results integrated using Rubin’s method . For SASS questionnaire patient response data, we will use several methods to handle missing observations, including mean value, worst-case, best-case, and multiple imputations . Plans to give access to the full protocol, participant-level data, and statistical code {31c} All data are stored in a master deidentified dataset at the SIMPRO Consortium coordinating center. In accordance with IMPACT funding requirements and the SIMPRO data use agreement, a deidentified data set will be shared with the National Institutes of Health (NIH) and collaborators. Investigators can request the data collected from this study for new research. Requests must be approved by WIRB, the Dana-Farber IRB, and the NIH prior to sharing.
This type II effectiveness-implementation hybrid study will assess the impact of eSyM and describe the facilitators and barriers to eSyM having an impact . The primary analysis will be conducted with the medical oncology and surgical cohorts combined. Descriptive statistics will be used to elucidate characteristics of clusters and participants; multilevel generalized linear regression models will be used to characterize relationships with outcomes controlling for other factors. For each outcome, modification of the intervention effect by cohort (i.e., surgery and medical oncology) will be assessed by including interaction tests. If the observed p -value for the test for interaction is greater than 0.2, the interaction term will be removed from the model and a common intervention effect will be estimated. If the observed p -value is below 0.2, analyses for the medical and surgical cohorts will be conducted separately and intervention effects will be estimated for each cohort. The primary study outcome is the occurrence of an EDTR event within 30 days of chemotherapy start or surgical discharge. This will be classified as a binary outcome: any or no EDTR within 30 days. Events occurring on the first day of chemotherapy infusion or the day of hospital discharge will be excluded, because they could not have been impacted by the eSyM program. Because each patient could experience multiple episodes during the study period (i.e., start more than one chemotherapy region or have more than one surgery), the analysis could include multiple data points from the same patient. Multilevel generalized linear regression with the logit-link will account for within-subject correlations and confounding by known covariates (e.g., age, sex, race/ethnicity, employment status, marital status, socio-economic status, type of cancer, type of surgery or chemotherapy, treating facility, number of co-morbidities). Factors included in the generalized linear regression models will include intervention, time, hospital (fixed effect), subject (random effect), and other potentially relevant predictive factors. The models will include random intercepts; we may explore inclusion of random slopes to assess for temporal changes. If a mixed effect model does not converge, we will use a generalized estimating equation approach instead. Results will be reported as odds ratios with 95% confidence intervals. Key secondary outcomes include the initiation of chemotherapy for surgery patients and the duration of chemotherapy for medical oncology patients. For surgery patients, we will look at the time to initiation of chemotherapy and whether chemotherapy is given within 90 days of discharge. For medical oncology patients, we will assess the time to discontinuation of chemotherapy and the total duration of chemotherapy treatment. For all patients, we will assess response to eSyM questionnaires and utilization of healthcare services. Multilevel generalized linear regression models will be used with an appropriate link function (e.g., logit-link for binary outcomes, log-link for count data, and time-to-event outcomes [e.g., time to admission/re-admission, time to surgery, time to death], and identity-link for continuous outcomes [e.g., self-reported quality of life]), to compare intervention vs. control patients while also controlling for other potential confounding variables. Participants in the SASS sub-study self-report five PROMIS short-form domains: pain, fatigue, depression, anxiety, and physical function. Past studies have reported minimally important difference ranges for these domains, which are approximately 3–5 using a T -score scale or 0.5 using a standard deviation scale [ – ]. To systematically assess patients’ care experience, participants in the SASS sub-study self-report using the Consumer Assessment of Healthcare Providers and Systems (CAHPS) cancer care surveys for drug therapy and surgery . For each of the five PROMIS domains and two CAPHS surveys, we will compare scores for eSyM-intervention versus control patients, adjusting for case-mix and other potential confounding variables.
eSyM utilization is assessed monthly to guide and adapt implementation efforts using two patient-level metrics: (1) response to at least one symptom monitoring questionnaire and (2) response to multiple symptom monitoring questionnaires. We had not planned a formal interim analysis, but the COVID-19 pandemic forced a change in plans. Although eSyM deployments have occurred on schedule, the COVID-19 pandemic has impacted the eSyM project in many ways. Most notably, emergency department visits plummeted during the pandemic . Since the project’s primary outcome is 30-day EDTR, the actual proportion of the event occurrence could be lower than estimated, adversely impacting study power. Therefore, we plan to conduct an interim analysis to estimate the event rate for the intervention cohort, without comparing the intervention and control groups. If needed, we will amend the protocol to extend accrual.
Analyses to assess for heterogeneity in treatment effects are considered exploratory and will be limited to pre-specified salient domains. Subgroups of interest are (1) computer experience, (2) rurality, (3) age (less than 70 versus greater than or equal to 70), (4) cancer or surgery type, and (5) patient versus patient-proxy reporting. We will also look to see if the intervention has a differential impact over time and by cluster.
Patients exposed to protocol non-adherence will be excluded from the analysis. To evaluate the robustness of the results for the primary analysis, sensitivity analyses will be performed with various approaches to handle missing observations, including best or worst case imputations, mean value imputation, and multiple imputations . For EHR data, substantial missing data is not anticipated but, if needed, multiple imputations will be performed and results integrated using Rubin’s method . For SASS questionnaire patient response data, we will use several methods to handle missing observations, including mean value, worst-case, best-case, and multiple imputations .
All data are stored in a master deidentified dataset at the SIMPRO Consortium coordinating center. In accordance with IMPACT funding requirements and the SIMPRO data use agreement, a deidentified data set will be shared with the National Institutes of Health (NIH) and collaborators. Investigators can request the data collected from this study for new research. Requests must be approved by WIRB, the Dana-Farber IRB, and the NIH prior to sharing.
Composition of the coordinating center and trial steering committee {5d} eSyM is deployed through the multi-center SIMPRO Consortium. The coordinating center (Dana-Farber) oversees administrative grant management, Epic software configuration, data analysis, and overall project and consortium coordination. The coordinating center includes a co-principal investigator, two statisticians, a program manager, and two research coordinators. Members of the coordinating center, along with the principal investigators from each participating SIMPRO site and the eSyM technical lead, provide oversight and monitoring of data collection and management. Composition of the data monitoring committee, its role, and reporting structure {21a} This is a minimal risk study assessing the impact of a standard-of-care implementation; there is no data monitoring committee. Adverse event reporting and harms {22} This is a minimal risk, standard-of-care implementation; routine adverse event reporting is not conducted. Frequency and plans for auditing trial conduct {23} The Epic extracts are audited quarterly by each site and by the SIMPRO coordinating center. Patient medical records are only accessible at individual sites; they can only be audited at the request of a site’s principal investigator. All other study records can be audited at the request of the project and site principal investigators. Audits will not be conducted by external groups. Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25} All protocol amendments are prepared, approved, and submitted to WIRB by the SIMPRO coordinating center. Once approved, memos are circulated to site project managers for record-keeping and submission to local IRBs in compliance with local policies. As this is a minimal risk study, patients are not notified of protocol amendments. Dissemination plans {31a} The SIMPRO Consortium plans to share results with participants, healthcare professionals, institutions, and software developers. At the conclusion of the study, all participants will be directed to clinicaltrials.gov and PubMed to view results. For healthcare professionals, results will be made available through manuscript publications and conference presentations. The study team is working with Epic to make eSyM available to all Epic-based healthcare intuitions via Epic’s User Web, SharePoint, and annual meetings. The SIMPRO website ( www.esymcancermoonshot.org ) includes build information, symptom management tip sheets, workbooks, and other resources.
eSyM is deployed through the multi-center SIMPRO Consortium. The coordinating center (Dana-Farber) oversees administrative grant management, Epic software configuration, data analysis, and overall project and consortium coordination. The coordinating center includes a co-principal investigator, two statisticians, a program manager, and two research coordinators. Members of the coordinating center, along with the principal investigators from each participating SIMPRO site and the eSyM technical lead, provide oversight and monitoring of data collection and management.
This is a minimal risk study assessing the impact of a standard-of-care implementation; there is no data monitoring committee.
This is a minimal risk, standard-of-care implementation; routine adverse event reporting is not conducted.
The Epic extracts are audited quarterly by each site and by the SIMPRO coordinating center. Patient medical records are only accessible at individual sites; they can only be audited at the request of a site’s principal investigator. All other study records can be audited at the request of the project and site principal investigators. Audits will not be conducted by external groups.
All protocol amendments are prepared, approved, and submitted to WIRB by the SIMPRO coordinating center. Once approved, memos are circulated to site project managers for record-keeping and submission to local IRBs in compliance with local policies. As this is a minimal risk study, patients are not notified of protocol amendments.
The SIMPRO Consortium plans to share results with participants, healthcare professionals, institutions, and software developers. At the conclusion of the study, all participants will be directed to clinicaltrials.gov and PubMed to view results. For healthcare professionals, results will be made available through manuscript publications and conference presentations. The study team is working with Epic to make eSyM available to all Epic-based healthcare intuitions via Epic’s User Web, SharePoint, and annual meetings. The SIMPRO website ( www.esymcancermoonshot.org ) includes build information, symptom management tip sheets, workbooks, and other resources.
The SIMPRO consortium is conducting a pragmatic type II hybrid effectiveness-implementation stepped wedge cluster-randomized trial to assess the impact of a symptom management program for patients treated with cancer chemotherapy or surgery in the routine care setting. To date, key successes include (1) creating an ePRO-based symptom management program that is integrated into a widely used EHR system; (2) deploying eSyM across six health systems; (3) adapting eSyM, and its associated implementation strategies, based on feedback from patients and clinicians; (4) providing access to symptom monitoring and management tools to thousands of cancer patients; and (5) beginning to collect data from six versions of the Epic EHR using a common data model. The pragmatic design employed by this protocol will enable systematic analysis of the effectiveness of a novel care delivery intervention in a real-world setting. This trial has faced several challenges that have underscored the importance of the adaptive approach: Operational : As a dynamic implementation project, eSyM is continuously refined. Differing clinic structures, technical capabilities, and leadership engagement across the sites impact the consistency, feasibility, and acceptability of the program. Program needs change frequently based on real-time feedback from patients and clinicians. Intervention and protocol modifications are considered on an ongoing basis. Optimizing the program is labor-intensive and operationally challenging. Technical : Partnering with Epic to develop eSyM has presented advantages (e.g., a robust EHR with a secure HIPAA-compliant patient portal), but technical challenges have nevertheless arisen. Healthcare institutions have unique EHR configurations and site-specific policies that can add time and complexity to system configuration and deployment efforts. Epic functional capabilities, such as limited user-interface display options, messaging capabilities, and notification settings, constrain what can be built into the system. Administrative : Deploying eSyM at six separate institutions has required substantial coordination. Each site has unique staffing, processes, and procedures. Multi-center IRB submissions, EHR builds, data use agreements, data extraction procedures, and funding agreements are needed to support this project, which requires substantial administrative work by each site and the coordinating center. Clinician : A key and persistent challenge has been clinician buy-in to a new symptom management program. eSyM is designed to integrate into existing workflows, but it still introduces new processes that have generated stress amidst pandemic-related work pressures and staffing shortages. We have adapted eSyM in response to clinician feedback. For example, the original questionnaire asked patients to report symptoms experienced over the last 7 days, but nurses expressed concern that this led patients to report symptoms that have resolved. Since the primary goal of eSyM is early identification and treatment of symptoms to prevent escalation, we revised the recall period to ask about symptoms experienced in the preceding 24 h. Effects of this modification will be analyzed. Patient : Some patients engage with eSyM’s questionnaires and educational resources more than others. Barriers to engagement include limited access to technology (e.g., computers, smartphones, internet access), limited understanding of eSyM program benefits, and skepticism that healthcare providers will use eSyM reports to guide management decisions. Site teams review this feedback routinely and look for strategies that encourage regular use of the program. Although the COVID pandemic has created many challenges, not all its impacts have been detrimental. It has prioritized telehealth in an unprecedented way, and it has provided a strong external impetus to engage stakeholders, including healthcare administrators, clinicians, and patients/caregivers, on the use of novel technologies and the need for novel approaches to healthcare delivery. A key aspect of our study design involves a detailed analysis of implementation outcomes, including patient adoption, clinician utilization, ePRO sustainability, penetration and scalability for symptom management, and extent of ePRO systems adaptation over the course of the implementation. Qualitative and quantitative implementation outcomes data, which are collected from stakeholders throughout the project, will help identify facilitators and barriers to implementation across multiple levels.
The study protocol was originally approved as a minimal risk research study on November 25, 2018 (protocol #20182593). Current protocol version 6.0 was approved on June 23, 2021. Pre-intervention SASS questionnaire data collection began July 25, 2019. The first cohort of eSyM patient recruitment began on September 10, 2019. Patient recruitment is expected to conclude on August 31, 2022. Data collection is expected to conclude in the last quarter of 2023.
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Preparation for cardiac procedures: a cross-sectional study identifying gaps between outpatients’ views and experiences of patient-centred care | 00cf1ea2-2bfa-49d5-8086-4bc5a5830150 | 11112521 | Patient-Centered Care[mh] | Cardiac catheterization is a widely performed procedure throughout the world, and whilst typically a relatively safe and well-tolerated procedure with a low complication rate, the potential impacts on morbidity and mortality can be significant. Patient-centred care is an essential, overarching component of quality health care. It is defined as ‘care that is respectful of and responsive to individual patient preferences, needs, and values and ensuring that patient values guide all clinical decisions’. In the context of patient-centred care, significant benefits to patients’ outcomes and experiences of care as well as benefits to the healthcare system, such as clinical quality have been reported. , Measurement of patient-reported outcomes and care experiences play a key role in the transformation towards patient-centred health systems. , For example, Patient-Reported Outcome Measures (PROMs) are currently used to obtain patients' views on health-related quality of life and symptoms. In comparison, Patient-Reported Experience Measures (PREMs) are those that obtain reports of what actually occurred during a care event, i.e. the occurrence of concrete and specific components of care, rather than patients’ evaluation of what occurred. Few studies, however, have examined patient experiences, or the quality of patient-centred care provided to patients who have undergone cardiac catheterization, and indeed patient-reported experiences of cardiovascular procedures more broadly. Shared decision is also an important aspect to be examined. , A recent review of opportunities for improving patient-reported experiences for cardiovascular disease identified the need for further research into measurement tools. A separate review examined quality improvement frameworks within cardiac catheterization laboratories. However, it focussed on clinical outcomes and patient safety, like most other work in relation to cardiac procedures, rather than the improvement of patient experiences and the provision of patient-centred care. Recent consensus statements, including those commissioned by the Society for Cardiovascular Angiography and Interventions (SCAI): SCAI expert consensus update on best practices in the cardiac catheterization laboratory include principles for patient experience optimization including patient surveys. However, it is also acknowledged in those guidelines that new surveys would need to be developed to examine patient experiences of the cardiac catheterization laboratory. An important component that should be examined is the provision of information. Patient education is essential for informed consent, and to ensure patients are well equipped to take an active role in their preparation and recovery from medical procedures including cardiac catheterization. However, a previous review found few measures of patient preparation for medical interventions exist. To improve patient outcomes, we need to identify any evidence-practice gaps i.e. a difference between components of care considered essential based on evidence-based guidelines and importance to patients, and the actual care provided to patients. Healthcare providers need access to patients’ views about care and any patient-perceived gaps in care and/or information provision across a broad range of components and phases of care to prioritize healthcare setting and system-level quality improvement initiatives, which can enhance the delivery of integrated, patient-centred care. As such, the need for further research and a new measure to examine patient experiences of cardiac catheterization was identified. To identify any gaps in patient-centred care, this study specifically examined outpatients’: (1) views on what is characterized as essential or important care and (2) experiences of care in relation to cardiac catheterization and other subsequent cardiovascular procedures.
Study type Cross-sectional descriptive study. Population and setting Participants were recruited from the Cardiology Department, Cardiac Catheterization Laboratory at a major public hospital in regional Australia, which services a population of approximately one million people. The cardiac catheterization laboratory is staffed by 20 specialist nurses, as well as senior interventional cardiologists, fellows, and training resident staff trainee doctors. Once a patient is referred by their treating Cardiologist, they are reviewed and contacted by a specialized nurse to confirm medical history as standard of care prior to the procedure. After the completion of the procedure, the patient has a standard discharge process, with post-operative instructions delivered by Medical and Nursing staff. A follow-up appointment is then arranged with their usual Cardiologist. For those patients who undergo a Percutaneous Coronary Intervention (PCI) referral to Cardiac Rehabilitation is standard of care. Recruitment and selection of participants Cardiology Department staff identified eligible patients utilizing hospital procedural lists. People considered eligible were individuals aged 18 years or older who had undergone an elective outpatient cardiac catheterization in the Cardiac Catheterization Laboratory at the participating site within the last 6 months. All eligible outpatients were sent a recruitment pack via post by staff from the Cardiology Department containing an invitation to participate, information statement, pen-and-paper survey, and reply-paid envelope for survey return to the researchers. Reminder packs were sent to all non-responders two weeks later. Data collection Measures Quality of care To reduce participant burden, patients were either asked for their views about: What characterizes essential or important care (Important Care Survey), see below; or Their actual care received (Actual Care Survey), in relation to the same aspects included in the Important Care Survey. To reduce recall bias, survey assignment was sequential: the Actual Care Survey was assigned to those who had elective outpatient cardiac catheterization in the last 3 months and the Important Care Survey to those who had elective outpatient cardiac catheterization 3–6 months ago. Important care survey The items describe components of care along the patient pathway [initial general practitioner (GP) consultation and referral process (4 items), preparation for the procedure (11 items), having the procedure (7 items), recovery (4 items), follow-up care (5 items), subsequent decision making for treatment (11 items), prognosis (6 items), and post-treatment follow-up (17 item)]. Item development, and face and content validation The published literature was assessed to identify the needs, concerns, and issues facing patients undergoing cardiac catheterization. Items of existing instruments were reviewed and considered for inclusion, including instruments assessing patient preparation and life expectancy; as well as the Institute of Medicine's dimensions of patient-centred care; and supportive and psychosocial care guidelines. , Item development was also informed by qualitative interviews undertaken as part of development of a generic instrument that examined preparedness for medical interventions. As reported elsewhere, this included 33 patients undergoing medical imaging procedures including angiography. The identified items were expanded to specifically address all phases across the cardiac catheterization care pathway, from the patient's consultation with their GP and referral to a cardiologist, to post-treatment follow-up care. To further confirm face validity (the degree to which items are an adequate reflection of the construct to be measured) and content validity (i.e. the degree to which the content of the measure is an adequate reflection of the construct to be measured), the draft items were reviewed by a multidisciplinary team of health behaviour scientists ( n = 4), clinicians ( n = 5), and consumer representatives ( n = 2). To examine patient endorsement of each component of care/item, participants were asked to indicate how important the criterion was if the best care possible was to be provided to patients. Participants were asked to respond to the 65 statements by choosing one of the following response options: ‘Essential’, ‘Very important’, ‘Moderately important’, ‘Somewhat important’, or ‘Not important’. Thirty-one items were about the initial cardiac catheterization, whilst the remaining 34 items were about any subsequent cardiac-related procedures the patient had, including angioplasty on same or different day; coronary artery bypass grafting; heart valve repair or replacement; pacemaker insertion; and cardiac defibrillator implant. Actual care survey For each of the same components of care included in the Important Care Survey, participants were asked about their receipt of that care or information. For example, ‘ Did your [healthcare team] give you information about … ?’ Participants responded to 65 statements by choosing ‘Yes’ or ‘No’ to indicate if the aspect of care was received. The yes/no response format was chosen instead of a Likert scale rating as it enables the participant to report an actual occurrence of care, rather than their perceptions or ratings of the experience. Sociodemographic characteristics Patient demographic and medical characteristics: age, gender, education, marital status, employment status, living arrangements, and travel time to hospital were also assessed in each survey. Sample size and statistical analyses Sample size Approximately, 1200 adult outpatient cardiac catheterization and percutaneous coronary interventions are performed per year at the participating hospital. Based on a conservative power calculation, a total sample size of 200 participants (100 per survey) was estimated to enable the proportion of patients reporting particular experiences of care with 95% confidence intervals within ± 6.9%. Statistical analysis Characteristics of the participants were compared using means, standard deviations, medians, and interquartile intervals for continuous variables and by percentages for categorical variables. Fisher's exact test was used to assess possible response bias by comparing the gender and age of those who completed a survey (consenters) with those who were sent a survey but did not respond (non-consenters); and to investigate differences between Important and Actual Care survey participants. P -values ≤ 0.05 were considered significant. Frequencies and percentages were used to determine the most frequently identified essential criteria for care for patients; and actual care received. To identify any gaps in patient-centred care, items rated as either ‘Essential’ or ‘Very important’ by at least 80% of participants were determined, reflecting patient endorsement of the importance of the component of care. A cut point of 80% was chosen, being a standard approach for measuring consensus. A gap in care was then identified as being an item that was endorsed as essential/very important by 80% or more of participants, but reported as received by less than 80% of participants, with associated Confidence Intervals (CIs) indicating that these endorsements were less than 80%. i.e. the CI does not cross the 80% threshold. Missing items were treated as missing and removed from the denominator for calculations. Analysis was conducted using STATA/IC 13. This study meets all five of the CODE-EHR minimum framework standards for the use of structured healthcare data in clinical research. However, this manuscript reports the findings from a cross-sectional study only which did not involve access to structured healthcare data.
Cross-sectional descriptive study.
Participants were recruited from the Cardiology Department, Cardiac Catheterization Laboratory at a major public hospital in regional Australia, which services a population of approximately one million people. The cardiac catheterization laboratory is staffed by 20 specialist nurses, as well as senior interventional cardiologists, fellows, and training resident staff trainee doctors. Once a patient is referred by their treating Cardiologist, they are reviewed and contacted by a specialized nurse to confirm medical history as standard of care prior to the procedure. After the completion of the procedure, the patient has a standard discharge process, with post-operative instructions delivered by Medical and Nursing staff. A follow-up appointment is then arranged with their usual Cardiologist. For those patients who undergo a Percutaneous Coronary Intervention (PCI) referral to Cardiac Rehabilitation is standard of care.
Cardiology Department staff identified eligible patients utilizing hospital procedural lists. People considered eligible were individuals aged 18 years or older who had undergone an elective outpatient cardiac catheterization in the Cardiac Catheterization Laboratory at the participating site within the last 6 months. All eligible outpatients were sent a recruitment pack via post by staff from the Cardiology Department containing an invitation to participate, information statement, pen-and-paper survey, and reply-paid envelope for survey return to the researchers. Reminder packs were sent to all non-responders two weeks later.
Measures Quality of care To reduce participant burden, patients were either asked for their views about: What characterizes essential or important care (Important Care Survey), see below; or Their actual care received (Actual Care Survey), in relation to the same aspects included in the Important Care Survey. To reduce recall bias, survey assignment was sequential: the Actual Care Survey was assigned to those who had elective outpatient cardiac catheterization in the last 3 months and the Important Care Survey to those who had elective outpatient cardiac catheterization 3–6 months ago.
Quality of care To reduce participant burden, patients were either asked for their views about: What characterizes essential or important care (Important Care Survey), see below; or Their actual care received (Actual Care Survey), in relation to the same aspects included in the Important Care Survey. To reduce recall bias, survey assignment was sequential: the Actual Care Survey was assigned to those who had elective outpatient cardiac catheterization in the last 3 months and the Important Care Survey to those who had elective outpatient cardiac catheterization 3–6 months ago.
To reduce participant burden, patients were either asked for their views about: What characterizes essential or important care (Important Care Survey), see below; or Their actual care received (Actual Care Survey), in relation to the same aspects included in the Important Care Survey. To reduce recall bias, survey assignment was sequential: the Actual Care Survey was assigned to those who had elective outpatient cardiac catheterization in the last 3 months and the Important Care Survey to those who had elective outpatient cardiac catheterization 3–6 months ago.
The items describe components of care along the patient pathway [initial general practitioner (GP) consultation and referral process (4 items), preparation for the procedure (11 items), having the procedure (7 items), recovery (4 items), follow-up care (5 items), subsequent decision making for treatment (11 items), prognosis (6 items), and post-treatment follow-up (17 item)]. Item development, and face and content validation The published literature was assessed to identify the needs, concerns, and issues facing patients undergoing cardiac catheterization. Items of existing instruments were reviewed and considered for inclusion, including instruments assessing patient preparation and life expectancy; as well as the Institute of Medicine's dimensions of patient-centred care; and supportive and psychosocial care guidelines. , Item development was also informed by qualitative interviews undertaken as part of development of a generic instrument that examined preparedness for medical interventions. As reported elsewhere, this included 33 patients undergoing medical imaging procedures including angiography. The identified items were expanded to specifically address all phases across the cardiac catheterization care pathway, from the patient's consultation with their GP and referral to a cardiologist, to post-treatment follow-up care. To further confirm face validity (the degree to which items are an adequate reflection of the construct to be measured) and content validity (i.e. the degree to which the content of the measure is an adequate reflection of the construct to be measured), the draft items were reviewed by a multidisciplinary team of health behaviour scientists ( n = 4), clinicians ( n = 5), and consumer representatives ( n = 2). To examine patient endorsement of each component of care/item, participants were asked to indicate how important the criterion was if the best care possible was to be provided to patients. Participants were asked to respond to the 65 statements by choosing one of the following response options: ‘Essential’, ‘Very important’, ‘Moderately important’, ‘Somewhat important’, or ‘Not important’. Thirty-one items were about the initial cardiac catheterization, whilst the remaining 34 items were about any subsequent cardiac-related procedures the patient had, including angioplasty on same or different day; coronary artery bypass grafting; heart valve repair or replacement; pacemaker insertion; and cardiac defibrillator implant.
The published literature was assessed to identify the needs, concerns, and issues facing patients undergoing cardiac catheterization. Items of existing instruments were reviewed and considered for inclusion, including instruments assessing patient preparation and life expectancy; as well as the Institute of Medicine's dimensions of patient-centred care; and supportive and psychosocial care guidelines. , Item development was also informed by qualitative interviews undertaken as part of development of a generic instrument that examined preparedness for medical interventions. As reported elsewhere, this included 33 patients undergoing medical imaging procedures including angiography. The identified items were expanded to specifically address all phases across the cardiac catheterization care pathway, from the patient's consultation with their GP and referral to a cardiologist, to post-treatment follow-up care. To further confirm face validity (the degree to which items are an adequate reflection of the construct to be measured) and content validity (i.e. the degree to which the content of the measure is an adequate reflection of the construct to be measured), the draft items were reviewed by a multidisciplinary team of health behaviour scientists ( n = 4), clinicians ( n = 5), and consumer representatives ( n = 2). To examine patient endorsement of each component of care/item, participants were asked to indicate how important the criterion was if the best care possible was to be provided to patients. Participants were asked to respond to the 65 statements by choosing one of the following response options: ‘Essential’, ‘Very important’, ‘Moderately important’, ‘Somewhat important’, or ‘Not important’. Thirty-one items were about the initial cardiac catheterization, whilst the remaining 34 items were about any subsequent cardiac-related procedures the patient had, including angioplasty on same or different day; coronary artery bypass grafting; heart valve repair or replacement; pacemaker insertion; and cardiac defibrillator implant.
For each of the same components of care included in the Important Care Survey, participants were asked about their receipt of that care or information. For example, ‘ Did your [healthcare team] give you information about … ?’ Participants responded to 65 statements by choosing ‘Yes’ or ‘No’ to indicate if the aspect of care was received. The yes/no response format was chosen instead of a Likert scale rating as it enables the participant to report an actual occurrence of care, rather than their perceptions or ratings of the experience.
Patient demographic and medical characteristics: age, gender, education, marital status, employment status, living arrangements, and travel time to hospital were also assessed in each survey.
Sample size Approximately, 1200 adult outpatient cardiac catheterization and percutaneous coronary interventions are performed per year at the participating hospital. Based on a conservative power calculation, a total sample size of 200 participants (100 per survey) was estimated to enable the proportion of patients reporting particular experiences of care with 95% confidence intervals within ± 6.9%. Statistical analysis Characteristics of the participants were compared using means, standard deviations, medians, and interquartile intervals for continuous variables and by percentages for categorical variables. Fisher's exact test was used to assess possible response bias by comparing the gender and age of those who completed a survey (consenters) with those who were sent a survey but did not respond (non-consenters); and to investigate differences between Important and Actual Care survey participants. P -values ≤ 0.05 were considered significant. Frequencies and percentages were used to determine the most frequently identified essential criteria for care for patients; and actual care received. To identify any gaps in patient-centred care, items rated as either ‘Essential’ or ‘Very important’ by at least 80% of participants were determined, reflecting patient endorsement of the importance of the component of care. A cut point of 80% was chosen, being a standard approach for measuring consensus. A gap in care was then identified as being an item that was endorsed as essential/very important by 80% or more of participants, but reported as received by less than 80% of participants, with associated Confidence Intervals (CIs) indicating that these endorsements were less than 80%. i.e. the CI does not cross the 80% threshold. Missing items were treated as missing and removed from the denominator for calculations. Analysis was conducted using STATA/IC 13. This study meets all five of the CODE-EHR minimum framework standards for the use of structured healthcare data in clinical research. However, this manuscript reports the findings from a cross-sectional study only which did not involve access to structured healthcare data.
Approximately, 1200 adult outpatient cardiac catheterization and percutaneous coronary interventions are performed per year at the participating hospital. Based on a conservative power calculation, a total sample size of 200 participants (100 per survey) was estimated to enable the proportion of patients reporting particular experiences of care with 95% confidence intervals within ± 6.9%.
Characteristics of the participants were compared using means, standard deviations, medians, and interquartile intervals for continuous variables and by percentages for categorical variables. Fisher's exact test was used to assess possible response bias by comparing the gender and age of those who completed a survey (consenters) with those who were sent a survey but did not respond (non-consenters); and to investigate differences between Important and Actual Care survey participants. P -values ≤ 0.05 were considered significant. Frequencies and percentages were used to determine the most frequently identified essential criteria for care for patients; and actual care received. To identify any gaps in patient-centred care, items rated as either ‘Essential’ or ‘Very important’ by at least 80% of participants were determined, reflecting patient endorsement of the importance of the component of care. A cut point of 80% was chosen, being a standard approach for measuring consensus. A gap in care was then identified as being an item that was endorsed as essential/very important by 80% or more of participants, but reported as received by less than 80% of participants, with associated Confidence Intervals (CIs) indicating that these endorsements were less than 80%. i.e. the CI does not cross the 80% threshold. Missing items were treated as missing and removed from the denominator for calculations. Analysis was conducted using STATA/IC 13. This study meets all five of the CODE-EHR minimum framework standards for the use of structured healthcare data in clinical research. However, this manuscript reports the findings from a cross-sectional study only which did not involve access to structured healthcare data.
Sample Overall, out of 582 eligible patients approached for this study, 264 (45%) consented to take part and returned a completed survey. Of those, 131 patients completed the Actual Care Survey and 133 patients completed the Important Care Survey. There were no significant differences between consenters compared to non-consenters in terms of gender ( P = 0.796). However, compared to non-consenters (mean age = 66.3 years, SD = 11.9), consenters (mean age =70.9 years, SD = 9.2) were older at the time of study recruitment ( P = <0.0001). Patients’ demographic characteristics are reported in . There were no significant differences between participants in relation to demographic and disease characteristics. Participants were aged 40–89 years and underwent their procedure for a variety of underlying cardiac conditions. Patients’ ratings of importance and whether components of care were received As shown in , participants completed 31 items identifying either: (i) aspects of care that patients perceive are important or essential for a healthcare team to provide in order to best support patients receiving care for a suspected or confirmed heart condition; or (ii) their actual care received in relation to the: GP consultation and referral process (4 items); preparation for the procedure (11 items); having the procedure (7 items); recovery (4 items); and follow-up care (5 items). Item endorsement and identified gaps in care Overall, most of these items ( n = 43/65) were endorsed as ‘essential’ or ‘very important’ by 80% or more of respondents. The number of responses is reported for each individual item in . presents a visual summary of the total number of items examined; the number of items rated as essential/very important by ≥80% of respondents; and the number of those for which <80% of respondents reported them as being received. Of the 43 items endorsed as essential or very important, the three items endorsed with the highest percentages for patient-reported as received were: (1) What the procedure involves (e.g. what will happen during the procedure) (92% endorsed as essential, 90% reported as received); (2) Follow-up appointments to make with their GP and/or specialist (86% endorsed as essential, 99% reported as received); and (3) Following treatment recommendations (e.g. taking medications) (87% endorsed as essential, 93% reported as received). Missing data ranged from 5–9 responses per item and were treated as missing. GP consultation and cardiologist referral process All four items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 93.9 to 96.9%. A total of 82.6% of participants were told why they were being referred to a cardiologist. However, gaps in patient-centred care for receipt of the component of care were identified. The item on how to manage symptoms while waiting for their specialist appointment was endorsed as received by less than 80% of participants (66.9%, i.e. 33.1% of participants reported they did not receive the item), with a 95% CI of 57.9–74.8% indicating that these endorsements were significantly <80%. Two other items (what the cardiac catheterization procedure might show) and (likely next steps after the procedure) also had point estimates that were < 80%. However, their 95% CI did cross 80%, indicating that the underlying endorsement (as to whether the item of care was received) could be as large as 81.5 and 80.2%, respectively. Preparation for cardiac catheterization Eight of the 11 items were endorsed as being essential or very important. Of the eight items, the most reported items for care received were: the expected benefits, and possible risks or complications, both highly endorsed by over 95% of respondents and received by 84.9% of participants. Gaps in the receipt of the component of care were identified for the four remaining items. Information on whether there were any other treatment options available was endorsed as received by <80% of participants (50.4%), with a 95% CI indicating that these endorsements were significantly less than 80%. Three other items what could happen if the patient didn't have the cardiac catheterization procedure, being given information in the amount of detail wanted, and being able to talk about their fears or worries with the healthcare team; also had point estimates that were <80% at 72.9, 78.3, and 79.3%, respectively. However, their 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 80.2, 84.6, and 85.7%, respectively. Having the procedure Five of the seven items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. What needs to happen before the procedure and what the procedure involves were both endorsed as essential and reported as experienced by 87.4 and 89.8% of participants, respectively. Two gaps in patient-centred care were identified in relation to what might be experienced during the procedure, and how they might feel after the procedure, reported by 72.8 and 78.7% of participants, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 80.0 and 85.1%, respectively. Recovery after the procedure One of the four items (adequate pain relief) was endorsed as being essential or very important. No gap in patient-centred care were identified in relation to recovery in the hospital was identified. Follow-up care after the procedure All five items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 84.7–96.2%. One gap in patient-centred care was identified in relation to how to manage any side-effects or complications if they occur, reported by 76.4% of participants as received. However, the 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 83.2%. Experiences across the care trajectory: subsequent cardiovascular procedures To examine care across the whole patient care trajectory from GP referral to diagnosis and treatment inclusive of any subsequent cardiac procedures, all participants were asked whether they had undergone any subsequent cardiovascular procedures after their initial cardiac catheterization. As shown in , 175 respondents indicated they had undergone a subsequent related procedure including: angioplasty on a different day as the cardiac catheterization ( n = 46 [17.8%]); angioplasty on the same day as the cardiac catheterization ( n = 29 [11.2%]); coronary artery bypass grafting (heart bypass surgery) ( n = 25 [9.7%]), heart valve repair or replacement ( n = 24 [9.3%]); pacemaker insertion ( n = 9 [3.5%]); and cardiac defibrillator implant ( n = 4 [1.5%]). An additional 38 respondents (13.5%) completed the additional module of questions but did not specify which subsequent procedure they had undergone. If participants selected any of the additional procedures, they were asked to complete an additional survey module regarding care in relation to that subsequent procedure. Patients’ ratings of importance and whether components of care were received in relation to their subsequent cardiovascular procedure As shown in , 130 participants completed 34 additional items identifying either: (i) aspects of care that patients perceive are important or essential for a healthcare team to provide in order to best support patients receiving care in relation to their subsequent cardiovascular procedure; or (ii) their actual care received in relation to: decision making about treatment (11 items); prognosis (6 items); and post-treatment follow-up care (17 items). Overall, most of these items ( n = 20) were endorsed as essential or very important by 80% or more of respondents. Similar to the items examining patients’ ratings and experiences of care related to their cardiac catheterization, for the items that were endorsed as very important or essential by 80% or more of respondents, a high proportion of respondents also reported that these components of care were received in relation to their subsequent heart procedure. Gaps between some aspects of patient-rated important care, and the actual care received by patients, are outlined below. Decision-making about treatment Six of the 11 items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. Gaps in patient-centred care were identified, including one item: being asked how involved they want to be in treatment decisions, which was endorsed by 82.0% of participants, but only reported as received by 53.6% of participants. For three items: possible risks or complications of each treatment decision, what might happen if they didn't have treatment and understanding how long it may take to recover from treatment; the point estimates were also under the 80% threshold at 76.8, 79.1, and 76.4%, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 85.5, 87.4, and 85.0%, respectively. Prognosis All six items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 88.5–94.4%. A patient-centred care gap was identified in relation to all six items, with the percentage of patients indicating they have received the item of care or information ranging from 13.9% in relation to whether they were explained their chance of dying within the next 12 months due to their heart condition; to being ask if they wanted to talk about whether their heart condition can be cured (59.4%). Post-treatment follow-up care Seventeen items examined post-treatment follow-up care and eight were endorsed by >80% of participants as essential or very important. Only one component of care was identified as having a gap in patient-centre care: being asked about and offered help or referral if needed for diet and nutrition advice.
Overall, out of 582 eligible patients approached for this study, 264 (45%) consented to take part and returned a completed survey. Of those, 131 patients completed the Actual Care Survey and 133 patients completed the Important Care Survey. There were no significant differences between consenters compared to non-consenters in terms of gender ( P = 0.796). However, compared to non-consenters (mean age = 66.3 years, SD = 11.9), consenters (mean age =70.9 years, SD = 9.2) were older at the time of study recruitment ( P = <0.0001). Patients’ demographic characteristics are reported in . There were no significant differences between participants in relation to demographic and disease characteristics. Participants were aged 40–89 years and underwent their procedure for a variety of underlying cardiac conditions.
As shown in , participants completed 31 items identifying either: (i) aspects of care that patients perceive are important or essential for a healthcare team to provide in order to best support patients receiving care for a suspected or confirmed heart condition; or (ii) their actual care received in relation to the: GP consultation and referral process (4 items); preparation for the procedure (11 items); having the procedure (7 items); recovery (4 items); and follow-up care (5 items). Item endorsement and identified gaps in care Overall, most of these items ( n = 43/65) were endorsed as ‘essential’ or ‘very important’ by 80% or more of respondents. The number of responses is reported for each individual item in . presents a visual summary of the total number of items examined; the number of items rated as essential/very important by ≥80% of respondents; and the number of those for which <80% of respondents reported them as being received. Of the 43 items endorsed as essential or very important, the three items endorsed with the highest percentages for patient-reported as received were: (1) What the procedure involves (e.g. what will happen during the procedure) (92% endorsed as essential, 90% reported as received); (2) Follow-up appointments to make with their GP and/or specialist (86% endorsed as essential, 99% reported as received); and (3) Following treatment recommendations (e.g. taking medications) (87% endorsed as essential, 93% reported as received). Missing data ranged from 5–9 responses per item and were treated as missing. GP consultation and cardiologist referral process All four items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 93.9 to 96.9%. A total of 82.6% of participants were told why they were being referred to a cardiologist. However, gaps in patient-centred care for receipt of the component of care were identified. The item on how to manage symptoms while waiting for their specialist appointment was endorsed as received by less than 80% of participants (66.9%, i.e. 33.1% of participants reported they did not receive the item), with a 95% CI of 57.9–74.8% indicating that these endorsements were significantly <80%. Two other items (what the cardiac catheterization procedure might show) and (likely next steps after the procedure) also had point estimates that were < 80%. However, their 95% CI did cross 80%, indicating that the underlying endorsement (as to whether the item of care was received) could be as large as 81.5 and 80.2%, respectively. Preparation for cardiac catheterization Eight of the 11 items were endorsed as being essential or very important. Of the eight items, the most reported items for care received were: the expected benefits, and possible risks or complications, both highly endorsed by over 95% of respondents and received by 84.9% of participants. Gaps in the receipt of the component of care were identified for the four remaining items. Information on whether there were any other treatment options available was endorsed as received by <80% of participants (50.4%), with a 95% CI indicating that these endorsements were significantly less than 80%. Three other items what could happen if the patient didn't have the cardiac catheterization procedure, being given information in the amount of detail wanted, and being able to talk about their fears or worries with the healthcare team; also had point estimates that were <80% at 72.9, 78.3, and 79.3%, respectively. However, their 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 80.2, 84.6, and 85.7%, respectively. Having the procedure Five of the seven items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. What needs to happen before the procedure and what the procedure involves were both endorsed as essential and reported as experienced by 87.4 and 89.8% of participants, respectively. Two gaps in patient-centred care were identified in relation to what might be experienced during the procedure, and how they might feel after the procedure, reported by 72.8 and 78.7% of participants, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 80.0 and 85.1%, respectively. Recovery after the procedure One of the four items (adequate pain relief) was endorsed as being essential or very important. No gap in patient-centred care were identified in relation to recovery in the hospital was identified. Follow-up care after the procedure All five items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 84.7–96.2%. One gap in patient-centred care was identified in relation to how to manage any side-effects or complications if they occur, reported by 76.4% of participants as received. However, the 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 83.2%.
Overall, most of these items ( n = 43/65) were endorsed as ‘essential’ or ‘very important’ by 80% or more of respondents. The number of responses is reported for each individual item in . presents a visual summary of the total number of items examined; the number of items rated as essential/very important by ≥80% of respondents; and the number of those for which <80% of respondents reported them as being received. Of the 43 items endorsed as essential or very important, the three items endorsed with the highest percentages for patient-reported as received were: (1) What the procedure involves (e.g. what will happen during the procedure) (92% endorsed as essential, 90% reported as received); (2) Follow-up appointments to make with their GP and/or specialist (86% endorsed as essential, 99% reported as received); and (3) Following treatment recommendations (e.g. taking medications) (87% endorsed as essential, 93% reported as received). Missing data ranged from 5–9 responses per item and were treated as missing.
All four items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 93.9 to 96.9%. A total of 82.6% of participants were told why they were being referred to a cardiologist. However, gaps in patient-centred care for receipt of the component of care were identified. The item on how to manage symptoms while waiting for their specialist appointment was endorsed as received by less than 80% of participants (66.9%, i.e. 33.1% of participants reported they did not receive the item), with a 95% CI of 57.9–74.8% indicating that these endorsements were significantly <80%. Two other items (what the cardiac catheterization procedure might show) and (likely next steps after the procedure) also had point estimates that were < 80%. However, their 95% CI did cross 80%, indicating that the underlying endorsement (as to whether the item of care was received) could be as large as 81.5 and 80.2%, respectively.
Eight of the 11 items were endorsed as being essential or very important. Of the eight items, the most reported items for care received were: the expected benefits, and possible risks or complications, both highly endorsed by over 95% of respondents and received by 84.9% of participants. Gaps in the receipt of the component of care were identified for the four remaining items. Information on whether there were any other treatment options available was endorsed as received by <80% of participants (50.4%), with a 95% CI indicating that these endorsements were significantly less than 80%. Three other items what could happen if the patient didn't have the cardiac catheterization procedure, being given information in the amount of detail wanted, and being able to talk about their fears or worries with the healthcare team; also had point estimates that were <80% at 72.9, 78.3, and 79.3%, respectively. However, their 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 80.2, 84.6, and 85.7%, respectively.
Five of the seven items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. What needs to happen before the procedure and what the procedure involves were both endorsed as essential and reported as experienced by 87.4 and 89.8% of participants, respectively. Two gaps in patient-centred care were identified in relation to what might be experienced during the procedure, and how they might feel after the procedure, reported by 72.8 and 78.7% of participants, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 80.0 and 85.1%, respectively.
One of the four items (adequate pain relief) was endorsed as being essential or very important. No gap in patient-centred care were identified in relation to recovery in the hospital was identified.
All five items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 84.7–96.2%. One gap in patient-centred care was identified in relation to how to manage any side-effects or complications if they occur, reported by 76.4% of participants as received. However, the 95% CI did cross 80%, indicating that the underlying endorsement could be as large as 83.2%.
To examine care across the whole patient care trajectory from GP referral to diagnosis and treatment inclusive of any subsequent cardiac procedures, all participants were asked whether they had undergone any subsequent cardiovascular procedures after their initial cardiac catheterization. As shown in , 175 respondents indicated they had undergone a subsequent related procedure including: angioplasty on a different day as the cardiac catheterization ( n = 46 [17.8%]); angioplasty on the same day as the cardiac catheterization ( n = 29 [11.2%]); coronary artery bypass grafting (heart bypass surgery) ( n = 25 [9.7%]), heart valve repair or replacement ( n = 24 [9.3%]); pacemaker insertion ( n = 9 [3.5%]); and cardiac defibrillator implant ( n = 4 [1.5%]). An additional 38 respondents (13.5%) completed the additional module of questions but did not specify which subsequent procedure they had undergone. If participants selected any of the additional procedures, they were asked to complete an additional survey module regarding care in relation to that subsequent procedure.
As shown in , 130 participants completed 34 additional items identifying either: (i) aspects of care that patients perceive are important or essential for a healthcare team to provide in order to best support patients receiving care in relation to their subsequent cardiovascular procedure; or (ii) their actual care received in relation to: decision making about treatment (11 items); prognosis (6 items); and post-treatment follow-up care (17 items). Overall, most of these items ( n = 20) were endorsed as essential or very important by 80% or more of respondents. Similar to the items examining patients’ ratings and experiences of care related to their cardiac catheterization, for the items that were endorsed as very important or essential by 80% or more of respondents, a high proportion of respondents also reported that these components of care were received in relation to their subsequent heart procedure. Gaps between some aspects of patient-rated important care, and the actual care received by patients, are outlined below. Decision-making about treatment Six of the 11 items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. Gaps in patient-centred care were identified, including one item: being asked how involved they want to be in treatment decisions, which was endorsed by 82.0% of participants, but only reported as received by 53.6% of participants. For three items: possible risks or complications of each treatment decision, what might happen if they didn't have treatment and understanding how long it may take to recover from treatment; the point estimates were also under the 80% threshold at 76.8, 79.1, and 76.4%, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 85.5, 87.4, and 85.0%, respectively. Prognosis All six items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 88.5–94.4%. A patient-centred care gap was identified in relation to all six items, with the percentage of patients indicating they have received the item of care or information ranging from 13.9% in relation to whether they were explained their chance of dying within the next 12 months due to their heart condition; to being ask if they wanted to talk about whether their heart condition can be cured (59.4%). Post-treatment follow-up care Seventeen items examined post-treatment follow-up care and eight were endorsed by >80% of participants as essential or very important. Only one component of care was identified as having a gap in patient-centre care: being asked about and offered help or referral if needed for diet and nutrition advice.
Six of the 11 items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important. Gaps in patient-centred care were identified, including one item: being asked how involved they want to be in treatment decisions, which was endorsed by 82.0% of participants, but only reported as received by 53.6% of participants. For three items: possible risks or complications of each treatment decision, what might happen if they didn't have treatment and understanding how long it may take to recover from treatment; the point estimates were also under the 80% threshold at 76.8, 79.1, and 76.4%, respectively. However, their 95% CIs did cross 80%, indicating that the underlying endorsement could be as large as 85.5, 87.4, and 85.0%, respectively.
All six items that examined this phase of care were endorsed by 80% or more of respondents as being essential or very important, with endorsement ranging from 88.5–94.4%. A patient-centred care gap was identified in relation to all six items, with the percentage of patients indicating they have received the item of care or information ranging from 13.9% in relation to whether they were explained their chance of dying within the next 12 months due to their heart condition; to being ask if they wanted to talk about whether their heart condition can be cured (59.4%).
Seventeen items examined post-treatment follow-up care and eight were endorsed by >80% of participants as essential or very important. Only one component of care was identified as having a gap in patient-centre care: being asked about and offered help or referral if needed for diet and nutrition advice.
This is the first Australian study and one of few internationally to examine patient-centred care among outpatients who have undergone cardiac catheterization, one of the most widely performed cardiac procedures. Internationally, some studies have examined aspects of patient-centred care via satisfaction surveys, and qualitative interviews. , However, this is the first study to quantitatively examine patient views on what characterizes essential or important care in relation to cardiac catheterization and combine this information with patient-reported experiences to identify gaps in care. This study also aimed to bridge another research gap by examining all preparatory content areas (risk communication, procedural information, sensory information, behavioural instruction, and psychosocial aspects), and care across the entire treatment pathway, from GP consultation, cardiologist referral, preparation for the procedure, diagnosis, involvement in decision-making about treatments, and follow-up care. Overall, aspects of follow-up care were highly endorsed by patients as essential components of care and well addressed, having been reported as experienced by the majority of patients. However, the findings of this study suggest that there are some gaps in patient-centred care across the care trajectory for patients. Overall, most of the items examined ( n = 43/65) were endorsed as ‘very important’ or ‘essential’ by 80% or more of respondents. Of those, for 22 items, less than 80% of respondents reported the care as received, indicating a gap in patient-centred care. Gaps were identified in relation to GP consultation (1 item), preparation (1 item), decision making for treatment (1 item), prognosis (6 items), and post-treatment follow-up (1 item). Overall, these results suggests that outpatients may benefit from increased information provision prior to their procedure, and also specific post-procedure information in relation to their prognosis. In particular, GP consultation and referral process and prognosis information warrant further examination. Whilst all four items that examined the GP consultation and referral process were rated as very important or essential by respondents, gaps in care were identified in relation to three of the items. However, for two of these items (what the cardiac catheterization procedure might show) and (likely next steps after the procedure), it should be noted that whilst the point estimates were less than 80%, their 95% CI did cross 80% threshold. It is also recognized that for these two items, GPs would not be considered the experts to know what the cardiac catheterization procedure may show and what the next steps may be. There may be an expectation from the GP that the cardiologist performing or ordering the test will explain these aspects. No other quantitative studies have been identified that have examined GP information provision at the point of referral for cardiology. However, whilst not specific to cardiac catheterization, it has been reported that ‘Communication between primary care physicians and specialists regarding referrals and consultations is often inadequate, with negative consequences for patients.’ Other research has also confirmed that patients have limited understanding of the procedure. For example, in a German cohort study of 200 patients prior to elective coronary angiography, whilst 95% of patients reported they had been well informed, less than half of the potential complications could be remembered by the patients. Further studies may be appropriate to address this current clinical deficit. Development of tailored written patient education resources for the primary care environment may offer a useful adjunct to patient care; alternatively, more detailed procedural information could be provided following specialist consultation. It should be noted not every cardiology referral will result in cardiac catheterization, which may influence the nature of the discussion between the GP and patient. The providing of prognostic information is a difficult topic to discuss with patients given the variable natural history of cardiovascular disease and difficulty in generalizing findings from population studies to individuals Furthermore, this study examined stable outpatients, so our results should be interpreted taking this into consideration. In this study, all six items that examined prognosis were endorsed by 80% or more of respondents as being essential or very important, with high endorsement ranging from 88.5 to 94.4%. These findings highlight the importance patients place on this information. A patient-centred care gap was identified in relation to all six items, with the percentage of patients indicating they received the item/information ranging from 13.9 to 59.4%. Whilst uncertainty of prognosis is acknowledged, this study indicates that patients could benefit from acknowledgement and discussion of the uncertainty in relation to these topics. The opportunity to address prognosis may also be limited within the procedural setting. It is also important to acknowledge that patient may also see more than one cardiologist, and thus from whom the patient receives any such information may differ. For example, the performing cardiologist may undertake the procedure and refer the patient back to another cardiologist who may be more likely to address patient information needs based on their ongoing therapeutic relationship. In our study, for the prognosis items we asked patients if their ‘healthcare team explained the chance of … [item]’. In addition, given the key role nurses have in cardiac care, including cardiac rehabilitation; future research could investigate from whom patients may expect or prefer this information to be received. Similar research has been performed in oncology, where additional work has been done in relation to methods for breaking bad news and discussing uncertainty regarding prognosis to patients. There are few other published studies on patient experiences of cardiac catheterization. Existing research has instead focused on patient experiences of pain and discomfort during the procedure, or has utilized other approaches, such as the Lean 6 Sigma approach to quality improvement. Such quality improvement work has commonly focussed on on-time patient and physician arrival, start time, and other clinical, organizational and procedural outcomes, including time-to-needle and other service-related factors, such as recovery statistics and MACE outcomes. Further research and publications are required to advance the field of patient experiences related to cardiac catheterization. One study conducted in Germany examined determinants of patient satisfaction after hospitalization for cardiac catheterization. However, that study examined satisfaction, rather than patient experiences, with Likert scale response options from ‘excellent’ to ‘very poor’. Thus, responses were evaluative, rather than examining actual experiences of care as in our study. In their study, the lowest ratings were reported for discharge procedures and instructions; patients were most satisfied with the kindness shown by medical practitioners and nurses. These findings similarly highlight the importance of the communication practices of healthcare professionals, with our study highlighting a particular need for caregivers to provide early procedural information and to also ensure detailed prognostic information is provided prior to discharge. No other study has examined the cardiac catheterization experience from the point of cardiologist referral to any subsequent cardiovascular procedures. Recent efforts to systematically measure data on patients’ perceptions of care quality have been implemented in several countries, including the USA and Australia. The suite of Picker Institute surveys are commonly used to assess patients’ experiences of care across eight patient-centred care domains. However, whilst such surveys are comprehensive, they do not reflect each sequence of the care pathway for patients undergoing cardiac catheterization, from referral through to treatment and follow-up care. Such nationwide surveys are also reported to not provide information at a local level suited for quality improvement. One of the advantages of this study was the ability to measure both patient importance, and experiences of care. Measuring components of care across the care pathway enables areas for improvement to be identified, and healthcare providers can use this format as quality assurance tool to identify areas for improvement, and areas of excellence. For example, future work could repeat these surveys at regular intervals as part of benchmarking and continuous quality improvement initiatives.
Sampling bias, due to recruitment from only one public outpatient Cardiac Catheterization Laboratory may limit the ability to generalize these findings to a broader population of cardiac catheterization patients. This study achieved a response rate of 45%; participation necessitated completion of a pen-and-paper survey and return via mail, which may have affected participant willingness to complete. However, survey completion rates of 35–40% are commonly reported for health research and considered acceptable for routine healthcare monitoring. The study measures were specifically designed for this research, and thus whilst content validity, considered the most important measurement property, has been established, examination of other psychometric properties should be considered as part of future work. In addition, the two surveys (the Important Care Survey and Actual Care Survey) were sent sequentially and completed by different samples of patients, whereby patients who had undergone cardiac catheterization 3–6 months ago answered the Important Care items, while patients who had undergone cardiac catheterization in the last 3 months answered the Actual Care items. This may have introduced some differences in perceptions and recall bias between the two different surveys, which need to be considered when interpreting the study results.
This study, designed to better understand how we can support patients before and after having cardiac catheterization and subsequent cardiovascular procedures, has provided new knowledge regarding patient experiences of cardiac catheterization. This study is novel in exploring all points in the cardiac catheterization pathway from the patient perspective to identify areas where care may be improved. This research highlights how care can be improved for future patients and the information gained in this study will be used to help develop ways to improve patient care and support both before and after cardiac procedures. The findings from this study suggest ways to address gaps across the care trajectory, particularly the GP consultation and referral process and prognosis information warrant investigation.
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A real-world based study for immunogenicity and safety for three immunization schedules of polio vaccine | 6e26b574-138a-4659-b992-1282adb53656 | 11842744 | Vaccination[mh] | In September 2015, the Global Polio Eradication Certification Committee announced the eradication of wild poliovirus type 2 (WPV2), prompting the World Health Organization (WHO) Strategic Advisory Committee to recommend a global discontinuation of using the type 2 polio vaccine component of oral poliovirus vaccine (OPV). In May 2016, 155 countries around the world, including China, simultaneously implemented a change in polio immunization strategies. At the same time, in response to the call from the World Health Organization (WHO) and the China government, Hebei Province also adjusted the vaccination strategy for polio vaccine. They ceased the use of trivalent OPV (tOPV) in their sequential immunization schedule and began using only bivalent OPV (bOPV) against poliovirus types 1 and 3 (PV1 and PV3) to prevent and control polio. Importantly, they also prioritized including at least one dose of inactivated polio vaccine (IPV) in their sequential immunization schedule to, as much as possible, avoid vaccine-associated paralytic poliomyelitis and circulating vaccine-derived poliovirus (cVDPV) caused by poliovirus types 2 (PV2) in the live polio vaccine while maintaining immunity to PV2, thus minimizing the potential risk of PV2 outbreaks – . Since January 2020, the routine polio vaccination program in Hebei Province has been adjusted to two doses of IPV followed by two doses of bOPV, that is, infants receive 1 dose of IPV at 2 months of age and 3 months of age respectively, and 1 dose of bOPV at 4 months of age and 4 years old respectively. The bOPV and IPV used in Hebei Province are both included in the Expanded Program on Immunization (EPI) schedule. Several studies have shown that the revised sequential polio immunization program combines the advantages of bOPV and IPV to reduce the incidence of vaccine associated paralytic poliomyelitis (VAPP) and to produce higher immunity against poliovirus – .The analysis conducted in this paper aimed to evaluate the immunogenicity and safety for three immunization schedules of polio vaccine, and to provide a basis for continuous improvement of the polio sequential immunization program.
Sample size Based on the Phase III clinical trial data for IPV from Beijing Institute of Biological Products Co., Ltd., positive conversion rate for Type I, Type II, and Type III antibodies were 96.2%, 93.8%, and 97.6%, respectively. The lowest positive conversion rate of 93.8% was selected as an indicator. Employing the formula \documentclass[12pt]{minimal}
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\begin{document}$$N = \left( {\frac{{Z_{{\left( {1 - \alpha } \right)}} + Z_{{\left( {1 - \beta } \right)}} }}{\delta }} \right)^{2} \cdot \pi _{0} \cdot \left( {1 - \pi _{0} } \right)$$\end{document} (α = 0.05, β = 0.01) to calculate, the calculated sample size was determined to be 50. Accounting for a dropout rate of 20%, the sample size was rounded up to 63, ensuring that the sample size per group is no less than 63 individuals. Research program The study was conducted a vaccination clinic in Hebei Province from June 1st to December 30th in 2018. Infants were included based on the following criteria: ① Age ≥ 2 months on the day of enrollment; ② The guardians of infants signed an informed consent form; ③ The guardians were able to participate in all follow-up plans and adhere to all research procedures; ④ The interval of the most recent vaccination was ≥ 14 days; ⑤ Healthy infants with a body temperature ≤ 37 °C, who had been physically examined and had their health status inquired by a clinical physician before entering the project. There were 216 individuals have provided their consent to participate in the experiment by signing the informed consent documents, and all of them have been enrolled in the study. Infants meeting the inclusion criteria were randomly divided into three immunization program groups: IPV-bOPV-bOPV (Group a), IPV-IPV-bOPV (Group b), and IPV-IPV-IPV (Group c), with 72 in each of groups a, b, and c. Eventually, due to the occurrence of withdrawl and migration, the number of infants who ultimately persevered through the study in the 3 groups was 69, 68, and 68, respectively. Active safety monitoring following polio vaccine administration was conducted on all 216 infants (Fig. ).The IPV and bOPV used in this research were both manufactured by Beijing Institute of Biological Products Co., Ltd., and were within their respective expiration dates. IPV: Liquid, each vial contains 0.5 mL; bOPV: Liquid, each vial contains 1.0 mL (for 10 doses). Immunogenicity study Vaccination procedure The three groups of infants received their first dose of the vaccine at 2 months of age (60–89 days post-birth), the second dose at 3 months of age (90–119 days post-birth), and the third dose at 4 months of age (120–149 days post-birth), with a 30-day interval between each vaccination. Serum sample collection Serum samples were collected at two time points: prior to the administration of the first dose of the vaccine at 2 months of age of infants, and 30 days after the administration of the third dose of the vaccine. Study endpoint This study is a non-inferiority study to evaluate the immunogenicity of different immunization schedules for polio vaccine, with the primary endpoint of positive conversion rate and antibody levels 30 days after the completion of vaccination procedure. Testing institutions and methods The detection of Type I and Type III poliovirus neutralizing antibodies was completed by the Polio Network Laboratory of the Beijing Center for Disease Prevention and Control. The detection of Type II poliovirus neutralizing antibodies was completed by Chinese Center for Disease Control and Prevention (CDC) using the micro-neutralization test to determine the poliovirus neutralizing antibodies. The tested serum was diluted fourfold with a nutrient solution prepared from cell culture medium (Minimum Eagle’s Medium, MEM) and inactivated at 56 °C in a water bath for 30 min, followed by further serum dilution. In a 96-well microtiter plate, 50 µl of MEM nutrient solution was added to each well, and inactivated serum samples (fourfold) were added to wells A1 to H1 (50 µl per well), with each serum sample added to two wells. Four samples of serum could be added per plate. Following this method, three plates were prepared, labeled for Type I, Type II, and Type III, respectively. A 12-channel pipette was used to mix from well A1 to H1, then 50 µl was drawn and serially diluted to wells A12 to H12, discarding 50 µl. Each batch of experiments included a virus control, a standard serum control, and a cell blank control, ensuring that the titer of the challenge virus was 100 CCID 50/0.05 ml and the cell suspension concentration was between 1.0 × 10 5 and 2.5 × 10 5 cells/ml. Immunogenicity indicators A neutralizing antibody titer of ≥ 1:8 is considered positive, indicating a protective effect against the poliovirus; a titer of < 1:8 before basic immunization and ≥ 1:8 after is considered a seroconversion, or an increase of 4-fold or more after basic immunization compared to before is also considered a seroconversion; poliovirus neutralizing antibody titers of < 8 are calculated as 4, and titers > 16,384 are calculated as 32,768 to determine the Geometric Mean Titer (GMT). Safety Surveillance Active monitoring All infants were observed on-site for 30 min after vaccination to collect and record any AEFI. Daily telephone follow-ups were conducted for seven consecutive days after each vaccine dose. Subsequently, a telephone follow-up was performed once a week until the next vaccination dose was administered. Referring to the literature , fever was categorized as follows: (1) Low-grade fever (≤ 38 °C); (2) Moderate fever (38.1–39 °C); (3) High fever (39.1–41 °C); (4) Extremely high fever (≥ 41 °C). Passive monitoring Data for AEFI reported in Hebei Province during the 3-year period, from January 2018 to December 2022, was collected through the NAEFISS. The yearly number of distributed doses of various vaccines in Hebei province during the study period was obtained from China Immunization Programming Information Management System and Vaccination Data Sheet. AEFI are classified into vaccine product-related reaction (includes common vaccine reactions and rare vaccine reactions), vaccine quality incident, program error, coincidental event and psychogenic reaction. According to severity, AEFI needs to be categorized into severe AEFI and non-severe AEFI. Each AEFI record needs to be followed up by the county-level CDC staff and mark the outcome of patients as cure, improved, required treatment, condition deteriorates, sequelae or death. Statistics analysis A database was organized as an Excel file (Microsoft Office Excel 2010), statistical analysis were performed by Stata 14.0 and SPSS 21.0. Quantitative data that were normally distributed are presented as mean ± standard deviation (‾x ± s), and group comparisons were made using analysis of variance (ANOVA). Quantitative data not normally distributed are represented by median and interquartile range [M(Q1, Q3)], with pre- and post-immunization GMT comparisons made using the Mann-Whitney U test. Group comparisons were conducted using the Kruskal-Wallis H test, and pairwise group comparisons were performed using the Nemenyi method. Categorical data were analyzed using the chi-square test and Fisher’s exact probability method, with a significance level of α = 0.05. Descriptive analysis was conducted for AEFI indicators, with the reporting rate of an AEFI for a vaccine (100 doses) = the number of AEFI reports / the number of vaccinations×100 doses. Statement All methods were performed in accordance with the relevant guidelines and regulations.
Based on the Phase III clinical trial data for IPV from Beijing Institute of Biological Products Co., Ltd., positive conversion rate for Type I, Type II, and Type III antibodies were 96.2%, 93.8%, and 97.6%, respectively. The lowest positive conversion rate of 93.8% was selected as an indicator. Employing the formula \documentclass[12pt]{minimal}
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\begin{document}$$N = \left( {\frac{{Z_{{\left( {1 - \alpha } \right)}} + Z_{{\left( {1 - \beta } \right)}} }}{\delta }} \right)^{2} \cdot \pi _{0} \cdot \left( {1 - \pi _{0} } \right)$$\end{document} (α = 0.05, β = 0.01) to calculate, the calculated sample size was determined to be 50. Accounting for a dropout rate of 20%, the sample size was rounded up to 63, ensuring that the sample size per group is no less than 63 individuals.
The study was conducted a vaccination clinic in Hebei Province from June 1st to December 30th in 2018. Infants were included based on the following criteria: ① Age ≥ 2 months on the day of enrollment; ② The guardians of infants signed an informed consent form; ③ The guardians were able to participate in all follow-up plans and adhere to all research procedures; ④ The interval of the most recent vaccination was ≥ 14 days; ⑤ Healthy infants with a body temperature ≤ 37 °C, who had been physically examined and had their health status inquired by a clinical physician before entering the project. There were 216 individuals have provided their consent to participate in the experiment by signing the informed consent documents, and all of them have been enrolled in the study. Infants meeting the inclusion criteria were randomly divided into three immunization program groups: IPV-bOPV-bOPV (Group a), IPV-IPV-bOPV (Group b), and IPV-IPV-IPV (Group c), with 72 in each of groups a, b, and c. Eventually, due to the occurrence of withdrawl and migration, the number of infants who ultimately persevered through the study in the 3 groups was 69, 68, and 68, respectively. Active safety monitoring following polio vaccine administration was conducted on all 216 infants (Fig. ).The IPV and bOPV used in this research were both manufactured by Beijing Institute of Biological Products Co., Ltd., and were within their respective expiration dates. IPV: Liquid, each vial contains 0.5 mL; bOPV: Liquid, each vial contains 1.0 mL (for 10 doses).
Vaccination procedure The three groups of infants received their first dose of the vaccine at 2 months of age (60–89 days post-birth), the second dose at 3 months of age (90–119 days post-birth), and the third dose at 4 months of age (120–149 days post-birth), with a 30-day interval between each vaccination. Serum sample collection Serum samples were collected at two time points: prior to the administration of the first dose of the vaccine at 2 months of age of infants, and 30 days after the administration of the third dose of the vaccine. Study endpoint This study is a non-inferiority study to evaluate the immunogenicity of different immunization schedules for polio vaccine, with the primary endpoint of positive conversion rate and antibody levels 30 days after the completion of vaccination procedure. Testing institutions and methods The detection of Type I and Type III poliovirus neutralizing antibodies was completed by the Polio Network Laboratory of the Beijing Center for Disease Prevention and Control. The detection of Type II poliovirus neutralizing antibodies was completed by Chinese Center for Disease Control and Prevention (CDC) using the micro-neutralization test to determine the poliovirus neutralizing antibodies. The tested serum was diluted fourfold with a nutrient solution prepared from cell culture medium (Minimum Eagle’s Medium, MEM) and inactivated at 56 °C in a water bath for 30 min, followed by further serum dilution. In a 96-well microtiter plate, 50 µl of MEM nutrient solution was added to each well, and inactivated serum samples (fourfold) were added to wells A1 to H1 (50 µl per well), with each serum sample added to two wells. Four samples of serum could be added per plate. Following this method, three plates were prepared, labeled for Type I, Type II, and Type III, respectively. A 12-channel pipette was used to mix from well A1 to H1, then 50 µl was drawn and serially diluted to wells A12 to H12, discarding 50 µl. Each batch of experiments included a virus control, a standard serum control, and a cell blank control, ensuring that the titer of the challenge virus was 100 CCID 50/0.05 ml and the cell suspension concentration was between 1.0 × 10 5 and 2.5 × 10 5 cells/ml. Immunogenicity indicators A neutralizing antibody titer of ≥ 1:8 is considered positive, indicating a protective effect against the poliovirus; a titer of < 1:8 before basic immunization and ≥ 1:8 after is considered a seroconversion, or an increase of 4-fold or more after basic immunization compared to before is also considered a seroconversion; poliovirus neutralizing antibody titers of < 8 are calculated as 4, and titers > 16,384 are calculated as 32,768 to determine the Geometric Mean Titer (GMT).
Active monitoring All infants were observed on-site for 30 min after vaccination to collect and record any AEFI. Daily telephone follow-ups were conducted for seven consecutive days after each vaccine dose. Subsequently, a telephone follow-up was performed once a week until the next vaccination dose was administered. Referring to the literature , fever was categorized as follows: (1) Low-grade fever (≤ 38 °C); (2) Moderate fever (38.1–39 °C); (3) High fever (39.1–41 °C); (4) Extremely high fever (≥ 41 °C). Passive monitoring Data for AEFI reported in Hebei Province during the 3-year period, from January 2018 to December 2022, was collected through the NAEFISS. The yearly number of distributed doses of various vaccines in Hebei province during the study period was obtained from China Immunization Programming Information Management System and Vaccination Data Sheet. AEFI are classified into vaccine product-related reaction (includes common vaccine reactions and rare vaccine reactions), vaccine quality incident, program error, coincidental event and psychogenic reaction. According to severity, AEFI needs to be categorized into severe AEFI and non-severe AEFI. Each AEFI record needs to be followed up by the county-level CDC staff and mark the outcome of patients as cure, improved, required treatment, condition deteriorates, sequelae or death.
A database was organized as an Excel file (Microsoft Office Excel 2010), statistical analysis were performed by Stata 14.0 and SPSS 21.0. Quantitative data that were normally distributed are presented as mean ± standard deviation (‾x ± s), and group comparisons were made using analysis of variance (ANOVA). Quantitative data not normally distributed are represented by median and interquartile range [M(Q1, Q3)], with pre- and post-immunization GMT comparisons made using the Mann-Whitney U test. Group comparisons were conducted using the Kruskal-Wallis H test, and pairwise group comparisons were performed using the Nemenyi method. Categorical data were analyzed using the chi-square test and Fisher’s exact probability method, with a significance level of α = 0.05. Descriptive analysis was conducted for AEFI indicators, with the reporting rate of an AEFI for a vaccine (100 doses) = the number of AEFI reports / the number of vaccinations×100 doses.
All methods were performed in accordance with the relevant guidelines and regulations.
Immunogenicity study Positive rate for neutralizing antibody and positive conversion rate Before immunization, there was no statistically significant difference in the positive rates for neutralizing antibodies among all types in groups a, b, and c ( P > 0.05), indicating that the levels of neutralizing antibodies before immunization were comparable across groups. After immunization, the positive rates for neutralizing antibodies for each type in all groups ranged from 98.53 to 100.00%, and the positive conversion rates ranged from 97.06 to 100.00%. There were no statistically significant differences in positive conversion rates among the groups for each type of neutralizing antibody ( P > 0.05) (Table ). The GMT levels of neutralizing antibodies Before and after immunization for groups a, b, and c, and for types I to III, all showed statistically significant differences ( P < 0.05). For type I, the differences between groups a and b, and between b and c were statistically significant. For type II, the differences between groups a and b, and between a and c were statistically significant. For type III, the differences among all groups were statistically significant. After primary immunization, the GMT levels of neutralizing antibodies in all three groups were the highest for type I, followed by type III, and the lowest for type II (Table ). Difference in the fold increase of polio neutralizing antibodies The differences for types II and III between different groups were statistically significant. For type I, there were no statistically significant differences among the three groups; for type II, all three groups showed statistically significant differences, with the GMT fold increase being group c > group b > group a; for type III, there were statistically significant differences between groups a and b, and between group b and c (Table ). Safety study by active surveillance The baseline characteristic of AEFI A total of 16 AEFI cases were reported, with a reporting rate of 2.52%. Group a collected 5 AEFI cases (2.23%), group b collected 2 AEFI cases (0.97%) and group c collected 9 AEFI cases (4.41%). The AEFI reporting rate in group b was lower than that in group c ( χ 2 = 4.683, P < 0.05). Clinical diagnosis of AEFI All 16 reported AEFI cases were common vaccine reactions, and presented with fever symptoms. There was 1 case of low-grade fever (0.16%), 11 cases of moderate fever (1.73%), and 4 cases of high fever (0.63%). The AEFI reporting rates for the three types of fever from highest to lowest were as follows: moderate fever, high fever, and low-grade fever ( χ 2 = 9.959, P < 0.05). No cases of VAPP or VDPV were detected (Table ). Time interval from vaccination to onset and outcome distribution All 16 AEFI cases occurred within 15–30 days post-vaccination, and all have fully recovered. Safety study by passive surveillance The baseline characteristic of AEFI cases From 2018 to 2022, a total of 2,903 AEFI cases were reported and 2,074,772 doses of vaccine were administered (group a: 1,108,960 doses, group b: 864,935 doses, group c: 100,877 doses), with a reported rate of 0.14%. The AEFI cases reported for groups a, b, and c were 1,489 cases (0.13%), 1,275 cases (0.15%), and 139 cases (0.14%), with the rate of AEFI in group b being higher than that in group a ( χ 2 = 6.000, P < 0.05). There were 2,837 cases of common vaccine reactions (0.14%), 52 cases of rare vaccine reactions (0.003%), and 14 cases of coincidental events (0.001%); 2,888 (0.14%) non-severe AEFI cases and 15 (0.001%) sever AEFI cases reported after vaccination (Table ). Clinical diagnosis of common and rare vaccine reactions Among the 2,837 cases of common vaccine reactions, fever were predominant, accounting for 2,261 cases (0.11%), followed by local redness and induration with 598 cases (0.03%) and 250 cases (0.01%). The reported rate of fever in Group b was higher than that in Group a ( χ 2 = 9.361, P < 0.05). Among the 52 cases of rare vaccine reactions, allergic reactions were the main type with 34 cases (0.002%), primarily consisting of allergic rashes with 21 cases (0.001%), followed by urticaria with 8 cases (0.001%). The reported rates of allergic reactions and other clinical diagnoses in the three groups showed no statistical significance ( P > 0.05). No cases of vaccine-derived poliovirus (VDPV) or vaccine-associated paralytic poliomyelitis (VAPP) were detected. (Table ). Interval between vaccination and onset There were 2,122 AEFI cases (73.10%) occurred < 1 d after vaccination and 781 AEFI cases (26.90%) occurred ≥ 1 d. Among 2,837 cases of common vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 2,079 (73.28%), 719 (25.34%), 37 (1.30%), and 2 (0.08%). Among 52 cases of rare vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 33 (63.46%), 14 (26.92%), 3 (5.77%) and 2 (3.85%). Outcome distribution 2,790 cases (96.11%) resulted in cured and improved, 111 cases (3.82%) of requiring treatment, and 2 cases (0.07%) of death (both were coincidental events).
Positive rate for neutralizing antibody and positive conversion rate Before immunization, there was no statistically significant difference in the positive rates for neutralizing antibodies among all types in groups a, b, and c ( P > 0.05), indicating that the levels of neutralizing antibodies before immunization were comparable across groups. After immunization, the positive rates for neutralizing antibodies for each type in all groups ranged from 98.53 to 100.00%, and the positive conversion rates ranged from 97.06 to 100.00%. There were no statistically significant differences in positive conversion rates among the groups for each type of neutralizing antibody ( P > 0.05) (Table ). The GMT levels of neutralizing antibodies Before and after immunization for groups a, b, and c, and for types I to III, all showed statistically significant differences ( P < 0.05). For type I, the differences between groups a and b, and between b and c were statistically significant. For type II, the differences between groups a and b, and between a and c were statistically significant. For type III, the differences among all groups were statistically significant. After primary immunization, the GMT levels of neutralizing antibodies in all three groups were the highest for type I, followed by type III, and the lowest for type II (Table ). Difference in the fold increase of polio neutralizing antibodies The differences for types II and III between different groups were statistically significant. For type I, there were no statistically significant differences among the three groups; for type II, all three groups showed statistically significant differences, with the GMT fold increase being group c > group b > group a; for type III, there were statistically significant differences between groups a and b, and between group b and c (Table ).
Before immunization, there was no statistically significant difference in the positive rates for neutralizing antibodies among all types in groups a, b, and c ( P > 0.05), indicating that the levels of neutralizing antibodies before immunization were comparable across groups. After immunization, the positive rates for neutralizing antibodies for each type in all groups ranged from 98.53 to 100.00%, and the positive conversion rates ranged from 97.06 to 100.00%. There were no statistically significant differences in positive conversion rates among the groups for each type of neutralizing antibody ( P > 0.05) (Table ).
Before and after immunization for groups a, b, and c, and for types I to III, all showed statistically significant differences ( P < 0.05). For type I, the differences between groups a and b, and between b and c were statistically significant. For type II, the differences between groups a and b, and between a and c were statistically significant. For type III, the differences among all groups were statistically significant. After primary immunization, the GMT levels of neutralizing antibodies in all three groups were the highest for type I, followed by type III, and the lowest for type II (Table ).
The differences for types II and III between different groups were statistically significant. For type I, there were no statistically significant differences among the three groups; for type II, all three groups showed statistically significant differences, with the GMT fold increase being group c > group b > group a; for type III, there were statistically significant differences between groups a and b, and between group b and c (Table ).
The baseline characteristic of AEFI A total of 16 AEFI cases were reported, with a reporting rate of 2.52%. Group a collected 5 AEFI cases (2.23%), group b collected 2 AEFI cases (0.97%) and group c collected 9 AEFI cases (4.41%). The AEFI reporting rate in group b was lower than that in group c ( χ 2 = 4.683, P < 0.05). Clinical diagnosis of AEFI All 16 reported AEFI cases were common vaccine reactions, and presented with fever symptoms. There was 1 case of low-grade fever (0.16%), 11 cases of moderate fever (1.73%), and 4 cases of high fever (0.63%). The AEFI reporting rates for the three types of fever from highest to lowest were as follows: moderate fever, high fever, and low-grade fever ( χ 2 = 9.959, P < 0.05). No cases of VAPP or VDPV were detected (Table ). Time interval from vaccination to onset and outcome distribution All 16 AEFI cases occurred within 15–30 days post-vaccination, and all have fully recovered.
A total of 16 AEFI cases were reported, with a reporting rate of 2.52%. Group a collected 5 AEFI cases (2.23%), group b collected 2 AEFI cases (0.97%) and group c collected 9 AEFI cases (4.41%). The AEFI reporting rate in group b was lower than that in group c ( χ 2 = 4.683, P < 0.05).
All 16 reported AEFI cases were common vaccine reactions, and presented with fever symptoms. There was 1 case of low-grade fever (0.16%), 11 cases of moderate fever (1.73%), and 4 cases of high fever (0.63%). The AEFI reporting rates for the three types of fever from highest to lowest were as follows: moderate fever, high fever, and low-grade fever ( χ 2 = 9.959, P < 0.05). No cases of VAPP or VDPV were detected (Table ).
All 16 AEFI cases occurred within 15–30 days post-vaccination, and all have fully recovered.
The baseline characteristic of AEFI cases From 2018 to 2022, a total of 2,903 AEFI cases were reported and 2,074,772 doses of vaccine were administered (group a: 1,108,960 doses, group b: 864,935 doses, group c: 100,877 doses), with a reported rate of 0.14%. The AEFI cases reported for groups a, b, and c were 1,489 cases (0.13%), 1,275 cases (0.15%), and 139 cases (0.14%), with the rate of AEFI in group b being higher than that in group a ( χ 2 = 6.000, P < 0.05). There were 2,837 cases of common vaccine reactions (0.14%), 52 cases of rare vaccine reactions (0.003%), and 14 cases of coincidental events (0.001%); 2,888 (0.14%) non-severe AEFI cases and 15 (0.001%) sever AEFI cases reported after vaccination (Table ). Clinical diagnosis of common and rare vaccine reactions Among the 2,837 cases of common vaccine reactions, fever were predominant, accounting for 2,261 cases (0.11%), followed by local redness and induration with 598 cases (0.03%) and 250 cases (0.01%). The reported rate of fever in Group b was higher than that in Group a ( χ 2 = 9.361, P < 0.05). Among the 52 cases of rare vaccine reactions, allergic reactions were the main type with 34 cases (0.002%), primarily consisting of allergic rashes with 21 cases (0.001%), followed by urticaria with 8 cases (0.001%). The reported rates of allergic reactions and other clinical diagnoses in the three groups showed no statistical significance ( P > 0.05). No cases of vaccine-derived poliovirus (VDPV) or vaccine-associated paralytic poliomyelitis (VAPP) were detected. (Table ). Interval between vaccination and onset There were 2,122 AEFI cases (73.10%) occurred < 1 d after vaccination and 781 AEFI cases (26.90%) occurred ≥ 1 d. Among 2,837 cases of common vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 2,079 (73.28%), 719 (25.34%), 37 (1.30%), and 2 (0.08%). Among 52 cases of rare vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 33 (63.46%), 14 (26.92%), 3 (5.77%) and 2 (3.85%).
From 2018 to 2022, a total of 2,903 AEFI cases were reported and 2,074,772 doses of vaccine were administered (group a: 1,108,960 doses, group b: 864,935 doses, group c: 100,877 doses), with a reported rate of 0.14%. The AEFI cases reported for groups a, b, and c were 1,489 cases (0.13%), 1,275 cases (0.15%), and 139 cases (0.14%), with the rate of AEFI in group b being higher than that in group a ( χ 2 = 6.000, P < 0.05). There were 2,837 cases of common vaccine reactions (0.14%), 52 cases of rare vaccine reactions (0.003%), and 14 cases of coincidental events (0.001%); 2,888 (0.14%) non-severe AEFI cases and 15 (0.001%) sever AEFI cases reported after vaccination (Table ).
Among the 2,837 cases of common vaccine reactions, fever were predominant, accounting for 2,261 cases (0.11%), followed by local redness and induration with 598 cases (0.03%) and 250 cases (0.01%). The reported rate of fever in Group b was higher than that in Group a ( χ 2 = 9.361, P < 0.05). Among the 52 cases of rare vaccine reactions, allergic reactions were the main type with 34 cases (0.002%), primarily consisting of allergic rashes with 21 cases (0.001%), followed by urticaria with 8 cases (0.001%). The reported rates of allergic reactions and other clinical diagnoses in the three groups showed no statistical significance ( P > 0.05). No cases of vaccine-derived poliovirus (VDPV) or vaccine-associated paralytic poliomyelitis (VAPP) were detected. (Table ).
There were 2,122 AEFI cases (73.10%) occurred < 1 d after vaccination and 781 AEFI cases (26.90%) occurred ≥ 1 d. Among 2,837 cases of common vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 2,079 (73.28%), 719 (25.34%), 37 (1.30%), and 2 (0.08%). Among 52 cases of rare vaccine reactions, the number of cases occurring < 1 d, 1−3 d, 4−14 d, ≥ 15 d after vaccination were 33 (63.46%), 14 (26.92%), 3 (5.77%) and 2 (3.85%).
2,790 cases (96.11%) resulted in cured and improved, 111 cases (3.82%) of requiring treatment, and 2 cases (0.07%) of death (both were coincidental events).
The reporting rates of AEFI and common vaccine reaction in active surveillance were higher than those in passive surveillance ( χ 2 = 239.307, 314.988, P < 0.05), while there was no statistically significant difference in the reporting rates of rare vaccine reactions between the two surveillance methods.
Since the goal of eradicating polio was set in 1988 and the Global Polio Eradication Initiative was launched worldwide, there has been a significant decline in polio cases globally, making polio the second infectious disease after smallpox that humanity hopes to eradicate . As of 2018, out of 194 countries/regions worldwide, 69 have included IPV in their national immunization programs, with 50 countries/regions adopting a full course of IPV, and 19 countries/regions using a strategy of administering IPV for the first 1–2 doses, followed by bOPV . This exploratory study could provide scientific data for future policy changes in China. In this study, the GMT of all types and all groups significantly increased compared to before the basic immunization, with the highest GMT levels for Type I, followed by Type III and the lowest for Type II. The reason might be that the first dose of all three vaccination schedules was IPV, which eliminated the interference and impact of Type II polio vaccine virus on Types I and III . The positive rate for neutralizing antibody and positive conversion rate for Types I, II, and III in all three groups were above 97.06%. However, the GMT and positive conversion rate for Type II antibodies were highest in Group c, followed by Group b and Group a, consistent with the findings of Hui Ye et al. and Qian Li et al. . The positive rate for neutralizing antibody for Types I and III in Groups a and Group b both reached 100.00%, in line with the results of Gao S et al. . The three immunization schedules were effective after the basic immunization, providing good immune protection against all three polio types, consistent with the results of related studies , . Active surveillance data indicates that the reporting rates of AEFI for the three immunization schedules are higher than those reported in China (0.03–0.1%) , Hebei (0.01–0.06%) , and Jilin Province (0.04–0.17%) . This could be attributed to the higher sensitivity of active surveillance, which allows for the timely acquisition of detailed information on AEFI occurrences. All AEFI cases were common vaccine reactions with moderate fever being the main type. All AEFI cases occurred within 15–30 days after vaccination, which differs from the finding reported in Jiangxi Province (mainly occurred within 2days after vaccination) . The specific reasons for this discrepancy warrant further investigation. No rare serious AEFI were detected during study period, and all cases have been cured. Passive surveillance data indicates that the overall reporting rate of AEFI is significantly higher than the findings reported in Guangxi Province (0.003%) and Shaanxi Province (0.01%) . This may be attributed to the incident of failure in the evaluation of the potency of acellular pertussis combined vaccine and the irregular production of rabies vaccines for human happened in 2018 which have likely heightened public awareness and concern about vaccine safety and AEFI, leading to a stronger willingness to report adverse events after vaccination. The common vaccine reactions are primarily fever and localized reactions at the injection site which are mild. Rare vaccine reactions are predominantly allergic reactions, possibly caused by the use of excipients or adjuvants, including magnesium chloride, during the production of bOPV. These reactions are mostly concentrated within one day after vaccination, with a generally positive outcome. This also suggests that caregivers should carefully inquire about the child’s allergy history and other relevant information from the guardian before vaccination. Additionally, no cases of VAPP or VDVP have been detected. Passive surveillance reports a significantly lower rate of AEFI and common vaccine reactions compared to active surveillance. On one hand, this may be attributed to the fact that vaccinees may neglect minor reactions and choose not to report them, thus making these cases undetectable by passive surveillance. On the other hand, current passive surveillance primarily relies on voluntary reporting by the parents and then reports are filled out and submitted by personnel from healthcare facility, CDC at any administrative levels, and vaccination units. Consequently, the reporting rate is influenced by multiple factors. Given various limitations, passive surveillance remains the primary method for monitoring the safety of post-marketing vaccines. The limitation of this study may include the following aspects. Firstly, the period of active surveillance is quite short, but we do our best to ensure that all researchers have standardized training and are able to guarantee the accuracy of the data. Secondly, for passive reporting system, number of mild AEFI may be easily neglected by healthcare workers and/or vaccinees to report resulting in underestimation of AEFI incidence rate.
All three immunization schedules for polio vaccine have demonstrated good immunogenicity and safety when administered to healthy populations. In particular, immunogenicity for Type II antibody was better when administering 3 doses of IPV than 2IPV + 1bOPV and 1IPV + 2bOPV program. Referring to the WHO’s recommendation, Hebei Province can gradually transition to a full IPV vaccination strategy considering the national policy and actual occurrence of poliomyelitis in neighboring countries.
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De-identification is not enough: a comparison between de-identified and synthetic clinical notes | b08e8eca-2f62-4fba-b4ee-24c9d0e2b044 | 11607336 | Psychiatry[mh] | Doctors write clinical notes for patients, which contain a wealth of information about the patient’s history, reason for admission, care received, medications administered, and the patient’s health progress from admission to discharge. These textual discharge notes are acknowledged for their rich information content . Applying Natural Language Processing techniques to this untapped wealth of information could revolutionize the healthcare industry. For instance, by using the clinical notes dataset, researchers are working to develop various classification/prediction models such as to identify diseases based on admission state data, to predict mortality rates, life expectancy, readmission rates at the ICU, length of stay under care, etc. – . Applications like these can improve patient outcomes, optimize resource utilization, and streamline healthcare operations. Extracting information from clinical notes is a difficult and ongoing research area. However, there is limited participation in this research area largely due to the challenge of accessing relevant healthcare data . The regulatory laws that govern the sharing and publishing of clinical notes, such as the Health Insurance Portability and Accountability Act (HIPAA) in the USA and the General Data Protection Regulation (GDPR) in the EU, rightfully restrict access to sensitive private data. HIPAA defines 18 types of data as protected health information (PHI) that must be redacted before data publication or sharing. Although de-identification may seem appealing, manual de-identification has been proven to be both expensive and prone to errors . In contrast, automated de-identification mechanisms cannot yet detect all the protected health information (PHI) tokens , . Furthermore, some de-identification models that exhibited strong performance in specific datasets have been observed to perform inadequately in other datasets . Researchers have mostly focused on the identity disclosure/re-identification risks of the clinical notes (e.g., , ). Recently, another type of privacy attack, the membership inference attack (MIA), has been introduced . In some cases, disclosing the membership to a dataset/machine learning model’s training set can become a very privacy-sensitive issue. Membership inference attack has been acknowledged as a serious breach of privacy (ref: NIST report ), and researchers have been continuously working to improve the success of the attack – . Consider a scenario where a machine learning classifier on a sensitive topic has been released, and this machine learning classifier was trained with de-identified clinical notes. Suppose that the nature of the classifier is so sensitive that disclosing membership information to its training dataset is damaging. Now, if an adversary somehow manages to get the doctor’s note of a target person, the adversary can de-identify it and mount a membership inference attack on the released model and find out with reasonable probability whether the person’s note was in the training dataset. Another application of membership inference attacks is that they are widely recognized as the “ de facto standard ” for practically evaluating a model’s privacy due to their straightforward implementation – . Consequently, the membership inference attack can be useful for identifying and measuring another kind of privacy vulnerability in machine learning models other than re-identification attacks. Although the membership inference attack has been previously mounted on models relying on structured health data , there are limited works that explored the MIA attacks on models that rely on textual clinical data. The privacy aspect of our work is unique from the existing works for bringing specific focus to de-identification and broader applicability (e.g., clinical note’s usage is not restricted to only ‘masked’ or ‘pre-trained’ language models; more on this in the “ ” section below). In this work, we demonstrated that de-identification of clinical notes does not protect a person’s clinical note from the membership inference attack. One potential solution to this privacy dilemma could be to generate and share synthetic clinical notes that preserve the information content of the original notes while respecting the regulatory requirements . Consequently, it is necessary to evaluate the quality of the synthetic notes, both in terms of utility and privacy, to determine whether they can effectively replace the original clinical notes in real-world applications and research. In this work, we also proposed a synthetic clinical note-generation approach using any pre-trained generative large language model (LLM). We evaluated the utility and privacy of the synthetic note generation approach using GPT-3.5. Related works Our privacy study is more aligned with the experimentation conducted by Vakili and Dalianis , but critical differences exist in the methodology and interpretation of the result. They concluded that the MIA attack fails to identify any privacy advantages gained by training the victim model with pseudonymized textual data. To point out the key differences with our privacy study, firstly, their proposed attack is restricted to pre-trained “masked” language models. More specifically, in their attack, they used what they refer to as “the normalized energy values,” which depend on a set of masking patterns (ref. section 2.2 ). Secondly, their clinical note usage significantly differs from our study in two aspects. Their masked model did not utilize the entire content of a MIMIC-III note. Their data points (i.e., notes under investigation) only comprised the sentences containing names. It is hard to imagine a medical application where only sentences containing names will be used. Lastly and most importantly, their perspective and conclusion are fundamentally different than ours. The authors claimed that since the MIA attack achieved similar success irrespective of whether a “real” or “pseudonymized” dataset is used, it “fails to detect the privacy benefits of pseudonymizing data” , and thus “such attacks may be inadequate for evaluating token-level privacy preservation of PIIs” . We agree with the validity of their conclusion, but we would like to point out that the question of whether MIA can evaluate token-level privacy (i.e., name alteration in this case) is not very pertinent regarding the objective of the MIA. The objective of the MIA attack is not to evaluate the token level privacy but rather to evaluate (infer) membership of the entire text content. We believe their conclusion should have been similar to ours, that pseudonymization does not protect notes from MIA attacks. In other words, the results from their study reinforce our findings although their study was focusing on a different aspect. The work by Jagannatha et al. performed MIA evaluation focusing very specifically on “pre-trained language models” (they experimented with GPT-2 and several variations of BERT). For GPT-2, the input comprises a token sequence, and the target is the next token in that sequence. For BERT and its variations, the input is the masked sequence, and the target is the masked tokens in those places. Our study is different in scope than their work as our study applies to any model that uses clinical notes for classification/prediction tasks. Moreover, if their adversary wishes to perform an MIA attack on a BERT-backed classification model, the adversary will require more intrusive access to the model than our adversary. In their black-box version, their adversary required access to the mean of the training error of the language model (ref. subsection 4.1.1, Jagannatha et al. ) and for the white-box version, they tried two variations: one required access to attention outputs from all the attention layers and the other required “ gradient values for each neural network layer by taking the squared-norm of all parameters in that layer ”. Lastly, their study was not focused on de-identification and thus did not provide any conclusion or remarks on the impact of de-identification on MIA attacks. Nonetheless, their experimental result on MIMIC-III notes reinforces our findings that the MIA attack is possible despite de-identification. The utility analyses of the synthetic clinical notes can be roughly categorized into three ways: (i) human evaluation (e.g., ), (ii) linguistic property-based metrics, and (iii) downstream-task-based metric. Currently, there is no agreement on how to measure the quality of synthetic clinical notes, which makes it difficult to evaluate their effectiveness. The linguistic property-based metrics such as BLEU, ROUGE, METEOR, adapted Levenstein distance, adapted KL-divergence, BERT-score, etc., have been used with synthetic medical records – . These metrics focus more on the token and sentence level similarity. Though linguistic utility metrics capture some syntactic quality, they usually fail to adequately capture the semantic content of the clinical notes, as highlighted in previous research studies , . On the other hand, human evaluation is costly and not time-efficient. Therefore, downstream-task-based evaluation could be a proper choice for measuring the quality of the generated notes. The downstream task-based evaluation compares the performance of the machine learning model trained with synthetic notes against models trained with real notes. Li et al. used four language generation models, namely- CharRNN, SeqGAN, GPT-2, and conditional transformers, to generate synthetic notes. They measured the performance of the synthetic notes on a named entity recognition (NER) task. They generated 500 notes (max sequence length: 256 tokens) and used the BLEU score as their initial quality metric. They found that the GPT-2 model produced the best BLEU (BLEU 1-4) scores among those four models. For the rest of their experimentation, they used the GPT-2 generated synthetic notes when they needed synthetic data. Their study used three Named Entity Recognizer instances to compare the quality of the synthetic text to natural text. These three NER models were trained on (i) only natural data, (ii) only synthetic data, and (iii) natural+synthetic data. The trained models (i) and (ii) were evaluated against different annotated natural corpora and synthetic data. Model (iii) was evaluated against one natural corpora only (570 notes, as mentioned earlier). The results were interesting. It showed that the model trained on synthetic data performed better than the model trained on natural data in one case. They gave a possible explanation that the 500 synthetic notes which were used in training dataset contained more named entities than the natural corpora. Hence, the synthetic models were trained better. Also, the augmented (natural+synthetic) NER classifier performed better, which was expected as its training dataset was relatively larger. Synthetic clinical text generation is a recent development. As pointed out by Li et al. , the previous works did not evaluate the utility of the notes even for common NLP tasks as basic as named entity recognition (NER). However, NER is not a core task in the healthcare sector, and this task cannot effectively measure the semantic or even syntactic quality of the synthetic text. On the other hand, the scarcity of research work in downstream-task-based evaluation is due to the fact that the usage of real clinical notes for a healthcare-related application is also scarce and has only begun to be investigated recently. Having discussed the various methods of evaluating synthetic clinical notes, we now turn to our contributions in this study to this field of research. Contributions Until recently, GPT-2 was shown to outperform other text generative models such as CharRNN, SeqGAN, and conditional transformers , . There have been major breakthroughs in the large generative language model arena with the release of huge pre-trained models. For example, the jump in the number of parameters from GPT-2 to GPT-3 is from 1.5 billion to 175 billion. This work particularly focuses on the recent prompt-based language generative models GPT-3.5-turbo. OpenAI mentioned in their model’s overview that GPT 3.5 is better than GPT-3. GPT 3.5 has been demonstrated to be able to generate human-like texts. For example, in simulated exams, GPT 3.5 is in the 87th percentile (score: 670/800) in SAT Evidence-Based Reading & Writing and in 54th percentile (score: 4/6) in Graduate Record Examination (GRE) Writing . GPT-3.5-turbo has a maximum window length (prompt+completion) of 4097 tokens. In this work, we made four core contributions to this research area, which are as follows: De-identification does not protect records from MIA attack De-identification was previously considered a sufficient privacy-preserving step to make clinical notes available for public usage . This study empirically demonstrated that de-identifying clinical notes fail to protect records from membership inference attacks. This finding has serious implications for cases where membership is a privacy-sensitive issue. Clinical notes generation using an LLM Our second contribution is proposing a novel way to generate synthetic clinical notes using a pre-trained large language model (e.g., GPT-3.5, GPT-4), where we create note-generating prompts by extracting key phrases from the real notes. A comparative experiment shows that the synthetic clinical notes closely follows the performance of the real notes even after using fewer number of key-phrases. Utility evaluation of synthetic clinical notes As there is no consensus on the utility metric of synthetic clinical notes, our third contribution is an empirical investigation of whether synthetic clinical notes can achieve comparable performance to real clinical notes. In this regard, we used the much-explored ICD code assignment (i.e., classification) problem as the target task. The ICD-9 code refers to the Ninth Revision of the International Classification of Diseases (ICD), a system used to code various diseases, conditions, and medical procedures. The ICD-9 code set was widely utilized for describing patient diagnoses, symptoms, and medical billing. Manual ICD-9 coding requires coders to have a specialized understanding of medicine, coding regulations, and medical terminologies . We measured the utility of the synthetic notes in terms of the performance of the underlying classifier against real notes when the classifier is trained using synthetic notes. Our experimentation showed that synthetic clinical notes attained a performance level close to real notes. Privacy evaluation of synthetic clinical notes Lastly, we demonstrated how a membership inference attack can be mounted when the underlying model is trained with synthetic textual data. Our proposed key-phrase-based synthetic note-generation technique follows a similar utility-privacy trade-off pattern observed in the real notes. Our literature review found no work that performed a membership inference attack on a machine-learning model trained with synthetic clinical notes. The novelty here is how the membership inference attack is mounted. In summary, we not only demonstrated the failure of de-identification to protect against MIA attacks but also made significant contributions to enhancing the methodology for generating synthetic clinical notes and evaluating their utility and privacy aspects. The rest of this article is organized as follows. “ ” section contains two sections: “ ”, and “ ”. The first subsection presents the results from mounting the membership inference attacks on the ICD-9 classifier instances. The impact of reducing the training-set size of the victim classifier on the success of the membership inference attack was investigated. We also investigated the impact of reducing the note length (i.e., less disclosed data) on the membership inference attack. The effect of these reductions on the ICD-9 classifiers’ performance is also shown, revealing the reduction mechanism’s utility-privacy trade-off. The second subsection presents the ICD-9 classification performance (on real test data) when instances of the classifier were trained and validated with the synthetic clinical notes. Similar to the previous subsection, we also present the utility and the privacy aspects and compare them with the real notes. The “ ” section explores the implications of this study and outlines potential future directions. Finally, in the “ ” section, we discussed our proposed techniques and the implementation details.
Our privacy study is more aligned with the experimentation conducted by Vakili and Dalianis , but critical differences exist in the methodology and interpretation of the result. They concluded that the MIA attack fails to identify any privacy advantages gained by training the victim model with pseudonymized textual data. To point out the key differences with our privacy study, firstly, their proposed attack is restricted to pre-trained “masked” language models. More specifically, in their attack, they used what they refer to as “the normalized energy values,” which depend on a set of masking patterns (ref. section 2.2 ). Secondly, their clinical note usage significantly differs from our study in two aspects. Their masked model did not utilize the entire content of a MIMIC-III note. Their data points (i.e., notes under investigation) only comprised the sentences containing names. It is hard to imagine a medical application where only sentences containing names will be used. Lastly and most importantly, their perspective and conclusion are fundamentally different than ours. The authors claimed that since the MIA attack achieved similar success irrespective of whether a “real” or “pseudonymized” dataset is used, it “fails to detect the privacy benefits of pseudonymizing data” , and thus “such attacks may be inadequate for evaluating token-level privacy preservation of PIIs” . We agree with the validity of their conclusion, but we would like to point out that the question of whether MIA can evaluate token-level privacy (i.e., name alteration in this case) is not very pertinent regarding the objective of the MIA. The objective of the MIA attack is not to evaluate the token level privacy but rather to evaluate (infer) membership of the entire text content. We believe their conclusion should have been similar to ours, that pseudonymization does not protect notes from MIA attacks. In other words, the results from their study reinforce our findings although their study was focusing on a different aspect. The work by Jagannatha et al. performed MIA evaluation focusing very specifically on “pre-trained language models” (they experimented with GPT-2 and several variations of BERT). For GPT-2, the input comprises a token sequence, and the target is the next token in that sequence. For BERT and its variations, the input is the masked sequence, and the target is the masked tokens in those places. Our study is different in scope than their work as our study applies to any model that uses clinical notes for classification/prediction tasks. Moreover, if their adversary wishes to perform an MIA attack on a BERT-backed classification model, the adversary will require more intrusive access to the model than our adversary. In their black-box version, their adversary required access to the mean of the training error of the language model (ref. subsection 4.1.1, Jagannatha et al. ) and for the white-box version, they tried two variations: one required access to attention outputs from all the attention layers and the other required “ gradient values for each neural network layer by taking the squared-norm of all parameters in that layer ”. Lastly, their study was not focused on de-identification and thus did not provide any conclusion or remarks on the impact of de-identification on MIA attacks. Nonetheless, their experimental result on MIMIC-III notes reinforces our findings that the MIA attack is possible despite de-identification. The utility analyses of the synthetic clinical notes can be roughly categorized into three ways: (i) human evaluation (e.g., ), (ii) linguistic property-based metrics, and (iii) downstream-task-based metric. Currently, there is no agreement on how to measure the quality of synthetic clinical notes, which makes it difficult to evaluate their effectiveness. The linguistic property-based metrics such as BLEU, ROUGE, METEOR, adapted Levenstein distance, adapted KL-divergence, BERT-score, etc., have been used with synthetic medical records – . These metrics focus more on the token and sentence level similarity. Though linguistic utility metrics capture some syntactic quality, they usually fail to adequately capture the semantic content of the clinical notes, as highlighted in previous research studies , . On the other hand, human evaluation is costly and not time-efficient. Therefore, downstream-task-based evaluation could be a proper choice for measuring the quality of the generated notes. The downstream task-based evaluation compares the performance of the machine learning model trained with synthetic notes against models trained with real notes. Li et al. used four language generation models, namely- CharRNN, SeqGAN, GPT-2, and conditional transformers, to generate synthetic notes. They measured the performance of the synthetic notes on a named entity recognition (NER) task. They generated 500 notes (max sequence length: 256 tokens) and used the BLEU score as their initial quality metric. They found that the GPT-2 model produced the best BLEU (BLEU 1-4) scores among those four models. For the rest of their experimentation, they used the GPT-2 generated synthetic notes when they needed synthetic data. Their study used three Named Entity Recognizer instances to compare the quality of the synthetic text to natural text. These three NER models were trained on (i) only natural data, (ii) only synthetic data, and (iii) natural+synthetic data. The trained models (i) and (ii) were evaluated against different annotated natural corpora and synthetic data. Model (iii) was evaluated against one natural corpora only (570 notes, as mentioned earlier). The results were interesting. It showed that the model trained on synthetic data performed better than the model trained on natural data in one case. They gave a possible explanation that the 500 synthetic notes which were used in training dataset contained more named entities than the natural corpora. Hence, the synthetic models were trained better. Also, the augmented (natural+synthetic) NER classifier performed better, which was expected as its training dataset was relatively larger. Synthetic clinical text generation is a recent development. As pointed out by Li et al. , the previous works did not evaluate the utility of the notes even for common NLP tasks as basic as named entity recognition (NER). However, NER is not a core task in the healthcare sector, and this task cannot effectively measure the semantic or even syntactic quality of the synthetic text. On the other hand, the scarcity of research work in downstream-task-based evaluation is due to the fact that the usage of real clinical notes for a healthcare-related application is also scarce and has only begun to be investigated recently. Having discussed the various methods of evaluating synthetic clinical notes, we now turn to our contributions in this study to this field of research.
Until recently, GPT-2 was shown to outperform other text generative models such as CharRNN, SeqGAN, and conditional transformers , . There have been major breakthroughs in the large generative language model arena with the release of huge pre-trained models. For example, the jump in the number of parameters from GPT-2 to GPT-3 is from 1.5 billion to 175 billion. This work particularly focuses on the recent prompt-based language generative models GPT-3.5-turbo. OpenAI mentioned in their model’s overview that GPT 3.5 is better than GPT-3. GPT 3.5 has been demonstrated to be able to generate human-like texts. For example, in simulated exams, GPT 3.5 is in the 87th percentile (score: 670/800) in SAT Evidence-Based Reading & Writing and in 54th percentile (score: 4/6) in Graduate Record Examination (GRE) Writing . GPT-3.5-turbo has a maximum window length (prompt+completion) of 4097 tokens. In this work, we made four core contributions to this research area, which are as follows: De-identification does not protect records from MIA attack De-identification was previously considered a sufficient privacy-preserving step to make clinical notes available for public usage . This study empirically demonstrated that de-identifying clinical notes fail to protect records from membership inference attacks. This finding has serious implications for cases where membership is a privacy-sensitive issue. Clinical notes generation using an LLM Our second contribution is proposing a novel way to generate synthetic clinical notes using a pre-trained large language model (e.g., GPT-3.5, GPT-4), where we create note-generating prompts by extracting key phrases from the real notes. A comparative experiment shows that the synthetic clinical notes closely follows the performance of the real notes even after using fewer number of key-phrases. Utility evaluation of synthetic clinical notes As there is no consensus on the utility metric of synthetic clinical notes, our third contribution is an empirical investigation of whether synthetic clinical notes can achieve comparable performance to real clinical notes. In this regard, we used the much-explored ICD code assignment (i.e., classification) problem as the target task. The ICD-9 code refers to the Ninth Revision of the International Classification of Diseases (ICD), a system used to code various diseases, conditions, and medical procedures. The ICD-9 code set was widely utilized for describing patient diagnoses, symptoms, and medical billing. Manual ICD-9 coding requires coders to have a specialized understanding of medicine, coding regulations, and medical terminologies . We measured the utility of the synthetic notes in terms of the performance of the underlying classifier against real notes when the classifier is trained using synthetic notes. Our experimentation showed that synthetic clinical notes attained a performance level close to real notes. Privacy evaluation of synthetic clinical notes Lastly, we demonstrated how a membership inference attack can be mounted when the underlying model is trained with synthetic textual data. Our proposed key-phrase-based synthetic note-generation technique follows a similar utility-privacy trade-off pattern observed in the real notes. Our literature review found no work that performed a membership inference attack on a machine-learning model trained with synthetic clinical notes. The novelty here is how the membership inference attack is mounted. In summary, we not only demonstrated the failure of de-identification to protect against MIA attacks but also made significant contributions to enhancing the methodology for generating synthetic clinical notes and evaluating their utility and privacy aspects. The rest of this article is organized as follows. “ ” section contains two sections: “ ”, and “ ”. The first subsection presents the results from mounting the membership inference attacks on the ICD-9 classifier instances. The impact of reducing the training-set size of the victim classifier on the success of the membership inference attack was investigated. We also investigated the impact of reducing the note length (i.e., less disclosed data) on the membership inference attack. The effect of these reductions on the ICD-9 classifiers’ performance is also shown, revealing the reduction mechanism’s utility-privacy trade-off. The second subsection presents the ICD-9 classification performance (on real test data) when instances of the classifier were trained and validated with the synthetic clinical notes. Similar to the previous subsection, we also present the utility and the privacy aspects and compare them with the real notes. The “ ” section explores the implications of this study and outlines potential future directions. Finally, in the “ ” section, we discussed our proposed techniques and the implementation details.
For all purposes of this study, we utilized the discharge summaries from the MIMIC-III dataset, which was de-identified. A discharge summary consolidates all pertinent information from a patient’s hospitalization into one comprehensive unstructured text document. Human coders assigned ICD-9 codes to each discharge summary. For synthetic note generation, we utilized the HIPAA-compliant Azure OpenAI platform provided by UTHealth in order to adhere to MIMIC-III’s data usage agreement requirement. Following the benchmark work for the utility aspect (ref. Table 2 in Vu et al. ), we limit ourselves to the discharge summary clinical notes and focus on the 50 most frequent ICD-9 codes as the classification targets. To assess the performance of the synthetic notes, micro- and macro-averaged values for AUC, precision, recall, and F1-score of the ICD-9 classifier were reported. Each pair of (clinical note, ICD-code) is treated as a distinct prediction to calculate the micro-averaged values. On the other hand, macro-averaged values are determined by computing metrics for each label and then averaging them. Classification precisions for top-k ICD-9 codes were also reported (k=1, 5, 8, 10, and 15). We mounted the membership inference attack as a privacy measurement technique (using the TensorFlow Privacy library released by Google; the details are discussed in the “ ” section). We used three attack models (membership inference classifiers) on real data: the K-nearest neighbor model, the multi-layer perceptron model, and the random forest model. Similar to , the random forest attack model achieved the highest attacker advantage. We used the results from the random forest attacker model for subsequent reporting. To assess the performance of the membership inference attack, we report the attacker’s advantage [12pt]{minimal}
$$(true\_positive\_rate(TPR) - false\_positive\_rate(FPR))$$ and the AUC. Membership inference attack on the real notes and the trade-off Our crucial finding is that the MIA attack was significantly successful despite the ICD-9 classifier being trained with de-identified real data. For the full training dataset with a maximum length of 4000 tokens for each note, the attacker had an advantage of 0.47 with an AUC of 0.79 (Fig. ). Table presents the performance of the ICD-9 code classifier and the membership attacker’s advantage on different training set sizes and note lengths. The ICD-9 classification score (F1) and the attacker’s advantage diminish gradually when the training-set size and the length of the notes decrease. However, this reduction in the attacker’s advantage came at the price of a drop in the ICD-9 classifier’s performance. Table shows the gradually declining precision with the reduction in the note length and the training set size. From these two tables, we observe the usual privacy-utility trade-off at play on the ICD-9 classifier. To reiterate our finding, as MIMIC-III clinical notes were already de-identified, this result demonstrates that membership inference attacks may become successful despite the absence of primary health identifier (PHI) tokens in the clinical notes. In other words, removing PHI tokens is not sufficient to provide full privacy. Performance of the synthetic notes The study we used as the benchmark utilized a window of 4000 tokens (byte-pair encoded). Due to using GPT-3.5-turbo, which is restricted to 4097 tokens (including both prompt and completion), we allocated a maximum of 3000 tokens for generating the synthetic notes. We reduced the training set to half (4033 notes) to reduce the time and the generating costs. We consider the performance of the benchmark classifier on this real dataset (4033 notes in the training set, note length of a maximum of 3000 tokens) as the baseline for our experiment. Our proposed algorithm for generating synthetic clinical notes has been described in the algorithm in “ ” section. The algorithm relies on extracting key phrases from real notes to prepare a prompt for the synthetic note generation. (Tables and present the performance of the ICD-9 code classifier on notes generated under three different amounts of key phrases. The synthetic notes show a small drop of 1–3 points in micro F1 and 1–4 points in macro F1 score. Similarly, the attacker’s advantage dropped by 2–5 points. In a similar study unrelated to the healthcare sector, GPT-2-large generated synthetic product reviews (of merely 100 tokens) dropped 16 points in accuracy when making predictions for a 45-class attribute, A2 . Our proposed approach of generating synthetic notes produces better notes with superior accuracy (a drop of ≈ 4–6 points) than the previous approaches. However, this synthetic note-generation approach has not yet solved the privacy dilemma. It demonstrates a clear privacy-utility trade-off where more key phrases produce better utility at the expense of less privacy.
Our crucial finding is that the MIA attack was significantly successful despite the ICD-9 classifier being trained with de-identified real data. For the full training dataset with a maximum length of 4000 tokens for each note, the attacker had an advantage of 0.47 with an AUC of 0.79 (Fig. ). Table presents the performance of the ICD-9 code classifier and the membership attacker’s advantage on different training set sizes and note lengths. The ICD-9 classification score (F1) and the attacker’s advantage diminish gradually when the training-set size and the length of the notes decrease. However, this reduction in the attacker’s advantage came at the price of a drop in the ICD-9 classifier’s performance. Table shows the gradually declining precision with the reduction in the note length and the training set size. From these two tables, we observe the usual privacy-utility trade-off at play on the ICD-9 classifier. To reiterate our finding, as MIMIC-III clinical notes were already de-identified, this result demonstrates that membership inference attacks may become successful despite the absence of primary health identifier (PHI) tokens in the clinical notes. In other words, removing PHI tokens is not sufficient to provide full privacy.
The study we used as the benchmark utilized a window of 4000 tokens (byte-pair encoded). Due to using GPT-3.5-turbo, which is restricted to 4097 tokens (including both prompt and completion), we allocated a maximum of 3000 tokens for generating the synthetic notes. We reduced the training set to half (4033 notes) to reduce the time and the generating costs. We consider the performance of the benchmark classifier on this real dataset (4033 notes in the training set, note length of a maximum of 3000 tokens) as the baseline for our experiment. Our proposed algorithm for generating synthetic clinical notes has been described in the algorithm in “ ” section. The algorithm relies on extracting key phrases from real notes to prepare a prompt for the synthetic note generation. (Tables and present the performance of the ICD-9 code classifier on notes generated under three different amounts of key phrases. The synthetic notes show a small drop of 1–3 points in micro F1 and 1–4 points in macro F1 score. Similarly, the attacker’s advantage dropped by 2–5 points. In a similar study unrelated to the healthcare sector, GPT-2-large generated synthetic product reviews (of merely 100 tokens) dropped 16 points in accuracy when making predictions for a 45-class attribute, A2 . Our proposed approach of generating synthetic notes produces better notes with superior accuracy (a drop of ≈ 4–6 points) than the previous approaches. However, this synthetic note-generation approach has not yet solved the privacy dilemma. It demonstrates a clear privacy-utility trade-off where more key phrases produce better utility at the expense of less privacy.
De-identification is often considered sufficient to ensure privacy. For example, the office of the Information and Privacy Commissioner of Ontario stated on their website the following . “De-identification protects the privacy of individuals because once de-identified, a data set is considered to no longer contain personal information. If a data set does not contain personal information, its use or disclosure cannot violate the privacy of individuals. Accordingly, the privacy protection provisions of the Freedom of Information and Protection of Privacy Act and Municipal Freedom of Information and Protection of Privacy Act would not apply to de-identified information.” We trained a machine learning classifier with de-identified clinical notes. We mounted a membership inference attack on the classifier and found the attack quite successful. This finding has far-reaching privacy implications for membership-sensitive models that use clinical notes in their training. The concern is that if an adversary obtains a target person’s clinical note, they could use a membership inference attack to determine with reasonable probability whether the person’s note was in the training dataset of the sensitive machine learning model. For example, similar to the re-identification scenarios mentioned by the European Medicines Agency , a person can be of significant public interest, leading to focused attention from the press or other entities. The adversary may plot a devious plan to get the clinical note and subsequently mount MIA attack. Or perhaps a random event occurs where an individual, familiar with a target participant came across the note and then tries to know the membership status. As a proactive precautionary step, our suggestion would be to refrain from publishing membership-sensitive models with full access to prediction probabilities until a better defense against this attack is developed. Our another main contribution is that we proposed a new approach to generate synthetic clinical notes and investigated whether these synthetic notes nullifies the membership inference attack. The pre-trained large language models, such as GPT-3.5, can generate synthetic clinical notes corresponding to the real notes. We have demonstrated that simply extracting key phrases from de-identified notes and instructing GPT to produce notes with those key phrases provide comparable utility like real notes but does not solve the membership inference attack. An important research topic in the future could be to investigate which features of the notes help distinguish between members and non-members in membership inference attacks. One interesting takeaway from our experiments is that reducing the number of key phrases to one-fourth (1000–250) does not drastically destroy the utility. This is a promising finding, as manipulating a small number of key phrases could solve this privacy dilemma, providing a better utility-privacy trade-off. The current landscape of pre-trained large language models is rapidly changing. The limitation in context windows that previously prohibited generating larger notes (e.g., 1024 tokens for GPT-2) is being overcome rapidly (e.g., 32k context length in GPT-4-32k) . As researchers and engineers continue to push the boundaries of language models, new architectures and training techniques are emerging to address the limitations of previous models. As a result, they will generate more accurate and contextually appropriate responses, making them increasingly valuable for real-world use cases. As the field continues to evolve, researchers should try to unlock the full potential of large language models, leading to groundbreaking and transformative applications. In conclusion, our research demonstrates the vulnerability of a machine learning model even when trained with de-identified data. We also provided a new algorithm for synthetic clinical note generation that performs comparably to real notes in a clinical domain task. The relatively small number of key phrases required to generate the synthetic notes might hold the key to the solution of the membership inference attack. Future research should continue to explore this promising approach.
The experimentation conducted in this paper relies on the methods presented in this section, which is divided into three subsections. The first subsection describes our proposed algorithm for generating synthetic clinical notes. The next subsection briefly describes a benchmark ICD-code classifier from the literature, which we used to measure the utility of the synthetic notes. The final subsection describes (i) the membership inference attack applied to the ICD-code classifier when trained with real data and (ii) our proposed attack strategy when the ICD-code classifier is trained with synthetic data. Synthetic clinical note generation Our proposed algorithm for synthetic clinical note generation consists of three main steps: (i) Keyword/key-phrase extraction, (ii) prompt creation, and (iii) note generation. For large language models, the quality of the generated text is primarily determined by the quality of the provided prompt. Our algorithm utilized key-phrase extraction to create the prompt for synthetic clinical note generation. Keyword/key-phrase extraction involves automatically extracting single or multiple-token phrases from a textual document that most effectively captures all essential aspects of its content. This process can be viewed as the automated generation of a concise document summary. Key-phrase extraction often serves as the foundational technology for document indexing, clustering, classification, and summarization . The reasoning behind utilizing key phrases in the prompt for synthetic clinical note generation is that, given key-phrases, synthetic note generation can be considered as the reverse task of key-phrase extraction. We hypothesized that a prompt containing the key-phrases in a certain orderly fashion (e.g., sorted by location of their appearance in the original note) would help the GPT to come up with a synthetic note that is similar to the original note in clinical aspects but different in the linguistic style (as many parts of the original note are not present in the key-phrases). We expected that since GPT will generate the synthetic note with somewhat different sentences than the original notes while maintaining the critical information pieces (i.e., key-phrases) in a similar order, it will provide utility similar to the original note while membership-privacy may be gained through the difference in the linguistic style of the sentences. It seemed a reasonable assumption considering a literary person may infer whether a text snippet is written by Shakespeare or not. Subtask: key-phrase extraction We used two key-phrase extraction algorithms, KP-miner and YAKE, to create prompts for generating synthetic notes. Both KP-Miner and YAKE are unsupervised keyword extraction algorithms that use certain statistical features of a document. KP-Miner leverages both the frequency and positional information of candidate keywords, incorporating a weighting mechanism for multi-token keywords. YAKE uses various statistics of the candidate keywords related to the position, frequency, context, etc., to create a score to rank the candidate keywords. In a survey , the statistical technique KP-miner has been found to be superior over nine other key-phrase extraction techniques (on tasks: Semeval, NUS, Krapivin). Another study found the best performance in indexing news articles using KP-miner and YAKE combinedly. We used open-source libraries for both KP-miner and YAKE . Subtask: key-phrase de-duplication For the de-duplication of key-phrases extracted by KP-miner, we utilized an open-source function from the fuzzywuzzy package that uses Levenshtein distance in the process for measuring similar key-phrases. Subtask: using an LLM for note generation The purpose of fine-tuning an LLM for clinical note generation is to adapt the model to specialized medical terminology, patient information context, structure, and domain knowledge. However, fine-tuning is not always necessary if the model’s pre-trained knowledge closely aligns with the desired output. In cases where only minimal structural adaptation is needed, prompt engineering may be sufficient to guide the LLM effectively. Additionally, fine-tuning may not be feasible if the LLM is hosted by a third party and privacy regulations prohibit sending private notes. Implementation detail We first preprocess the notes for keyword extraction according to . It removed numeric data from the notes and made all words lowercase. For key-phrases extraction using the KP-miner, we set its least allowable seen frequency (lasf) parameter to 1. For the YAKE algorithm, we kept the maximum n-gram size to default 3 and the de-duplication function to the default ‘sequencematcher’ function with a threshold of 0.70. After getting the keywords, we sort them based on the place of appearance in the note. We use this sorted sequence of phrases to merge and remove duplicate phrases. Finally, we use this list of phrases in the prompt for note generation. We used the same set of key-phrases for gpt-3.5-turbo-0301 and gpt-3.5-turbo-0613. The difference in the prompts is: in version-0301, the instruction that precedes the list of key phrases is “ Write a description of a patient using 2250 words containing the following phrases sequentially:[... comma-separated list of phrases...] ”. For gpt-3.5-turbo-0613, the preceding instruction was “ Write a description of a patient using 2250 words. The description should contain the following phrases sequentially: [... comma-separated list of phrases...] ”. Utility: ICD coding from clinical text To compare the synthetic notes’ utility aspect, we used the ICD-9 code classifier proposed in . This model employs a bidirectional Long-Short Term Memory (BiLSTM) encoder to learn label-specific vectors representing essential clinical text fragments related to specific ICD labels. They proposed a novel label attention mechanism. The final layer involves an array of 50 binary classifiers, one for each of the 50 most occurring ICD-9 codes. Figure presents the architecture of their model (they name it LAAT, short for Label Attention). At the time of its publication, this model was state-of-the-art (SOTA), and currently, it is slightly behind the new SOTA (Precision@15: 59.1 vs. 61.5 on the full test set; micro-F1: 57.5 vs. 59.9) . We adopt this model for the benchmark due to its open-source nature and simple architecture. Privacy: membership inference attack Threat model Our threat model is similar to the model described by Salem et al. (ref. section III, page 4 ). The attacker is a supervised binary classifier, distinguishing between members and non-members. The adversary has access to the victim’s original record and the knowledge of PHI fields (It is a reasonable assumption as HIPAA lists 18 categories of PHI attributes and notes are usually de-identified on those attributes). The adversary may or may not know the particular PHI de-identification algorithm used by the victim model, but knowing about the PHI token fields makes it possible to de-identify the note. To facilitate the training of this attack model, the adversary needs to obtain a labelled training dataset (clinical notes with ground truth membership information). The adversary accomplishes this by training a shadow model using a shadow dataset sourced from the identical underlying distribution to the target model’s training data. This approach aims to emulate the behaviour of the target model, relying on the shadow model to acquire the ground truth membership required for training the attack model. The shadow model is assumed to operate under the same algorithm and architecture as the target model. When using synthetic notes, it is assumed that the attacker also knows the synthetic note generation approach used by the victim classifier. Figure shows the conceptual architecture of the attack. It involves two classifiers: the victim classifier (in this experiment, the ICD-9 code classifier) and the membership-inference classifier (in this experiment, the MIA classifier from the TensorFlow-privacy library). The assumption is that the victim classifier will behave differently to training data than non-training data when it gets them as input. For example, it may predict the class label more confidently (i.e., higher probability). The attacker’s classifier is trained to capture this behaviour and distinguish between members and non-members, given the class prediction vector. Figure b shows how the attacker’s inference classifier is trained when the victim classifier is trained with real data. At first, the attacker trains a shadow model of the victim classifier with shadow data. After training, the attacker derives class prediction vectors for the shadow training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ , label: member) and the shadow non-training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Out}$$ , label: non-member). The attacker then trains a membership inference classifier on these labelled class prediction vectors. After the training is completed, the attacker uses the target’s prediction vector from the victim classifier as input to infer the target’s membership. Figure shows our proposed adaptation to how the attacker’s inference classifier is trained when the victim classifier is trained with synthetic data. In this scenario, there is a synthetic data generator that takes real data as input and produces synthetic data as output which is then used by the victim classifier (e.g., the ICD-9 code classifier) to train itself. The attacker assumes that the victim’s classifier, trained on synthetic data, may behave differently when it sees the real data that was used to train the synthetic data generator. Similar to the earlier scenario, the attacker gets two shadow datasets ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ marked in a green box and [12pt]{minimal}
$$D_{Shadow}^{Out}$$ marked in a brown box). The [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset is used to train a synthetic data generator, and a synthetic dataset sampled from this synthetic data generator is used to train the shadow victim model (i.e., the synthetic dataset is used to train the victim classifier, ICD-9 code classifier). Then, the attacker derives class prediction vectors from the victim model for the [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset (label: member) and non-training dataset [12pt]{minimal}
$$D_{Shadow}^{Out}$$ (label: non-member). The attacker then trains the membership inference classifier (e.g., the MIA classifier from the TensorFlow-privacy library) on these labelled class prediction vectors and uses this trained MIA classifier to infer the target’s membership. Experimental setup for tensorflow-privacy’s MIA In this work, we used TensorFlow Privacy library’s membership inference attack as released by Google Research . It has a different approach than the original attack proposed by Shokri et al. The attack does not involve training multiple shadow models as described in the original attack. Instead, it leverages the findings reported by Salem et al. Salem et al.’s approach uses one shadow model , eliminating the need to train multiple shadow models that approximate the original model’s behavior. In the TensorFlow Privacy’s MIA attack, the original model being targeted acts as the shadow model, perfectly approximating its behaviour. The purpose of a shadow model is to emulate the behavior of the victim model as closely as possible so that the attacker can acquire the ground truth membership required for training the attack model (i.e., prediction vectors of the training set are ‘member’ and prediction vectors of the testing set are ‘non-member’). Suppose the owner of a (victim) model wants to assess its MIA privacy state. To capture the worst-case leakage, the shadow model needed to behave the same as the target model. The TensorFlow-privacy library’s MIA attack does this exact replication of behaviour by making disjoint subsets of the victim’s training dataset and uses these disjoint subsets to act as both the shadow dataset and the target dataset (but not simultaneously, i.e., when one subset acts as the shadow dataset, another subset acts as the target dataset). When the attacker is trained, an equal number of member and non-member examples is chosen for the attacker training similar to Salem et al. (if member and non-member datasets are unequal in size, the attacker’s dataset size becomes the fewer of the two; uniform random sampling without replacement is used on the larger class). To get the membership scores of all samples, the experiment is done multiple times in a way that each example gets its score assigned only once. It uses StratifiedKFold (cross-validation folds = 2 by default) for this purpose. When the member and non-member datasets are unequal in size, the left-out samples of the larger dataset are evaluated using the last attacker. We believe that this approach in the TensorFlow-privacy’s MIA attack captures the worst leakage possible under Salem et al.’s MIA attack. It is a way to follow Murphy’s law: “Anything that can go wrong will go wrong and at the worst possible time.” Let us elaborate on the process with an example. Suppose the owner of the victim model has 4033 clinical notes for training and 1729 clinical notes for testing. The owner wishes to measure the susceptibility of the ICD-9 classifier to an MIA attack. The owner first trains the ICD-9 classifier on 4033 notes. Then, the owner gets the class prediction vectors of training data (4033 notes, label: member) and testing data (1729 notes, label: non-member). The owner then fed these labelled class prediction vectors (size: 4033 × 50 and 1729 × 50) to the TensorFlow-privacy’s MIA attack module. Since the member and non-member datasets are unequal in size, the attacker’s dataset contains 1729 member and 1729 non-member samples, where the 1729 ‘member’ samples were chosen by uniform random sampling without replacement from the 4033 samples). This resulted in 2304 left-out member samples. These 1729 member and 1729 non-member samples are used to train and test the attacker classifier via stratified 2-fold unshuffled sampling (In each fold, the attack model receive half of the 1729 member and 1729 non-member prediction vectors. The testing phase involves the other half of the 1729 member and 1729 non-member prediction vectors.). The second attack model (i.e., the attacker from the 2nd fold) is used to infer the membership of the 2304 leftout member samples, resulting in all the samples (1729 + 1729 + 2304) getting their membership assigned exactly once.(For details, check the [12pt]{minimal}
$$\_run\_trained\_attack()$$ ) To train the attacker’s inference classifier when the victim classifier (ICD-9 classifier) was trained with synthetic data, we first generated synthetic notes based on the real train and validation data. Then, we trained the ICD-9 classifier on these synthetic data. Then, we got the class prediction vectors of the real training data (label: member) and the real testing data (label: non-member). We then fed these labelled class prediction vectors to the random forest classifier for training as the attacker’s inference classifier. For replication purposes, here we describe the parameters that we configured. In the AttackInputData, we set “ multilabel_data = True ” because the ICD-9 classifier works with 50 classes. In the SlicingSpec, we set “ entire_dataset = True ”. Our attacks included threshold attack, random forest model, logistic regression, KNN, and multi-layer perceptron (set in attack_types ). During “ run_attacks ”, we set “ balance_attacker_training = True ”.
Our proposed algorithm for synthetic clinical note generation consists of three main steps: (i) Keyword/key-phrase extraction, (ii) prompt creation, and (iii) note generation. For large language models, the quality of the generated text is primarily determined by the quality of the provided prompt. Our algorithm utilized key-phrase extraction to create the prompt for synthetic clinical note generation. Keyword/key-phrase extraction involves automatically extracting single or multiple-token phrases from a textual document that most effectively captures all essential aspects of its content. This process can be viewed as the automated generation of a concise document summary. Key-phrase extraction often serves as the foundational technology for document indexing, clustering, classification, and summarization . The reasoning behind utilizing key phrases in the prompt for synthetic clinical note generation is that, given key-phrases, synthetic note generation can be considered as the reverse task of key-phrase extraction. We hypothesized that a prompt containing the key-phrases in a certain orderly fashion (e.g., sorted by location of their appearance in the original note) would help the GPT to come up with a synthetic note that is similar to the original note in clinical aspects but different in the linguistic style (as many parts of the original note are not present in the key-phrases). We expected that since GPT will generate the synthetic note with somewhat different sentences than the original notes while maintaining the critical information pieces (i.e., key-phrases) in a similar order, it will provide utility similar to the original note while membership-privacy may be gained through the difference in the linguistic style of the sentences. It seemed a reasonable assumption considering a literary person may infer whether a text snippet is written by Shakespeare or not. Subtask: key-phrase extraction We used two key-phrase extraction algorithms, KP-miner and YAKE, to create prompts for generating synthetic notes. Both KP-Miner and YAKE are unsupervised keyword extraction algorithms that use certain statistical features of a document. KP-Miner leverages both the frequency and positional information of candidate keywords, incorporating a weighting mechanism for multi-token keywords. YAKE uses various statistics of the candidate keywords related to the position, frequency, context, etc., to create a score to rank the candidate keywords. In a survey , the statistical technique KP-miner has been found to be superior over nine other key-phrase extraction techniques (on tasks: Semeval, NUS, Krapivin). Another study found the best performance in indexing news articles using KP-miner and YAKE combinedly. We used open-source libraries for both KP-miner and YAKE . Subtask: key-phrase de-duplication For the de-duplication of key-phrases extracted by KP-miner, we utilized an open-source function from the fuzzywuzzy package that uses Levenshtein distance in the process for measuring similar key-phrases. Subtask: using an LLM for note generation The purpose of fine-tuning an LLM for clinical note generation is to adapt the model to specialized medical terminology, patient information context, structure, and domain knowledge. However, fine-tuning is not always necessary if the model’s pre-trained knowledge closely aligns with the desired output. In cases where only minimal structural adaptation is needed, prompt engineering may be sufficient to guide the LLM effectively. Additionally, fine-tuning may not be feasible if the LLM is hosted by a third party and privacy regulations prohibit sending private notes. Implementation detail We first preprocess the notes for keyword extraction according to . It removed numeric data from the notes and made all words lowercase. For key-phrases extraction using the KP-miner, we set its least allowable seen frequency (lasf) parameter to 1. For the YAKE algorithm, we kept the maximum n-gram size to default 3 and the de-duplication function to the default ‘sequencematcher’ function with a threshold of 0.70. After getting the keywords, we sort them based on the place of appearance in the note. We use this sorted sequence of phrases to merge and remove duplicate phrases. Finally, we use this list of phrases in the prompt for note generation. We used the same set of key-phrases for gpt-3.5-turbo-0301 and gpt-3.5-turbo-0613. The difference in the prompts is: in version-0301, the instruction that precedes the list of key phrases is “ Write a description of a patient using 2250 words containing the following phrases sequentially:[... comma-separated list of phrases...] ”. For gpt-3.5-turbo-0613, the preceding instruction was “ Write a description of a patient using 2250 words. The description should contain the following phrases sequentially: [... comma-separated list of phrases...] ”.
We first preprocess the notes for keyword extraction according to . It removed numeric data from the notes and made all words lowercase. For key-phrases extraction using the KP-miner, we set its least allowable seen frequency (lasf) parameter to 1. For the YAKE algorithm, we kept the maximum n-gram size to default 3 and the de-duplication function to the default ‘sequencematcher’ function with a threshold of 0.70. After getting the keywords, we sort them based on the place of appearance in the note. We use this sorted sequence of phrases to merge and remove duplicate phrases. Finally, we use this list of phrases in the prompt for note generation. We used the same set of key-phrases for gpt-3.5-turbo-0301 and gpt-3.5-turbo-0613. The difference in the prompts is: in version-0301, the instruction that precedes the list of key phrases is “ Write a description of a patient using 2250 words containing the following phrases sequentially:[... comma-separated list of phrases...] ”. For gpt-3.5-turbo-0613, the preceding instruction was “ Write a description of a patient using 2250 words. The description should contain the following phrases sequentially: [... comma-separated list of phrases...] ”.
To compare the synthetic notes’ utility aspect, we used the ICD-9 code classifier proposed in . This model employs a bidirectional Long-Short Term Memory (BiLSTM) encoder to learn label-specific vectors representing essential clinical text fragments related to specific ICD labels. They proposed a novel label attention mechanism. The final layer involves an array of 50 binary classifiers, one for each of the 50 most occurring ICD-9 codes. Figure presents the architecture of their model (they name it LAAT, short for Label Attention). At the time of its publication, this model was state-of-the-art (SOTA), and currently, it is slightly behind the new SOTA (Precision@15: 59.1 vs. 61.5 on the full test set; micro-F1: 57.5 vs. 59.9) . We adopt this model for the benchmark due to its open-source nature and simple architecture.
Threat model Our threat model is similar to the model described by Salem et al. (ref. section III, page 4 ). The attacker is a supervised binary classifier, distinguishing between members and non-members. The adversary has access to the victim’s original record and the knowledge of PHI fields (It is a reasonable assumption as HIPAA lists 18 categories of PHI attributes and notes are usually de-identified on those attributes). The adversary may or may not know the particular PHI de-identification algorithm used by the victim model, but knowing about the PHI token fields makes it possible to de-identify the note. To facilitate the training of this attack model, the adversary needs to obtain a labelled training dataset (clinical notes with ground truth membership information). The adversary accomplishes this by training a shadow model using a shadow dataset sourced from the identical underlying distribution to the target model’s training data. This approach aims to emulate the behaviour of the target model, relying on the shadow model to acquire the ground truth membership required for training the attack model. The shadow model is assumed to operate under the same algorithm and architecture as the target model. When using synthetic notes, it is assumed that the attacker also knows the synthetic note generation approach used by the victim classifier. Figure shows the conceptual architecture of the attack. It involves two classifiers: the victim classifier (in this experiment, the ICD-9 code classifier) and the membership-inference classifier (in this experiment, the MIA classifier from the TensorFlow-privacy library). The assumption is that the victim classifier will behave differently to training data than non-training data when it gets them as input. For example, it may predict the class label more confidently (i.e., higher probability). The attacker’s classifier is trained to capture this behaviour and distinguish between members and non-members, given the class prediction vector. Figure b shows how the attacker’s inference classifier is trained when the victim classifier is trained with real data. At first, the attacker trains a shadow model of the victim classifier with shadow data. After training, the attacker derives class prediction vectors for the shadow training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ , label: member) and the shadow non-training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Out}$$ , label: non-member). The attacker then trains a membership inference classifier on these labelled class prediction vectors. After the training is completed, the attacker uses the target’s prediction vector from the victim classifier as input to infer the target’s membership. Figure shows our proposed adaptation to how the attacker’s inference classifier is trained when the victim classifier is trained with synthetic data. In this scenario, there is a synthetic data generator that takes real data as input and produces synthetic data as output which is then used by the victim classifier (e.g., the ICD-9 code classifier) to train itself. The attacker assumes that the victim’s classifier, trained on synthetic data, may behave differently when it sees the real data that was used to train the synthetic data generator. Similar to the earlier scenario, the attacker gets two shadow datasets ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ marked in a green box and [12pt]{minimal}
$$D_{Shadow}^{Out}$$ marked in a brown box). The [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset is used to train a synthetic data generator, and a synthetic dataset sampled from this synthetic data generator is used to train the shadow victim model (i.e., the synthetic dataset is used to train the victim classifier, ICD-9 code classifier). Then, the attacker derives class prediction vectors from the victim model for the [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset (label: member) and non-training dataset [12pt]{minimal}
$$D_{Shadow}^{Out}$$ (label: non-member). The attacker then trains the membership inference classifier (e.g., the MIA classifier from the TensorFlow-privacy library) on these labelled class prediction vectors and uses this trained MIA classifier to infer the target’s membership. Experimental setup for tensorflow-privacy’s MIA In this work, we used TensorFlow Privacy library’s membership inference attack as released by Google Research . It has a different approach than the original attack proposed by Shokri et al. The attack does not involve training multiple shadow models as described in the original attack. Instead, it leverages the findings reported by Salem et al. Salem et al.’s approach uses one shadow model , eliminating the need to train multiple shadow models that approximate the original model’s behavior. In the TensorFlow Privacy’s MIA attack, the original model being targeted acts as the shadow model, perfectly approximating its behaviour. The purpose of a shadow model is to emulate the behavior of the victim model as closely as possible so that the attacker can acquire the ground truth membership required for training the attack model (i.e., prediction vectors of the training set are ‘member’ and prediction vectors of the testing set are ‘non-member’). Suppose the owner of a (victim) model wants to assess its MIA privacy state. To capture the worst-case leakage, the shadow model needed to behave the same as the target model. The TensorFlow-privacy library’s MIA attack does this exact replication of behaviour by making disjoint subsets of the victim’s training dataset and uses these disjoint subsets to act as both the shadow dataset and the target dataset (but not simultaneously, i.e., when one subset acts as the shadow dataset, another subset acts as the target dataset). When the attacker is trained, an equal number of member and non-member examples is chosen for the attacker training similar to Salem et al. (if member and non-member datasets are unequal in size, the attacker’s dataset size becomes the fewer of the two; uniform random sampling without replacement is used on the larger class). To get the membership scores of all samples, the experiment is done multiple times in a way that each example gets its score assigned only once. It uses StratifiedKFold (cross-validation folds = 2 by default) for this purpose. When the member and non-member datasets are unequal in size, the left-out samples of the larger dataset are evaluated using the last attacker. We believe that this approach in the TensorFlow-privacy’s MIA attack captures the worst leakage possible under Salem et al.’s MIA attack. It is a way to follow Murphy’s law: “Anything that can go wrong will go wrong and at the worst possible time.” Let us elaborate on the process with an example. Suppose the owner of the victim model has 4033 clinical notes for training and 1729 clinical notes for testing. The owner wishes to measure the susceptibility of the ICD-9 classifier to an MIA attack. The owner first trains the ICD-9 classifier on 4033 notes. Then, the owner gets the class prediction vectors of training data (4033 notes, label: member) and testing data (1729 notes, label: non-member). The owner then fed these labelled class prediction vectors (size: 4033 × 50 and 1729 × 50) to the TensorFlow-privacy’s MIA attack module. Since the member and non-member datasets are unequal in size, the attacker’s dataset contains 1729 member and 1729 non-member samples, where the 1729 ‘member’ samples were chosen by uniform random sampling without replacement from the 4033 samples). This resulted in 2304 left-out member samples. These 1729 member and 1729 non-member samples are used to train and test the attacker classifier via stratified 2-fold unshuffled sampling (In each fold, the attack model receive half of the 1729 member and 1729 non-member prediction vectors. The testing phase involves the other half of the 1729 member and 1729 non-member prediction vectors.). The second attack model (i.e., the attacker from the 2nd fold) is used to infer the membership of the 2304 leftout member samples, resulting in all the samples (1729 + 1729 + 2304) getting their membership assigned exactly once.(For details, check the [12pt]{minimal}
$$\_run\_trained\_attack()$$ ) To train the attacker’s inference classifier when the victim classifier (ICD-9 classifier) was trained with synthetic data, we first generated synthetic notes based on the real train and validation data. Then, we trained the ICD-9 classifier on these synthetic data. Then, we got the class prediction vectors of the real training data (label: member) and the real testing data (label: non-member). We then fed these labelled class prediction vectors to the random forest classifier for training as the attacker’s inference classifier. For replication purposes, here we describe the parameters that we configured. In the AttackInputData, we set “ multilabel_data = True ” because the ICD-9 classifier works with 50 classes. In the SlicingSpec, we set “ entire_dataset = True ”. Our attacks included threshold attack, random forest model, logistic regression, KNN, and multi-layer perceptron (set in attack_types ). During “ run_attacks ”, we set “ balance_attacker_training = True ”.
Our threat model is similar to the model described by Salem et al. (ref. section III, page 4 ). The attacker is a supervised binary classifier, distinguishing between members and non-members. The adversary has access to the victim’s original record and the knowledge of PHI fields (It is a reasonable assumption as HIPAA lists 18 categories of PHI attributes and notes are usually de-identified on those attributes). The adversary may or may not know the particular PHI de-identification algorithm used by the victim model, but knowing about the PHI token fields makes it possible to de-identify the note. To facilitate the training of this attack model, the adversary needs to obtain a labelled training dataset (clinical notes with ground truth membership information). The adversary accomplishes this by training a shadow model using a shadow dataset sourced from the identical underlying distribution to the target model’s training data. This approach aims to emulate the behaviour of the target model, relying on the shadow model to acquire the ground truth membership required for training the attack model. The shadow model is assumed to operate under the same algorithm and architecture as the target model. When using synthetic notes, it is assumed that the attacker also knows the synthetic note generation approach used by the victim classifier. Figure shows the conceptual architecture of the attack. It involves two classifiers: the victim classifier (in this experiment, the ICD-9 code classifier) and the membership-inference classifier (in this experiment, the MIA classifier from the TensorFlow-privacy library). The assumption is that the victim classifier will behave differently to training data than non-training data when it gets them as input. For example, it may predict the class label more confidently (i.e., higher probability). The attacker’s classifier is trained to capture this behaviour and distinguish between members and non-members, given the class prediction vector. Figure b shows how the attacker’s inference classifier is trained when the victim classifier is trained with real data. At first, the attacker trains a shadow model of the victim classifier with shadow data. After training, the attacker derives class prediction vectors for the shadow training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ , label: member) and the shadow non-training dataset ( [12pt]{minimal}
$$D_{Shadow}^{Out}$$ , label: non-member). The attacker then trains a membership inference classifier on these labelled class prediction vectors. After the training is completed, the attacker uses the target’s prediction vector from the victim classifier as input to infer the target’s membership. Figure shows our proposed adaptation to how the attacker’s inference classifier is trained when the victim classifier is trained with synthetic data. In this scenario, there is a synthetic data generator that takes real data as input and produces synthetic data as output which is then used by the victim classifier (e.g., the ICD-9 code classifier) to train itself. The attacker assumes that the victim’s classifier, trained on synthetic data, may behave differently when it sees the real data that was used to train the synthetic data generator. Similar to the earlier scenario, the attacker gets two shadow datasets ( [12pt]{minimal}
$$D_{Shadow}^{Train}$$ marked in a green box and [12pt]{minimal}
$$D_{Shadow}^{Out}$$ marked in a brown box). The [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset is used to train a synthetic data generator, and a synthetic dataset sampled from this synthetic data generator is used to train the shadow victim model (i.e., the synthetic dataset is used to train the victim classifier, ICD-9 code classifier). Then, the attacker derives class prediction vectors from the victim model for the [12pt]{minimal}
$$D_{Shadow}^{Train}$$ dataset (label: member) and non-training dataset [12pt]{minimal}
$$D_{Shadow}^{Out}$$ (label: non-member). The attacker then trains the membership inference classifier (e.g., the MIA classifier from the TensorFlow-privacy library) on these labelled class prediction vectors and uses this trained MIA classifier to infer the target’s membership.
In this work, we used TensorFlow Privacy library’s membership inference attack as released by Google Research . It has a different approach than the original attack proposed by Shokri et al. The attack does not involve training multiple shadow models as described in the original attack. Instead, it leverages the findings reported by Salem et al. Salem et al.’s approach uses one shadow model , eliminating the need to train multiple shadow models that approximate the original model’s behavior. In the TensorFlow Privacy’s MIA attack, the original model being targeted acts as the shadow model, perfectly approximating its behaviour. The purpose of a shadow model is to emulate the behavior of the victim model as closely as possible so that the attacker can acquire the ground truth membership required for training the attack model (i.e., prediction vectors of the training set are ‘member’ and prediction vectors of the testing set are ‘non-member’). Suppose the owner of a (victim) model wants to assess its MIA privacy state. To capture the worst-case leakage, the shadow model needed to behave the same as the target model. The TensorFlow-privacy library’s MIA attack does this exact replication of behaviour by making disjoint subsets of the victim’s training dataset and uses these disjoint subsets to act as both the shadow dataset and the target dataset (but not simultaneously, i.e., when one subset acts as the shadow dataset, another subset acts as the target dataset). When the attacker is trained, an equal number of member and non-member examples is chosen for the attacker training similar to Salem et al. (if member and non-member datasets are unequal in size, the attacker’s dataset size becomes the fewer of the two; uniform random sampling without replacement is used on the larger class). To get the membership scores of all samples, the experiment is done multiple times in a way that each example gets its score assigned only once. It uses StratifiedKFold (cross-validation folds = 2 by default) for this purpose. When the member and non-member datasets are unequal in size, the left-out samples of the larger dataset are evaluated using the last attacker. We believe that this approach in the TensorFlow-privacy’s MIA attack captures the worst leakage possible under Salem et al.’s MIA attack. It is a way to follow Murphy’s law: “Anything that can go wrong will go wrong and at the worst possible time.” Let us elaborate on the process with an example. Suppose the owner of the victim model has 4033 clinical notes for training and 1729 clinical notes for testing. The owner wishes to measure the susceptibility of the ICD-9 classifier to an MIA attack. The owner first trains the ICD-9 classifier on 4033 notes. Then, the owner gets the class prediction vectors of training data (4033 notes, label: member) and testing data (1729 notes, label: non-member). The owner then fed these labelled class prediction vectors (size: 4033 × 50 and 1729 × 50) to the TensorFlow-privacy’s MIA attack module. Since the member and non-member datasets are unequal in size, the attacker’s dataset contains 1729 member and 1729 non-member samples, where the 1729 ‘member’ samples were chosen by uniform random sampling without replacement from the 4033 samples). This resulted in 2304 left-out member samples. These 1729 member and 1729 non-member samples are used to train and test the attacker classifier via stratified 2-fold unshuffled sampling (In each fold, the attack model receive half of the 1729 member and 1729 non-member prediction vectors. The testing phase involves the other half of the 1729 member and 1729 non-member prediction vectors.). The second attack model (i.e., the attacker from the 2nd fold) is used to infer the membership of the 2304 leftout member samples, resulting in all the samples (1729 + 1729 + 2304) getting their membership assigned exactly once.(For details, check the [12pt]{minimal}
$$\_run\_trained\_attack()$$ ) To train the attacker’s inference classifier when the victim classifier (ICD-9 classifier) was trained with synthetic data, we first generated synthetic notes based on the real train and validation data. Then, we trained the ICD-9 classifier on these synthetic data. Then, we got the class prediction vectors of the real training data (label: member) and the real testing data (label: non-member). We then fed these labelled class prediction vectors to the random forest classifier for training as the attacker’s inference classifier. For replication purposes, here we describe the parameters that we configured. In the AttackInputData, we set “ multilabel_data = True ” because the ICD-9 classifier works with 50 classes. In the SlicingSpec, we set “ entire_dataset = True ”. Our attacks included threshold attack, random forest model, logistic regression, KNN, and multi-layer perceptron (set in attack_types ). During “ run_attacks ”, we set “ balance_attacker_training = True ”.
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Association of Social Determinants of Health With Hospital Readmission and Mortality: A Prospective Cohort Study | 242d01fa-2aea-4317-9db9-d78c6eefd73d | 11540449 | Health Literacy[mh] | Study Setting and Design The Vanderbilt Inpatient Cohort Study (VICS) was a prospective longitudinal study of the impact of patient, social, and medical factors on post-discharge health outcomes such as quality of life, unplanned hospital utilization, and mortality in adults with ACS or acute decompensated heart failure (ADHF). The rationale and design of VICS are detailed elsewhere . Briefly, the framework that guided this study posits that demographic factors such as age, race, ethnicity, and socioeconomic status may influence health status, social support, and health literacy. As a result, those three factors may affect how patients interact with health systems, health care providers, and their disease self-management. Taken together, all factors may impact health outcomes such as functional status, health-related quality of life, unplanned health care utilization, and mortality. The study was approved by the Vanderbilt University Medical Center Institutional Review Board. Participants Research staff screened patients admitted to Vanderbilt University Hospital who presented with symptoms consistent with ADHF or an intermediate or high likelihood of ACS. A study hospitalist or cardiologist confirmed the diagnosis by reviewing the electronic health record (EHR). Exclusion criteria included: age younger than 18 years, non-English speaker, hearing or vision impairment, unstable psychiatric illness, delirium, low likelihood of follow-up (e.g., no reliable telephone number), on hospice, too ill to complete an interview, or prior enrollment in the study. Once patients with cardiovascular disease agreed to participate, written informed consent was obtained during hospitalization. Enrollment spanned from October 2011 to December 2015. Herein, we report on results for participants with ACS. An analysis of participants with ADHF has been reported previously . During participants' hospitalization, research assistants administered a 45-minute baseline interview at the bedside. Baseline measures included demographic characteristics such as age, gender, and self-reported race. Measures of Medical History Participants reported their number of hospitalizations in the prior year. Additionally, a comorbidity index, based on 30 conditions identified by Elixhauser, was calculated from billing codes from the index hospitalization and prior utilization . This single numerical index calculated from the 30 Elixhauser comorbidities had equivalent discrimination when compared to the inclusion of the 30 variables individually (c-statistic 0.763 vs 0.760, respectively), while conserving degrees of freedom. Measures of Social Support and Marital and Living Status We determined social support of family and friends prior to hospitalization using measures that characterize instrumental as well as emotional support. Instrumental support is the tangible support received from other people, their informal support network, and unmet personal needs . For instrumental support, we drew questions from: (1) the Health and Retirement Study, which quantified the number of friends and family members with whom they had close relationships ; and (2) the Midlife Development in the United States (MIDUS), which quantified the number and frequency of contacts, level of support from friends, families, and neighbors . To assess emotional support (e.g. someone to listen to them, give advice, show love and affection), we drew questions from the ENRICHD Social Support Inventory (ESSI), which has a Cronbach α of 0.86 and Pearson correlation coefficient (ρ) of 0.62 with the Perceived Social Support Scale ( ; ; The ENRICHD Investigators, 2000). Additionally, we asked participants their marital status and whether they lived alone. From their responses we created home status, a two-level categorical variable: married or living with someone versus not married and living alone. Measures of Health Literacy and Numeracy Health literacy is “the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions” . During the baseline interview, we assessed subjective health literacy using the 3-item Brief Health Literacy Screen (BHLS), scored on a 5-point Likert scale . We report the sum on a scale ranging from 3 to 15 points, with higher scores indicating higher health literacy. In the hospital setting, the Cronbach α is 0.79, and the Pearson correlation coefficient (ρ) was 0.48 when compared to s-TOFHLA . Numeracy is “the ability to use and understand numbers in daily life” . We measured numeracy using the 3-item Subjective Numeracy Scale (SNS-3). This self-reported measure captures participants' quantitative abilities with numerical data and preferences for numerical information. The SNS-3 is reported as a mean on a scale of 1 to 6. The SNS-3's Cronbach's α for internal reliability ranges from 0.67 to 0.86 for 7 study samples, and it correlates very highly with the original longer measure, the SNS-8 (range of ρ = 0.89 − 0.95) . Measures of SES Participants reported their highest level of education achieved and employment status. We assessed financial strain with a question: “How difficult is it for you (and your family) to pay your monthly bills?” Responses were reverse coded and ranged from 1, very difficult , to 4, not at all difficult . Outcome Measures The primary outcomes were a composite endpoint of all-cause readmission or death, assessed as time to event during the first 30 or 90 days after discharge. Readmission included hospitalization in any acute care hospital. Outcomes were compiled from the Vanderbilt EHR, participant report during follow-up phone calls, and a complete review of outside hospital records. Participants who died during the index hospitalization ( n = 23) were excluded from these analyses because they did not enter the follow-up period. Analysis We describe the VICS participants with ACS using proportions for categorical variables and percentiles (i.e., 25th, 50th, 75th) for quantitative variables. To test for unadjusted, covariate associations with readmission/death at 30 and 90 days, we used Pearson Chi-Square test and Wilcoxon Rank-Sum test for the categorical and quantitative variables, respectively. For primary analyses, we conducted multivariable Cox proportional hazards regression analyses to investigate associations between participant characteristics and the two dependent variables: time to readmission or death up to 30 days and time to readmission or death up to 90 days after discharge. We report hazard ratios, confidence intervals, and p values to describe adjusted associations with outcomes. Specifically, we report hazard ratios and confidence intervals associated with interquartile range changes in independent, continuous variables. Guided by the study's conceptual framework, and in addition to examining individual independent variable associations with outcomes, we report outcome associations with five independent variable domains--demographics, medical history, social support, health literacy/numeracy, and SES. We conducted domain-outcome association tests using likelihood ratio tests (LRT) with degrees of freedom equal to the number of parameters estimated for the domain. For these domain-specific associations, the LRT compares a model that excludes all variables in the domain to a model that includes them all, in both cases adjusting for all other independent variables. To further characterize the overall associations of the medical history, social support, health literacy/numeracy, and SES domains with time to readmission or death at 30 and 90 days, we examined association with simultaneous independent variable changes within each domain. Specifically, we examined time to readmission or death associations as follows: (1) for the medical history domain, a simultaneous 1 additional prior admission within 12 months and a 4.5 point increase in Elixhauser score; (2) for the social support domain, a 3 point increase in ESSI and living with someone versus living alone; (3) for the health literacy/numeracy domain, a 2.5 point increase in BHLS and 1 point increase in subjective numeracy; (4) for the SES domain, a 2 year increase in education and a 1 category increase in paying bills score (i.e. when reverse coded it is an increased ease of paying bills). The simultaneous changes in the quantitative variables correspond to approximately one-half interquartile range changes. To avoid case-wise deletion of records with missing covariates we conducted multiple imputation with five imputation samples using a predictive mean matching algorithm . Missingness rates were low. We conducted all analyses in R version 4.1.3 (R ) with packages rms and survival , and used 0.05-level significance tests.
The Vanderbilt Inpatient Cohort Study (VICS) was a prospective longitudinal study of the impact of patient, social, and medical factors on post-discharge health outcomes such as quality of life, unplanned hospital utilization, and mortality in adults with ACS or acute decompensated heart failure (ADHF). The rationale and design of VICS are detailed elsewhere . Briefly, the framework that guided this study posits that demographic factors such as age, race, ethnicity, and socioeconomic status may influence health status, social support, and health literacy. As a result, those three factors may affect how patients interact with health systems, health care providers, and their disease self-management. Taken together, all factors may impact health outcomes such as functional status, health-related quality of life, unplanned health care utilization, and mortality. The study was approved by the Vanderbilt University Medical Center Institutional Review Board.
Research staff screened patients admitted to Vanderbilt University Hospital who presented with symptoms consistent with ADHF or an intermediate or high likelihood of ACS. A study hospitalist or cardiologist confirmed the diagnosis by reviewing the electronic health record (EHR). Exclusion criteria included: age younger than 18 years, non-English speaker, hearing or vision impairment, unstable psychiatric illness, delirium, low likelihood of follow-up (e.g., no reliable telephone number), on hospice, too ill to complete an interview, or prior enrollment in the study. Once patients with cardiovascular disease agreed to participate, written informed consent was obtained during hospitalization. Enrollment spanned from October 2011 to December 2015. Herein, we report on results for participants with ACS. An analysis of participants with ADHF has been reported previously . During participants' hospitalization, research assistants administered a 45-minute baseline interview at the bedside. Baseline measures included demographic characteristics such as age, gender, and self-reported race.
Participants reported their number of hospitalizations in the prior year. Additionally, a comorbidity index, based on 30 conditions identified by Elixhauser, was calculated from billing codes from the index hospitalization and prior utilization . This single numerical index calculated from the 30 Elixhauser comorbidities had equivalent discrimination when compared to the inclusion of the 30 variables individually (c-statistic 0.763 vs 0.760, respectively), while conserving degrees of freedom.
We determined social support of family and friends prior to hospitalization using measures that characterize instrumental as well as emotional support. Instrumental support is the tangible support received from other people, their informal support network, and unmet personal needs . For instrumental support, we drew questions from: (1) the Health and Retirement Study, which quantified the number of friends and family members with whom they had close relationships ; and (2) the Midlife Development in the United States (MIDUS), which quantified the number and frequency of contacts, level of support from friends, families, and neighbors . To assess emotional support (e.g. someone to listen to them, give advice, show love and affection), we drew questions from the ENRICHD Social Support Inventory (ESSI), which has a Cronbach α of 0.86 and Pearson correlation coefficient (ρ) of 0.62 with the Perceived Social Support Scale ( ; ; The ENRICHD Investigators, 2000). Additionally, we asked participants their marital status and whether they lived alone. From their responses we created home status, a two-level categorical variable: married or living with someone versus not married and living alone.
Health literacy is “the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions” . During the baseline interview, we assessed subjective health literacy using the 3-item Brief Health Literacy Screen (BHLS), scored on a 5-point Likert scale . We report the sum on a scale ranging from 3 to 15 points, with higher scores indicating higher health literacy. In the hospital setting, the Cronbach α is 0.79, and the Pearson correlation coefficient (ρ) was 0.48 when compared to s-TOFHLA . Numeracy is “the ability to use and understand numbers in daily life” . We measured numeracy using the 3-item Subjective Numeracy Scale (SNS-3). This self-reported measure captures participants' quantitative abilities with numerical data and preferences for numerical information. The SNS-3 is reported as a mean on a scale of 1 to 6. The SNS-3's Cronbach's α for internal reliability ranges from 0.67 to 0.86 for 7 study samples, and it correlates very highly with the original longer measure, the SNS-8 (range of ρ = 0.89 − 0.95) .
Participants reported their highest level of education achieved and employment status. We assessed financial strain with a question: “How difficult is it for you (and your family) to pay your monthly bills?” Responses were reverse coded and ranged from 1, very difficult , to 4, not at all difficult .
The primary outcomes were a composite endpoint of all-cause readmission or death, assessed as time to event during the first 30 or 90 days after discharge. Readmission included hospitalization in any acute care hospital. Outcomes were compiled from the Vanderbilt EHR, participant report during follow-up phone calls, and a complete review of outside hospital records. Participants who died during the index hospitalization ( n = 23) were excluded from these analyses because they did not enter the follow-up period.
We describe the VICS participants with ACS using proportions for categorical variables and percentiles (i.e., 25th, 50th, 75th) for quantitative variables. To test for unadjusted, covariate associations with readmission/death at 30 and 90 days, we used Pearson Chi-Square test and Wilcoxon Rank-Sum test for the categorical and quantitative variables, respectively. For primary analyses, we conducted multivariable Cox proportional hazards regression analyses to investigate associations between participant characteristics and the two dependent variables: time to readmission or death up to 30 days and time to readmission or death up to 90 days after discharge. We report hazard ratios, confidence intervals, and p values to describe adjusted associations with outcomes. Specifically, we report hazard ratios and confidence intervals associated with interquartile range changes in independent, continuous variables. Guided by the study's conceptual framework, and in addition to examining individual independent variable associations with outcomes, we report outcome associations with five independent variable domains--demographics, medical history, social support, health literacy/numeracy, and SES. We conducted domain-outcome association tests using likelihood ratio tests (LRT) with degrees of freedom equal to the number of parameters estimated for the domain. For these domain-specific associations, the LRT compares a model that excludes all variables in the domain to a model that includes them all, in both cases adjusting for all other independent variables. To further characterize the overall associations of the medical history, social support, health literacy/numeracy, and SES domains with time to readmission or death at 30 and 90 days, we examined association with simultaneous independent variable changes within each domain. Specifically, we examined time to readmission or death associations as follows: (1) for the medical history domain, a simultaneous 1 additional prior admission within 12 months and a 4.5 point increase in Elixhauser score; (2) for the social support domain, a 3 point increase in ESSI and living with someone versus living alone; (3) for the health literacy/numeracy domain, a 2.5 point increase in BHLS and 1 point increase in subjective numeracy; (4) for the SES domain, a 2 year increase in education and a 1 category increase in paying bills score (i.e. when reverse coded it is an increased ease of paying bills). The simultaneous changes in the quantitative variables correspond to approximately one-half interquartile range changes. To avoid case-wise deletion of records with missing covariates we conducted multiple imputation with five imputation samples using a predictive mean matching algorithm . Missingness rates were low. We conducted all analyses in R version 4.1.3 (R ) with packages rms and survival , and used 0.05-level significance tests.
Figure displays the study flow diagram. Of 44,600 patient charts screened, 12,736 (28.6%) had confirmed diagnoses of ACS and/or ADHF. Of 12,736 patients, nearly 30% (3,763) met all eligibility criteria, 80% of whom enrolled. Of the 3,000 participants in the cohort, 2,977 participants were discharged alive. For these analyses, 1168 (39%) had ACS with no prior diagnosis of congestive heart failure. Tables and describe the ACS sample stratified by 30-day and 90-day death/readmission status, respectively. Overall, participants had a median age of 60 years and a median of 14 years of education ( Table ). There were 113 (9.7%) participants who were Black or African American, Asian, Native Hawaiian or other Pacific Islander, American Indian or Alaska Native, other underrepresented races, and unknown race, and 445 (38%) were female. Approximately 10% of participants ( n = 118) were readmitted or died within 30 days after discharge; 17% ( n = 206) were readmitted or died within 90 days ( Table ). In unadjusted tests, we observed statistically significant differences in the distributions of income, employment status, number of admissions in the past 12 months, health literacy, numeracy and difficulty paying bills, between participants who were readmitted or died at 30 and 90 days. Additionally, at 90 days there were significant differences in education, Elixhauser score, and social support. Table shows results from the multivariable Cox models for the 30- and 90-day outcomes. We display estimated hazard ratios, 95% confidence intervals and p values for individual variable associations with instantaneous rates of readmission or death within 30 and 90 days of discharge. We also report likelihood ratio test p values corresponding to outcome associations with key domains (i.e., groups of variables) and hazard ratio and 95% confidence interval estimates to characterize outcome associations with simultaneous changes in multiple variables within the social support, health literacy, and SES domains. For the 30-day analysis, prior admissions were positively associated with readmission or death ( HR = 1.32, 95% confidence interval [CI]: 1.11 − 1.58 per 2 prior admissions within the last year). The health literacy/numeracy domain was significantly associated with readmission or death (domain p = 0.016). A simultaneous increase in BHLS (2.5 points) and subjective numeracy (1 point) was associated with a hazard ratio of 0.76 (95% CI: 0.63 – 0.91). We did not observe an association between the social support or SES domains and readmission or death at 30 days after discharge. Figure shows individual variable and domain associated Chi-Square statistics as well as a measure of relative explained variability. We observed that the health literacy/numeracy domain explains far more variability than either of the socioeconomic position and social support domains ( Figures ), although medical history explained the most variability in time to readmission/death by 30 days post discharge. The 90-day Cox proportional hazard model was similar to the 30-day model; however, due to the larger number of events by 90 days, confidence interval widths are smaller. Prior admissions were significantly associated with readmission or death ( HR = 1.44, 95% CI: 1.27 − 1.62 per 2 prior admissions), and higher BHLS scores were associated with lower rates of readmission or death ( HR = 0.68, 95% CI: 0.53 − 0.86 per 5-point change). Overall, the medical history and health literacy/numeracy domains were associated with 90-day readmission or death (domain, p < .0001 and p < .002, respectively), though the SES domain was marginally associated (domain, p = .052). A simultaneous increase in BHLS (2.5 points) and subjective numeracy (1 point) scores was associated with a hazard ratio of 0.78 (95% CI: 0.68 – 0.90), and a simultaneous increase in education (2 years) and difficulty paying bills (1 category increase) was associated with a hazard ratio of 0.88 (95% CI: 0.75 − 1.03), which was marginally significant. We observed in Figure that medical history explained the most variability in time to readmission/death ( Figures ), but that the health literacy/numeracy domain explained far more variability than socioeconomic position and social support domains.
In this large cohort study of participants with ACS, we found complex associations between social determinants of health and post-discharge outcomes. After adjustment for prior health care utilization and medical comorbidities, the domain of health literacy/numeracy was independently associated with hospital readmission or death through 90 days post-discharge. SES was associated with outcomes in unadjusted analyses but was not statistically significant ( p = 0.052 and p = .072) in adjusted analyses. Surprisingly, social support, measured in a variety of ways, was unrelated to readmission or death when adjusting for other factors. This research demonstrates that, when these common social determinants of health are considered together, health literacy/numeracy has the most dominant and consistent effect on the post-discharge outcomes examined. Our findings have implications for the ongoing national dialogue on how social determinants of health affect hospital readmission rates and which factors may be most important to measure and address in hospitalized patients. Models for readmission vary in their predictive ability, depending on which types of variables are included. In our prior systematic review, we reported the majority of models used comorbidities and prior utilization to predict readmission with modest discrimination (c-statistics 0.6–0.77) . Interestingly, models that utilized administrative data as well as social determinants of health have demonstrated better predictive abilities. Yet, thus far there has been no agreement on what the most predictive social determinants of health are . No published models have included health literacy, which our findings suggest is an important omission. We found an independent association between health literacy/numeracy and outcomes among participants with ACS. Previously using data on participants from the same cohort who had acute decompensated heart failure (ADHF), we had also found health literacy was associated with greater medical complexity, including being admitted for ADHF for the index hospitalization and more hospitalizations in the prior year . Our prior finding supports the notion that health literacy has already exerted an effect on medical complexity which leads to readmissions and/or death. Moreover, the health literacy/numeracy domain is thought to affect post-discharge outcomes through effects on patients' self-management of their medical conditions. For example, medication use or ability to detect and respond to warning signs of clinical decompensation. The current results are consistent with other investigations which have demonstrated associations between health literacy and readmission rates for ACS . Further investigations into the mechanism by which health literacy/numeracy impacts self-management activities and risk for readmission are warranted for patients with cardiovascular disease. A few potential mediators particularly warranting study, which are known to be more common among patients with low health literacy/numeracy, are medication errors, medication nonadherence (particularly unintentional nonadherence), and missed follow-up appointments . Our hypothesis that a=dverse post-discharge outcomes would be related to poorer social support was noted in unadjusted results at 90 days, but its effect was attenuated by other factors in the adjusted models, which was surprising. Being a widow(er) or nonmarried have also been associated previously with increased risk of mortality in ACS . Perhaps the measures we utilized did not adequately capture the challenges patients with ACS face with regard to social support. We examined the overall direct effects of the specified social determinants of health on readmissions and mortality. From the same cohort, we found that health literacy indirectly affects 1-year mortality via worse health behaviors, lower perceived health competence, and more medical complexity, including comorbidities and being admitted for ADHF, but not via social support . In the present analysis, we did not examine moderating variables, such as severity of illness; therefore, it may be premature to conclude that social support is not predictive of post-discharge outcomes. Among patients with severe illness, prognosis may be determined primarily by physiologic factors, whereas in patients with less severe illness, health literacy and numeracy may play a greater role in prognosis through their effect on self-management. At present, we maintain that assessing social determinants of health for patients is critical to providing appropriate and equitable care , and they may manifest in other ways not measured here, ranging from patient satisfaction to medication safety. For example, health literacy sensitive materials should be used for patient discharge education as a commonsense approach . Additionally, social services and care transitions teams should determine hospitalized patients' social support to maximize success after discharge.
Our study's strengths include a large sample size including 38% women, minimal missing or incomplete data, multiple measures of health literacy and social support, and outcome assessment including data from any reported hospital. In fact, for the overall study 29% of first readmissions captured were to another facility. In contrast, we must consider the potential limitations. The participants came from one referral hospital, though they originated from more than 20 states. We excluded 2% of eligible patients from enrollment who lacked a stable phone number for follow up. These individuals might have experienced greater impact of social determinants of health on outcomes, so excluding them may bias our results toward the null. We focused on one health condition, ACS, so it is unclear how generalizable our results are to a wider hospitalized population. We had time horizons of 30- and 90-days follow-up for our readmissions and mortality data; however, these time points are relevant to current policies regarding readmission penalties and episodes of care. As with many psychosocial factors, mediating factors may influence the effect of social support and health literacy on outcomes (e.g. adherence, self-management), which we did not examine. We did not include environmental or neighborhood SES factors. Finally, the study relied on data from participant self-report, which is subject to reporting bias, although we used well-validated instruments, and patient-level social data are superior to community-level data .
In this cohort of participants hospitalized with ACS, we determined that health literacy/numeracy was significantly associated with readmission or mortality in the 30-to-90-day postdischarge period, when adjusting for other factors. Other social determinants of health were not consistently related to outcomes. Health literacy/numeracy warrant greater attention amidst growing national efforts to screen social determinants of health in hospital settings.
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Effect of behavior modification combined with health belief model education on adherence to skin moisturizing care in patients with psoriasis vulgaris | 45255d78-2f03-4587-b3ac-527c1e6e62ac | 11685565 | Patient Education as Topic[mh] | Psoriasis vulgaris is an immune-mediated condition characterized by an interplay of genetic, environmental, and immunological factors. Aberrant activation of dendritic cells and T-cells leads to overproduction of cytokines such as IL-17 and TNF-alpha, driving keratinocyte proliferation and inflammation. This disrupts skin barrier function, exacerbating symptoms recurring, chronic inflammatory skin condition characterized like scaling, erythema, and itching . Psoriasis vulgaris affects approximately 2–3% of the global population, with pathogenesis involving complex immune mechanisms. Current treatments primarily target cytokine pathways to control inflammation, but patient adherence to topical therapies remains a significant barrier to successful outcomes. Research has demonstrated that compromised skin barrier function is a pivotal factor in the development of psoriasis vulgaris . Addressing skin barrier repair can effectively alleviate clinical symptoms and prevent disease recurrence . Consequently, alongside conventional treatments, clinical emphasis should be placed on repairing the skin barrier . Skin moisturizing care plays a crucial role in restoring skin barrier function , , encompassing skin cleansing and the application of moisturizing emollients . Appropriate skin cleansing helps prevent exacerbation of skin barrier damage , improves patient comfort by removing scales, and eliminates harmful bacteria on the skin surface, thereby preventing infections and averting psoriasis recurrence. The application of moisturizing emollients post-cleansing aids in repairing the skin barrier, softening skin keratin, increasing skin moisture content, and reducing skin itching. Additionally, it enhances the effectiveness of other topical medications by improving skin permeability , . Research indicates that cognitive and behavioral levels of skin moisturizing care in patients with psoriasis vulgaris are relatively low . While domestic dermatologists acknowledge the importance of daily skin moisturizing care, enhancing patients’ adherence to it remains a significant challenge. Many patients exhibit insufficient compliance due to the time-consuming nature of daily moisturizer application, the inconvenience involved, and the need for assistance in applying to certain body parts. Cost concerns also contribute to reluctance, as the prolonged use of moisturizers for skin barrier repair may seem costly with unclear benefits. Weather-related factors, such as discomfort in winter and summer, further contribute to patients deviating from recommended cognitive behavior. It has been noted that a more positive attitude in patients correlates with a stronger willingness to act, leading to increased adherence to daily skin moisturizing care . Behavior modification has been shown to significantly improve adherence to care routines in chronic conditions, fostering sustained behavioral changes . In response to this cognitive behavior, efforts should be directed towards improving patients’ disease awareness, correcting poor behaviors, enhancing compliance, and alleviating symptoms. Objectives This study primarily explores the intervention effect of behavior modification combined with health belief model education on moisturizing care adherence in patients with psoriasis vulgaris, as detailed below.
This study primarily explores the intervention effect of behavior modification combined with health belief model education on moisturizing care adherence in patients with psoriasis vulgaris, as detailed below.
Participants We enrolled 108 patients diagnosed with psoriasis vulgaris admitted between November 1, 2022, and October 30, 2023, as our study participants. Participants were recruited as inpatient from the Dermatology Department of Hangzhou Third People’s Hospital during regular clinic hours. During the two-month intervention, educational sessions and behavior modification activities were conducted biweekly. These interventions were delivered by physician primarily face-to-face during inpatient, supplemented by WeChat online contact during outpatient. Ethics approval has been obtained from the Ethics Committee of The Third People’s Hospital of Hangzhou (No. 2022KAO49). Informed consent was obtained from all participants, who were over 18 years old and cognitively unimpaired, ensuring no involvement of legal guardians. All methods were performed in accordance with the relevant guidelines and regulations and was subject to the supervision of the Ethics Committee of The Third People’s Hospital of Hangzhou. Inclusion criteria comprised: (1) meeting the diagnostic criteria for psoriasis vulgaris ; (2) age over 18 years; (3) maintaining good mental health with no cognitive impairment; (4) providing informed and signed consent for participation. Exclusion criteria encompassed: (a) presence of other primary diseases, or allergies induced by food or drugs resulting in itching; (b) concurrent acute infectious diseases; (c) mental disorders or cognitive impairment hindering cooperation with the intervention; (d) involvement in other ongoing studies. Utilizing a randomized numerical table method, we allocated 54 cases to both the experimental and control groups. Study design and setting Both groups received standard medications for both internal and external application, specifically loratadine tablets at a dosage of 10 mg per administration, once daily, for a course of 10 days. The treatment’s effectiveness was evaluated after completing one course. Additionally, throughout the treatment period, external applications included pimecrolimus cream, compound flumethasone cream, vitamin E allantoin cream (I), and black light therapy. (i) Control group. The control group underwent standard nursing interventions, which encompassed the distribution of informational brochures and the implementation of health education. Patients were guided to adhere to the prescribed medication regimen, adopt a balanced diet, rectify detrimental habits, engage in suitable physical activities, sustain a positive psychological state, and refrain from scratching. This comprehensive intervention spanned a duration of two months. (ii) Experimental group. The intervention involved a combination of behavior modification, health belief model education, and nursing care. Initial data collection aimed to gather comprehensive information on patients, including their general details, disease history, treatment, skin condition, educational background, and family situation. The study’s purpose was then explained to establish rapport and trust with patients. Health belief model education and nursing: Assessment of Health Beliefs: Evaluate patients’ understanding and coping attitudes towards psoriasis, identifying adverse behaviors, psychological responses, willpower, comprehension, and treatment adherence. Health Education: Deliver personalized education using diverse methods like visuals, videos, and case studies to enhance patients’ knowledge of psoriasis. Assess their informational needs and encourage strict adherence to medical advice, providing guidance on diet and exercise. Psychological Intervention: Understand patients’ psychological states, address negative emotions promptly, and foster positive health beliefs. 2. Behavior modification: Awareness Training: Communicate the significance of moisturizing care, utilizing visuals of aggravated symptoms due to poor compliance. Issue self-supervision cards, instructing patients to record moisturizing details to reinforce the importance. Behavioral Assessment: Analyze self-monitoring card data to infer causes of weak compliance, patient psychology during care, and factors influencing symptom severity. Guide patients to identify and monitor symptoms for timely control. Behavioral Training: Instruct patients to enact counteractive changes when signs of psychological and behavioral abnormalities emerge, using visuals to counter misconceptions. Control of Change: Implement supervision and reminders to correct behavior when changes fall short. Results Evaluation and Cognitive Consolidation: Assess patients’ cognitive mastery and encourage continued training for those with successful implementation. For those with insufficient implementation, identify influencing factors and provide targeted guidance to strengthen health beliefs, enhance awareness, and improve implementation. The entire intervention spanned two months. Observational indicators Itch assessment: Before and after the intervention, the Pruritus Scale was employed to evaluate patients’ itching severity, frequency, and affected area, using a total score of 10. Higher scores indicated more pronounced itching. Self-efficacy evaluation: The General Self-Efficacy Scale (GSES) was administered pre- and post-intervention to gauge patients’ self-efficacy. This Chinese version, comprising 10 items, used a scoring system of 1–4 points for “never,” “occasionally,” “often,” and “always.” Elevated scores denoted enhanced self-efficacy. Medication adherence assessment: The MORISKY Medication Adherence Questionnaire (MMAS8) was utilized before and after the intervention. The scale, featuring 8 items, included true/false questions with scores of 0 for correct and 1 for incorrect responses. The eighth question offered a range of responses, from “all the time” (0 points) to “never” (1 point). Scores were inversely correlated with patient adherence, with a maximum score of 8. Quality of life measurement: The Dermatologic Quality of Life Index (DLQI) was employed pre- and post-intervention. This index encompassed six dimensions—symptom perception, daily life, leisure and recreation, work and study, interpersonal relationships, and treatment—summing up to a total of 30 points. Higher scores indicated a diminished quality of life. Statistical methods The data analysis employed SPSS 23.0 statistical software. Descriptive statistics were used for measurement data, expressed as mean ± standard deviation (mean ± SD), with the t-test applied. Count data were presented as the number of cases and percentage, analyzed using the χ2 test. For ordinal data, the rank and test method was utilized. Ordinal data were analyzed using the Mann-Whitney U test for non-parametric comparisons. Statistical significance was determined at P < 0.05.
We enrolled 108 patients diagnosed with psoriasis vulgaris admitted between November 1, 2022, and October 30, 2023, as our study participants. Participants were recruited as inpatient from the Dermatology Department of Hangzhou Third People’s Hospital during regular clinic hours. During the two-month intervention, educational sessions and behavior modification activities were conducted biweekly. These interventions were delivered by physician primarily face-to-face during inpatient, supplemented by WeChat online contact during outpatient. Ethics approval has been obtained from the Ethics Committee of The Third People’s Hospital of Hangzhou (No. 2022KAO49). Informed consent was obtained from all participants, who were over 18 years old and cognitively unimpaired, ensuring no involvement of legal guardians. All methods were performed in accordance with the relevant guidelines and regulations and was subject to the supervision of the Ethics Committee of The Third People’s Hospital of Hangzhou. Inclusion criteria comprised: (1) meeting the diagnostic criteria for psoriasis vulgaris ; (2) age over 18 years; (3) maintaining good mental health with no cognitive impairment; (4) providing informed and signed consent for participation. Exclusion criteria encompassed: (a) presence of other primary diseases, or allergies induced by food or drugs resulting in itching; (b) concurrent acute infectious diseases; (c) mental disorders or cognitive impairment hindering cooperation with the intervention; (d) involvement in other ongoing studies. Utilizing a randomized numerical table method, we allocated 54 cases to both the experimental and control groups.
Both groups received standard medications for both internal and external application, specifically loratadine tablets at a dosage of 10 mg per administration, once daily, for a course of 10 days. The treatment’s effectiveness was evaluated after completing one course. Additionally, throughout the treatment period, external applications included pimecrolimus cream, compound flumethasone cream, vitamin E allantoin cream (I), and black light therapy. (i) Control group. The control group underwent standard nursing interventions, which encompassed the distribution of informational brochures and the implementation of health education. Patients were guided to adhere to the prescribed medication regimen, adopt a balanced diet, rectify detrimental habits, engage in suitable physical activities, sustain a positive psychological state, and refrain from scratching. This comprehensive intervention spanned a duration of two months. (ii) Experimental group. The intervention involved a combination of behavior modification, health belief model education, and nursing care. Initial data collection aimed to gather comprehensive information on patients, including their general details, disease history, treatment, skin condition, educational background, and family situation. The study’s purpose was then explained to establish rapport and trust with patients. Health belief model education and nursing: Assessment of Health Beliefs: Evaluate patients’ understanding and coping attitudes towards psoriasis, identifying adverse behaviors, psychological responses, willpower, comprehension, and treatment adherence. Health Education: Deliver personalized education using diverse methods like visuals, videos, and case studies to enhance patients’ knowledge of psoriasis. Assess their informational needs and encourage strict adherence to medical advice, providing guidance on diet and exercise. Psychological Intervention: Understand patients’ psychological states, address negative emotions promptly, and foster positive health beliefs. 2. Behavior modification: Awareness Training: Communicate the significance of moisturizing care, utilizing visuals of aggravated symptoms due to poor compliance. Issue self-supervision cards, instructing patients to record moisturizing details to reinforce the importance. Behavioral Assessment: Analyze self-monitoring card data to infer causes of weak compliance, patient psychology during care, and factors influencing symptom severity. Guide patients to identify and monitor symptoms for timely control. Behavioral Training: Instruct patients to enact counteractive changes when signs of psychological and behavioral abnormalities emerge, using visuals to counter misconceptions. Control of Change: Implement supervision and reminders to correct behavior when changes fall short. Results Evaluation and Cognitive Consolidation: Assess patients’ cognitive mastery and encourage continued training for those with successful implementation. For those with insufficient implementation, identify influencing factors and provide targeted guidance to strengthen health beliefs, enhance awareness, and improve implementation. The entire intervention spanned two months.
Itch assessment: Before and after the intervention, the Pruritus Scale was employed to evaluate patients’ itching severity, frequency, and affected area, using a total score of 10. Higher scores indicated more pronounced itching. Self-efficacy evaluation: The General Self-Efficacy Scale (GSES) was administered pre- and post-intervention to gauge patients’ self-efficacy. This Chinese version, comprising 10 items, used a scoring system of 1–4 points for “never,” “occasionally,” “often,” and “always.” Elevated scores denoted enhanced self-efficacy. Medication adherence assessment: The MORISKY Medication Adherence Questionnaire (MMAS8) was utilized before and after the intervention. The scale, featuring 8 items, included true/false questions with scores of 0 for correct and 1 for incorrect responses. The eighth question offered a range of responses, from “all the time” (0 points) to “never” (1 point). Scores were inversely correlated with patient adherence, with a maximum score of 8. Quality of life measurement: The Dermatologic Quality of Life Index (DLQI) was employed pre- and post-intervention. This index encompassed six dimensions—symptom perception, daily life, leisure and recreation, work and study, interpersonal relationships, and treatment—summing up to a total of 30 points. Higher scores indicated a diminished quality of life.
The data analysis employed SPSS 23.0 statistical software. Descriptive statistics were used for measurement data, expressed as mean ± standard deviation (mean ± SD), with the t-test applied. Count data were presented as the number of cases and percentage, analyzed using the χ2 test. For ordinal data, the rank and test method was utilized. Ordinal data were analyzed using the Mann-Whitney U test for non-parametric comparisons. Statistical significance was determined at P < 0.05.
Population characteristics of the experimental and control groups In the experimental group, gender distribution included 34 male cases and 20 female cases, with an average age of (50.96 ± 3.14) years. The duration of the disease was (4.33 ± 1.21) months, and disease severity was classified as follows: 3 cases as mild, 16 cases as moderate, 31 cases as severe, and 4 cases as very severe. Disease severity was assessed using the Pruritus Scale, a validated scoring system measuring patients’ itching severity, frequency, and affected area, using a total score of 10. Educational background comprised 13 cases with primary school education, 16 cases with junior high school education, 8 cases ith high school or junior college education, and 16 cases with college or bachelor’s degrees. Additionally, there were 1 case pursuing postgraduate studies. Similarly, in the control group, there were 34 male cases and 20 female cases, with an average age of (51.58 ± 3.25) years. The duration of the disease was (4.25 ± 1.19) months, and disease severity included 3 cases classified as mild, 17 cases as moderate, and 30 cases as severe, and 4 cases as very severe. Educational backgrounds consisted of 13 cases with primary education, 15 cases with junior high school education, 9 cases with high school or junior college education, 16 cases with college or bachelor’s degrees, and 1 case (1.85%) pursuing postgraduate studies. No statistically significant differences were observed in the general clinical data between the two groups ( P > 0.05). The demographic and baseline characteristics of the experimental and control groups summarized in Table . Comparison of skin itching before and after the intervention in the two groups is shown in Table . Comparison of GSES scores between the two groups before and after the intervention See Table . Comparison of adherence between the two groups See Table . Comparison of DLQI scores between the two groups before and after the intervention see Table . Effect size calculations To calculate the effect sizes for the statistically significant differences in the study, using metrics Cohen’s d for continuous data (e.g., comparing means between two groups) for categorical outcomes. Here’s how effect sizes can be interpreted: [12pt]{minimal}
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$${}:{}\,=\,0.{}$$ Pooled standard deviation (pooled SD) : The pooled SD accounts for the variability within both the pre- and post-intervention measurements and is calculated as: [12pt]{minimal}
$${}\;{}\;{}\; { - 1) SD_{1}^{2}+({n_2} - 1) SD_{2}^{2}}}{{{n_1}+{n_2} - 2}}}$$ Effect size is calculated as: d = Mean difference/Pooled SD. Effect size calculations for Pruritus scores (degree of itchiness) For “degree of itchiness” (pre- and post-intervention), Cohen’s d for the experimental and control groups calculation as below: Experimental group: Pooled standard deviation: 0.38. Cohen’s d: 5.16 (very large effect). Control group: Pooled standard deviation: 0.41. Cohen’s d: 2.67 (very large effect). Therefore, these values indicate that the intervention had a strong impact on reducing itchiness in both groups, with a more pronounced effect in the experimental group. 2. Effect size calculations for GSES scores Experimental group: Pooled SD: 3.73. Cohen’s d: 3.76 (very large effect). Control group: Pooled SD: 3.58. Cohen’s d: 3.06 (very large effect). Therefore, both the experimental and control groups exhibited significant improvements in GSES scores following the intervention, with very large effect sizes. However, the experimental group showed a slightly stronger effect. This suggests that the combined intervention of behavior modification and Health Belief Model education had a significant impact on self-efficacy in psoriasis patients. 3. DLQI dimensions Symptom perception Experimental group: Pooled SD: 0.66. Cohen’s d: 2.60 (very large effect). Control group: Pooled SD: 0.76. Cohen’s d: 1.33 (large effect). Therefore, these values indicate that the intervention had larger effect in the experimental group on Symptom Perception compared with control group. (b) Everyday lives Experimental group: Pooled SD: 0.67. Cohen’s d: 1.04 (large effect). Control group: Pooled SD: 0.54. Cohen’s d: 0.71 (medium to large effect). Therefore, these values indicate that the intervention had larger effect in the experimental group on everyday lives compared with control group. (c) Entertainment Experimental group: Pooled SD: 0.48. Cohen’s d: 1.75 (large effect). Control group: Pooled SD: 0.45. Cohen’s d: 1.28 (large effect). Therefore, these values indicate that the intervention had large effect in both groups on entertainment, with a more pronounced effect in the experimental group. (d) Work-based learning Experimental group: Pooled SD: 0.50. Cohen’s d: 0.91 (large effect). Control group: Pooled SD: 0.43. Cohen’s d: 0.99 (large effect). Therefore, these values indicate that the intervention had large effect in both groups, with a slightly more pronounced effect in the control group. (e) Interpersonal relationships Experimental group: Pooled SD: 0.52. Cohen’s d: 1.71 (large effect). Control group: Pooled SD: 0.47. Cohen’s d: 1.11 (large effect). Therefore, these values indicate that the intervention had large effect in both groups on interpersonal relationships, with a more pronounced effect in the experimental group. (f) Treatment Experimental group: Pooled SD: 0.42. Cohen’s d: 2.50 (very large effect). Control group: Pooled SD: 0.41. Cohen’s d: 1.96 (large effect). Therefore, these values indicate that the intervention had very large effect in experimental groups on treatment, with a more pronounced effect compared to the control group. Overall, the experimental group consistently showed larger effects than the control group, with the most pronounced differences observed in symptom perception, treatment, and interpersonal relationships. The control group also showed large effects, particularly in work-based learning, but the experimental group generally benefitted more from the intervention across the various categories measured. The intervention had a substantial and positive impact on both groups, but the experimental group generally experienced stronger effects, particularly in the areas of symptom perception, treatment, and interpersonal relationships.
In the experimental group, gender distribution included 34 male cases and 20 female cases, with an average age of (50.96 ± 3.14) years. The duration of the disease was (4.33 ± 1.21) months, and disease severity was classified as follows: 3 cases as mild, 16 cases as moderate, 31 cases as severe, and 4 cases as very severe. Disease severity was assessed using the Pruritus Scale, a validated scoring system measuring patients’ itching severity, frequency, and affected area, using a total score of 10. Educational background comprised 13 cases with primary school education, 16 cases with junior high school education, 8 cases ith high school or junior college education, and 16 cases with college or bachelor’s degrees. Additionally, there were 1 case pursuing postgraduate studies. Similarly, in the control group, there were 34 male cases and 20 female cases, with an average age of (51.58 ± 3.25) years. The duration of the disease was (4.25 ± 1.19) months, and disease severity included 3 cases classified as mild, 17 cases as moderate, and 30 cases as severe, and 4 cases as very severe. Educational backgrounds consisted of 13 cases with primary education, 15 cases with junior high school education, 9 cases with high school or junior college education, 16 cases with college or bachelor’s degrees, and 1 case (1.85%) pursuing postgraduate studies. No statistically significant differences were observed in the general clinical data between the two groups ( P > 0.05). The demographic and baseline characteristics of the experimental and control groups summarized in Table . Comparison of skin itching before and after the intervention in the two groups is shown in Table . Comparison of GSES scores between the two groups before and after the intervention See Table . Comparison of adherence between the two groups See Table . Comparison of DLQI scores between the two groups before and after the intervention see Table .
To calculate the effect sizes for the statistically significant differences in the study, using metrics Cohen’s d for continuous data (e.g., comparing means between two groups) for categorical outcomes. Here’s how effect sizes can be interpreted: [12pt]{minimal}
$${}:{}\,=\,0.{}$$ [12pt]{minimal}
$${}:{}\,=\,0.{}$$ [12pt]{minimal}
$${}:{}\,=\,0.{}$$ Pooled standard deviation (pooled SD) : The pooled SD accounts for the variability within both the pre- and post-intervention measurements and is calculated as: [12pt]{minimal}
$${}\;{}\;{}\; { - 1) SD_{1}^{2}+({n_2} - 1) SD_{2}^{2}}}{{{n_1}+{n_2} - 2}}}$$ Effect size is calculated as: d = Mean difference/Pooled SD. Effect size calculations for Pruritus scores (degree of itchiness) For “degree of itchiness” (pre- and post-intervention), Cohen’s d for the experimental and control groups calculation as below: Experimental group: Pooled standard deviation: 0.38. Cohen’s d: 5.16 (very large effect). Control group: Pooled standard deviation: 0.41. Cohen’s d: 2.67 (very large effect). Therefore, these values indicate that the intervention had a strong impact on reducing itchiness in both groups, with a more pronounced effect in the experimental group. 2. Effect size calculations for GSES scores Experimental group: Pooled SD: 3.73. Cohen’s d: 3.76 (very large effect). Control group: Pooled SD: 3.58. Cohen’s d: 3.06 (very large effect). Therefore, both the experimental and control groups exhibited significant improvements in GSES scores following the intervention, with very large effect sizes. However, the experimental group showed a slightly stronger effect. This suggests that the combined intervention of behavior modification and Health Belief Model education had a significant impact on self-efficacy in psoriasis patients. 3. DLQI dimensions Symptom perception Experimental group: Pooled SD: 0.66. Cohen’s d: 2.60 (very large effect). Control group: Pooled SD: 0.76. Cohen’s d: 1.33 (large effect). Therefore, these values indicate that the intervention had larger effect in the experimental group on Symptom Perception compared with control group. (b) Everyday lives Experimental group: Pooled SD: 0.67. Cohen’s d: 1.04 (large effect). Control group: Pooled SD: 0.54. Cohen’s d: 0.71 (medium to large effect). Therefore, these values indicate that the intervention had larger effect in the experimental group on everyday lives compared with control group. (c) Entertainment Experimental group: Pooled SD: 0.48. Cohen’s d: 1.75 (large effect). Control group: Pooled SD: 0.45. Cohen’s d: 1.28 (large effect). Therefore, these values indicate that the intervention had large effect in both groups on entertainment, with a more pronounced effect in the experimental group. (d) Work-based learning Experimental group: Pooled SD: 0.50. Cohen’s d: 0.91 (large effect). Control group: Pooled SD: 0.43. Cohen’s d: 0.99 (large effect). Therefore, these values indicate that the intervention had large effect in both groups, with a slightly more pronounced effect in the control group. (e) Interpersonal relationships Experimental group: Pooled SD: 0.52. Cohen’s d: 1.71 (large effect). Control group: Pooled SD: 0.47. Cohen’s d: 1.11 (large effect). Therefore, these values indicate that the intervention had large effect in both groups on interpersonal relationships, with a more pronounced effect in the experimental group. (f) Treatment Experimental group: Pooled SD: 0.42. Cohen’s d: 2.50 (very large effect). Control group: Pooled SD: 0.41. Cohen’s d: 1.96 (large effect). Therefore, these values indicate that the intervention had very large effect in experimental groups on treatment, with a more pronounced effect compared to the control group. Overall, the experimental group consistently showed larger effects than the control group, with the most pronounced differences observed in symptom perception, treatment, and interpersonal relationships. The control group also showed large effects, particularly in work-based learning, but the experimental group generally benefitted more from the intervention across the various categories measured. The intervention had a substantial and positive impact on both groups, but the experimental group generally experienced stronger effects, particularly in the areas of symptom perception, treatment, and interpersonal relationships.
Zhang Li et al.‘s survey results suggested that patients with psoriasis vulgaris generally held positive attitudes toward skin moisturizing care . They recognized its significance and expressed a willingness to engage in it for an extended period. While psoriasis patients demonstrated relatively high content knowledge about skin moisturizing care, it reflected a lower-level knowledge change. Procedural knowledge, specifically understanding how to establish and implement skin moisturizing care behaviors, scored relatively low. This aspect necessitates attention in health education and promotion, as procedural knowledge is pivotal for behavioral change , . Many patients perceive emollients as non-medicinal with no therapeutic effect, resulting in haphazard usage. To address this, healthcare professionals should provide detailed guidance on the frequency, dosage, and integration with other topical medications when advising patients on skin moisturizing care to enhance their cognitive understanding . In this study, health education played a crucial role in helping patients comprehend moisturizing care knowledge, enhancing their self-care abilities, and promoting self-health management. Studies have highlighted the significant association between self-health management ability and adherence, considering adherence as the foundation of self-health management . Key health education messages included elucidating the role of moisturizing care, emphasizing frequency, timing, and dosage, contributing positively to enhancing patients’ self-health management ability. Post-intervention, the experimental group exhibited higher compliance than the control group, and their General Self-Efficacy Scale (GSES) score was also higher. This indicates that health belief model education guided by behavior modification has the potential to improve adherence to skin moisturizing care in patients with psoriasis vulgaris. Possible contributing factors include: (1) Health belief model education enhancing patients’ awareness of disease severity and cooperation with nursing care; (2) behavior modification targeting the correction of poor behavioral habits and changing procedural knowledge. Self-efficacy, as a personal belief in one’s behavioral ability, plays a crucial role in determining whether individuals can achieve their set goals. Adjusting self-efficacy levels can effectively promote behavioral change . Therefore, behavior modification, when combined with health belief cognitive preaching, serves as a holistic approach to assisting patients in achieving positive changes in their health behaviors. Based on the data analysis, the following statistically significant differences were identified. After the intervention, the Pruritus Scale significantly decreased in the experimental group compared to the control group. The reduction in Pruritus Scale in the experimental group was notably greater than in the control group ( P < 0.05), indicating that the combined behavioral intervention and health belief education effectively alleviated itching. Both groups showed improvements in GSES scores post-intervention, but the experimental group experienced a significantly larger increase than the control group ( P < 0.05). This demonstrates that the intervention significantly enhanced patients’ confidence in managing their care. The experimental group had significantly lower MORISKY Medication Adherence scores after the intervention compared to the control group, reflecting improved adherence in medication timing, frequency, and a reduction in self-discontinuation ( P < 0.05). These results suggest that the intervention was effective in enhancing treatment compliance. Post-intervention, the DLQI scores were significantly lower across all dimensions in the experimental group compared to the control group, including symptom perception, daily life, leisure activities, work and study, interpersonal relationships, and treatment ( P < 0.05). This indicates a substantial improvement in the overall quality of life for the experimental group. The significant reduction in Dermatology Life Quality Index (DLQI) scores among the experimental group underscores the potential for combining behavioral education with clinical treatments. However, further multicenter studies are warranted to establish generalizability across diverse populations. These statistically significant differences highlight that the combined behavioral modification and health belief education intervention was more effective in improving key outcomes—itching severity, self-efficacy, medication adherence, and quality of life—compared to standard care. In China, there is a lack of widespread awareness about psoriasis, resulting in insufficient knowledge among patients. This knowledge gap hinders the scientific and effective prevention and control of psoriasis, leading to a notable increase in recurrence rates and adversely impacting patients’ physical and mental well-being . Existing studies highlight that common clinical symptoms of psoriasis, such as itching, plaques, and papules, often prompt patients to scratch their skin, causing skin breakouts and negatively affecting their external appearance . Evaluating quality of life becomes crucial in clinical research, encompassing both physiological and psychological aspects of patient interventions. A study conducted by Long et al. involved behavioral habit reversal corrective intervention for psoriasis patients, revealing significant relief in patients’ itchiness and a notable improvement in overall quality of life. This underscores the vital role of behavioral interventions in enhancing the well-being of psoriasis patients. The health belief model serves as a primary theoretical framework for elucidating health-related behaviors from a social psychological perspective. This model has demonstrated satisfactory results in various medical conditions , . Its application in understanding and addressing health behaviors is particularly relevant, providing valuable insights for improving patient outcomes in psoriasis management. The results of this study demonstrate statistically significant improvements in self-efficacy and quality of life among patients with psoriasis vulgaris who underwent interventions combining behavioral modification and health belief model education. These findings carry several important implications for clinical practice and the management of chronic dermatological conditions. The integration of behavior modification and health education could be adapted for other chronic skin disorders, such as eczema or atopic dermatitis, where adherence to skin care regimens is similarly critical. The focus on enhancing self-efficacy through tailored education and behavior tracking can address common barriers to compliance, such as misunderstanding of treatments or behavioral resistance. By addressing psychological and behavioral aspects, this intervention moves beyond symptom-focused treatments. The approach is aligned with patient-centered care, emphasizing the importance of empowering individuals to actively participate in their disease management. Improved adherence and symptom management may reduce the long-term costs associated with more severe disease progression, hospital readmissions, or advanced treatments. This is particularly relevant for healthcare systems looking to optimize resource use. The results of effect size demonstrate that the intervention had a larger and more pronounced effect on the experimental group across most domains, particularly in areas related to symptom perception, treatment, and interpersonal relationships. The very large effect sizes observed in the experimental group suggest that the intervention was particularly effective in these areas, offering significant improvements in how participants perceived and dealt with their symptoms, as well as their overall treatment outcomes. However, the control group also showed large effects in several domains, such as work-based learning and entertainment, indicating that even without the specific intervention, participants in the control group experienced positive changes. This suggests that factors outside of the intervention may have contributed to some of the observed effects, and the control group’s improvements should not be overlooked. For instance, natural changes over time or other external influences could have played a role.While the results are promising, particularly in the experimental group, further research is needed to explore the specific mechanisms behind these improvements. In conclusion, the intervention appears to be effective across a variety of domains, with particularly large effects on symptom perception, treatment, and interpersonal relationships in the experimental group. The control group also showed positive results, but the experimental group consistently experienced stronger outcomes, suggesting that the intervention had a meaningful and impactful role in the study. While the combination of behavior modification and health belief education demonstrates significant benefits, it is important to note that these methods are supplementary and do not replace internationally recommended pharmacological therapies. Future studies should integrate these educational approaches with standard international protocols to validate their broader applicability. Limitations of study While the study offers valuable insights into the effectiveness of an educational approach incorporating behavioral modification and the Health Belief Model in individuals with psoriasis vulgaris, several limitations warrant consideration. The study’s single-center design and a relatively modest sample size of 108 patients may limit the generalizability of findings. The short two-month intervention period may not capture sustained long-term effects on adherence to skin moisturizing care, itch severity, self-efficacy, and quality of life. The reliance on self-reported measures, such as the Pruritus Scale, General Self-Efficacy Scale, Medication Adherence Scale (MORISKY), and Dermatologic Quality of Life Index (DLQI), introduces the potential for response bias. Additionally, the absence of a robust placebo or sham intervention in the control group raises concerns about the possibility of a placebo effect influencing outcomes. Future research with a larger, more diverse sample, an extended intervention period, and rigorous control conditions could provide a more comprehensive understanding of the long-term impact and generalizability of the educational interventions studied.
While the study offers valuable insights into the effectiveness of an educational approach incorporating behavioral modification and the Health Belief Model in individuals with psoriasis vulgaris, several limitations warrant consideration. The study’s single-center design and a relatively modest sample size of 108 patients may limit the generalizability of findings. The short two-month intervention period may not capture sustained long-term effects on adherence to skin moisturizing care, itch severity, self-efficacy, and quality of life. The reliance on self-reported measures, such as the Pruritus Scale, General Self-Efficacy Scale, Medication Adherence Scale (MORISKY), and Dermatologic Quality of Life Index (DLQI), introduces the potential for response bias. Additionally, the absence of a robust placebo or sham intervention in the control group raises concerns about the possibility of a placebo effect influencing outcomes. Future research with a larger, more diverse sample, an extended intervention period, and rigorous control conditions could provide a more comprehensive understanding of the long-term impact and generalizability of the educational interventions studied.
The study’s findings indicate that, following the intervention, the Dermatologic Quality of Life Index (DLQI) score in the experimental group surpassed that of the control group. Additionally, the experimental group exhibited an improvement in skin itching compared to the control group. These results suggest that the combination of behavior modification and health belief model education can effectively enhance the quality of life and alleviate itching symptoms in psoriasis patients. This underscores the positive significance of behavior modification in ameliorating clinical symptoms among patients. Several factors may contribute to these outcomes: Health belief model education plays a role in enhancing patients’ understanding of emollient use and fostering greater cooperation in nursing care. Behavior modification targets the correction of patients’ unfavorable behavioral habits, resulting in improved compliance with skin moisturizing care. The integration of behavior modification and health belief model education effectively addresses non-compliance and promotes positive changes in moisturizing care habits, thus reducing the occurrence and progression of undesirable symptoms. These findings underscore the critical role of behavior modification and health belief model education in improving not only adherence to care but also enhancing the quality of life for psoriasis patients by reducing pruritus and emotional distress.
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COVID‐19 and vertical transmission: assessing the expression of ACE2/TMPRSS2 in the human fetus and placenta to assess the risk of SARS‐CoV‐2 infection | 414525e1-8f61-4e73-a8f3-279ecb4c9efe | 8652560 | Anatomy[mh] | The COVID‐19 pandemic has brought about unprecedented research efforts in attempts to prevent and treat infection across all ages. SARS‐CoV‐2 viral entry mechanisms into the human body have been well established, highlighting the importance of tissue‐level co‐expression of ACE2 and TMPRSS2 (along with potential roles for further surface markers, such as NRP1). , The risk profile and infection mechanisms of SARS‐CoV‐2 appear significantly different in young children than in older individuals. Clinical reports of confirmed perinatal infection in the neonate have led to concerns of a potential mechanism for vertical transmission. Recent data suggest that the fetus may have some susceptibility to SARS‐CoV‐2 infection, , , alongside a plausible increased risk of preterm birth. These observed risks appear to relate to the severity of maternal infection, and documented placental pathology has been reported to correlate with severe maternal symptoms. , Documented cases of confirmed vertical transmission indicate that this seems to occur around the time of birth, with low neonatal morbidity. Although neonatal SARS‐CoV‐2 infection is rarely of significant severity, there remains concern surrounding disruption of the pregnancy during the 2nd trimester, as was observed during outbreaks of similar coronaviruses SARS and MERS. , Additionally, there are concerns regarding the impact of fetal infection during critical developmental phases, observed in other viral infections such as cytomegalovirus. Therefore, understanding the potential for, and impact of, mid‐gestation fetal infection remains an ongoing public health question. Various mechanisms of vertical transmission have been hypothesised: direct infection of syncytiotrophoblast with subsequent transmission through the cytotrophoblast has been demonstrated in several histopathological and immunological studies , , and appears not to involve the fetal‐origin Hofbauer cells in the majority of transplacental infections. Infection via trafficked maternal cells has been suggested, as evidenced by an observed expression of ACE2 protein in infiltrating maternal cells in human placentas with chorioamnionitis. However, it is of note that despite widely reported placental pathology in viraemic mothers, infection in the fetus has not been well characterised and does not seem to be a common feature of preterm birth in association with a confirmed infection in the mother. Neonatal infection plausibly could occur either through an ascending infection through the vagina and cervical canal or during vaginal birth via direct infant contact with maternal virus. It is worth noting, however, that a number of case series demonstrate negative vaginal swabs in the presence of confirmed maternal SARS‐CoV2 pneumonia. , To explore the susceptibility of the mid‐gestation human fetus to SARS‐CoV‐2 infection, we studied multiple fetal tissues at different gestational stages. We initially probed publicly available single‐cell RNA sequencing data from fetal tissues at different developmental stages (10–18 post‐gestational weeks [PCW]). We then validated our findings by exploring gene expression levels of ACE2 and TMPRSS2 via quantitative PCR analysis of the fetal tissues that could be exposed to virus in utero and examined expression at protein level using multicolour immunohistochemistry. This enabled us to explore both expression of proteins implicated in SARS‐CoV‐2 infection and their tissue colocalisation. Finally, we studied amniotic membrane and placental samples of matching developmental stages and at term, to identify potential viral entry points at the maternal–fetal interface.
Samples and ethics Human fetal tissues were obtained with consent through the Human Developmental Biology Resource (HDBR; REC 18/LO/0822 – IRAS 244325; Project ID 200568). Fetal samples were obtained from fetuses ranging from 14 to 22 PCW (12–20 post menstrual weeks of gestation). Fetal staging was calculated based on foot length (mm) and referred to as PCW. The tissue library included fetal lung, intestine, kidney, bladder, skin, amniotic membrane and placenta (CV, chorionic villi). Placental samples were obtained at delivery of an uncomplicated, full‐term pregnancy (median 39 weeks PCW, range 38 +1 to 39 +4 ) for six patients recruited through the EVERREST Prospective Study as normal controls (National Research Ethics reference 13/LO/1254), NCT02097667 registered 31 October 2013. Tissue staining and RNA expression level was referenced to that of human adult lung controls, commercially obtained from Insight Biotechnology and Takara. Single‐cell RNA sequencing Suitable Single‐Cell RNA sequencing datasets were identified in public repositories from broad high‐impact Single‐Cell studies (available at www.proteinatlas.org and https://descartes.brotmanbaty.org/) , . These covered human fetal specimens from multiple gestational ages, as well as human adult reference samples. For the adult data, a normalised count matrix (i.e. TPM normalised) was downloaded, containing samples from different origins, annotated by cell‐type. Fetal data were downloaded as a raw count matrix, with analysis carried out after random sampling of 5000 cells per cell type per organ (in cases where <5000 cells of a given cell type were represented in a given organ, all cells were taken). The sampled data comprise gene count information for 377 456 cells across 15 organs. The data was then CPM‐normalised, and log‐transformed using the Seurat R package (satijalab.org/seurat). A custom R script was then used to extract and plot (using the ggplot2 package by tidyverse, ggplot2.tidyverse.org) the expression data for ACE2 and TMPRSS2 across a range of fetal tissues (adrenal, heart, lung, cerebellum, intestine, muscle, spleen, cerebrum, kidney, pancreas, stomach, eye, liver, thymus and placenta) and time‐points between 10 and 18 PCW. Gene expression analysis via RT‐qPCR Whole tissue gene expression was analysed by Real‐Time quantitative Polymerase Chain Reaction (RT‐qPCR). First, RNA was extracted from formalin‐fixed paraffin‐embedded tissue blocks (RNAEasy FFPE Kit; 73504, Qiagen, Hilden, Germany). The cDNA was then generated upon retro‐transcription following the manufacturer’s recommendation (Super Script VILO IV Master Mix; 11756050, Life Technologies, Carlsbad, CA, USA). RT‐qPCR was performed using an Applied Biosystem Step One v23 machine, utilising SYBR Green (Agilent, 600882, Santa Clara, CA, USA) and predesigned KiCqStart primers for ACE2, TMPRSS2 and GAPDH (Merck, Darmstadt, Germany). Primer sequences are available in Table . Relative expression of the analysed genes was calculated based on Δ C T values, compared with the adult lung expression level as positive control, using the ∆∆ C T Livak method. Statistical significance was assessed by non‐parametric one‐sample Wilcoxon signed rank test against the positive adult lung control. Two‐colour immunohistochemistry to assess protein localisation Tissue slides were analysed by two‐colour immunohistochemistry. Staining was performed utilising primary antibodies for ACE2 (R&D Systems, Minneapolis, Minnesota, USA, MAB933, RRID:AB_2223153; Mouse anti‐Human 1:200 with red chromogen) and TMPRSS2 (Abcam, Cambridge, UK, ab109131, RRID:AB_10863728; rabbit anti‐human 1:500 with Brown chromogen). The Leica refine polymer kit (Leica, Wetzlar, Germany, DS9800, RRID:AB_2891238) and refine red kit (DS9390) were utilised to stain the antibody–antigen complex. Sections were counterstained with haematoxylin to highlight the localisation of the nuclei. Staining specificity and quality were evaluated by the Department of Histopathology of Great Ormond Street Hospital. Qualitative analysis of the staining localisation within each tissue was performed to assess localisation and co‐localisation of the staining. A representative panel showing negative controls and single colour staining is presented in Figure . Quantitative analysis was performed using QuPath: specifically, tissue sections were segmented using a semi‐automated pixel classifier. Positively stained areas for each chromogen were measured using machine‐learning based pixel classifiers and the percentage of staining area relative to total tissue area was computed. Double positive expression was defined by the percentage of staining areas that co‐expressed ACE2 and TMPRSS2. This was then compared between samples across different gestational stages and compared with adult lung sections as positive control reference. Statistical analyses Gestational expression changes were explored using linear regression modelling comparing expression level and developmental stages. We obtained and analysed seven tissues from six fetal samples, in addition to seven term placenta samples. Statistical significance between each tissue and the adult lung expression threshold was assessed, given the internal positive control of adult lung RNA used as a reference for each PCR plate; the pooled mean and standard deviation of all tissue samples from each gestational time point were compared with this value in a one‐sample t ‐test. The ACE2 and TMPRSS2 levels were graphically depicted as the mean of the fold change in expression in each tissue. The temporal variation for each tissue is also presented as individual graphs, simple linear regression with 95% CI was performed to illustrate temporal trends. Statistical analyses were performed using Microsoft EXCEL (Microsoft Corporation, WA, USA) and GraphPad PRISM v9.0 (GraphPad Software, CA, USA). Data are displayed in the text as Mean ± SEM unless otherwise stated, and a P ‐value of <0.05 was accepted as denoting statistical significance.
Human fetal tissues were obtained with consent through the Human Developmental Biology Resource (HDBR; REC 18/LO/0822 – IRAS 244325; Project ID 200568). Fetal samples were obtained from fetuses ranging from 14 to 22 PCW (12–20 post menstrual weeks of gestation). Fetal staging was calculated based on foot length (mm) and referred to as PCW. The tissue library included fetal lung, intestine, kidney, bladder, skin, amniotic membrane and placenta (CV, chorionic villi). Placental samples were obtained at delivery of an uncomplicated, full‐term pregnancy (median 39 weeks PCW, range 38 +1 to 39 +4 ) for six patients recruited through the EVERREST Prospective Study as normal controls (National Research Ethics reference 13/LO/1254), NCT02097667 registered 31 October 2013. Tissue staining and RNA expression level was referenced to that of human adult lung controls, commercially obtained from Insight Biotechnology and Takara.
Suitable Single‐Cell RNA sequencing datasets were identified in public repositories from broad high‐impact Single‐Cell studies (available at www.proteinatlas.org and https://descartes.brotmanbaty.org/) , . These covered human fetal specimens from multiple gestational ages, as well as human adult reference samples. For the adult data, a normalised count matrix (i.e. TPM normalised) was downloaded, containing samples from different origins, annotated by cell‐type. Fetal data were downloaded as a raw count matrix, with analysis carried out after random sampling of 5000 cells per cell type per organ (in cases where <5000 cells of a given cell type were represented in a given organ, all cells were taken). The sampled data comprise gene count information for 377 456 cells across 15 organs. The data was then CPM‐normalised, and log‐transformed using the Seurat R package (satijalab.org/seurat). A custom R script was then used to extract and plot (using the ggplot2 package by tidyverse, ggplot2.tidyverse.org) the expression data for ACE2 and TMPRSS2 across a range of fetal tissues (adrenal, heart, lung, cerebellum, intestine, muscle, spleen, cerebrum, kidney, pancreas, stomach, eye, liver, thymus and placenta) and time‐points between 10 and 18 PCW.
Whole tissue gene expression was analysed by Real‐Time quantitative Polymerase Chain Reaction (RT‐qPCR). First, RNA was extracted from formalin‐fixed paraffin‐embedded tissue blocks (RNAEasy FFPE Kit; 73504, Qiagen, Hilden, Germany). The cDNA was then generated upon retro‐transcription following the manufacturer’s recommendation (Super Script VILO IV Master Mix; 11756050, Life Technologies, Carlsbad, CA, USA). RT‐qPCR was performed using an Applied Biosystem Step One v23 machine, utilising SYBR Green (Agilent, 600882, Santa Clara, CA, USA) and predesigned KiCqStart primers for ACE2, TMPRSS2 and GAPDH (Merck, Darmstadt, Germany). Primer sequences are available in Table . Relative expression of the analysed genes was calculated based on Δ C T values, compared with the adult lung expression level as positive control, using the ∆∆ C T Livak method. Statistical significance was assessed by non‐parametric one‐sample Wilcoxon signed rank test against the positive adult lung control.
Tissue slides were analysed by two‐colour immunohistochemistry. Staining was performed utilising primary antibodies for ACE2 (R&D Systems, Minneapolis, Minnesota, USA, MAB933, RRID:AB_2223153; Mouse anti‐Human 1:200 with red chromogen) and TMPRSS2 (Abcam, Cambridge, UK, ab109131, RRID:AB_10863728; rabbit anti‐human 1:500 with Brown chromogen). The Leica refine polymer kit (Leica, Wetzlar, Germany, DS9800, RRID:AB_2891238) and refine red kit (DS9390) were utilised to stain the antibody–antigen complex. Sections were counterstained with haematoxylin to highlight the localisation of the nuclei. Staining specificity and quality were evaluated by the Department of Histopathology of Great Ormond Street Hospital. Qualitative analysis of the staining localisation within each tissue was performed to assess localisation and co‐localisation of the staining. A representative panel showing negative controls and single colour staining is presented in Figure . Quantitative analysis was performed using QuPath: specifically, tissue sections were segmented using a semi‐automated pixel classifier. Positively stained areas for each chromogen were measured using machine‐learning based pixel classifiers and the percentage of staining area relative to total tissue area was computed. Double positive expression was defined by the percentage of staining areas that co‐expressed ACE2 and TMPRSS2. This was then compared between samples across different gestational stages and compared with adult lung sections as positive control reference.
Gestational expression changes were explored using linear regression modelling comparing expression level and developmental stages. We obtained and analysed seven tissues from six fetal samples, in addition to seven term placenta samples. Statistical significance between each tissue and the adult lung expression threshold was assessed, given the internal positive control of adult lung RNA used as a reference for each PCR plate; the pooled mean and standard deviation of all tissue samples from each gestational time point were compared with this value in a one‐sample t ‐test. The ACE2 and TMPRSS2 levels were graphically depicted as the mean of the fold change in expression in each tissue. The temporal variation for each tissue is also presented as individual graphs, simple linear regression with 95% CI was performed to illustrate temporal trends. Statistical analyses were performed using Microsoft EXCEL (Microsoft Corporation, WA, USA) and GraphPad PRISM v9.0 (GraphPad Software, CA, USA). Data are displayed in the text as Mean ± SEM unless otherwise stated, and a P ‐value of <0.05 was accepted as denoting statistical significance.
Analysis of scRNA‐sequencing data Our analysis of public repository data identified the human fetal intestine as highly co‐expressing both ACE2 and TMPRSS2. Upon interrogation of expression in the different specific cell types, we identified the intestinal epithelial cells as being the main contributors to overall intestine positivity for these genes (Figure ). This analysis also indicated that whereas other tissues, notably kidney and lung, showed expression of ACE2, the lack of co‐expression with TMPRSS2 suggests these tissues are unlikely to be susceptible to SARS‐CoV‐2 infection during gestation. Co‐expression of ACE2 and TMPRSS2 in the intestine increased during gestation in an exponential manner across the first and second trimester timepoints studied (10–18 PCW). None of the other tissues analysed showed such significant increase in gene expression over the gestational age range for which data were available. In line with this observation, the adult intestine also showed the greatest co‐expression. This was further supported by analysis of cell‐specific expression, with the greatest expression in adult intestinal enterocytes. Overall, this analysis of open access RNA sequencing atlas data suggests that transcription of ACE2 and TMPRSS2 differs markedly in human fetal subjects compared with what has been reported for children and adults. Analysis of gene expression at tissue level across the second trimester RT‐qPCR gene expression analysis was carried out on a library of fetal tissues (ranging from 14 to 22 PCW) that are potentially susceptible to SARS‐CoV‐2 infection (Figure , Table ). Using the adult lung as reference, the following was observed. The fetal intestine demonstrated the highest relative expression of ACE2 and TMPRSS2, (fold change relative to adult lung: ACE2 15.49 ± 4.54, P = 0.0243 and TMPRSS2 10.80 ± 2.61, P = 0.0132). The fetal lung also expressed significant TMPRSS2 expression but showed significantly lower ACE2, far below that observed in the adult lung. Although the fetal kidney showed increased expression of ACE2 and TMPRSS2, the latter did not reach statistical significance. In contrast, the skin and bladder both showed ACE2 expression significantly below that of the adult lung, and TMPRSS2 levels similar to that of the adult lung. Placental tissues showed significantly lower expression than adult lung for both ACE2 and TMPRSS2. Analysis of protein expression at tissue level across the second trimester Two‐colour immunohistochemistry was used to investigate expression and localisation of ACE2 and TMPRSS2 proteins in multiple fetal tissues across second trimester. Tissues positively expressing the antigens showed localisation of TMPRSS2 (Brown) across the plasma membrane of the epithelial cells, whereas ACE2 (Red) localised specifically to the apical membrane of the epithelia (Figure ). These data validate the mRNA findings confirming little to no ACE2 expression in fetal skin, bladder and lung, with lung and bladder expressing detectable levels of TMPRSS2. The fetal intestine and kidney specimens showed a strong protein co‐expression, with the intestine having the most significant co‐localisation on the mucosal epithelium, highlighted in the high magnification images (Table , Figure , Right and Figure ). Placental samples expressed low to absent ACE2, whereas TMPRSS2 seemed to be present at variable levels in the chorionic villi; a finding that is consistent across the gestational window of study but which did not match the gene expression data by tissue‐level PCR. The lack of co‐localisation with ACE2 was also true for the term placenta samples (Figure ).
Our analysis of public repository data identified the human fetal intestine as highly co‐expressing both ACE2 and TMPRSS2. Upon interrogation of expression in the different specific cell types, we identified the intestinal epithelial cells as being the main contributors to overall intestine positivity for these genes (Figure ). This analysis also indicated that whereas other tissues, notably kidney and lung, showed expression of ACE2, the lack of co‐expression with TMPRSS2 suggests these tissues are unlikely to be susceptible to SARS‐CoV‐2 infection during gestation. Co‐expression of ACE2 and TMPRSS2 in the intestine increased during gestation in an exponential manner across the first and second trimester timepoints studied (10–18 PCW). None of the other tissues analysed showed such significant increase in gene expression over the gestational age range for which data were available. In line with this observation, the adult intestine also showed the greatest co‐expression. This was further supported by analysis of cell‐specific expression, with the greatest expression in adult intestinal enterocytes. Overall, this analysis of open access RNA sequencing atlas data suggests that transcription of ACE2 and TMPRSS2 differs markedly in human fetal subjects compared with what has been reported for children and adults.
RT‐qPCR gene expression analysis was carried out on a library of fetal tissues (ranging from 14 to 22 PCW) that are potentially susceptible to SARS‐CoV‐2 infection (Figure , Table ). Using the adult lung as reference, the following was observed. The fetal intestine demonstrated the highest relative expression of ACE2 and TMPRSS2, (fold change relative to adult lung: ACE2 15.49 ± 4.54, P = 0.0243 and TMPRSS2 10.80 ± 2.61, P = 0.0132). The fetal lung also expressed significant TMPRSS2 expression but showed significantly lower ACE2, far below that observed in the adult lung. Although the fetal kidney showed increased expression of ACE2 and TMPRSS2, the latter did not reach statistical significance. In contrast, the skin and bladder both showed ACE2 expression significantly below that of the adult lung, and TMPRSS2 levels similar to that of the adult lung. Placental tissues showed significantly lower expression than adult lung for both ACE2 and TMPRSS2.
Two‐colour immunohistochemistry was used to investigate expression and localisation of ACE2 and TMPRSS2 proteins in multiple fetal tissues across second trimester. Tissues positively expressing the antigens showed localisation of TMPRSS2 (Brown) across the plasma membrane of the epithelial cells, whereas ACE2 (Red) localised specifically to the apical membrane of the epithelia (Figure ). These data validate the mRNA findings confirming little to no ACE2 expression in fetal skin, bladder and lung, with lung and bladder expressing detectable levels of TMPRSS2. The fetal intestine and kidney specimens showed a strong protein co‐expression, with the intestine having the most significant co‐localisation on the mucosal epithelium, highlighted in the high magnification images (Table , Figure , Right and Figure ). Placental samples expressed low to absent ACE2, whereas TMPRSS2 seemed to be present at variable levels in the chorionic villi; a finding that is consistent across the gestational window of study but which did not match the gene expression data by tissue‐level PCR. The lack of co‐localisation with ACE2 was also true for the term placenta samples (Figure ).
In this study, we assess the expression of ACE2 and TMPRSS2 at the gene and protein level, across a library of human fetal tissues obtained from the second trimester (14–22 PCW) to term. Our findings demonstrate that most of the fetal tissues analysed lack expression (or co‐localisation) of the proteins required for SARS‐CoV‐2 infection. However, two tissues (fetal kidney and intestine) manifested co‐expression of both target proteins. As the fetal kidney is not anatomically directly exposed to the amniotic fluid, we believe it is unlikely to be a relevant route for viral infection. Haematogenous spread as a mechanism of infection and transmission across the placenta into the fetal circulation appears unlikely, due to inefficient viral replication in placental tissues. The fetal intestine, directly exposed to the amniotic fluid via fetal swallowing, shows an increase in the expression of ACE2 throughout gestation with a high level of TMPRSS2 expression in the mucosa. Results from publicly available fetal single cell atlas data support our findings, allowing extension of these observations to 8 PCW, before the gestational age that fetal swallowing is known to begin. The intestinal findings are also in line with recent demonstration that the human fetal stomach highly co‐expresses proteins required for SARS‐CoV‐2 infection and that fetal stomach‐derived organoids are susceptible to viral infection. ACE2 expression has also been reported in an immunohistochemistry study of fetal ileum and rectum samples from 15 weeks of gestation, in which the authors also noted ACE2 expression in the fetal kidney but none in the fetal brain or heart. Taken together, these results suggest that both the upper and lower gastrointestinal tract may be a potential entry route for SARS‐CoV‐2 into the second‐trimester human fetus. This is also consistent with our additional retrospective analysis, performed on all the other fetal tissues present in the reference single cell atlas, indicating that the co‐expression of the two genes is also present in the stomach (Figure ). Previous studies have assimilated data available from expression profiles on scRNA atlas in the public domain to demonstrate ACE2/TMPRSS2 expression in human fetal tissues and at the maternal‐fetal interface. However, these studies have not explored expression within the fetal intestine, and lack validation at a protein level. To the best of our knowledge, this is the first work to explore ACE2/TMPRSS2 both at gene expression and protein levels in the human fetus, and specifically in the second trimester of pregnancy. Our findings support clinical observations from meta‐analyses that the incidence of COVID‐19‐related fetal complications during pregnancy is low given the number of adult COVID‐19 cases worldwide (234 million confirmed cases, 4.8 million deaths at the time of writing: https://github.com/CSSEGISandData/COVID‐19 ), including large numbers of pregnant women. Comparatively, in previous coronavirus epidemics, far fewer cases have been reported, albeit with a higher frequency of fetal adverse events. The UK Obstetric Surveillance System reports that pregnant women in later gestation are not protected from severe infection; with an increased frequency of iatrogenic preterm birth, possibly due to severe maternal illness. There have been speculative data published suggesting that women may be at risk of severe SARS‐CoV2‐related illness in the peripartum period, which has led to regional policy that the non‐compromised fetus should remain undelivered if possible. , This study contains novel data that corroborate real world observations, but it nonetheless is important to recognise a few limitations of the data we present. The Human Developmental Biology Resource includes human fetal tissues for research purposes only up to 22 weeks of gestation, therefore we are unable to investigate the expression of ACE2 and TMPRSS2 in fetal tissues past this time point. Furthermore, we have not directly validated the susceptibility to infection in the tissues of interest with infection assays; work with live SARS‐CoV‐2 virus is beyond the scope of this study. Previous collaborative studies from our group have demonstrated infection in tissue and organoids derived from human fetal stomach demonstrating that a high expression at both RNA and protein level corresponds to a significant propensity for viral infection. Hence, the proposed route of infection via the gastrointestinal tract is reasonable, in keeping with others’ published work on the adult intestine. Furthermore, this corresponds to proposed mechanisms for spread among younger children, as gastrointestinal symptoms and fecal shedding are more characteristic of infection in younger patients, , , and may possibly be associated with a milder disease phenotype. The hypothesis of intrauterine infection through the gastrointestinal tract requires viral entry to the fetal gastrointestinal lumen through fetal swallowing of infected amniotic fluid, and presumes that the amniotic fluid can contain infectious viral particles. Our data indicate that term placenta expresses low to absent ACE2, a key protein for SARS‐CoV‐2 infection, making it difficult for the virus to pass from the maternal blood to the fetus or amniotic fluid. In one study of 31 mothers with COVID‐19, there were only two cases of vertical transmission in which the viral genome was detected in term placentas, and these cases were associated with strong maternal pro‐inflammatory response. In contrast, single cell transcriptomic studies of early placenta (6–14 post menstrual age gestational weeks) reported co‐expression of ACE2 and TMPRSS2 in stromal and perivascular cells in decidua, and villous cytotrophoblast and syncytiotrophoblast. It is therefore plausible that women infected early in pregnancy could potentially pass SARS‐CoV‐2 to the fetus, but with low fetal infection rates due to the minimal ACE2 and TMPRSS2 co‐expression in the fetal tissues studied, including the gastrointestinal tract, early in pregnancy. Furthermore, placental pathology including fibrin deposition and intervillous thrombosis associated with preterm labour, have been sporadically observed in SARS‐CoV2‐positive mothers, linked to immunochemical evidence of virus expression in the trophoblast. , One possible reason for discordant results within the published literature may be the widespread presence of Fc receptors in the human placenta, as these are known to bind antibodies to varying affinities and may therefore lead to non‐specific staining. This emphasises the need for molecular validation, such as the RT‐qPCR or RNA‐seq data presented here together with the placental immunohistochemistry studies. Regarding perinatal transmission, there have been several studies reporting an absence of detectable virus in genital tract swabs in women with severe symptoms, or in pregnant women with mild symptoms. , However, given the immunological changes occurring around the time of labour, we would suggest that there is currently inadequate evidence to rule this out as the potential route for infection of neonates who are known to have been infected. , , In conclusion, we would propose that maternal viraemia‐associated presence of virus within the amniotic fluid and birth canal, as reported, , may produce an environment where the fetus is susceptible to infection through the gastrointestinal tract, and that this susceptibility may be present from the late second trimester. Contribution to authorship MFMG and PDC conceived the study and designed the experiments with the help of ALD. MAB and JRD contributed equally to this work, conducted the experiments and analysed the data with the help and support of MFMG. FP and DC helped MAB in performing the retrospective sequencing analyses. SS, DS, BCJ, OO and NJS helped with staining optimisation, interpretation and imaging. KM procured the term placental RNA. MAB, JRD, MFMG and PDC wrote this manuscript. All authors contributed to manuscript revision and approved the final version. Disclosure of interests The authors declare no conflict of interests related to this work or its developments. DC is founder, shareholder and consultant of Next Generation Diagnostic SRL. Funding This work was made possible by an MRC/UKRI COVID‐19 Rapid response initiative grant (MR/V028480/1).
MFMG and PDC conceived the study and designed the experiments with the help of ALD. MAB and JRD contributed equally to this work, conducted the experiments and analysed the data with the help and support of MFMG. FP and DC helped MAB in performing the retrospective sequencing analyses. SS, DS, BCJ, OO and NJS helped with staining optimisation, interpretation and imaging. KM procured the term placental RNA. MAB, JRD, MFMG and PDC wrote this manuscript. All authors contributed to manuscript revision and approved the final version.
The authors declare no conflict of interests related to this work or its developments. DC is founder, shareholder and consultant of Next Generation Diagnostic SRL.
This work was made possible by an MRC/UKRI COVID‐19 Rapid response initiative grant (MR/V028480/1).
Figure S1 . A retrospective analysis performed on public repository single‐cell RNA sequencing data, investigating the expression of ACE2 (Cyan) and TMPRSS2 (Purple). Click here for additional data file. Figure S2 . Higher magnification panel of the two‐colour immunohistochemical staining for ACE2 (Red) and TMPRSS2 (Brown) presented in Figure 3. Click here for additional data file. Figure S3 . Single‐colour immunohistochemistry on tissues obtained from a 14 PCW fetus, and used as control for ACE2 (Red) and TMPRSS2 (Brown) staining and to establish the thresholds for image quantification. Click here for additional data file. Table S1 . List of the primers utilised in the RT‐qPCR experiments. Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file. Supplementary Material Click here for additional data file.
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Gut microbial dysbiosis exacerbates long-term cognitive impairments by promoting intestinal dysfunction and neuroinflammation following neonatal hypoxia-ischemia | fec4e610-ed14-4e7c-b1c3-ca869d99c0a1 | 11866968 | Digestive System[mh] | Neonatal hypoxic-ischemic brain damage (HIBD) represents a predominant cause of neurocognitive disorders in children, profoundly impacting their physical and mental development and quality of life, while imposing significant burdens on families and society. , Brain magnetic resonance imaging (MRI) of human neonates with HIBD and HIBD animal models has revealed that among the various brain regions affected by hypoxic-ischemic (HI) insult, the hippocampal damage is particularly severe. This condition frequently stems from the intense and sustained neuroinflammation in the hippocampus following HIBD, culminating in significant synaptic impairments and neuronal damage, which represents one of primary pathological mechanism underlying the long-term cognitive impairments attributed to HIBD. Nevertheless, the upstream factors responsible for triggering
neuroinflammation in the hippocampus following HIBD remain incompletely understood, and effective preventive measures are still to be discovered. Increasing evidence suggests that the gut microbiota can influence brain function and behavior through the microbiome-gut-brain axis, offering a novel perspective for researching a range of diseases associated with brain function. The research on stroke indicates that gut microbiota can influence the neurological functional outcome in mice after cerebral ischemia. Additionally, available works demonstrate that fecal microbiota transplantation (FMT) from healthy individuals can mitigate the activation of microglia, reduce neuroinflammation, and improve behavior across various neurological disorders, such as Parkinson’s disease (PD), Alzheimer’s disease (AD) and perioperative neurocognitive disorders (PND). Especially, a recent work by Drobyshevsky et al. on neonatal HIBD animal model investigated the manipulation of gut microbial composition using an established murine model of perinatal HI insult. Their findings suggest that gut microbiota may influence neuroinflammatory responses and brain injury following neonatal HI insult, hinting at a potential role of gut microbiota in determining the neurocognitive outcomes of HIBD in humans. However, it remains unclear how gut microbial dysbiosis mediates neuroinflammation, potentially exacerbating synaptic damage and long-term cognitive impairments following HIBD. The gut microbiota can directly influence intestinal epithelial cells, interfering their gene expression and subsequently changing intestinal function and related signaling pathways. Furthermore, recent studies , , have indicated that intestinal dysfunction induced by gut microbial dysbiosis, including intestinal inflammation and intestinal barrier impairments, is closely associated with outcomes of the various neurological diseases, such as PND and AD. Additionally, excessive intestinal inflammatory responses can further exacerbate the intestinal barrier damage, known as “leaky gut,” allowing more harmful substances, such as gut microbiota-derived Lipopolysaccharide (LPS) and intestinal epithelial cells-secreted inflammatory cytokines (tumor necrosis factor-α, TNF-α; interleukin-6, IL-6; interleukin-1β, IL-1β), to enter the bloodstream, thereby promoting neuroinflammation and impairing neural functions. However, it remains unclear if gut microbial dysbiosis after HIBD may cause intestinal dysfunction, increase pro-inflammatory mediators in the blood, and induce hippocampal neuroinflammation, as well as the underlying molecular mechanisms. In this study, we investigated the correlation between gut microbial dysbiosis following HI insult and HIBD-induced long-term cognitive impairments, and established the role of microbiota-gut-brain axis in regulating intestinal function and neuroinflammation after HIBD. Specifically, employing neonatal rats model of HIBD, we observed a significant correlation between changes in gut microbiota composition and severity of cognitive impairments after HI insult. Subsequently, we examined the intestinal inflammatory responses, intestinal barrier integrity, levels of pro-inflammatory mediators in peripheral circulation,
hippocampal neuroinflammation, synaptic injury and neural damage following HI insult to explore the potential mechanisms of the microbiota-gut-brain axis in neonatal HIBD. Correlation analysis revealed significant links between intestinal dysfunction and both hippocampal neuroinflammation and synaptic injury. In the causal relationship validation experiments, the FMT from cognitively normal rats was found to restore gut microbial composition, improve intestinal function, reduce serum levels of LPS and inflammatory mediators, and alleviate neuroinflammation, synaptic damage, and cognitive impairments in the neonatal HIBD recipient rats. Conversely, the FMT from neonatal HIBD rats induced similar adverse pathological changes in the normal recipient rats. In addition, we demonstrated that oral anti-inflammatory agent dexamethasone (DEX) treatment could exert neuroprotective effects by partially reducing intestinal inflammation and improving gut microbial dysbiosis. We further revealed that the intestinal LPS/toll-like receptor 4 (TLR4) signaling pathway was a potential molecular mechanism of the microbiota-gut-brain axis following HI insult, regulating intestinal function and systemic inflammation. Collectively, our study provides the new insights for developing potential therapeutic strategies for long-term cognitive impairments induced by the neonatal HIBD from the microbiota-gut-brain axis perspective.
Animals and experimental design The handling of laboratory animals adhered strictly to the Guide for the Care and Use of Laboratory Animals. Our laboratory acquired pregnant Sprague-Dawley rats, specific pathogen-free (SPF) strain, at a gestational age of 13 days from Fujian Medical University (Fuzhou, China). Appropriate transport containers were selected to maintain optimal temperature and humidity within the transport vehicle, while efforts were made to reduce noise and vibrations during transit, ensuring a transport duration of under 1 hour. Upon their arrival at our facility, the pregnant rats were placed in a calm single-cage environment conducive to acclimatization, where temperature
conditions were regulated, and a constant supply of food and water was provided while minimizing potential stressors. Daily monitoring of the pregnant rats’ delivery status was conducted to accurately determine gestational age and postnatal pup age. Throughout the experiment, neonatal rats were housed in cages with their littermates and nursing mothers under regulated temperature and lighting conditions (12 hours of light/12 hours of darkness), ensuring unrestricted access to food and water. Neonatal rats of both sexes from each litter were used in this study. To mitigate sex-related bias, an equal distribution of female and male pups was maintained within each experimental group. The Animal Care and Use Committee at Fujian Provincial Hospital (Fuzhou, China) granted ethical approval for this research (Approval No: IACUC-FPH-SL-20230825[0088]). In the initial experiment ( ), postnatal day 7 rats were chosen and randomly sorted into two groups: (1) the sham group, where rats underwent anesthesia and their left carotid artery was exposed but not ligated or subjected to subsequent hypoxic intervention, and (2) the HI insult group, where the Rice-Vannucci modeling method was utilized to create an animal model of HIBD. On the 3rd day after the HI insult, fecal samples were collected from both groups of neonatal rats for 16S rRNA sequencing, aiming to investigate any alterations in gut microbial composition during the acute phase after HI insult. Cognitive behavioral assessments, including the Morris water maze (MWM), novel object recognition (NOR), and Y-maze test, were performed 28–37 days post-HI insult. To explore the potential microbiota-gut-brain axis mechanisms underlying long-term cognitive impairments after HI insult, the colonic tissues, serum, and hippocampal tissues were collected on the 3rd day post-HI insult ( ). Furthermore, various techniques including Hematoxylin and Eosin (HE) staining, immunofluorescence (IF) staining, immunohistochemistry (IHC) staining, enzyme-linked immunosorbent assay (ELISA), transmission electron microscopy (TEM), Golgi staining, and Nissl staining were utilized to evaluate the integrity of the intestinal barrier, the inflammatory response in the intestine, serum levels of pro-inflammatory mediators, activation of neuroinflammatory glial
cells in the hippocampus, synaptic structure, and the quantity and morphology of hippocampal neurons following HIBD. Additionally, the correlation analysis was conducted to determine the possible link between gut microbial dysbiosis and long-term cognitive impairments post-HI insult, and between intestinal dysfunction and hippocampal pathological changes. To further validate the potential causal relationship between gut microbial dysbiosis following HI insult and long-term cognitive impairments, various FMT strategies, including transferring fecal microbiota from rats in the sham group to recipient rats in the HI group and vice versa ( ), were conducted. Transplantations were performed daily from the 7th postnatal day to the 3rd day post-HI insult. The effectiveness of FMT was validated through quantitative PCR (qPCR) analysis, followed by evaluations of intestinal inflammation, integrity of the intestinal barrier, serum levels of pro-inflammatory mediators, activation of neuroinflammatory glial cells in the hippocampus, synaptic structure, and long-term cognitive function. Increased intestinal inflammation is a primary factor of barrier impairments. DEX, a conventional anti-inflammatory drug, can significantly mitigate the intestinal barrier damage caused by diverse etiologies through exerting a protective anti-inflammatory effect. , , Moreover, available literatures suggest that the gut microbiota is a key regulatory factor for the observed anti-inflammatory effects on intestinal tissues after DEX treatment. , Thus, the observed beneficial effects of FMT on cognitive impairments induced by HI insult encouraged us to determine the potential impacts of oral DEX treatment within a similar framework. Previous research indicated that an oral dose of DEX 1 mg/kg was safe in the mouse models of other neurological diseases and beneficial for gut microbiota, intestinal function, and cognitive function. In our pilot experiments (see Supplementary note 1 and Supplementary Figure S1), we investigated oral DEX dosage gradients in neonatal HIBD rats and demonstrated that an oral dose of DEX 1 mg/kg was safe and effective. Then, postnatal day 7 rats were randomly assigned to the sham group, HI group and HI+DEX group ( ). The rats
in the HI+DEX group were administered DEX (ST1254, beyotime, China) orally at a dosage of 1 mg/kg daily from the 7th postnatal day to the 3rd day after HI insult. Subsequently, intestinal inflammation, intestinal barrier integrity, serum levels of pro-inflammatory mediators, activation of hippocampal neuroinflammatory glial cells, synaptic structure, and long-term cognitive function were tested. To further verify whether the gut microbiota were also the key mediators for the neuroprotective effect of oral DEX, the FMT was conducted for validation. Fecal microbiota from both the HI group and HI+DEX group donor rats were transplanted into the HI group recipients daily from the 7th day after birth to the 3rd day post HI insult ( ). The efficacy of FMT was confirmed by the qPCR, followed by assessments of activation of hippocampal neuroinflammatory glial cells, synaptic structure, and long-term cognitive function. To further explore the potential molecular mechanisms of intestinal inflammation following HIBD, a high-throughput RNA-Seq was conducted to determine the related genes and molecular pathways ( ). Based on the literature reports, we selected TLR4-IN-C34, an orally active and specific TLR4 inhibitor, for further study. Furthermore, in our pilot experiments (see Supplementary note s2 and Supplementary figure s2), we investigated the dose-response relation of oral TLR4-IN-C34 in the neonatal HIBD rats and demonstrated that an oral dose of TLR4-IN-C34 1 mg/kg was safe and effective. Then, the rats in the HI+TLR4-IN-C34 group were administered TLR4-IN-C34 (HY-107575, MedChemExpress, USA) orally at a dosage of 1 mg/kg daily from the 7th postnatal day to the 3rd day after HI insult. Subsequently, intestinal TLR4 expression, intestinal function, systemic inflammation, synaptic structure, and long-term cognitive function were determined. Furthermore, additional experiments were performed to determine whether the neuroprotective effects of FMT and oral DEX interventions were related to the regulation of intestinal LPS/TLR4 signaling pathway. To simulate the clinical scenario of oral drug administration, the oral DEX and TLR4-IN-C34 method used in this study followed the conventional approach, that is, the drug powders was added to the rats’ regular sterile drinking
water. , Considering that 7–10-day-old rats are not yet able to drink water independently, we added DEX and TLR4-IN-C34 powders into centrifuge tubes with 2 ml of sterile drinking water, thoroughly mixed them through shaking, and slowly administered them orally using a syringe while monitoring swallowing to ensure accurate dosing. To ensure experimental consistency, neonatal rats in the other groups received equivalent volume of sterile drinking water. For histological analyses, five tissue sections from different levels of consecutive slices from the brain and intestine tissues of each animal were selected and evaluated at three positions in each section relevant to the experimental objectives. For each sample, a minimum of ten measurements were taken from non-overlapping, well-oriented areas. The average counts from these evaluations were then included in the final statistical analysis. Five animals from each group were included in the analysis. The number of animal samples used in the pilot study and in different experimental groups at various stages of the main study are shown in Supplementary Tables S1 and S2. Neonatal HIBD animal model In this study, the Rice – Vannucci model approach was performed to construct a neonatal HIBD animal model, following the protocols outlined in our previous research. Initially, on postnatal day 7, the left common carotid artery of SD rats was ligated under anesthesia with 3% isoflurane. Following a recovery period of 1 hour in the proximity of their dams, the neonatal rats were then placed in a hypoxic chamber with 8% O 2 at a temperature of 37°C for 2 hours. This procedure resulted in HI insult in the neonatal rats. Cognitive behavioral tests Cognitive behavioral tests, including the MWM, NOR, and Y-maze tests, were conducted in accordance with previous reports. , , MWM The MWM test was performed from the 28th to the 33rd day post HI insult to evaluate the cognitive
functions of rats. The MWM test spanned 6 days, starting with a place navigation test for the initial 5 days, followed by a probe trial on the final day. All tests were completed consistently between 9:00 a.m. and 3:00 p.m. to mitigate disruptions from diurnal variations and light influences on experimental results. A video camera positioned above the pool, segmented into four quadrants with a submerged platform (12 cm in diameter) in one quadrant, recorded rat movements. Prior to the formal tests, rats were allowed 90 seconds of free swim in the pool. During the place navigation phase, rats, starting against the pool wall, were given 90 seconds to locate the escape platform. The rats unable to find the platform within this timeframe were guided to it and remained there for 30 seconds. Four trials were conducted daily for five days, and the average escape latency was recorded to evaluate spatial learning and memory capabilities. On the 6th day, during the probe trial, the hidden platform was removed, and rats were allowed to swim for 90 seconds; spatial memory was assessed by observing the number of platform crossings and time spent in the target quadrant. NOR The NOR test was performed from the 34th and 36th days post HI insult to assess the cognitive functions of rats. Beginning on the 34th day post HI insult, all rats designated for the NOR test were placed in a box-shaped space for a 10-minute acclimation period. The following day, a log-colored cylindrical wooden block (Object A) and a blue cylindrical wooden block (Object B) were positioned at opposite ends of the same wall within the box-shaped space. Rats were then introduced into the box-shaped space with their backs to these objects to commence a training session aimed at exploring Objects A and B, which was documented via an overhead video recorder for 10 minutes. On the 36th day post HI insult, we substituted Object B with a red triangular wooden block (Object C) and recorded the rats’ exploratory behavior toward this new object for an additional 10 minutes. Following video review, the duration of time that the rats spent in the novel object (Object C) was noted. The Recognition Index (RI) was subsequently calculated as follows: RI = [(time spent
exploring the novel object)/(total time spent exploring both objects)] × 100%. Y maze The Y maze test was performed on the 37th days post HI insult to assess the cognitive functions of rats. The maze consisted of three arms. During the test, each test rat was placed in one arm and permitted to move freely among the arms for a duration of five minutes. The alternation rate was calculated using the formula: actual alternations/maximum possible alternations × 100%. The term “actual alternations” refers to rats entering the three arms consecutively and is recorded as one alternation, while “maximum possible alternations” is defined as the total number of arm entries minus 2. 16S rRNA sequencing and bioinformatic analysis Fresh fecal samples from rats of each group were collected on the 3rd day post HI insult. Bacterial genomic DNA was then extracted from these samples using the QIAamp Power Fecal Pro DNA Kit (QIAGEN, Germany), adhering to the manufacturer’s instructions. Subsequently, the V3-V4 regions of the microbial 16S rRNA genes were amplified using specific primers (forward: 5′-CCTACGGGNGGCWGCAG-3′; reverse: 5′-GGACTACHVGGGTATCTAAT-3′). Amplification conditions included an initial step at 95°C for 5 minutes, followed by 30 cycles of denaturation at 72°C for 1 minute, and a final extension at 72°C for 7 minutes. Equal concentrations of the quantified amplicons were pooled for Illumina MiSeq sequencing (Illumina, Inc., CA, USA). Gene Denovo (Guangzhou, China) conducted DNA extraction, quality assessment, library construction, and high-throughput sequencing, and further collaborated with us to process and analyze the 16S rRNA sequencing data. In brief, FASTP (V0.18) was employed to filter the clean reads, specifically excluding those with an average Phred score below 20, those containing adapter sequences, and those with more than 10% unknown nucleotides (N). Subsequently, Operational Taxonomic Units (OTUs) were clustered at a similarity threshold exceeding 97% utilizing UPARSE (V9.2.64). The OTU sequences thus
obtained were annotated to classify taxa using the SILVA database (V138.1). Then using the OmicShare tools ( https://www.omicshare.com/tools/ ) provided by Gene Denovo to analyze α-diversity, β-diversity, analysis of similarity (ANOSIM), composition of gut microbiota, linear discriminant analysis effect size (LEfSe), and indicator species analysis. HE staining The colonic tissues from each group were collected on the 3rd day post HI insult. The rats were anesthetized and subjected to cardiac perfusion with saline, followed by fixation with paraformaldehyde (PFA). The colons were then excised, sectioned into 1 cm lengths, fixed in 4% PFA for 24 hours, and embedded in paraffin. Following embedding, sections measuring 4-μm in thickness were cut, deparaffinized, and stained with hematoxylin and eosin using standard protocols. The severity of colon injury was assessed employing a modified Chiu’s scoring system, which focuses on changes in the villi and glands of the intestinal mucosa. IF and IHC staining Brain and colon tissues from each group were collected on the 3rd day post HI insult. Rats were anesthetized and underwent cardiac perfusion with saline, followed by fixation with PFA. Subsequently, the tissues were removed, fixed again, and dehydrated in a 30% sucrose solution. Both the IF and IHC staining analyses were performed as described in previous studies. , For IF staining of the colon, Occludin (1:200, ab216327, Abcam, USA) and ZO-1 (1:200, ab221547, Abcam, USA) antibodies were used to detect the intestinal barrier integrity, and TLR4 (1:50, sc -293,072, Santa Cruz, USA) antibodies was used to detect the intestinal TLR4 expression. According to literature reports, , IL-17a and IL-22 are initiators of inflammatory responses in intestinal tissue, which can trigger a series of inflammatory cascades. Hence, for IHC staining of the colon, IL-17a (1:200, ab214588, Abcam, USA) and IL-22 (1:200, ab203211, Abcam, USA) antibodies were used to detect the inflammatory response of intestine.
Brain sections were stained for IF using IBA-1 (1:100, EPR16589, Abcam, USA) and GFAP (1:200, ab279289, Abcam, USA) to detect hippocampal neuroinflammatory response. All stained sections were randomly assigned for independent analysis by observer blind to the experimental conditions. Image-Pro Plus 6.0 software facilitated the analysis and export of IF and IHC measurement data. ELISA Serum and fecal samples from each group were collected on the 3rd day following the HI insult. Pre-coated plates equipped with specific capture antibodies for LPS (Jianglai Industrial Limited, China), TNF-α (E-EL-R2856, Elabscience, China), IL-6 (E-EL-R0015, Elabscience, China), and IL-1β (E-EL-R0012, Elabscience, China) were prepared. To determine the fecal and serum LPS levels and the serum levels of inflammatory mediators including TNF-α, IL-6, and IL-1β, the respective standards and target samples were placed into corresponding wells. The plates were incubated for 24 hours at room temperature, facilitating the binding of the target proteins to the capture antibodies. Subsequently, a substrate solution for horseradish peroxidase (HRP) was added to each well, with the color development meticulously monitored over a 10 to 30 minutes interval. The enzymatic reaction was terminated by the addition of a stop solution, which changed the solution’s color to yellow. Absorbance measurements were obtained using a microplate reader. TEM Brain tissues from each group were obtained on the 3rd day following the HI insult. These tissues were then fixed with 2.5% glutaraldehyde for 1 hour at room temperature and subsequently dehydrated in ethanol for 10 minutes. Following dehydration, the tissues were embedded in epoxy resin, sectioned, and stained with uranyl acetate and lead citrate. The hippocampal microstructure was examined using TEM (JEM-2100), which allowed for the observation of ultrastructural morphological changes in hippocampal synapses. Golgi staining Brain tissues from each group were collected on the 3rd day following the HI insult for Golgi-Cox staining. The dissected brains were submerged in Golgi-Cox solution containing 5% potassium dichromate, 5% mercuric chloride, and 5% potassium chromate for 35 days. Following immersion, the brains were placed in a 20% sucrose solution overnight and then sectioned coronally at 150 μm using a freezing microtome. The staining process included two washes with distilled water, a 2-minute treatment with 5% sodium thiosulfate, and another two washes with distilled water. The sections were dehydrated through sequential immersion in 70%, 90%, and 100% ethanol, followed by xylene, and then rinsed three times with bidistilled water. Images of the stained sections were acquired using a Nikon E600 camera. Nissl staining Brain tissues from each group were harvested on the 3rd day post HI insult for Nissl staining, a technique applied to assess neuronal loss and neuron morphology in the hippocampus’s CA1 region. Following paraffin embedding and sectioning, the tissue sections underwent dewaxing and dehydration before being stained with Cresyl violet acetate for 5 to 10 minutes. This was succeeded by two quick, 10-second rinses in distilled water. The sections were then subjected to sequential dehydration through ethanol and xylene for 5 minutes each before being mounted on glass slides. The morphology, quantity, and thickness of the neurons in the hippocampus’s CA1 region were observed and analyzed using light microscopy. FMT This study implemented three FMT strategies. The first strategy involved transferring fecal microbiota from sham group and HI group donor rats to sham group recipient rats. The second strategy involved transferring fecal microbiota from HI group and sham group donor rats to HI group recipient rats. The aim of the above two FMT strategies was to verify the causal relationship between gut microbiota and long-term cognitive impairments in
neonatal HIBD. The third strategy involved transplanting fecal microbiota from HI group and HI+DEX group donor rats to HI group recipient rats to observe whether gut microbiota is a key mediator for the neuroprotective effect of DEX in neonatal HIBD rats. Following the methodology outlined by Deshmukh et al. pregnant rats received sterile drinking water containing a combination of five antibiotics (ampicillin, gentamicin, metronidazole, vancomycin, neomycin) from the 15th day of gestation to the 5th day post-birth to generate recipient rats with depleted gut microbiota, facilitating successful colonization by the transplanted microbiota. Donor and recipient rats for each FMT strategy were synchronized and housed separately in sterile environments. Fecal samples from donor rats were collected daily from postnatal day 7 until the 3rd day post-HI insult and transplanted to age-matched recipient rats. In line with the methodology outlined by He et al. fresh fecal pellets were collected immediately after defecation, diluted in 100 mg/ml sterile saline, stored correctly, and administered to the recipients via gavage in a sterile environment. Quantification of f_Enterobacteriaceae and f_Akkermansiaceae of feces Two representative bacteria with significant differences in the gut microbiota between the sham and HI groups were identified from the 16S rRNA data, that is, f_Enterobacteriaceae and f_Akkermansiaceae . Therefore, after FMT, fresh feces were collected from the rats and quantification of f_Enterobacteriaceae and f_Akkermansiaceae was performed using the qPCR to assess the effect of the FMT. Total genomic DNA was extracted from fecal samples using the Stool DNA Kit (TransGen Biotech Co, China). The DNA templates were diluted to a concentration of 12.5 ng/µL using RNase-Free Distilled Water. Subsequently, 2 µL of this dilution, corresponding to 25 ng of total DNA, was used in triplicate for analysis. For f_Enterobacteriaceae identification, the forward primer 5′-CATTGACGTTACCCGCAGAAGAAGC-3′ and the reverse primer 5′-CTCTACGAGACTCAAGCTTGC-3′ were used. Similarly, for f_Akkermansiaceae detection, the forward primer
was 5′-CAGCACGTGAAGGTGGGGAC-3′ and the reverse primer was 5′-CCTTGCGGTTGGCTTCAGAT-3′. Both sets of primers were utilized in conjunction with SYBR Green Nucleic Acid Gel Stains (ABclonal, China), adhering to the manufacturer’s protocol. qPCR analyses were conducted on the ABI QuantStudio 3 Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA). The reaction mixtures, with a total volume of 20 µL, underwent an initial denaturation at 95°C for 3 minutes, followed by 40 cycles of denaturation at 95°C for 5 seconds and annealing/extension at 60°C for 30 seconds. A melting curve analysis was performed to ensure the specificity of the amplification. To quantify absolute 16S rRNA gene copy numbers in the samples, standard curves were generated from serial dilutions of plasmid DNA encompassing a conserved sequence of Enterobacteriaceae and Akkermansiaceae . High-throughput RNA-Seq of intestinal tissues Colonic tissues from each group were collected on the 3rd day post HI insult. Total RNA was extracted utilizing the TRIzol reagent kit (Invitrogen). The integrity and quality of the RNA were confirmed by RNase-free agarose gel electrophoresis via the Agilent 2100 Bioanalyzer (Agilent Technologies). Enriched mRNA was then reverse-transcribed into cDNA with the help of DNA polymerase I, RNase H, dNTPs, and appropriate buffer. The resulting cDNA fragments were purified and underwent end-repair using the QiaQuick PCR extraction kit (Qiagen). Following the addition of poly(A) tails, Illumina sequencing adapters were attached to the fragments. Agarose gel electrophoresis was subsequently used to select the PCR amplification products, which were then sequenced using the NovaSeq6000 by Gene Denovo Biotechnology Co. Western blot analysis Colon tissues from each group were collected on the 3rd day post HI insult. The tissues were homogenized in a lysis buffer containing protease inhibitors. Proteins (40 μg/well) were separated by the SDS-PAGE and then transferred onto polyvinylidene fluoride (PVDF) membranes. The
membranes were incubated overnight at 4°C with primary antibodies: anti-TLR4 (1:500, sc -293,072, Santa Cruz, USA). At the next day, the membranes were incubated with secondary antibodies for 2 hours at room temperature. Protein bands were detected using enhanced chemiluminescence substrate kits (ab133406, Abcam) and visualized with a GE Amersham Imager 600 (AI600; GE Healthcare). Full unedited gel/blot from this study are available in Supplementary Figure S7–9. Statistical analysis The data of 16S rRNA sequencing and intestinal RNA-Seq were analyzed using the tools and methodologies provided by Gene Denovo (Guangzhou, China). Other data was analyzed employing SPSS 22.0 software. The Shapiro – Wilk test assessed data normality, while Levene’s test evaluated variance homogeneity. Data that followed a normal distribution were presented as mean ± standard deviation. The student’s t-test was used for pairwise group comparisons. For analyses involving three or more groups, a one-way analysis of variance (ANOVA) was executed, with Bonferroni’s post hoc test applied for data with normal distribution. For data not fitting a normal distribution, the nonparametric Kruskal – Wallis test was used. The MWM test’s escape latency was analyzed using repeated measure two-way ANOVA, considering “day” as the within-subject factor and “group” as the between-subject factor. Correlations between different experiments were determined using Spearman correlation analysis conducted in R (version 3.5.3). P < 0.05 as statistically significant.
The handling of laboratory animals adhered strictly to the Guide for the Care and Use of Laboratory Animals. Our laboratory acquired pregnant Sprague-Dawley rats, specific pathogen-free (SPF) strain, at a gestational age of 13 days from Fujian Medical University (Fuzhou, China). Appropriate transport containers were selected to maintain optimal temperature and humidity within the transport vehicle, while efforts were made to reduce noise and vibrations during transit, ensuring a transport duration of under 1 hour. Upon their arrival at our facility, the pregnant rats were placed in a calm single-cage environment conducive to acclimatization, where temperature
conditions were regulated, and a constant supply of food and water was provided while minimizing potential stressors. Daily monitoring of the pregnant rats’ delivery status was conducted to accurately determine gestational age and postnatal pup age. Throughout the experiment, neonatal rats were housed in cages with their littermates and nursing mothers under regulated temperature and lighting conditions (12 hours of light/12 hours of darkness), ensuring unrestricted access to food and water. Neonatal rats of both sexes from each litter were used in this study. To mitigate sex-related bias, an equal distribution of female and male pups was maintained within each experimental group. The Animal Care and Use Committee at Fujian Provincial Hospital (Fuzhou, China) granted ethical approval for this research (Approval No: IACUC-FPH-SL-20230825[0088]). In the initial experiment ( ), postnatal day 7 rats were chosen and randomly sorted into two groups: (1) the sham group, where rats underwent anesthesia and their left carotid artery was exposed but not ligated or subjected to subsequent hypoxic intervention, and (2) the HI insult group, where the Rice-Vannucci modeling method was utilized to create an animal model of HIBD. On the 3rd day after the HI insult, fecal samples were collected from both groups of neonatal rats for 16S rRNA sequencing, aiming to investigate any alterations in gut microbial composition during the acute phase after HI insult. Cognitive behavioral assessments, including the Morris water maze (MWM), novel object recognition (NOR), and Y-maze test, were performed 28–37 days post-HI insult. To explore the potential microbiota-gut-brain axis mechanisms underlying long-term cognitive impairments after HI insult, the colonic tissues, serum, and hippocampal tissues were collected on the 3rd day post-HI insult ( ). Furthermore, various techniques including Hematoxylin and Eosin (HE) staining, immunofluorescence (IF) staining, immunohistochemistry (IHC) staining, enzyme-linked immunosorbent assay (ELISA), transmission electron microscopy (TEM), Golgi staining, and Nissl staining were utilized to evaluate the integrity of the intestinal barrier, the inflammatory response in the intestine, serum levels of pro-inflammatory mediators, activation of neuroinflammatory glial
cells in the hippocampus, synaptic structure, and the quantity and morphology of hippocampal neurons following HIBD. Additionally, the correlation analysis was conducted to determine the possible link between gut microbial dysbiosis and long-term cognitive impairments post-HI insult, and between intestinal dysfunction and hippocampal pathological changes. To further validate the potential causal relationship between gut microbial dysbiosis following HI insult and long-term cognitive impairments, various FMT strategies, including transferring fecal microbiota from rats in the sham group to recipient rats in the HI group and vice versa ( ), were conducted. Transplantations were performed daily from the 7th postnatal day to the 3rd day post-HI insult. The effectiveness of FMT was validated through quantitative PCR (qPCR) analysis, followed by evaluations of intestinal inflammation, integrity of the intestinal barrier, serum levels of pro-inflammatory mediators, activation of neuroinflammatory glial cells in the hippocampus, synaptic structure, and long-term cognitive function. Increased intestinal inflammation is a primary factor of barrier impairments. DEX, a conventional anti-inflammatory drug, can significantly mitigate the intestinal barrier damage caused by diverse etiologies through exerting a protective anti-inflammatory effect. , , Moreover, available literatures suggest that the gut microbiota is a key regulatory factor for the observed anti-inflammatory effects on intestinal tissues after DEX treatment. , Thus, the observed beneficial effects of FMT on cognitive impairments induced by HI insult encouraged us to determine the potential impacts of oral DEX treatment within a similar framework. Previous research indicated that an oral dose of DEX 1 mg/kg was safe in the mouse models of other neurological diseases and beneficial for gut microbiota, intestinal function, and cognitive function. In our pilot experiments (see Supplementary note 1 and Supplementary Figure S1), we investigated oral DEX dosage gradients in neonatal HIBD rats and demonstrated that an oral dose of DEX 1 mg/kg was safe and effective. Then, postnatal day 7 rats were randomly assigned to the sham group, HI group and HI+DEX group ( ). The rats
in the HI+DEX group were administered DEX (ST1254, beyotime, China) orally at a dosage of 1 mg/kg daily from the 7th postnatal day to the 3rd day after HI insult. Subsequently, intestinal inflammation, intestinal barrier integrity, serum levels of pro-inflammatory mediators, activation of hippocampal neuroinflammatory glial cells, synaptic structure, and long-term cognitive function were tested. To further verify whether the gut microbiota were also the key mediators for the neuroprotective effect of oral DEX, the FMT was conducted for validation. Fecal microbiota from both the HI group and HI+DEX group donor rats were transplanted into the HI group recipients daily from the 7th day after birth to the 3rd day post HI insult ( ). The efficacy of FMT was confirmed by the qPCR, followed by assessments of activation of hippocampal neuroinflammatory glial cells, synaptic structure, and long-term cognitive function. To further explore the potential molecular mechanisms of intestinal inflammation following HIBD, a high-throughput RNA-Seq was conducted to determine the related genes and molecular pathways ( ). Based on the literature reports, we selected TLR4-IN-C34, an orally active and specific TLR4 inhibitor, for further study. Furthermore, in our pilot experiments (see Supplementary note s2 and Supplementary figure s2), we investigated the dose-response relation of oral TLR4-IN-C34 in the neonatal HIBD rats and demonstrated that an oral dose of TLR4-IN-C34 1 mg/kg was safe and effective. Then, the rats in the HI+TLR4-IN-C34 group were administered TLR4-IN-C34 (HY-107575, MedChemExpress, USA) orally at a dosage of 1 mg/kg daily from the 7th postnatal day to the 3rd day after HI insult. Subsequently, intestinal TLR4 expression, intestinal function, systemic inflammation, synaptic structure, and long-term cognitive function were determined. Furthermore, additional experiments were performed to determine whether the neuroprotective effects of FMT and oral DEX interventions were related to the regulation of intestinal LPS/TLR4 signaling pathway. To simulate the clinical scenario of oral drug administration, the oral DEX and TLR4-IN-C34 method used in this study followed the conventional approach, that is, the drug powders was added to the rats’ regular sterile drinking
water. , Considering that 7–10-day-old rats are not yet able to drink water independently, we added DEX and TLR4-IN-C34 powders into centrifuge tubes with 2 ml of sterile drinking water, thoroughly mixed them through shaking, and slowly administered them orally using a syringe while monitoring swallowing to ensure accurate dosing. To ensure experimental consistency, neonatal rats in the other groups received equivalent volume of sterile drinking water. For histological analyses, five tissue sections from different levels of consecutive slices from the brain and intestine tissues of each animal were selected and evaluated at three positions in each section relevant to the experimental objectives. For each sample, a minimum of ten measurements were taken from non-overlapping, well-oriented areas. The average counts from these evaluations were then included in the final statistical analysis. Five animals from each group were included in the analysis. The number of animal samples used in the pilot study and in different experimental groups at various stages of the main study are shown in Supplementary Tables S1 and S2.
In this study, the Rice – Vannucci model approach was performed to construct a neonatal HIBD animal model, following the protocols outlined in our previous research. Initially, on postnatal day 7, the left common carotid artery of SD rats was ligated under anesthesia with 3% isoflurane. Following a recovery period of 1 hour in the proximity of their dams, the neonatal rats were then placed in a hypoxic chamber with 8% O 2 at a temperature of 37°C for 2 hours. This procedure resulted in HI insult in the neonatal rats.
Cognitive behavioral tests, including the MWM, NOR, and Y-maze tests, were conducted in accordance with previous reports. , ,
The MWM test was performed from the 28th to the 33rd day post HI insult to evaluate the cognitive
functions of rats. The MWM test spanned 6 days, starting with a place navigation test for the initial 5 days, followed by a probe trial on the final day. All tests were completed consistently between 9:00 a.m. and 3:00 p.m. to mitigate disruptions from diurnal variations and light influences on experimental results. A video camera positioned above the pool, segmented into four quadrants with a submerged platform (12 cm in diameter) in one quadrant, recorded rat movements. Prior to the formal tests, rats were allowed 90 seconds of free swim in the pool. During the place navigation phase, rats, starting against the pool wall, were given 90 seconds to locate the escape platform. The rats unable to find the platform within this timeframe were guided to it and remained there for 30 seconds. Four trials were conducted daily for five days, and the average escape latency was recorded to evaluate spatial learning and memory capabilities. On the 6th day, during the probe trial, the hidden platform was removed, and rats were allowed to swim for 90 seconds; spatial memory was assessed by observing the number of platform crossings and time spent in the target quadrant.
The NOR test was performed from the 34th and 36th days post HI insult to assess the cognitive functions of rats. Beginning on the 34th day post HI insult, all rats designated for the NOR test were placed in a box-shaped space for a 10-minute acclimation period. The following day, a log-colored cylindrical wooden block (Object A) and a blue cylindrical wooden block (Object B) were positioned at opposite ends of the same wall within the box-shaped space. Rats were then introduced into the box-shaped space with their backs to these objects to commence a training session aimed at exploring Objects A and B, which was documented via an overhead video recorder for 10 minutes. On the 36th day post HI insult, we substituted Object B with a red triangular wooden block (Object C) and recorded the rats’ exploratory behavior toward this new object for an additional 10 minutes. Following video review, the duration of time that the rats spent in the novel object (Object C) was noted. The Recognition Index (RI) was subsequently calculated as follows: RI = [(time spent
exploring the novel object)/(total time spent exploring both objects)] × 100%.
The Y maze test was performed on the 37th days post HI insult to assess the cognitive functions of rats. The maze consisted of three arms. During the test, each test rat was placed in one arm and permitted to move freely among the arms for a duration of five minutes. The alternation rate was calculated using the formula: actual alternations/maximum possible alternations × 100%. The term “actual alternations” refers to rats entering the three arms consecutively and is recorded as one alternation, while “maximum possible alternations” is defined as the total number of arm entries minus 2.
Fresh fecal samples from rats of each group were collected on the 3rd day post HI insult. Bacterial genomic DNA was then extracted from these samples using the QIAamp Power Fecal Pro DNA Kit (QIAGEN, Germany), adhering to the manufacturer’s instructions. Subsequently, the V3-V4 regions of the microbial 16S rRNA genes were amplified using specific primers (forward: 5′-CCTACGGGNGGCWGCAG-3′; reverse: 5′-GGACTACHVGGGTATCTAAT-3′). Amplification conditions included an initial step at 95°C for 5 minutes, followed by 30 cycles of denaturation at 72°C for 1 minute, and a final extension at 72°C for 7 minutes. Equal concentrations of the quantified amplicons were pooled for Illumina MiSeq sequencing (Illumina, Inc., CA, USA). Gene Denovo (Guangzhou, China) conducted DNA extraction, quality assessment, library construction, and high-throughput sequencing, and further collaborated with us to process and analyze the 16S rRNA sequencing data. In brief, FASTP (V0.18) was employed to filter the clean reads, specifically excluding those with an average Phred score below 20, those containing adapter sequences, and those with more than 10% unknown nucleotides (N). Subsequently, Operational Taxonomic Units (OTUs) were clustered at a similarity threshold exceeding 97% utilizing UPARSE (V9.2.64). The OTU sequences thus
obtained were annotated to classify taxa using the SILVA database (V138.1). Then using the OmicShare tools ( https://www.omicshare.com/tools/ ) provided by Gene Denovo to analyze α-diversity, β-diversity, analysis of similarity (ANOSIM), composition of gut microbiota, linear discriminant analysis effect size (LEfSe), and indicator species analysis.
The colonic tissues from each group were collected on the 3rd day post HI insult. The rats were anesthetized and subjected to cardiac perfusion with saline, followed by fixation with paraformaldehyde (PFA). The colons were then excised, sectioned into 1 cm lengths, fixed in 4% PFA for 24 hours, and embedded in paraffin. Following embedding, sections measuring 4-μm in thickness were cut, deparaffinized, and stained with hematoxylin and eosin using standard protocols. The severity of colon injury was assessed employing a modified Chiu’s scoring system, which focuses on changes in the villi and glands of the intestinal mucosa.
Brain and colon tissues from each group were collected on the 3rd day post HI insult. Rats were anesthetized and underwent cardiac perfusion with saline, followed by fixation with PFA. Subsequently, the tissues were removed, fixed again, and dehydrated in a 30% sucrose solution. Both the IF and IHC staining analyses were performed as described in previous studies. , For IF staining of the colon, Occludin (1:200, ab216327, Abcam, USA) and ZO-1 (1:200, ab221547, Abcam, USA) antibodies were used to detect the intestinal barrier integrity, and TLR4 (1:50, sc -293,072, Santa Cruz, USA) antibodies was used to detect the intestinal TLR4 expression. According to literature reports, , IL-17a and IL-22 are initiators of inflammatory responses in intestinal tissue, which can trigger a series of inflammatory cascades. Hence, for IHC staining of the colon, IL-17a (1:200, ab214588, Abcam, USA) and IL-22 (1:200, ab203211, Abcam, USA) antibodies were used to detect the inflammatory response of intestine.
Brain sections were stained for IF using IBA-1 (1:100, EPR16589, Abcam, USA) and GFAP (1:200, ab279289, Abcam, USA) to detect hippocampal neuroinflammatory response. All stained sections were randomly assigned for independent analysis by observer blind to the experimental conditions. Image-Pro Plus 6.0 software facilitated the analysis and export of IF and IHC measurement data.
Serum and fecal samples from each group were collected on the 3rd day following the HI insult. Pre-coated plates equipped with specific capture antibodies for LPS (Jianglai Industrial Limited, China), TNF-α (E-EL-R2856, Elabscience, China), IL-6 (E-EL-R0015, Elabscience, China), and IL-1β (E-EL-R0012, Elabscience, China) were prepared. To determine the fecal and serum LPS levels and the serum levels of inflammatory mediators including TNF-α, IL-6, and IL-1β, the respective standards and target samples were placed into corresponding wells. The plates were incubated for 24 hours at room temperature, facilitating the binding of the target proteins to the capture antibodies. Subsequently, a substrate solution for horseradish peroxidase (HRP) was added to each well, with the color development meticulously monitored over a 10 to 30 minutes interval. The enzymatic reaction was terminated by the addition of a stop solution, which changed the solution’s color to yellow. Absorbance measurements were obtained using a microplate reader.
Brain tissues from each group were obtained on the 3rd day following the HI insult. These tissues were then fixed with 2.5% glutaraldehyde for 1 hour at room temperature and subsequently dehydrated in ethanol for 10 minutes. Following dehydration, the tissues were embedded in epoxy resin, sectioned, and stained with uranyl acetate and lead citrate. The hippocampal microstructure was examined using TEM (JEM-2100), which allowed for the observation of ultrastructural morphological changes in hippocampal synapses.
Brain tissues from each group were collected on the 3rd day following the HI insult for Golgi-Cox staining. The dissected brains were submerged in Golgi-Cox solution containing 5% potassium dichromate, 5% mercuric chloride, and 5% potassium chromate for 35 days. Following immersion, the brains were placed in a 20% sucrose solution overnight and then sectioned coronally at 150 μm using a freezing microtome. The staining process included two washes with distilled water, a 2-minute treatment with 5% sodium thiosulfate, and another two washes with distilled water. The sections were dehydrated through sequential immersion in 70%, 90%, and 100% ethanol, followed by xylene, and then rinsed three times with bidistilled water. Images of the stained sections were acquired using a Nikon E600 camera.
Brain tissues from each group were harvested on the 3rd day post HI insult for Nissl staining, a technique applied to assess neuronal loss and neuron morphology in the hippocampus’s CA1 region. Following paraffin embedding and sectioning, the tissue sections underwent dewaxing and dehydration before being stained with Cresyl violet acetate for 5 to 10 minutes. This was succeeded by two quick, 10-second rinses in distilled water. The sections were then subjected to sequential dehydration through ethanol and xylene for 5 minutes each before being mounted on glass slides. The morphology, quantity, and thickness of the neurons in the hippocampus’s CA1 region were observed and analyzed using light microscopy.
This study implemented three FMT strategies. The first strategy involved transferring fecal microbiota from sham group and HI group donor rats to sham group recipient rats. The second strategy involved transferring fecal microbiota from HI group and sham group donor rats to HI group recipient rats. The aim of the above two FMT strategies was to verify the causal relationship between gut microbiota and long-term cognitive impairments in
neonatal HIBD. The third strategy involved transplanting fecal microbiota from HI group and HI+DEX group donor rats to HI group recipient rats to observe whether gut microbiota is a key mediator for the neuroprotective effect of DEX in neonatal HIBD rats. Following the methodology outlined by Deshmukh et al. pregnant rats received sterile drinking water containing a combination of five antibiotics (ampicillin, gentamicin, metronidazole, vancomycin, neomycin) from the 15th day of gestation to the 5th day post-birth to generate recipient rats with depleted gut microbiota, facilitating successful colonization by the transplanted microbiota. Donor and recipient rats for each FMT strategy were synchronized and housed separately in sterile environments. Fecal samples from donor rats were collected daily from postnatal day 7 until the 3rd day post-HI insult and transplanted to age-matched recipient rats. In line with the methodology outlined by He et al. fresh fecal pellets were collected immediately after defecation, diluted in 100 mg/ml sterile saline, stored correctly, and administered to the recipients via gavage in a sterile environment.
f_Enterobacteriaceae and f_Akkermansiaceae of feces Two representative bacteria with significant differences in the gut microbiota between the sham and HI groups were identified from the 16S rRNA data, that is, f_Enterobacteriaceae and f_Akkermansiaceae . Therefore, after FMT, fresh feces were collected from the rats and quantification of f_Enterobacteriaceae and f_Akkermansiaceae was performed using the qPCR to assess the effect of the FMT. Total genomic DNA was extracted from fecal samples using the Stool DNA Kit (TransGen Biotech Co, China). The DNA templates were diluted to a concentration of 12.5 ng/µL using RNase-Free Distilled Water. Subsequently, 2 µL of this dilution, corresponding to 25 ng of total DNA, was used in triplicate for analysis. For f_Enterobacteriaceae identification, the forward primer 5′-CATTGACGTTACCCGCAGAAGAAGC-3′ and the reverse primer 5′-CTCTACGAGACTCAAGCTTGC-3′ were used. Similarly, for f_Akkermansiaceae detection, the forward primer
was 5′-CAGCACGTGAAGGTGGGGAC-3′ and the reverse primer was 5′-CCTTGCGGTTGGCTTCAGAT-3′. Both sets of primers were utilized in conjunction with SYBR Green Nucleic Acid Gel Stains (ABclonal, China), adhering to the manufacturer’s protocol. qPCR analyses were conducted on the ABI QuantStudio 3 Real-Time PCR System (Applied Biosystems, Carlsbad, CA, USA). The reaction mixtures, with a total volume of 20 µL, underwent an initial denaturation at 95°C for 3 minutes, followed by 40 cycles of denaturation at 95°C for 5 seconds and annealing/extension at 60°C for 30 seconds. A melting curve analysis was performed to ensure the specificity of the amplification. To quantify absolute 16S rRNA gene copy numbers in the samples, standard curves were generated from serial dilutions of plasmid DNA encompassing a conserved sequence of Enterobacteriaceae and Akkermansiaceae .
Colonic tissues from each group were collected on the 3rd day post HI insult. Total RNA was extracted utilizing the TRIzol reagent kit (Invitrogen). The integrity and quality of the RNA were confirmed by RNase-free agarose gel electrophoresis via the Agilent 2100 Bioanalyzer (Agilent Technologies). Enriched mRNA was then reverse-transcribed into cDNA with the help of DNA polymerase I, RNase H, dNTPs, and appropriate buffer. The resulting cDNA fragments were purified and underwent end-repair using the QiaQuick PCR extraction kit (Qiagen). Following the addition of poly(A) tails, Illumina sequencing adapters were attached to the fragments. Agarose gel electrophoresis was subsequently used to select the PCR amplification products, which were then sequenced using the NovaSeq6000 by Gene Denovo Biotechnology Co.
Colon tissues from each group were collected on the 3rd day post HI insult. The tissues were homogenized in a lysis buffer containing protease inhibitors. Proteins (40 μg/well) were separated by the SDS-PAGE and then transferred onto polyvinylidene fluoride (PVDF) membranes. The
membranes were incubated overnight at 4°C with primary antibodies: anti-TLR4 (1:500, sc -293,072, Santa Cruz, USA). At the next day, the membranes were incubated with secondary antibodies for 2 hours at room temperature. Protein bands were detected using enhanced chemiluminescence substrate kits (ab133406, Abcam) and visualized with a GE Amersham Imager 600 (AI600; GE Healthcare). Full unedited gel/blot from this study are available in Supplementary Figure S7–9.
The data of 16S rRNA sequencing and intestinal RNA-Seq were analyzed using the tools and methodologies provided by Gene Denovo (Guangzhou, China). Other data was analyzed employing SPSS 22.0 software. The Shapiro – Wilk test assessed data normality, while Levene’s test evaluated variance homogeneity. Data that followed a normal distribution were presented as mean ± standard deviation. The student’s t-test was used for pairwise group comparisons. For analyses involving three or more groups, a one-way analysis of variance (ANOVA) was executed, with Bonferroni’s post hoc test applied for data with normal distribution. For data not fitting a normal distribution, the nonparametric Kruskal – Wallis test was used. The MWM test’s escape latency was analyzed using repeated measure two-way ANOVA, considering “day” as the within-subject factor and “group” as the between-subject factor. Correlations between different experiments were determined using Spearman correlation analysis conducted in R (version 3.5.3). P < 0.05 as statistically significant.
HI insult induced long-term cognitive impairments and gut microbial dysbiosis in neonatal rats The classical Rice – Vannucci modeling approach was performed to construct the neonatal HIBD model in postnatal day 7 rats. Cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results of MWM ( ) demonstrated that HI insult did not cause motor
dysfunction in rats, as evidenced by the lack of statistically significant differences in swimming speed between the sham group and the HI group over five consecutive days post-HI insult ( ). However, rats in the HI group demonstrated a significantly increased escape latency, and a substantial reduction in both number of platform crossing and duration of stay in the target quadrant ( ). Likewise, the NOR ( ) and Y-Maze ( ) evaluations revealed a notable decrease in the recognition index and spontaneous alternation rate in the HI group. These findings collectively corroborate that HI insult can elicit long-term cognitive impairments in neonatal rats, aligning with the outcomes observed in the infants with neonatal HIBD. To further determine the roles of gut microbial factors in the HI insult-induced cognitive impairments, the 16S rRNA gene sequencing was used to analyze the composition of the gut microbiota in the fecal samples of the two groups on the 3rd day following HI insult ( ). The results of α-diversity analysis ( ) indicated no statistically significant differences in the abundances (Chao1) and diversities (Shannon and Simpson) of gut microbiota in the fecal samples from the two groups of rats. However, when analyzing β-diversity of the gut microbiota in feces using Principal Coordinates Analysis (PCoA), the results revealed a distinct separation of microbial community structures between two groups ( ). In the Analysis of Similarities (ANOSIM), we found that a higher value in the “Between” category compared to within-group (Sham and HI group) values indicates that the between-group differences are significantly larger than within-group differences, with R = 0.4688 and p = 0.002 ( ). These results suggest that HI insult can causes severe gut microbial dysbiosis in neonatal rats. At the phylum level, the relative abundance of the p_Proteobacteria increased in the HI group, while the relative abundance of the phylum p_Bacteroidetes decreased ( ). At the family level, we observed dysbiosis in multiple gut microbiota between the two groups ( ). Additionally, using Linear discriminant analysis Effect Size (LEfSe) and indicator species analysis at the family level ( ), we identified significant microbiota differences between the groups, with f_Fusobacteriaceae , f_Enterobacteriaceae , f_Prevotellaceae, f_Streptococcaceae, and f_Vibrionaceae enriched in the HI group rats, while f_Akkermansiaceae , f_Enterococcaceae, f_Victivallaceae, f_Helicobacteraceae, and f_Planococcaceae were enriched in the sham group rats. Available studies have shown that f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae are linked to inflammatory responses, whereas f_Akkermansiaceae and f_Enterococcaceae exhibit anti-inflammatory effects. Thus, we determined the differences in the relative abundances of these five bacteria between the sham and HI groups and found that the relative abundances of f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae in the gut microbiota were significantly elevated in the HI group compared with the Sham group ( ). Conversely, the abundances of f_Akkermansiaceae and f_Enterococcaceae were notably reduced in the HI group ( ). All of these findings suggest that HI insult induces gut microbial dysbiosis in the early-stage in the neonatal HIBD rats. To better explore the correlation between gut microbial dysbiosis and cognitive impairments caused by HI insult, the correlation analyses between the relative abundance of five significantly altered gut microbial families screened from the 16S rRNA sequencing data and relevant index data from cognitive behavior tests (including escape latency of D32, the time of crossing, the time spent in target quadrant, recognition index, and Y maze alternation) were conducted. The results demonstrated a significant association
between increased relative abundance of f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae and more severe cognitive impairments, whereas a decreased relative abundance of f_Akkermansiaceae and f_Enterococcaceae correlated with more severe cognitive impairments ( ). The correlation results underscore the role of gut microbiota in the onset of long-term cognitive impairments following HI insult in the neonatal rats. HI insult induced intestinal dysfunction, and increased serum levels of LPS and inflammatory mediators in the neonatal rats The experimental flow chart exploring the possible role of microbiota-gut-brain axis in the neonatal HIBD is shown in . The HI group demonstrated significantly worsened histopathological damages and higher histology scores in the colon, compared to the sham group, as evidenced by HE staining ( ). The IF staining revealed a significant reduction in the colonic Occludin and ZO-1 expression in the HI group compared to the sham group ( ). Moreover, the results of IHC staining showed that, compared to the sham group, the IOD intensity of IL-17a and IL-22 were significantly increased in the HI group ( ). To further investigate whether intestinal dysfunction caused by HI insult affected the concentrations of pro-inflammatory mediators in the blood, an Elisa test was conducted on the serum of neonatal rats on the day 3 following HI insult ( ). The results of Elisa showed that, compared to the sham group, the serum concentrations of LPS, TNF-α, IL-6, and IL-1β were significantly increased in the HI group ( ). Additionally, the correlational analysis revealed that the more severe the intestinal dysfunction, the higher the serum concentrations of pro-inflammatory mediators ( ). In summary, these results indicate that HI insult can cause the intestinal barrier damage and intestinal
inflammation in the neonatal rats. Additionally, intestinal dysfunction induced by HI insult is strongly correlated with increased pro-inflammatory mediators in the circulation. Correlation analyses supported the involvement of intestinal dysfunction induced by HI insult in the hippocampal neuroinflammation and synaptic injury On the day 3 following HI insult, the hippocampal tissues were collected for test ( ). The results of IF staining showed that HI insult led to significant activation of microglia and astrocytes in the hippocampal CA1 region of neonatal rats ( ), manifested by increased number and intensities of both IBA1 and GFAP positive cells ( ). Furthermore, the confocal images revealed that HI insult caused microglia in the hippocampal region of neonatal rats to transition from a morphology characterized by small nuclei, long protrusions, and complex shapes to an activated state with enlarged cell bodies, thickened, and reduced branching ( ). The TEM was used to observe the ultrastructure of synapses in the hippocampal CA1 region and showed that, in the HI group, pronounced pathological alterations were evident, exemplified by a marked decrease in the thickness of the postsynaptic density (PSD) and an expansion of the synaptic cleft relative to the sham group ( ). The Golgi-Cox staining was utilized to determine the impact of HI insult on the morphology of pyramidal neurons and synaptic structures in the hippocampal CA1 region of neonatal rats. The results showed that HI insult resulted in a significant reduction in the density of dendritic spines and dendritic branches in the neonatal rats ( ). Additionally, the Nissl staining revealed significant neuropathological alterations in the hippocampal CA1 region in the HI group when compared to the sham group, which included nuclear shrinkage, neuronal loss, and reduced thickness ( ). These results indicate
that HI insult induces severe hippocampal neuroinflammation, synaptic injury and neuronal damage in the neonatal rats To better explore the correlation between the intestinal dysfunction and the hippocampal pathological changes following HI insult, the additional correlation analyses were conducted to determine the possible relationships between the representative indicators of intestinal dysfunction (mean fluorescence intensity of ZO-1 and mean IOD/Area of IL-17a) and the representative indicators of hippocampal pathological changes (mean
intensities of IBA-1 and GFAP per view, endpoints/cell of microglia, thickness of PSD, dendritic spines density, and average number of CA1 neurons per view). The results revealed significant negative correlations between the mean fluorescence intensity of ZO-1 in the colon and the mean intensities of both IBA-1 ( r = −0.7817, p = 0.0117) and GFAP ( r = −0.8061, p = 0.0082) per view in the hippocampal CA1 region ( ). Conversely, the mean fluorescence intensity of ZO-1 in the colon was significantly positively correlated with the endpoints per cell of microglia ( r =
0.7939, p = 0.0098), PSD thickness ( r = 0.9273, p = 0.0001), dendritic spine density ( r = 0.6748, p = 0.0323), and the average number of neurons per view ( r = 0.8788, p = 0.0002) in the hippocampal CA1 region ( ). These findings imply that the more severe the intestinal barrier damage, the more significant the pathological changes of hippocampal damage, including neuroinflammation, synaptic injury, and neuronal damage. Additionally, the results also revealed significant positive correlations between the mean IOD/Area of IL-17a in the colon and the mean intensities of both IBA-1 ( r = 0.903, p = 0.0009) and GFAP ( r = 0.8667, p = 0.0027) per view in the hippocampal CA1 region ( ). Conversely, the mean IOD/Area of IL-17a in the colon was significantly negatively correlated with the endpoints per cell of microglia ( r = −0.6848, p = 0.0351), dendritic spine density ( r = −0.772, p = 0.0089), and the average number of neurons per view ( r = −0.7939, p = 0.0098) in the hippocampal CA1 region ( ). These findings suggest that the more severe the intestinal inflammatory responses, the more significant the pathological changes of hippocampal damage, including neuroinflammation, synaptic injury, and neuronal damage. Together, all of these data suggest that the gut microbial dysbiosis following HI insult may exacerbate long-term cognitive impairments by promoting intestinal dysfunction, leading to the entry of gut microbiota-derived LPS and intestine-derived inflammatory mediators into the bloodstream, worsening hippocampal neuroinflammation, synaptic injury, and neuronal damage. The effects of FMT treatment on the intestinal function, systemic inflammation, synaptic structure and long-term cognitive function in the neonatal rats The experimental flow chart to explore the causal relationship between gut microbiota and long-term cognitive impairments induced by HI insult through the FMT is shown in . Fecal microbiota
from sham group and HI group donor rats were transferred to sham group and HI group recipient rats, respectively. The transplantation procedure involved administering FMT once daily from the postnatal 7th day until the 3rd day after HI insult. The samples of feces, colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult, and cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult. The effect of FMT was assessed through the quantification of specific fecal bacteria using PCR. Two representative bacteria, f_Enterobacteriaceae and f_Akkermansiaceae , previously identified from 16S rRNA sequencing data, were found to exhibit significant changes following HI insult. Specifically, Enterobacteriaceae , identified as harmful bacteria, showed a significant increase, while f_Akkermansiaceae , identified as beneficial bacteria, exhibited a significant decrease post-HI insult. The results showed that the content of Enterobacteriaceae in the group (Sham+hiFMT, HI+ hiFMT) receiving FMT from HI group donor rats was significantly higher than that in the group (Sham+shamFMT, HI+ shamFMT) receiving FMT from sham group donor rats. Conversely, the content of f_Akkermansiaceae in the Sham+hiFMT and HI+ hiFMT groups was significantly lower than that in the Sham+shamFMT and HI+ shamFMT groups ( ). These findings suggest that the FMT strategy in this study could effectively replace the original microbiota with the transplanted microbiota. Next, the findings from IHC and IF analysis on colon of neonatal rats demonstrated that, compared to the Sham+shamFMT group, rats in the Sham+hiFMT group exhibited intestinal dysfunction, which was characterized by a significant upregulation of IL-17a and IL-22 expression in colon, and a downregulation of the expression of tight junction-associated proteins occludin and ZO-1. Additionally, the intervention with FMT from the sham group donor rats led to a significant reduction in the expression levels of IL-17a and IL-22 cytokines, as well as an increase in the expression levels of tight junction-associated proteins occludin and ZO-1 in neonatal HIBD rats (HI
+shamFMT), compared to those in the HI+hiFMT group ( ). The Elisa results showed that the serum levels of LPS, TNF-α, IL-6, and IL-1β in the Sham+hiFMT group were significantly higher than those in the Sham+shamFMT group. However, the serum levels of above pro-inflammatory mediators in the HI+shamFMT group were significantly lower than those in the HI + hiFMT group ( ). These findings suggest that gut microbial dysbiosis following HI insult can induce intestinal dysfunction and elevate serum levels of pro-inflammatory mediators in the neonatal rats, and transplanting normal fecal microbiota can effectively ameliorate the intestinal dysfunction and serum inflammation levels in the neonatal HIBD rats. Interestingly, compared to HI+shamFMT group, the Sham+hiFMT group exhibited more severe intestinal dysfunction and higher serum levels of pro-inflammatory mediators ( ). These findings suggest that gut microbial dysbiosis following HI insult is a main factor causing intestinal dysfunction and peripheral inflammation in the neonatal rats. To determine the effects of FMT on hippocampus and long-term cognitive function in neonatal rats, further experiments were conducted. The results of IF analysis showed a significant increase in the number and intensity of IBA-1 and GFAP-positive cells in the hippocampal CA1 region in the Sham+hiFMT group compared to the Sham+shamFMT group. Additionally, a significant decrease in the number and intensity of IBA-1 and GFAP-positive cells was observed in the hippocampal CA1 region in the rats from the HI+shamFMT group compared to the HI+hiFMT group ( ). Subsequently, a notable reduction in the density of dendritic spines and branches in the hippocampal CA1 region was noted in the Sham+hiFMT group compared to the Sham+shamFMT group, as revealed by Golgi staining. Conversely, there was a marked elevation in the density of dendritic spines and branches in the hippocampal CA1 region in the HI+shamFMT group compared to the HI+hiFMT group ( ). In the cognitive behavior test, the results of MWM showed that the Sham+hiFMT group demonstrated a significantly increased escape latency and
a substantial decrease in both number of platform crossing and duration of stay in the target quadrant compared to the Sham+shamFMT group. Additionally, the HI+shamFMT group demonstrated a significantly decreased escape latency and a substantial increase in both platform crossings and duration of stay in the target quadrant compared to those in the HI+hiFMT group ( ). There was no significant difference in swim velocity among these groups ( ), indicating that the above differences are due to differences in cognitive function. Likewise, the results of NOR and Y-Maze revealed a notable decrease in the recognition index and spontaneous alternation rate in the Sham+hiFMT group compared to the Sham+shamFMT group, and a notable increase in the recognition index and spontaneous alternation rate in rats from the HI+shamFMT group compared to the HI+hiFMT group ( ). These results indicate that gut microbial dysbiosis following HI insult can induce hippocampal neuroinflammation, and synaptic damage, and long-term cognitive impairments. Moreover, FMT from normal fecal microbiota can mitigate hippocampal neuroinflammation, synaptic injury and long-term cognitive impairments in the neonatal HIBD rats. In summary, these data confirms that HI insult-induced gut microbial dysbiosis exacerbates long-term cognitive impairments in neonatal rats by promoting intestinal dysfunction, characterized by the activation of intestinal inflammation and disruption of intestinal barrier integrity. This dysregulation of intestinal function ultimately leads to elevated levels of pro-inflammatory mediators, including TNF-α, IL-6, IL-1β, and gut microbiota-derived LPS in the bloodstream, thereby promoting hippocampal neuroinflammation and synaptic damage. Moreover, our data further indicates that the transplantation of normal fecal microbiota can effectively mitigate the aforementioned pathological changes, ultimately alleviating long-term cognitive impairments in the neonatal HIBD rats. Oral DEX improved intestinal and long-term cognitive function in the neonatal HIBD rats by partially dependent on gut microbiota The HIBD neonatal rats were subjected to oral administration of DEX daily for a total of four times, from the day of HI insult to 3 days post-insult, and the samples of colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult ( ), as well the cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results of IHC analysis showed that oral DEX significantly inhibited the expression of IL-17a and IL-22 in the colonic tissues of neonatal HIBD rats, as evidenced by the significant reductions in the intensity of IOD of both cytokines ( ). Furthermore, the IF results indicated that oral DEX significantly enhanced the integrity of intestinal barrier, as evidenced by increased expression of tight junction-associated proteins occludin and ZO-1 in the colon of neonatal HIBD rats ( ). Additionally, serum levels of LPS, TNF-α, IL-6, and IL-1β in the HI + DEX group were significantly lower than those in the HI group ( ). These results suggest that oral DEX significantly suppresses intestinal inflammation and regulates intestinal barrier function, consequently leading to a reduction in circulating pro-inflammatory mediators. To assess the effect of oral DEX on hippocampal pathological changes in the neonatal HIBD rats, further experiments were performed. Analogous to the effects of FMT treatment, the results revealed that oral DEX markedly mitigated hippocampal neuroinflammation, evidenced by significant decreases in both the number and intensities of IBA-1 and GFAP positive cells in the hippocampal CA1 region ( ). Additionally, DEX treatment considerably improved the morphology of CA1 pyramidal neurons and their synaptic configurations, notably increasing the densities of dendritic spines and branches ( ). In the MWM test, oral DEX treatment resulted in a reduced escape latency ( ) and significant increases in both number of platform crossing ( ) and duration of stay in the target quadrant ( ) relative to the HI group. There was no significant difference in swim velocity among three groups ( ). Likewise, the results of NOR and Y-Maze revealed a notable increase in the recognition index and spontaneous alternation rate in the HI + DEX group compared to the HI group ( ). These results suggest that oral DEX treatment can mitigate hippocampal neuroinflammation, synaptic injury and long-term cognitive impairments in the neonatal HIBD rats. To determine whether oral DEX influenced the gut microbiota in the neonatal HIBD rats, the qPCR was used to quantify two specific bacteria, f_Enterobacteriaceae and f_Akkermansiaceae , in the feces of the Sham group, HI group, and HI+DEX group rats on the 3rd day following HI insult. The results showed that the content of f_Enterobacteriaceae in the HI+DEX group was significantly lower than that in the HI group. Conversely, the content of f_Akkermansiaceae in the HI+DEX groups was significantly higher than that in the HI groups (Figure s3a, b). Then, a newly designed FMT strategy was designed to verify whether ameliorating gut microbial dysbiosis post-HI insult was a key factor through which oral DEX treatment exerted anti-inflammatory and neuroprotective effects. The fecal microbiota from HI group and HI+DEX group donor rats were transplanted to HI group recipient rats. The transplantation procedure involved administering FMT once daily from the postnatal 7th day until the 3rd day after HI insult. The samples of feces and hippocampus were collected for analysis on the day 3 following HI insult, and cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results showed that FMT from the HI+DEX group (HI+dexFMT) resulted in a significant decrease in f_Enterobacteriaceae content and a significant increase in f_Akkermansiaceae content compared to those receiving transplantation from the HI group (HI+hiFMT) ( ), suggesting the efficacy of FMT. The results of IF analysis showed significantly decreased number and intensity of IBA-1 and GFAP-positive cells in the hippocampal CA1 region in the HI+dexFMT group compared to the HI+hiFMT group ( ). Furthermore, the increased density of dendritic spines and dendritic branches in the hippocampal CA1 region were observed in the HI+dexFMT group compared to the HI+hiFMT group ( ). In the cognitive
behavior tests, the results of MWM showed that the HI+dexFMT group demonstrated a decreased escape latency and an increase in both number of platform crossing and duration of stay in the target quadrant compared to the HI+hiFMT group ( ). There was no significant difference in swim velocity between two groups ( ). Likewise, the results of NOR and Y-Maze revealed a notable increase in the recognition index and spontaneous alternation rate in the HI+dexFMT group compared to the HI+hiFMT group ( ). These findings confirm that ameliorating gut microbial dysbiosis following HI insult is one of the key mediators through which DEX treatment exerts its anti-inflammatory and neuroprotective effects. The activation of intestinal LPS/TLR4 signaling pathway induced intestinal dysfunction and systemic inflammation, and exacerbated synaptic and cognitive impairments in the neonatal HIBD rats The experimental flow chart to further explore the potential molecular mechanisms of intestinal inflammation following HI insult was shown in . Firstly, the RNA-Seq analysis on the intestinal tissues from the Sham and HI groups was performed. Then, the HIBD neonatal rats were subjected to oral administration of TLR4 specific inhibitor TLR4-IN-C34 for a total of four times, from the day of HI insult to 3 days post-insult, and the samples of colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult, as well as cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult. The RNA-Seq data showed that genes in the intestinal tissues
significantly changed after HI insult ( ), with a notable increase in TLR4 ( ). Additionally, the results of Western blot (WB) and IF staining also showed that the expression of TLR4 in intestine was significantly increased following HI insult ( ). This corresponds with above findings about abnormally elevated LPS in neonatal HIBD rats. The analysis of gene ontology (GO) enrichment demonstrated that the upregulating differentially expressed genes (DEGs) were primarily associated with inflammatory responses and TLR4 signaling pathway ( ). Moreover, additional experiments were conducted to examine the fecal LPS levels between the Sham and HI groups. The result indicated that fecal LPS levels were significantly elevated in the HI group compared to the Sham group (Figure S4). These findings suggest that intestinal LPS/TLR4 signaling pathway may be the potential molecular mechanism mediating intestinal dysfunction, exacerbating systemic inflammation, and worsening synaptic and cognitive impairments following HI insult. To further examine the role of intestinal LPS/TLR signaling in the microbiota-gut-brain axis mechanisms underlying neonatal HIBD, orally TLR4-IN-C34 was used. The results of WB and IF showed that oral TLR4-IN-C34 significantly inhibited the expression of intestinal TLR4 ( ). Furthermore, the results of IHC analysis showed that oral TLR4-IN-C34 also significantly inhibited the expressions of IL-17a and IL-22 in the colonic tissues of neonatal HIBD rats, as evidenced by the significant reduction in the intensity of IOD of both cytokines ( ). The IF results indicated that oral TLR4-IN-C34 significantly enhanced the integrity of intestinal barrier, as evidenced by increasing the expression of tight
junction-associated proteins occludin and ZO-1 in the colons of neonatal HIBD rats ( ). In addition, our findings revealed that oral TLR4-IN-C34 also markedly mitigated systemic inflammation, evidenced by significantly decreased serum levels of LPS, TNF-α, IL-6, and IL-1β (Figure S5a-d), as well as the number and intensity of IBA-1 and GFAP positive cells in the hippocampal CA1 region (Figure S5e-g). Most importantly, our findings revealed that oral TLR4-IN-C34 improved the morphology of CA1 pyramidal neurons and their synaptic configurations, notably increasing the density of dendritic spines and branches ( ). In the cognitive behavioral tests, the MWM test showed that oral TLR4-IN-C34 treatment resulted in evidently reduced escape latency, and significant increases in both number of platform crossing and duration of stay in the target quadrant relative to the HI group ( ). However, there was also no significant difference in swim velocity among three groups ( ). Likewise, the results of NOR and Y-Maze revealed that the recognition index and spontaneous alternation rate were significantly increased in the HI + TLR4-IN-C34 group compared to the HI group ( ). To validate whether intestinal dysfunction induced by gut microbial dysbiosis following HI insult was related to the intestinal LPS/TLR4 signaling pathway, further experiments were performed. The results of WB and IF showed that the FMT from sham group rats significantly inhibited the expression of intestinal TLR4 in neonatal HIBD rats (Figure s6a-d). Likewise, oral DEX treatment could also significantly inhibit the expression of intestinal TLR4 in the neonatal HIBD rats (Figure s6e-h). These findings suggest that gut microbial dysbiosis following HI insult activates the LPS/TLR4 signaling pathway, leading to intestinal inflammation and
dysfunction, which exacerbates systemic inflammation and, in turn, worsens synaptic and long-term cognitive impairments. Inhibition of intestinal LPS/TLR4 signaling pathway can exert neuroprotective effects in the neonatal HIBD rats.
The classical Rice – Vannucci modeling approach was performed to construct the neonatal HIBD model in postnatal day 7 rats. Cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results of MWM ( ) demonstrated that HI insult did not cause motor
dysfunction in rats, as evidenced by the lack of statistically significant differences in swimming speed between the sham group and the HI group over five consecutive days post-HI insult ( ). However, rats in the HI group demonstrated a significantly increased escape latency, and a substantial reduction in both number of platform crossing and duration of stay in the target quadrant ( ). Likewise, the NOR ( ) and Y-Maze ( ) evaluations revealed a notable decrease in the recognition index and spontaneous alternation rate in the HI group. These findings collectively corroborate that HI insult can elicit long-term cognitive impairments in neonatal rats, aligning with the outcomes observed in the infants with neonatal HIBD. To further determine the roles of gut microbial factors in the HI insult-induced cognitive impairments, the 16S rRNA gene sequencing was used to analyze the composition of the gut microbiota in the fecal samples of the two groups on the 3rd day following HI insult ( ). The results of α-diversity analysis ( ) indicated no statistically significant differences in the abundances (Chao1) and diversities (Shannon and Simpson) of gut microbiota in the fecal samples from the two groups of rats. However, when analyzing β-diversity of the gut microbiota in feces using Principal Coordinates Analysis (PCoA), the results revealed a distinct separation of microbial community structures between two groups ( ). In the Analysis of Similarities (ANOSIM), we found that a higher value in the “Between” category compared to within-group (Sham and HI group) values indicates that the between-group differences are significantly larger than within-group differences, with R = 0.4688 and p = 0.002 ( ). These results suggest that HI insult can causes severe gut microbial dysbiosis in neonatal rats. At the phylum level, the relative abundance of the p_Proteobacteria increased in the HI group, while the relative abundance of the phylum p_Bacteroidetes decreased ( ). At the family level, we observed dysbiosis in multiple gut microbiota between the two groups ( ). Additionally, using Linear discriminant analysis Effect Size (LEfSe) and indicator species analysis at the family level ( ), we identified significant microbiota differences between the groups, with f_Fusobacteriaceae , f_Enterobacteriaceae , f_Prevotellaceae, f_Streptococcaceae, and f_Vibrionaceae enriched in the HI group rats, while f_Akkermansiaceae , f_Enterococcaceae, f_Victivallaceae, f_Helicobacteraceae, and f_Planococcaceae were enriched in the sham group rats. Available studies have shown that f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae are linked to inflammatory responses, whereas f_Akkermansiaceae and f_Enterococcaceae exhibit anti-inflammatory effects. Thus, we determined the differences in the relative abundances of these five bacteria between the sham and HI groups and found that the relative abundances of f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae in the gut microbiota were significantly elevated in the HI group compared with the Sham group ( ). Conversely, the abundances of f_Akkermansiaceae and f_Enterococcaceae were notably reduced in the HI group ( ). All of these findings suggest that HI insult induces gut microbial dysbiosis in the early-stage in the neonatal HIBD rats. To better explore the correlation between gut microbial dysbiosis and cognitive impairments caused by HI insult, the correlation analyses between the relative abundance of five significantly altered gut microbial families screened from the 16S rRNA sequencing data and relevant index data from cognitive behavior tests (including escape latency of D32, the time of crossing, the time spent in target quadrant, recognition index, and Y maze alternation) were conducted. The results demonstrated a significant association
between increased relative abundance of f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae and more severe cognitive impairments, whereas a decreased relative abundance of f_Akkermansiaceae and f_Enterococcaceae correlated with more severe cognitive impairments ( ). The correlation results underscore the role of gut microbiota in the onset of long-term cognitive impairments following HI insult in the neonatal rats.
The experimental flow chart exploring the possible role of microbiota-gut-brain axis in the neonatal HIBD is shown in . The HI group demonstrated significantly worsened histopathological damages and higher histology scores in the colon, compared to the sham group, as evidenced by HE staining ( ). The IF staining revealed a significant reduction in the colonic Occludin and ZO-1 expression in the HI group compared to the sham group ( ). Moreover, the results of IHC staining showed that, compared to the sham group, the IOD intensity of IL-17a and IL-22 were significantly increased in the HI group ( ). To further investigate whether intestinal dysfunction caused by HI insult affected the concentrations of pro-inflammatory mediators in the blood, an Elisa test was conducted on the serum of neonatal rats on the day 3 following HI insult ( ). The results of Elisa showed that, compared to the sham group, the serum concentrations of LPS, TNF-α, IL-6, and IL-1β were significantly increased in the HI group ( ). Additionally, the correlational analysis revealed that the more severe the intestinal dysfunction, the higher the serum concentrations of pro-inflammatory mediators ( ). In summary, these results indicate that HI insult can cause the intestinal barrier damage and intestinal
inflammation in the neonatal rats. Additionally, intestinal dysfunction induced by HI insult is strongly correlated with increased pro-inflammatory mediators in the circulation.
On the day 3 following HI insult, the hippocampal tissues were collected for test ( ). The results of IF staining showed that HI insult led to significant activation of microglia and astrocytes in the hippocampal CA1 region of neonatal rats ( ), manifested by increased number and intensities of both IBA1 and GFAP positive cells ( ). Furthermore, the confocal images revealed that HI insult caused microglia in the hippocampal region of neonatal rats to transition from a morphology characterized by small nuclei, long protrusions, and complex shapes to an activated state with enlarged cell bodies, thickened, and reduced branching ( ). The TEM was used to observe the ultrastructure of synapses in the hippocampal CA1 region and showed that, in the HI group, pronounced pathological alterations were evident, exemplified by a marked decrease in the thickness of the postsynaptic density (PSD) and an expansion of the synaptic cleft relative to the sham group ( ). The Golgi-Cox staining was utilized to determine the impact of HI insult on the morphology of pyramidal neurons and synaptic structures in the hippocampal CA1 region of neonatal rats. The results showed that HI insult resulted in a significant reduction in the density of dendritic spines and dendritic branches in the neonatal rats ( ). Additionally, the Nissl staining revealed significant neuropathological alterations in the hippocampal CA1 region in the HI group when compared to the sham group, which included nuclear shrinkage, neuronal loss, and reduced thickness ( ). These results indicate
that HI insult induces severe hippocampal neuroinflammation, synaptic injury and neuronal damage in the neonatal rats To better explore the correlation between the intestinal dysfunction and the hippocampal pathological changes following HI insult, the additional correlation analyses were conducted to determine the possible relationships between the representative indicators of intestinal dysfunction (mean fluorescence intensity of ZO-1 and mean IOD/Area of IL-17a) and the representative indicators of hippocampal pathological changes (mean
intensities of IBA-1 and GFAP per view, endpoints/cell of microglia, thickness of PSD, dendritic spines density, and average number of CA1 neurons per view). The results revealed significant negative correlations between the mean fluorescence intensity of ZO-1 in the colon and the mean intensities of both IBA-1 ( r = −0.7817, p = 0.0117) and GFAP ( r = −0.8061, p = 0.0082) per view in the hippocampal CA1 region ( ). Conversely, the mean fluorescence intensity of ZO-1 in the colon was significantly positively correlated with the endpoints per cell of microglia ( r =
0.7939, p = 0.0098), PSD thickness ( r = 0.9273, p = 0.0001), dendritic spine density ( r = 0.6748, p = 0.0323), and the average number of neurons per view ( r = 0.8788, p = 0.0002) in the hippocampal CA1 region ( ). These findings imply that the more severe the intestinal barrier damage, the more significant the pathological changes of hippocampal damage, including neuroinflammation, synaptic injury, and neuronal damage. Additionally, the results also revealed significant positive correlations between the mean IOD/Area of IL-17a in the colon and the mean intensities of both IBA-1 ( r = 0.903, p = 0.0009) and GFAP ( r = 0.8667, p = 0.0027) per view in the hippocampal CA1 region ( ). Conversely, the mean IOD/Area of IL-17a in the colon was significantly negatively correlated with the endpoints per cell of microglia ( r = −0.6848, p = 0.0351), dendritic spine density ( r = −0.772, p = 0.0089), and the average number of neurons per view ( r = −0.7939, p = 0.0098) in the hippocampal CA1 region ( ). These findings suggest that the more severe the intestinal inflammatory responses, the more significant the pathological changes of hippocampal damage, including neuroinflammation, synaptic injury, and neuronal damage. Together, all of these data suggest that the gut microbial dysbiosis following HI insult may exacerbate long-term cognitive impairments by promoting intestinal dysfunction, leading to the entry of gut microbiota-derived LPS and intestine-derived inflammatory mediators into the bloodstream, worsening hippocampal neuroinflammation, synaptic injury, and neuronal damage.
The experimental flow chart to explore the causal relationship between gut microbiota and long-term cognitive impairments induced by HI insult through the FMT is shown in . Fecal microbiota
from sham group and HI group donor rats were transferred to sham group and HI group recipient rats, respectively. The transplantation procedure involved administering FMT once daily from the postnatal 7th day until the 3rd day after HI insult. The samples of feces, colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult, and cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult. The effect of FMT was assessed through the quantification of specific fecal bacteria using PCR. Two representative bacteria, f_Enterobacteriaceae and f_Akkermansiaceae , previously identified from 16S rRNA sequencing data, were found to exhibit significant changes following HI insult. Specifically, Enterobacteriaceae , identified as harmful bacteria, showed a significant increase, while f_Akkermansiaceae , identified as beneficial bacteria, exhibited a significant decrease post-HI insult. The results showed that the content of Enterobacteriaceae in the group (Sham+hiFMT, HI+ hiFMT) receiving FMT from HI group donor rats was significantly higher than that in the group (Sham+shamFMT, HI+ shamFMT) receiving FMT from sham group donor rats. Conversely, the content of f_Akkermansiaceae in the Sham+hiFMT and HI+ hiFMT groups was significantly lower than that in the Sham+shamFMT and HI+ shamFMT groups ( ). These findings suggest that the FMT strategy in this study could effectively replace the original microbiota with the transplanted microbiota. Next, the findings from IHC and IF analysis on colon of neonatal rats demonstrated that, compared to the Sham+shamFMT group, rats in the Sham+hiFMT group exhibited intestinal dysfunction, which was characterized by a significant upregulation of IL-17a and IL-22 expression in colon, and a downregulation of the expression of tight junction-associated proteins occludin and ZO-1. Additionally, the intervention with FMT from the sham group donor rats led to a significant reduction in the expression levels of IL-17a and IL-22 cytokines, as well as an increase in the expression levels of tight junction-associated proteins occludin and ZO-1 in neonatal HIBD rats (HI
+shamFMT), compared to those in the HI+hiFMT group ( ). The Elisa results showed that the serum levels of LPS, TNF-α, IL-6, and IL-1β in the Sham+hiFMT group were significantly higher than those in the Sham+shamFMT group. However, the serum levels of above pro-inflammatory mediators in the HI+shamFMT group were significantly lower than those in the HI + hiFMT group ( ). These findings suggest that gut microbial dysbiosis following HI insult can induce intestinal dysfunction and elevate serum levels of pro-inflammatory mediators in the neonatal rats, and transplanting normal fecal microbiota can effectively ameliorate the intestinal dysfunction and serum inflammation levels in the neonatal HIBD rats. Interestingly, compared to HI+shamFMT group, the Sham+hiFMT group exhibited more severe intestinal dysfunction and higher serum levels of pro-inflammatory mediators ( ). These findings suggest that gut microbial dysbiosis following HI insult is a main factor causing intestinal dysfunction and peripheral inflammation in the neonatal rats. To determine the effects of FMT on hippocampus and long-term cognitive function in neonatal rats, further experiments were conducted. The results of IF analysis showed a significant increase in the number and intensity of IBA-1 and GFAP-positive cells in the hippocampal CA1 region in the Sham+hiFMT group compared to the Sham+shamFMT group. Additionally, a significant decrease in the number and intensity of IBA-1 and GFAP-positive cells was observed in the hippocampal CA1 region in the rats from the HI+shamFMT group compared to the HI+hiFMT group ( ). Subsequently, a notable reduction in the density of dendritic spines and branches in the hippocampal CA1 region was noted in the Sham+hiFMT group compared to the Sham+shamFMT group, as revealed by Golgi staining. Conversely, there was a marked elevation in the density of dendritic spines and branches in the hippocampal CA1 region in the HI+shamFMT group compared to the HI+hiFMT group ( ). In the cognitive behavior test, the results of MWM showed that the Sham+hiFMT group demonstrated a significantly increased escape latency and
a substantial decrease in both number of platform crossing and duration of stay in the target quadrant compared to the Sham+shamFMT group. Additionally, the HI+shamFMT group demonstrated a significantly decreased escape latency and a substantial increase in both platform crossings and duration of stay in the target quadrant compared to those in the HI+hiFMT group ( ). There was no significant difference in swim velocity among these groups ( ), indicating that the above differences are due to differences in cognitive function. Likewise, the results of NOR and Y-Maze revealed a notable decrease in the recognition index and spontaneous alternation rate in the Sham+hiFMT group compared to the Sham+shamFMT group, and a notable increase in the recognition index and spontaneous alternation rate in rats from the HI+shamFMT group compared to the HI+hiFMT group ( ). These results indicate that gut microbial dysbiosis following HI insult can induce hippocampal neuroinflammation, and synaptic damage, and long-term cognitive impairments. Moreover, FMT from normal fecal microbiota can mitigate hippocampal neuroinflammation, synaptic injury and long-term cognitive impairments in the neonatal HIBD rats. In summary, these data confirms that HI insult-induced gut microbial dysbiosis exacerbates long-term cognitive impairments in neonatal rats by promoting intestinal dysfunction, characterized by the activation of intestinal inflammation and disruption of intestinal barrier integrity. This dysregulation of intestinal function ultimately leads to elevated levels of pro-inflammatory mediators, including TNF-α, IL-6, IL-1β, and gut microbiota-derived LPS in the bloodstream, thereby promoting hippocampal neuroinflammation and synaptic damage. Moreover, our data further indicates that the transplantation of normal fecal microbiota can effectively mitigate the aforementioned pathological changes, ultimately alleviating long-term cognitive impairments in the neonatal HIBD rats.
The HIBD neonatal rats were subjected to oral administration of DEX daily for a total of four times, from the day of HI insult to 3 days post-insult, and the samples of colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult ( ), as well the cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results of IHC analysis showed that oral DEX significantly inhibited the expression of IL-17a and IL-22 in the colonic tissues of neonatal HIBD rats, as evidenced by the significant reductions in the intensity of IOD of both cytokines ( ). Furthermore, the IF results indicated that oral DEX significantly enhanced the integrity of intestinal barrier, as evidenced by increased expression of tight junction-associated proteins occludin and ZO-1 in the colon of neonatal HIBD rats ( ). Additionally, serum levels of LPS, TNF-α, IL-6, and IL-1β in the HI + DEX group were significantly lower than those in the HI group ( ). These results suggest that oral DEX significantly suppresses intestinal inflammation and regulates intestinal barrier function, consequently leading to a reduction in circulating pro-inflammatory mediators. To assess the effect of oral DEX on hippocampal pathological changes in the neonatal HIBD rats, further experiments were performed. Analogous to the effects of FMT treatment, the results revealed that oral DEX markedly mitigated hippocampal neuroinflammation, evidenced by significant decreases in both the number and intensities of IBA-1 and GFAP positive cells in the hippocampal CA1 region ( ). Additionally, DEX treatment considerably improved the morphology of CA1 pyramidal neurons and their synaptic configurations, notably increasing the densities of dendritic spines and branches ( ). In the MWM test, oral DEX treatment resulted in a reduced escape latency ( ) and significant increases in both number of platform crossing ( ) and duration of stay in the target quadrant ( ) relative to the HI group. There was no significant difference in swim velocity among three groups ( ). Likewise, the results of NOR and Y-Maze revealed a notable increase in the recognition index and spontaneous alternation rate in the HI + DEX group compared to the HI group ( ). These results suggest that oral DEX treatment can mitigate hippocampal neuroinflammation, synaptic injury and long-term cognitive impairments in the neonatal HIBD rats. To determine whether oral DEX influenced the gut microbiota in the neonatal HIBD rats, the qPCR was used to quantify two specific bacteria, f_Enterobacteriaceae and f_Akkermansiaceae , in the feces of the Sham group, HI group, and HI+DEX group rats on the 3rd day following HI insult. The results showed that the content of f_Enterobacteriaceae in the HI+DEX group was significantly lower than that in the HI group. Conversely, the content of f_Akkermansiaceae in the HI+DEX groups was significantly higher than that in the HI groups (Figure s3a, b). Then, a newly designed FMT strategy was designed to verify whether ameliorating gut microbial dysbiosis post-HI insult was a key factor through which oral DEX treatment exerted anti-inflammatory and neuroprotective effects. The fecal microbiota from HI group and HI+DEX group donor rats were transplanted to HI group recipient rats. The transplantation procedure involved administering FMT once daily from the postnatal 7th day until the 3rd day after HI insult. The samples of feces and hippocampus were collected for analysis on the day 3 following HI insult, and cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult ( ). The results showed that FMT from the HI+DEX group (HI+dexFMT) resulted in a significant decrease in f_Enterobacteriaceae content and a significant increase in f_Akkermansiaceae content compared to those receiving transplantation from the HI group (HI+hiFMT) ( ), suggesting the efficacy of FMT. The results of IF analysis showed significantly decreased number and intensity of IBA-1 and GFAP-positive cells in the hippocampal CA1 region in the HI+dexFMT group compared to the HI+hiFMT group ( ). Furthermore, the increased density of dendritic spines and dendritic branches in the hippocampal CA1 region were observed in the HI+dexFMT group compared to the HI+hiFMT group ( ). In the cognitive
behavior tests, the results of MWM showed that the HI+dexFMT group demonstrated a decreased escape latency and an increase in both number of platform crossing and duration of stay in the target quadrant compared to the HI+hiFMT group ( ). There was no significant difference in swim velocity between two groups ( ). Likewise, the results of NOR and Y-Maze revealed a notable increase in the recognition index and spontaneous alternation rate in the HI+dexFMT group compared to the HI+hiFMT group ( ). These findings confirm that ameliorating gut microbial dysbiosis following HI insult is one of the key mediators through which DEX treatment exerts its anti-inflammatory and neuroprotective effects.
The experimental flow chart to further explore the potential molecular mechanisms of intestinal inflammation following HI insult was shown in . Firstly, the RNA-Seq analysis on the intestinal tissues from the Sham and HI groups was performed. Then, the HIBD neonatal rats were subjected to oral administration of TLR4 specific inhibitor TLR4-IN-C34 for a total of four times, from the day of HI insult to 3 days post-insult, and the samples of colon, serum, and hippocampus were collected for analysis on the day 3 following HI insult, as well as cognitive behavior was assessed using the MWM, NOR, and Y-maze tests between days 28 and 37 following HI insult. The RNA-Seq data showed that genes in the intestinal tissues
significantly changed after HI insult ( ), with a notable increase in TLR4 ( ). Additionally, the results of Western blot (WB) and IF staining also showed that the expression of TLR4 in intestine was significantly increased following HI insult ( ). This corresponds with above findings about abnormally elevated LPS in neonatal HIBD rats. The analysis of gene ontology (GO) enrichment demonstrated that the upregulating differentially expressed genes (DEGs) were primarily associated with inflammatory responses and TLR4 signaling pathway ( ). Moreover, additional experiments were conducted to examine the fecal LPS levels between the Sham and HI groups. The result indicated that fecal LPS levels were significantly elevated in the HI group compared to the Sham group (Figure S4). These findings suggest that intestinal LPS/TLR4 signaling pathway may be the potential molecular mechanism mediating intestinal dysfunction, exacerbating systemic inflammation, and worsening synaptic and cognitive impairments following HI insult. To further examine the role of intestinal LPS/TLR signaling in the microbiota-gut-brain axis mechanisms underlying neonatal HIBD, orally TLR4-IN-C34 was used. The results of WB and IF showed that oral TLR4-IN-C34 significantly inhibited the expression of intestinal TLR4 ( ). Furthermore, the results of IHC analysis showed that oral TLR4-IN-C34 also significantly inhibited the expressions of IL-17a and IL-22 in the colonic tissues of neonatal HIBD rats, as evidenced by the significant reduction in the intensity of IOD of both cytokines ( ). The IF results indicated that oral TLR4-IN-C34 significantly enhanced the integrity of intestinal barrier, as evidenced by increasing the expression of tight
junction-associated proteins occludin and ZO-1 in the colons of neonatal HIBD rats ( ). In addition, our findings revealed that oral TLR4-IN-C34 also markedly mitigated systemic inflammation, evidenced by significantly decreased serum levels of LPS, TNF-α, IL-6, and IL-1β (Figure S5a-d), as well as the number and intensity of IBA-1 and GFAP positive cells in the hippocampal CA1 region (Figure S5e-g). Most importantly, our findings revealed that oral TLR4-IN-C34 improved the morphology of CA1 pyramidal neurons and their synaptic configurations, notably increasing the density of dendritic spines and branches ( ). In the cognitive behavioral tests, the MWM test showed that oral TLR4-IN-C34 treatment resulted in evidently reduced escape latency, and significant increases in both number of platform crossing and duration of stay in the target quadrant relative to the HI group ( ). However, there was also no significant difference in swim velocity among three groups ( ). Likewise, the results of NOR and Y-Maze revealed that the recognition index and spontaneous alternation rate were significantly increased in the HI + TLR4-IN-C34 group compared to the HI group ( ). To validate whether intestinal dysfunction induced by gut microbial dysbiosis following HI insult was related to the intestinal LPS/TLR4 signaling pathway, further experiments were performed. The results of WB and IF showed that the FMT from sham group rats significantly inhibited the expression of intestinal TLR4 in neonatal HIBD rats (Figure s6a-d). Likewise, oral DEX treatment could also significantly inhibit the expression of intestinal TLR4 in the neonatal HIBD rats (Figure s6e-h). These findings suggest that gut microbial dysbiosis following HI insult activates the LPS/TLR4 signaling pathway, leading to intestinal inflammation and
dysfunction, which exacerbates systemic inflammation and, in turn, worsens synaptic and long-term cognitive impairments. Inhibition of intestinal LPS/TLR4 signaling pathway can exert neuroprotective effects in the neonatal HIBD rats.
The neurological sequelae caused by neonatal HIBD, including long-term cognitive impairments, remain a significant clinical challenge that is difficult to address. , Due to the complex pathological factors of neural damage post-HIBD, there are still no effective clinical intervention measures available. Consequently, the exploration of novel strategies and the provision of theoretical foundations hold crucial clinical significance. Consistent with clinical situations , and previous animal studies, , this study found that HI insult could cause severe long-term cognitive impairments in the neonatal rats. Increasing evidence highlights the critical role of gut microbiota in regulating brain function and cognitive processes. Moreover, recent studies have demonstrated alterations in gut microbial composition in both human neonates with HIBD and HIBD animal models after HI insults. However, the associations between early gut microbial dysbiosis post-HI insult and subsequent long-term cognitive impairments, as well as the underlying microbiota-gut-brain axis mechanisms, remain inadequately explored. Here, we established a causal relationship between early gut microbiota dysbiosis following HI insult and long-term cognitive impairments induced by HIBD. In the neonatal HIBD rat model, we observed significant changes in the relative abundances of certain key bacteria, which were significantly correlated with the metrics of long-term cognitive function. Further research revealed that
gut microbiota dysbiosis led to enhanced intestinal inflammatory responses and aggravated intestinal dysfunction, which were closely associated with systemic inflammation, synaptic damage, and long-term cognitive impairments. Using the FMT, we confirmed the causative role of microbiota-gut-brain axis mechanism in the development of long-term cognitive impairments by the neonatal HIBD, suggesting that early correction of gut microbiota dysbiosis after HI insult may prevent the progression of long-term cognitive impairments. Further investigation into the therapeutic effects of oral DEX treatment in neonatal HIBD rat model revealed that its neuroprotective effect was at least partially dependent on suppression of intestinal inflammation and improvement of gut microbial dysbiosis. Analysis of potential molecular mechanisms indicated that activation of the intestinal LPS/TLR4 signaling was the intrinsic mechanism by which gut microbiota dysbiosis led to neurotoxicity post-HI insult, and further oral TLR4-IN-C34 treatment provided effective neuroprotection through the gut-brain axis mechanism by inhibiting TLR4 expression in intestine. Based on these results, this study established the role of the microbiota-gut-brain axis in regulating intestinal function and neuroinflammation following HI insult and proposed the intestinal LPS/TLR4 signaling as a key mechanistic target in mediating this process, providing new insights for molecular mechanisms and potential strategies of long-term cognitive impairments associated with neonatal HIBB. Our results clearly displayed significant changes in the gut microbiota of neonatal rats on the 3rd day post-HI insult compared to the sham group. Notable increases in f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae , along with significant decreases in f_Akkermansiaceae and f_Enterococcaceae , were observed post-HI insult. Studies indicate that f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae act as promoters of inflammatory responses in a variety of diseases, such as inflammatory bowel diseases and colorectal cancer, through their secretion of metabolites or immune modulation capabilities. f_Akkermansiaceae , a key mucosal resident in the gut, has the capacity to uphold gut barrier integrity and prevents cognitive impairments in sleep-deprived mice. Additionally, f_Enterococcaceae has been reported to have anti-cancer, cholesterol-lowering, and immune-modulatory effects. For example, E. durans M4–5, belonging to one of the genera within f_Enterococcaceae , has been found to produce butyrate, a short-chain fatty acid, known to exert significant anti-inflammatory effects and enhance intestinal epithelium integrity. To determine the role of gut microbial alterations following HI insult in the progression of cognitive impairments, the correlations between the relative abundances of these five microbial groups and cognitive behavioral test scores were analyzed in our study. The findings demonstrated a positive correlation between cognitive impairments severity and the abundances of f_Fusobacteriaceae , f_Enterobacteriaceae , and f_Prevotellaceae , alongside a negative correlation with f_Akkermansiaceae and f_Enterococcaceae . These data suggest that dysbiosis of the gut microbiota post-HI insult, characterized by the upregulation of harmful gut microbiota associated with inflammation and the downregulation of beneficial gut microbiota with protective effects, may further trigger inflammatory responses, and exacerbate the progression of long-term cognitive impairments via the microbiota-gut-brain axis mechanisms. Furthermore, the identified microbial groups may act as potential biomarkers for the neurocognitive prognosis of HIBD. It is well-known that the intestine directly interacts with the gut microbiota, which can directly modulate the immune and inflammatory responses of the intestinal tissue. It has been shown that gut microbiota is involved in regulating intestinal inflammation. Our preliminary research has confirmed that early changes in the gut microbiota following HI insult may be related to enhanced intestinal inflammatory response. Based on the above, we hypothesized that dysbiosis of the gut microbiota following HI insult induces inflammatory response in intestinal epithelial cells and the intestinal barrier damage. This facilitates the entry of pro-inflammatory mediators, including LPS from the gut microbiota and inflammatory cytokines (TNF-α, IL-6, IL-1β) secreted by epithelial cells, into the brain via the bloodstream, promoting systemic inflammation and participating in mediating neural damage after HIBD. In experiments
exploring the microbiota-gut-brain axis mechanisms underlying HIBD, our results demonstrated that HI insult significantly compromises the integrity of the intestinal barrier, intensifies the intestinal inflammatory responses, and elevates the serum levels of LPS, TNF-α, IL-6, and IL-1β in the neonatal rats on the 3rd day following the HI insult. Additionally, the correlation analyses about the relationships between the integrity of the intestinal barrier and the serum levels of pro-inflammatory mediators, and between degree of intestinal inflammatory responses and serum levels of pro-inflammatory mediator indicated that both the decreased integrity of intestinal barrier and increased intestinal inflammation were significantly associated with increased serum levels of pro-inflammatory mediators. Neuroinflammation is a key pathological mechanism of neural damage following HIBD, with the activation of microglia and astrocytes being significant components of neuroinflammation. Previous studies, including own, have confirmed that inhibiting abnormal activation of microglia and astrocytes can effectively mitigate synaptic damage and neurological deficits post-HIBD. , , , , Importantly, the synapses in the hippocampus are crucial for the formation and regulation of cognitive functions. Excessive neuroinflammatory responses may destroy hippocampal synapses, leading to cognitive impairments. Additionally, peripheral pro-inflammatory mediators entering the brain can mediate the activation of microglia and astrocytes, thus further amplifying the neuroinflammatory responses. The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and protecting against harmful substances and pathogens. Previous studies have fully demonstrated that HI insult severely damages the BBB, allowing more peripheral harmful substances to penetrate the central nervous system, resulting in central nervous system damage. Similarly, our study observed excessive activation of microglia and astrocytes in the hippocampal CA1 region on the 3rd day after HI insult. Additionally, through TEM, Golgi staining, and Nissl staining, we found the destruction in the synaptic structures of neurons in the hippocampal CA1 region, along with significant abnormalities in neuronal morphology and number. Further application of correlation analysis to assess the
relationships between the integrity of the intestinal barrier and hippocampal pathological changes, as well as the degree of intestinal inflammatory responses and hippocampal pathological changes, indicated that the decreased integrity of intestinal barrier and intensification of intestinal inflammation were associated with increased activation of microglia and astrocytes, extensive synaptic damage, and reduced number of neurons in the hippocampal CA1 region. These data strongly suggest that dysbiosis of the gut microbiota following HI insult may promote intestinal dysfunction, leading to increased serum pro-inflammatory mediators crossing the BBB to the brain, thereby promoting hippocampal neuroinflammation and ultimately exacerbating damage to hippocampal synapses and long-term cognitive impairments. The FMT has been proven to improve the prognosis of various neurological diseases, which also serves as a key method to demonstrate the causal relationship between gut microbiota and disease symptoms. , To determine the causal relationship between early gut microbial dysbiosis following HI insult, the speculated microbiota-gut-brain axis mechanisms, and long-term cognitive impairments, we conducted FMT based on the methods of previous studies. , In this study, we firstly designed two different FMT strategies. Similar to previous studies , in other neurological disease, we found that transplanting the fecal microbiota of sham group rats into neonatal HIBD rats could restore the composition of their gut microbiota, alleviate intestinal inflammation, improve intestinal barrier integrity, reduce serum levels of pro-inflammatory mediators, thereby mitigating hippocampal neuroinflammation, synaptic damage, and long-term cognitive impairments. Conversely, transplanting the fecal microbiota from HIBD rats into sham group recipient rats induced gut microbial dysbiosis, mediated intestinal inflammation, reduced barrier integrity, increased serum pro-inflammatory mediator levels, thereby mediating hippocampal neuroinflammation, synaptic damage, and long-term cognitive impairments. Moreover, our analysis comparing the two FMT strategies revealed that, relative to the HI+shamFMT group, rats in the Sham+hiFMT group exhibited more severe intestinal dysfunction and higher serum levels of pro-inflammatory
mediators. These results suggest that gut microbial dysbiosis following HI insult is a significant contributor to intestinal dysfunction and systemic inflammation in neonatal HIBD rats. This observation underscores that early-stage gut microbial dysbiosis has a more profound impact on intestinal function than the HI insult itself, aligning with existing literature on the critical role of gut microbiota in maintaining intestinal health. , In terms of brain function, although the HI insult was the primary cause of brain damage, gut microbiota significantly influenced the extent of neural injury. These findings are corroborated by other studies investigating the gut-brain axis and neural injury. Additionally, numerous studies have shown that gut microbiota can influence the permeability of the BBB, with dysbiosis facilitating the translocation of intestinal bacteria-derived pathogens and harmful toxins into the circulatory system, leading to BBB breakdown and neuroinflammation. Our study also showed that hippocampal neuroinflammation, synaptic injury, and cognitive impairments occurred in normal rats receiving FMT from HI-insulted donor rats. These findings imply that the gut microbial dysbiosis following HI insult may contribute to BBB disruption, thereby facilitating the entry of more deleterious circulating substances into the brain and exacerbating neurological damage. Therefore, investigating the impact of gut microbial dysbiosis following HI insult on the function of the BBB will be one of the main directions of our future research. Overall, these data demonstrate that gut microbial dysbiosis following HI insult participates in mediating hippocampal neuroinflammation, synaptic damage, and cognitive impairments induced by HIBD through promoting intestinal dysfunction and increasing serum pro-inflammatory mediator levels; therefore, correcting early gut microbial dysbiosis by FMT may be a potential therapeutic strategy for alleviating the long-term neurological sequelae in children with HIBD. The observed beneficial effects of FMT on cognitive impairments induced by HI insult have motivated us to explore the potential effects of intervening in intestinal dysfunction within a similar research framework. Excessive intestinal inflammation is a key factor in the impairments of intestinal
barrier integrity. DEX, a conventional glucocorticoid and anti-inflammatory drug, has been reported to alleviate intestinal inflammation and intestinal barrier damage caused by various pathogenic factors through oral administration. , , However, in the neonatal HIBD model, the neuroprotective and neurotoxic effects of DEX remain contentious. Studies , have shown that glucocorticoids can influence the vulnerability of fetal and neonatal brains to HI challenges, though the outcomes are inconsistent and vary based on experimental protocols, dosages, timings, animal ages, strains, and species. Additionally, the dose and duration of glucocorticoid treatment appear to be the critical factors that determine whether the effects on the brain are detrimental or beneficial. While prolonged exposure to high levels of glucocorticoids increases neurotoxic effects, a physiological or slightly elevated levels provide neuroprotection against HI challenges. Several studies have demonstrated that glucocorticoid pretreatment, particularly DEX, yields a neuroprotective outcome in some animal models of neonatal HIBD. Despite the promise of these findings, translating them into clinical practice is still challenging. It is noteworthy that prophylactic interventions for HIBD are impractical due to the low incidence and the acute nature of HI events. , Interestingly, available evidence shows that post-HI insult treatment with DEX can be both neurotoxic and neuroprotective. , However, the neurotoxic effects are typically associated with administration methods, such as high doses and repeated administrations via intraperitoneal and subcutaneous injections, which result in increased systemic effects and side effects. In this study, we focused on the effects of oral DEX administration on the intestine and enhanced the clinical translatability of this intervention by implementing post-treatment. The oral bioavailability of DEX is reported to range between 70% and 78% in humans. However, this value may differ in neonatal HIBD rat models. Therefore, the administration method and dosage employed in this study were based on previous study and our pilot experiments. Our pilot findings demonstrated that an oral dose of 1 mg/kg of DEX administered daily for four consecutive days, commencing from the day of HI insult in neonatal HIBD rat model, was safe and effective, with no significant side effects. Based on the above, our main findings further demonstrated that
oral DEX treatment effectively suppressed intestinal inflammation, ameliorated intestinal barrier damage, and reduced systemic inflammation, and alleviated synaptic damage, and improved long-term cognitive impairments in neonatal rats with HIBD. In addition, studies indicate that gut microbiota is a critical regulatory factor for the observed anti-inflammatory effects on intestinal tissues after DEX administration. , To determine whether gut microbiota also mediates the neuroprotective effects of oral DEX treatment, we employed FMT for validation. Based on the findings of the above work, our results demonstrated that FMT from donor rats in the HI+DEX group alleviated hippocampal neuroinflammation, synaptic injury, and long-term cognitive impairments in neonatal rats with HIBD. These findings suggest that mitigating gut microbial dysbiosis and intestinal dysfunction following HI insult is a crucial mechanism through which oral DEX treatment exerts its neuroprotective effects. To explore the potential molecular mechanisms of the microbiota-gut-brain axis underlying neonatal rats with HIBD, the high-throughput RNA-Seq was conducted to observe the genes and molecular pathways involved in intestinal inflammation following HI insult. Our analysis revealed a significant increase in TLR4 expression in the intestines of neonatal HIBD rats. The TLR4 is a specific receptor for LPS and plays a crucial role in inflammation mediated by the microbiota-gut-brain axis mechanisms. A major producer of LPS in the gut microbiota is Gram-negative bacteria, with f_Enterobacteriaceae being a key example. A recent study suggested the excessive proliferation of f_Enterobacteriaceae exacerbates systemic inflammation and worsens cerebral infarction via the LPS/TLR4 pathway. In our study, we found a significant increase in the abundance of f_Enterobacteriaceae and the levels of LPS in the feces of neonatal rats after HI insult. Based on the findings of the above work, we further speculated that the LPS/TLR4 signaling pathway in intestinal tissue was a key intrinsic molecular mechanism of the microbiota-gut-brain axis in neonatal HIBD rats. Therefore, effectively inhibiting TLR4 expression in intestinal tissue is crucial for validating this hypothesis. Previous studies have demonstrated that TLR4-IN-C34 is an orally active, selective TLR4 inhibitor that can suppress TLR4 signaling activation through oral administration, improving intestinal
and systemic inflammation in necrotizing enterocolitis, ulcerative colitis and other intestinal disease models, suggesting its therapeutic potential for intestinal inflammation. Therefore, TLR4-IN-C34 was selected in this study. The administration method and dosage employed in this study were based on previous study and our pilot experiments. Furthermore, our results showed that treatment with the orally active TLR4-specific inhibitor TLR4-IN-C34 significantly improved intestinal dysfunction, systemic inflammation, and brain function damage in neonatal HIBD rats. Through reviewing the literature, we found that TAK-242 is also a widely used selective TLR4 inhibitor, but its administration in neonatal HIBD or other disease animal models is mostly through intraperitoneal injection, rather than the oral administration used in our study, a more clinically applicable method. However, inhibiting TLR4 through intraperitoneal injection of TAK-242 can also improve effectively the gut microbiota. This provides a new interventional method of TLR4 signaling pathway in our future researches of neonatal HIBD. Additionally, both FMT and oral DEX treatment also significantly inhibited the intestinal LPS/TLR4 signaling pathway. These results suggest that activation of the intestinal LPS/TLR4 signaling pathway is a potential molecular mechanism for the involvement of microbiota-gut-brain axis in the long-term cognitive impairments associated with the neonatal HIBD. Our study has some limitations that deserve attention. Firstly, this study was conducted in rats, as many factors such as diet that can alter the gut microbiota could be well controlled. Therefore, the five specific gut microbial biomarkers identified from our study need further validation in a large cohort of children with HIBD before they can be applied to humans. Secondly, although this study did not use germ-free pups for FMT intervention, according to methods specified in previous studies, , , a combined antibiotic regimen was administered to the dams producing the recipient pups in order to maximize the elimination of the original gut microbiota of the recipient pups, and applied an effective FMT regimen to the recipient pups. Additionally, after completing the FMT, the qPCR was further utilized to quantify specific bacterial groups identified from our 16S rRNA data to assess the effectiveness of the FMT. These
measures minimized the impact of this issue on our research conclusions. Finally, oral DEX has the opportunity to exert a direct protective effect on the brain through the first-pass effect. However, this study detected the intestinal LPS/TLR4 signaling pathway and intestinal function in the neonatal HIBD rats treated with oral DEX, and further verified through the FMT that oral DEX treatment exerted neuroprotective effects on the neonatal HIBD rats at least partially by improving gut microbial dysbiosis and intestinal dysfunction.
In summary, our study suggests that early-stage dysbiosis of the gut microbiota following HI insult can activate the intestinal LPS/TLR4 signaling pathway, leading to excessive intestinal inflammatory responses and intestinal barrier damage. This promotes systemic inflammation, and ultimately worsens hippocampal synaptic damage and long-term cognitive impairments in the neonatal HIBD rats. Transplantation of healthy gut microbiota and oral anti-inflammatory agent DEX can
effectively counteract these detrimental effects and alleviate long-term cognitive impairments caused by neonatal HIBD. Moreover, oral administration of TLR-IN-C34 can exert neuroprotective effect by inhibiting the intestinal LPS/TLR4 signaling pathway in the neonatal HIBD rats ( ). Therefore, early correction of gut microbial dysbiosis and intestinal dysfunction may be the potential interventions to alleviate long-term cognitive impairments in children suffering from neonatal HIBD.
Supplementary Information R3.docx
|
Getting the Numbers Right in Medicinal Chemistry | e208c5a0-96e1-440b-bb5c-19b848e4fa17 | 11694604 | Pharmacology[mh] | In many sub‐disciplines of Chemistry, the properties of compounds are studied. These properties are often investigated in experiments that furnish quantitative data. Medicinal Chemistry is one of these sub‐disciplines, as Medicinal Chemists often make (or sometimes purchase) compounds and then investigate them for their biological properties. In this regard, Medicinal Chemistry is not completely different from, for instance, Physical Chemistry, with the notable exception that Medicinal Chemists are usually more interested in biological rather than physical properties of chemical matter. In the field of Medicinal Chemistry, quantitative data obtained from biological assays are often represented with parameters such as IC 50 values or percentage remaining activities for target inhibition, or half‐lives for stability in relevant biological media. The way these numbers are reported reflects on the precision of the respective experiment. Medicinal Chemists usually learn at rather early stages in their careers that any work with biological material, even in the controlled setting of an in vitro assay, involves significant experimental uncertainties, leading to rather high standard deviations (SD) of the obtained mean values. Hence, SD values of, for example, 10 %, 20 % or even more of the mean value are not uncommon at all in this discipline, which is perfectly acceptable though. Medicinal Chemists usually aim for improvements of biological properties that are way beyond these percentages when they optimise a hit or lead structure, and we all can therefore be completely at ease with these experimental uncertainties. However, problems arise when such data from biological experiments are reported in a way that is in obvious contradiction to the acceptance of a significant experimental error, that is, when data are provided with unreasonable numbers of significant figures. In this Persepctive, I would like to argue that this is a rather widespread phenomenon in the Medicinal Chemistry literature and that we all should aim to do better. It should be noted that I do not intend to call out specific colleagues or editors, but I would rather like to alert us all (including myself) that we should pay more attention to the way we report quantitiative data in the field of Medicinal Chemistry. In order to make the message of this Perspective as clear as possible, I hereby would like to provide a short reminder of the way quantitative scientific data should ideally be reported. Significant figures are essential in this context, that is, the digits of a number starting with the digit furthest to the left that is not zero, and ending with the digit furthest to the right. For example, the number 1.24 has three significant figures as has the number 0.124 or the number 0.120. The significant figures of an experimentally obtained number should correspond to the precision of the respective experiment: the last digit to the right usually is the one with the experimental uncertainty. Hence, numbers from very precise experiments should be reported with more significant figures than results from less precise experiments with larger errors. In synthetic chemistry, it can be a useful rule to report amounts of employed reagents with three significant figures, if this is justified by the experimental precision. The latter is sometimes not the case when volumes of liquids are measured as this is often done with less precision in synthetic laboratories. Thus, an amount of e. g. 5.24 g for a starting material would probably be universally accepted in the synthetic literature, while a number such as 5.2404 g would be universally criticised and should be rounded. The question therefore arises if a similarly useful rule of thumb can be identified for reporting numbers from biological assays in the field of Medicinal Chemistry. In my estimation, this is perfectly possible when one reflects the aforementioned statements regarding experimental uncertainties in such assays. If SD values of more than 10 % of the mean value are acceptable in most biological assays, then the number of significant figures for the mean value should be limited to two . I would like to further clarify this statement: With such significant experimental errors (>10 %), the experimental uncertainty is usually already reflected in the second significant figure. Hence, any further significant figure would be superfluous and without informational value. The SD then has to be adjusted accordingly so that it has the same number of decimal places as the mean value. However, in my estimation, one should always round up the SD in order to avoid reporting values that appear to be more precise than the experiment has actually been. The latter recommendation might be controversial and not universally accepted though. To illustrate these statements, Table provides some made‐up examples of incorrect and correct versions of experimental data. As with any rule of thumb, the proposed guideline to report mean values of data from biological assays with just two significant figures should be applied with some caveats. For instance, some assays might have an intrinsically higher experimental precision than described above, that is, they might consistently furnish SD values significantly below 10 % of the respective mean values. Naturally, such data should be reported with significant figures that reflect the higher experimental precision. It should be noted though that such precise biological assays are the fairly rare exception in most Medicinal Chemistry publications. I became alert to the problem discussed in this Perspective in a slightly unusual way. We teach a research seminar for our undergraduate students in their last semester prior to their final exam. For this research seminar, groups of two students each present a rather recent paper from the Medicinal Chemistry literature that is then further discussed by the whole class. In this scenario, I have had the opportunity to look at papers in great detail that I probably would just quickly go through when browsing the latest literature in our field. After a while, I have noticed that nearly every presented paper, even those from esteemed journals, had some issues with the way biological data are presented: there simply were too many significant figures provided in most of the tables. However, statements on such a delicate topic should not be misled by subjective impressions, but should rather be based on objective observations. In the preparation of this contribution, I have therefore gone through the most recent issues of five selected and esteemed journals in the field of Medicinal Chemistry: the Journal of Medicinal Chemistry , the European Journal of Medicinal Chemistry , ChemMedChem , ACS Medicinal Chemistry Letters , and RSC Medicinal Chemistry . For each of these issues, I have only taken original research papers into account, no reviews or other articles. Papers without numerical data from biological assays were neglected, and no Supporting Informations were taken into account. My original idea had been to generate some sort of statistics by grouping the relevant papers into different categories with respect to the representation of numbers from biological assays. However, I have soon realised that such a meticulous exercise would not be necessary to get the main point across. I have simply looked for mistakes in the style of those depicted in Table , and I have found them in the vast majority of all studied research papers. An arbitrary selection of such mistakes is provided in Table , with two examples from each of the investigated journal issues. It is astonishing how similar the examples 1–10 (Table ) – that can actually be found in recent Medicinal Chemistry literature – are to the made‐up examples of ′incorrect’ numbers in Table . It should be noted that the imaginary examples listed in Table had been compiled before the described literature search, so they have not been adjusted by any means to what was found in the cited publications. This observed phenomenon is certainly not limited to a specific type of assay or to a certain journal, but appears to be of almost ubiquitous nature. Having in mind that such examples could be found in many papers in all of the five studied journals, one could almost identify an epidemic of superfluous digits in Medicinal Chemistry data . In this context, it is important to make several clarifications: (i) No concerns with the quality of the actual data and their integrity are meant to be implied. The discussed issue is only with the formal representation of experimental data, not with the experiments themselves. (ii) No specific papers are explicitly cited that could serve as particularly bad examples. This article is intended to be a constructive contribution to our scientific community, not some sort of medieval pillory. In particular because the problem appears to be of nearly ubiquitous nature, it would be pointless to call out some selected authors on it. All of the examples listed in Table can easily be found in the respective journal issues if desired. (iii) Sometimes, overly precise numbers are provided with respect to readability. For instance, if a table has nM activity data for most of its entries, it can make sense to list all entries with nM numbers, even if that means that some of the entries will have three (or even more) significant figures. In my estimation, such practice should not be of concern as readability is a noble cause. (iv) In some of the papers I have studied, experimental numbers were treated with great care and are flawlessly presented. However, if negative examples are not explicitly called out here, it appears to be consistent to not explicitly cite best‐practice examples either. Overall, I would simply encourage readers of this Perspective to repeat my exercise and browse recent issues of some Medicinal Chemistry journals. It is very likely that the outcome will be similar, with some examples of good practice and a worrying number of flaws similar to those listed in Table . In summary, this Perspective is intended to discuss a problem with the way quantitative data are often reported in the Medicinal Chemistry literature. The identification of this problem is based on two hypotheses: (i) Medicinal Chemistry is a quantitative science, and therefore, quantitative data should be treated with great care and rigor. (ii) Biological assays conducted in the field of Medicinal Chemistry often come with significant experimental uncertainties (i. e. SD values of more than 10 % of the mean value), which is perfectly acceptable in this discipline. From these hypotheses, a general guideline is derived: For most datasets from biological assays in Medicinal Chemistry, the number of significant figures for the mean value should be limited to two . Browsing the recent Medicinal Chemistry literature, it becomes obvious that it is the exception rather than the rule that biological data are reported in such a consistent way. Far too often, data are provided with significant flaws (see selected examples in Table ). As this is not limited to specific types of assays or to certain journals, an epidemic of superfluous digits in Medicinal Chemistry data can be identified. The obvious argument against these statements might be that they concern a mere technicality rather than the substance of Medicinal Chemistry research. I would like to argue against this. Firstly, a quantitative science should always be rigorous with the way quantitative data are reported. Secondly, one has to wonder if authors who report data in such an unfortunate way are really aware of the inherently limited precision of their experiments. In any case, it would be no problem to do better and there is no obvious reason why we should not aim to do so. It is a bit mysterious to me why the described phenomenon exists in the first place. One explanation might be that some authors believe that reporting numbers with many digits is an indication of precision. However, this is certainly not the case as experimental precision is part of the experiments themselves. An experiment with significant error does not become more precise by throwing many digits at the reader to whom its results are communicated. Another potential explanation would be even simpler: the scientific community of Medicinal Chemists just has not paid sufficient attention to this issue yet. This brings me to another aspect: What can we do about this problem? I would like to propose a significant change in editorial policies in Medicinal Chemistry journals. There should be explicit guidelines for authors on the way quantitative data from biological assays are reported, and editorial offices should check if submissions follow these guidelines. In case of significant violations, submissions should be sent back to their authors before they enter the peer review process. Referees should pay attention to the issue as well and should address any remaining inconsistencies in their reports. In my estimation, all of these measures could be implemented in a relatively straightforward manner. It is important to note that this Perspective only addresses the widespread habit to report data with superfluous digits, but that there are other discussible issues with how data are presented in the Medicinal Chemistry literature. Most notably, there are several scholars who advocate for the use of pIC 50 instead of IC 50 values when activity data are reported (with pIC 50 being the negative decadic logarithm of IC 50 ). This mainly results from the multiplicative nature of experimental errors in biological systems that therefore lead to log‐normal distributions. However, this topic (despite such reasonable arguments) is not within the scope of this contribution. Finally, I would like to point out again that this Perspective is not intended to call out anyone or to cause controversy, but to stimulate fruitful discussions on the presentation of quantitative data within our scientific community. Most of us have probably been guilty of not rounding our numbers properly here and there (including myself), but we all can do our best to improve the way we report data from biological assays. It would be very much appreciated if this contribution might help to reach this goal. The authors declare no conflict of interest. |
Establishing a prognostic model with immune-related genes and investigating | ad782de6-f9ab-410c-85e1-464b0e3796ce | 11850720 | Anatomy[mh] | Breast cancer is the most frequently diagnosed cancer among women globally, and its high mortality rate highlights the urgent need for ongoing research and advancements in treatment . While significant progress has been made in treatment options, such as surgery, chemotherapy, radiotherapy, endocrine therapy, targeted therapy, and immunotherapy , the complexity of breast cancer remains a challenge. Recent research has focused on the tumor microenvironment (TME), particularly the interactions between tumor cells and the immune microenvironment, which includes surrounding immune cells, stromal cells, extracellular matrix molecules, and cytokines , . The TME’s impact on breast cancer prognosis and treatment response is increasingly evident, with the immune microenvironment playing a crucial role in immunotherapy efficacy and patient outcomes , . Evidence shows that the immune microenvironment significantly affects immunotherapy effectiveness and the overall survival of breast cancer patients , . The presence of infiltrating immune cells like T cells and B cells is linked to better clinical outcomes in breast cancer , . Additionally, alterations in the expression of immune-related genes and pathways have been implicated in tumor immune evasion and resistance to therapy . These findings have driven intensive research to understand the interplay between the immune system and breast cancer cells. For instance, recent studies have identified immune-related genes that may serve as biomarkers for breast cancer prognosis and treatment response, shedding light on this critical area , . Based on this background, our study analyzed publicly available breast cancer datasets and employed various bioinformatics tools to identify a series of immune-related prognostic genes. Among these, EPHB6 , a prominent member of the receptor tyrosine kinase superfamily (comprising EPHAs and EPHBs ) , , emerged as the most significant prognostic gene for overall survival (OS) in breast cancer. EPH receptors and their ligands are crucial in cell processes like migration, interactions, and vascular development . Humans have nine EPHA receptors ( EPHA1 - EPHA8 , EPHA10 ) that bind to five ephrin-A ligands ( ephrin-A1-A5 ), and five EPHB receptors ( EPHB1-EPHB4 , EPHB6 ) that bind to three ephrin-B ligands ( ephrin-B1-B3 ) . Ephrin-As link to EPHAs via a plasma membrane anchor, and ephrin-Bs connect to EPHBs through a transmembrane domain . We also constructed a gene set consisting of seven key genes that represent the immune characteristics within the TME. Functional analysis showed that these genes are closely associated with various immune cells, such as T cells and B cells, and are involved in a wide range of immune processes, emphasizing their significant role in the breast cancer immune environment. Furthermore, our research introduces a new focus on the EPHB6 gene, providing the first evidence of its differential expression in benign and malignant breast tissues. These findings not only offer new insights for immunotherapy in breast cancer but also lay the foundation for the development of future personalized treatment strategies. Identification of immune-related prognostic genes In this study, we first obtained the immune and stromal scores of the TCGA breast cancer dataset from the ESTIMATE website. Then, we classified patients into four distinct groups based on their scores: high/low immune score and high/low stromal score groups. After this classification, we performed a survival analysis on these categorized cohorts. We found that patients in the high immune score group had significantly better OS compared to those in the low immune score group (Supplementary Fig. 1A). However, there was no statistically significant difference in OS between patients with high and low stromal scores (Supplementary Fig. 1B). The findings of this study indicate that immune scores may serve as a valuable tool for identifying patients with a better prognosis, potentially guiding more personalized management strategies for breast cancer. Future research should focus on validating these results in larger cohorts and exploring the biological mechanisms underlying the association between immune scores and patient outcomes. Next, we employed the ‘limma’ package to identify differentially expressed genes (DEGs) between the high and low immune score groups. Following this, we intersected these genes with the DEGs between breast cancer and normal breast tissue obtained from the GEPIA2 website, resulting in 88 potential immune-related prognostic genes. Through Lasso regression analysis, we further pinpointed 8 key genes (Supplementary Fig. 2A-B). The best combination of prognostic genes was selected based on area under the curve (AUC) values using the GMM method. Then we identified an immune signature gene set that consists of seven genes (Supplementary Fig. 2C), including CD2 , CXCL13 , PPP1R16B , LILRB5 , EPHB6 , TACR1 , and SAA2 . Using the BEST platform for tumor immune infiltration, GO (gene ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses, we found that these genes held strong correlations with various immune cells such as T cells, B cells (Supplementary Fig. 3). GO analysis revealed that these genes participated in multiple immune processes, such as the immune system process and immune response (Supplementary Fig. 4). KEGG analysis demonstrated that these genes were related to numerous immune-related pathways, such as cytokine-cytokine receptor interaction, natural killer cell-mediated cytotoxicity (Supplementary Fig. 5). Consequently, these genes were selected for subsequent analyses. Notably, the random forest algorithm confirmed the pivotal role of the EPHB6 in predicting overall survival (OS) prognosis (Fig. A). Construction and validation of the prognostic model First, we evaluated the effect of the risk group on patient outcomes in both the TCGA and METABRIC datasets. Consistently, both univariable and multivariable COX regression analyses identified the risk group as an independent predictor of OS (Fig. B-C). Further survival analysis confirmed that patients in the low-risk group had significantly longer OS compared to those in the high-risk group (Fig. D-E). Using the TCGA cohort as the training dataset, we developed a nomogram prognostic model incorporating four variables: age, stage, subtype, and risk group (Fig. A). This model achieved impressive AUC values of 0.857, 0.788, and 0.745 for predicting 1-year, 3-year, and 5-year OS, respectively, in the TCGA cohort (Fig. B). Upon validation in the METABRIC cohort, the corresponding AUC values were 0.832, 0.653, and 0.679 (Fig. B). Calibration and DCA curves further supported the model’s robust predictive power, providing additional evidence of its reliability (Fig. C-D). Notably, the model demonstrated the highest net benefit in predicting 5-year OS (Fig. D), indicating that our prognostic tool is dependable and can accurately guide treatment decisions and estimate patient survival. The risk score predicts therapeutic benefits To explore the response of breast cancer patients in different risk groups to commonly used chemotherapy drugs, we utilized the GDSC2 database as a reference and employed the Oncopredict package for predicting drug sensitivity. Among the six chemotherapy medications we selected—taxanes (including docetaxel), epirubicin, cisplatin, gemcitabine, and vinorelbine—taxanes and epirubicin are key components in breast cancer chemotherapy regimens. Our results showed that TCGA patients in the low-risk group exhibited greater responsiveness, especially to taxanes and epirubicin, as well as the other medications (Fig. A). This finding suggests that patients in this group may gain more substantial benefits from these therapies, potentially guiding the development of personalized treatment strategies in the future. We validated these findings using the METABRIC dataset, further strengthening the credibility of our research (Fig. B). Subgroup analysis revealed distinct drug response patterns. In the TCGA cohort, the low-risk group demonstrated significantly enhanced sensitivity to gemcitabine across Luminal A, Luminal B, and HER2-positive subtypes (Supplementary Fig. 6A). However, the METABRIC validation cohort exhibited a broader response profile, with the low-risk group showing superior sensitivity to nearly all six selected chemotherapeutic agents, except in the TNBC subgroup (Supplementary Fig. 6B). This discrepancy between cohorts may be attributed to inherent variations in patient characteristics, or methodological approaches. Further investigations are warranted to elucidate the underlying mechanisms and validate the generalizability of these findings across diverse clinical settings. In the GSE20685 dataset, we observed that breast cancer patients with distant metastases had higher risk scores compared to those without (Fig. C). Furthermore, deceased patients exhibited higher risk scores than those who were still alive (Fig. D). In the GSE35640 dataset, patients with metastatic melanoma who responded to MAGE-A3 immunotherapy had significantly lower risk scores than non-responders (Fig. E). Similarly, within the IMvigor210 cohort, bladder cancer patients who responded to anti-PD-1/PD-L1 therapy had lower risk scores than non-responders (Fig. F). Collectively, these results indicate that patients with lower risk scores experience greater therapeutic benefits. Single-cell analysis of immune-related prognostic gene expression When comparing normal breast samples with different breast cancer subtypes, we applied harmony batch correction to mitigate batch effects (Supplementary Fig. 7). As shown in Fig. A, normal breast tissue and cancer cells share several cell subgroups, including epithelial cells, endothelial cells, T cells, myeloid cells, plasma cells, fibroblasts, and pericytes. In normal breast samples, epithelial cells are further subdivided into mature luminal epithelial cells, luminal progenitor cells, and basal cells. Different types of cancer samples each contained a subgroup of B cells. Specifically, in both ER-positive and Her2-positive cancer samples, we identified a group of normal basal cell subpopulations . The stacked bar chart illustrates the proportion of cell types in each sample (Supplementary Fig. 7). Figure B lists the marker genes associated with these subpopulations. Single-cell analysis revealed that the immune-related genes CD2 and CXCL13 are primarily expressed in T cells (Fig. C), which supports the accuracy of our findings. SAA2 was mainly expressed in normal breast basal cells, while LILRB5 was expressed at low levels, mainly in myeloid cells. EPHB6 and PPP1R16B showed limited expression, mainly in T cells, whereas TACR1 was detected in only a minority of cells (Fig. C). However, it’s worth noting that the previous sections of this study reported EPHB6 as one of the differentially expressed genes between breast cancer and benign breast tissues, with a prominent contribution to the OS of breast cancer patients. In contrast, the current single-cell analysis failed to uncover a distinct expression pattern for EPHB6 . Given the potential for technical artifacts and data quality issues in single-cell sequencing, we plan to further validate EPHB6 expression in both benign and malignant breast tissues in subsequent sections of this study. Functional analysis To better understand the genetic differences between high-risk and low-risk groups, we conducted the KEGG pathway analysis. Using the advanced Scissor algorithm, we identified cell subgroups associated with each risk category and analyzed single-cell data across three subtypes of breast cancer. Specifically, Scissor cells are associated with the high-risk group, while Scissor cells are linked to the low-risk group. KEGG analysis of DEGs between Scissor and Scissor cells indicated that these genes were associated with several immune-related pathways (Fig. A-C). This pattern was consistently observed in the TCGA cohort as well, where DEGs between distinct risk groups similarly exhibited correlations with immune pathways (Fig. D). Importantly, we identified overlapping pathways at both the bulk and single-cell levels, which include Th1 and Th2 cell differentiation, Th17 cell differentiation, inflammatory bowel disease, graft-versus-host disease, IgA production within the intestinal immune network, allograft rejection, type I diabetes, and, finally, antigen processing and presentation. These findings underscore a robust relationship between risk groups and the involvement of the immune system in breast cancer. After integrating single-cell data from all cancer cells, we observed differences in the composition ratios of Scissor + and Scissor- cell populations within the immune microenvironment (Supplementary Fig. 8A-C). This pattern was also observed in Luminal, HER2-positive, and TNBC, respectively (Supplementary Fig. 8D-F). This finding offers additional context for the KEGG pathway enrichment analysis results (Table ). EPHB6 expression in benign and malignant breast tissues In this section, we used IHC to assess EPHB6 expression across a variety of breast tissues, including fibroadenomas, cancer tissues, and adjacent non-cancerous samples (Fig. A-F). Our IHC analysis revealed the presence of EPHB6 in both epithelial cells and the surrounding tissue. Specifically, strong expression (3+) of EPHB6 was observed in both adjacent normal tissues and fibroadenoma tissues (Fig. E-F). Among different types of breast cancer, TNBC stood out with the highest levels of EPHB6 expression, scored as 3+, whereas other types generally displayed lower (1+) or moderate (2+) expression levels (Table ). It is also worth mentioning that high EPHB6 expression in non-TNBC was exclusively associated with in situ carcinoma (Table ). To further investigate EPHB6 expression at the protein level, we performed an analysis of the integrated optical density (IOD) per area, which revealed a significant pattern in the expression of EPHB6 (Fig. G): Firstly, no significant difference was observed in the expression of EPHB6 between fibroadenomas and adjacent normal tissues. Secondly, the expression of EPHB6 was significantly lower in malignant tumors compared to benign breast tissues. Lastly, and perhaps most notably, the expression of EPHB6 was significantly higher in in situ carcinomas than in invasive cancers. Additionally, EPHB6 expression was conspicuously higher in triple-negative breast cancer (TNBC) compared to non-TNBC cases (Fig. G). On the other hand, EPHB6 mRNA levels were higher in normal breast tissue than in cancerous tissue, with TNBC samples showing significantly elevated EPHB6 expression compared to non-TNBC cases (Fig. H-J). These RNA-level findings are consistent with our protein-level results. We also evaluated EPHB6 expression in axillary lymph nodes. Notably, in nodes without cancer metastasis, prominent EPHB6 expression was detected in the interstitium, indicating its importance for preserving the normal structure and function of the lymph nodes (Fig. A-C). In contrast, upon cancer cell invasion into the lymph nodes, EPHB6 expression was virtually absent within the cancer cells (Fig. A-C). This finding strengthens the hypothesis that reduced EPHB6 expression may be associated with the tumor’s invasive nature and metastatic capacity. Interestingly, in a section of metastatic lymph node, both well-differentiated and poorly differentiated carcinomas were found. Notably, EPHB6 expression was present in well-differentiated carcinomas but absent in poorly differentiated ones. (Fig. D). Nevertheless, further research is needed to validate this observation and explore the underlying mechanisms. We then focused our efforts on a more in-depth exploration of EPHB6 expression in distant breast cancer metastases. In the GSE46141 dataset, we analyzed the expression of EPHB6 at six metastatic sites: liver, breast, lymph nodes, skin, bone, and lung. Our pairwise comparisons revealed a significant finding: the expression level of EPHB6 was significantly lower in hepatic metastatic lesions compared to pulmonary lesions and was also markedly decreased in lymph nodes when compared to the lungs (Supplementary Fig. 9A). Conversely, upon pairwise examination, no significant differences were detected among the remaining metastatic sites (Supplementary Fig. 9A). In the GSE56493 dataset, which also included six metastatic sites of breast cancer (liver, breast, lymph nodes, skin, skeletal muscle, and lung/pleura), we found that EPHB6 expression was significantly lower in hepatic metastatic lesions compared to those in the breast, skin, and lung/pleura (Supplementary Fig. 9B). This observation highlights significant variations in EPHB6 expression across different metastatic sites, suggesting potential differences in tumor behavior or microenvironment. However, pairwise comparisons among the remaining metastatic sites failed to reveal any statistically significant differences (Supplementary Fig. 9B). The GSE56493 dataset provides PAM50 subtype information of metastatic lesions. The metastatic lesions in skin and lymph nodes contain both basal and non-basal samples. Surprisingly, we found that in lymph node metastatic cancer, the expression level of EPHB6 was significantly elevated in basal samples compared to non-basal ones (Supplementary Fig. 9C). This intriguing discovery may shed light on the potential role of EPHB6 in specific tumor subtypes. In contrast, no significant difference in EPHB6 expression was observed between basal and non-basal samples in skin metastatic cancer (Supplementary Fig. 9D). However, given the limitation of the sample size, these preliminary results warrant further validation through larger-scale studies. In this study, we first obtained the immune and stromal scores of the TCGA breast cancer dataset from the ESTIMATE website. Then, we classified patients into four distinct groups based on their scores: high/low immune score and high/low stromal score groups. After this classification, we performed a survival analysis on these categorized cohorts. We found that patients in the high immune score group had significantly better OS compared to those in the low immune score group (Supplementary Fig. 1A). However, there was no statistically significant difference in OS between patients with high and low stromal scores (Supplementary Fig. 1B). The findings of this study indicate that immune scores may serve as a valuable tool for identifying patients with a better prognosis, potentially guiding more personalized management strategies for breast cancer. Future research should focus on validating these results in larger cohorts and exploring the biological mechanisms underlying the association between immune scores and patient outcomes. Next, we employed the ‘limma’ package to identify differentially expressed genes (DEGs) between the high and low immune score groups. Following this, we intersected these genes with the DEGs between breast cancer and normal breast tissue obtained from the GEPIA2 website, resulting in 88 potential immune-related prognostic genes. Through Lasso regression analysis, we further pinpointed 8 key genes (Supplementary Fig. 2A-B). The best combination of prognostic genes was selected based on area under the curve (AUC) values using the GMM method. Then we identified an immune signature gene set that consists of seven genes (Supplementary Fig. 2C), including CD2 , CXCL13 , PPP1R16B , LILRB5 , EPHB6 , TACR1 , and SAA2 . Using the BEST platform for tumor immune infiltration, GO (gene ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses, we found that these genes held strong correlations with various immune cells such as T cells, B cells (Supplementary Fig. 3). GO analysis revealed that these genes participated in multiple immune processes, such as the immune system process and immune response (Supplementary Fig. 4). KEGG analysis demonstrated that these genes were related to numerous immune-related pathways, such as cytokine-cytokine receptor interaction, natural killer cell-mediated cytotoxicity (Supplementary Fig. 5). Consequently, these genes were selected for subsequent analyses. Notably, the random forest algorithm confirmed the pivotal role of the EPHB6 in predicting overall survival (OS) prognosis (Fig. A). First, we evaluated the effect of the risk group on patient outcomes in both the TCGA and METABRIC datasets. Consistently, both univariable and multivariable COX regression analyses identified the risk group as an independent predictor of OS (Fig. B-C). Further survival analysis confirmed that patients in the low-risk group had significantly longer OS compared to those in the high-risk group (Fig. D-E). Using the TCGA cohort as the training dataset, we developed a nomogram prognostic model incorporating four variables: age, stage, subtype, and risk group (Fig. A). This model achieved impressive AUC values of 0.857, 0.788, and 0.745 for predicting 1-year, 3-year, and 5-year OS, respectively, in the TCGA cohort (Fig. B). Upon validation in the METABRIC cohort, the corresponding AUC values were 0.832, 0.653, and 0.679 (Fig. B). Calibration and DCA curves further supported the model’s robust predictive power, providing additional evidence of its reliability (Fig. C-D). Notably, the model demonstrated the highest net benefit in predicting 5-year OS (Fig. D), indicating that our prognostic tool is dependable and can accurately guide treatment decisions and estimate patient survival. To explore the response of breast cancer patients in different risk groups to commonly used chemotherapy drugs, we utilized the GDSC2 database as a reference and employed the Oncopredict package for predicting drug sensitivity. Among the six chemotherapy medications we selected—taxanes (including docetaxel), epirubicin, cisplatin, gemcitabine, and vinorelbine—taxanes and epirubicin are key components in breast cancer chemotherapy regimens. Our results showed that TCGA patients in the low-risk group exhibited greater responsiveness, especially to taxanes and epirubicin, as well as the other medications (Fig. A). This finding suggests that patients in this group may gain more substantial benefits from these therapies, potentially guiding the development of personalized treatment strategies in the future. We validated these findings using the METABRIC dataset, further strengthening the credibility of our research (Fig. B). Subgroup analysis revealed distinct drug response patterns. In the TCGA cohort, the low-risk group demonstrated significantly enhanced sensitivity to gemcitabine across Luminal A, Luminal B, and HER2-positive subtypes (Supplementary Fig. 6A). However, the METABRIC validation cohort exhibited a broader response profile, with the low-risk group showing superior sensitivity to nearly all six selected chemotherapeutic agents, except in the TNBC subgroup (Supplementary Fig. 6B). This discrepancy between cohorts may be attributed to inherent variations in patient characteristics, or methodological approaches. Further investigations are warranted to elucidate the underlying mechanisms and validate the generalizability of these findings across diverse clinical settings. In the GSE20685 dataset, we observed that breast cancer patients with distant metastases had higher risk scores compared to those without (Fig. C). Furthermore, deceased patients exhibited higher risk scores than those who were still alive (Fig. D). In the GSE35640 dataset, patients with metastatic melanoma who responded to MAGE-A3 immunotherapy had significantly lower risk scores than non-responders (Fig. E). Similarly, within the IMvigor210 cohort, bladder cancer patients who responded to anti-PD-1/PD-L1 therapy had lower risk scores than non-responders (Fig. F). Collectively, these results indicate that patients with lower risk scores experience greater therapeutic benefits. When comparing normal breast samples with different breast cancer subtypes, we applied harmony batch correction to mitigate batch effects (Supplementary Fig. 7). As shown in Fig. A, normal breast tissue and cancer cells share several cell subgroups, including epithelial cells, endothelial cells, T cells, myeloid cells, plasma cells, fibroblasts, and pericytes. In normal breast samples, epithelial cells are further subdivided into mature luminal epithelial cells, luminal progenitor cells, and basal cells. Different types of cancer samples each contained a subgroup of B cells. Specifically, in both ER-positive and Her2-positive cancer samples, we identified a group of normal basal cell subpopulations . The stacked bar chart illustrates the proportion of cell types in each sample (Supplementary Fig. 7). Figure B lists the marker genes associated with these subpopulations. Single-cell analysis revealed that the immune-related genes CD2 and CXCL13 are primarily expressed in T cells (Fig. C), which supports the accuracy of our findings. SAA2 was mainly expressed in normal breast basal cells, while LILRB5 was expressed at low levels, mainly in myeloid cells. EPHB6 and PPP1R16B showed limited expression, mainly in T cells, whereas TACR1 was detected in only a minority of cells (Fig. C). However, it’s worth noting that the previous sections of this study reported EPHB6 as one of the differentially expressed genes between breast cancer and benign breast tissues, with a prominent contribution to the OS of breast cancer patients. In contrast, the current single-cell analysis failed to uncover a distinct expression pattern for EPHB6 . Given the potential for technical artifacts and data quality issues in single-cell sequencing, we plan to further validate EPHB6 expression in both benign and malignant breast tissues in subsequent sections of this study. To better understand the genetic differences between high-risk and low-risk groups, we conducted the KEGG pathway analysis. Using the advanced Scissor algorithm, we identified cell subgroups associated with each risk category and analyzed single-cell data across three subtypes of breast cancer. Specifically, Scissor cells are associated with the high-risk group, while Scissor cells are linked to the low-risk group. KEGG analysis of DEGs between Scissor and Scissor cells indicated that these genes were associated with several immune-related pathways (Fig. A-C). This pattern was consistently observed in the TCGA cohort as well, where DEGs between distinct risk groups similarly exhibited correlations with immune pathways (Fig. D). Importantly, we identified overlapping pathways at both the bulk and single-cell levels, which include Th1 and Th2 cell differentiation, Th17 cell differentiation, inflammatory bowel disease, graft-versus-host disease, IgA production within the intestinal immune network, allograft rejection, type I diabetes, and, finally, antigen processing and presentation. These findings underscore a robust relationship between risk groups and the involvement of the immune system in breast cancer. After integrating single-cell data from all cancer cells, we observed differences in the composition ratios of Scissor + and Scissor- cell populations within the immune microenvironment (Supplementary Fig. 8A-C). This pattern was also observed in Luminal, HER2-positive, and TNBC, respectively (Supplementary Fig. 8D-F). This finding offers additional context for the KEGG pathway enrichment analysis results (Table ). In this section, we used IHC to assess EPHB6 expression across a variety of breast tissues, including fibroadenomas, cancer tissues, and adjacent non-cancerous samples (Fig. A-F). Our IHC analysis revealed the presence of EPHB6 in both epithelial cells and the surrounding tissue. Specifically, strong expression (3+) of EPHB6 was observed in both adjacent normal tissues and fibroadenoma tissues (Fig. E-F). Among different types of breast cancer, TNBC stood out with the highest levels of EPHB6 expression, scored as 3+, whereas other types generally displayed lower (1+) or moderate (2+) expression levels (Table ). It is also worth mentioning that high EPHB6 expression in non-TNBC was exclusively associated with in situ carcinoma (Table ). To further investigate EPHB6 expression at the protein level, we performed an analysis of the integrated optical density (IOD) per area, which revealed a significant pattern in the expression of EPHB6 (Fig. G): Firstly, no significant difference was observed in the expression of EPHB6 between fibroadenomas and adjacent normal tissues. Secondly, the expression of EPHB6 was significantly lower in malignant tumors compared to benign breast tissues. Lastly, and perhaps most notably, the expression of EPHB6 was significantly higher in in situ carcinomas than in invasive cancers. Additionally, EPHB6 expression was conspicuously higher in triple-negative breast cancer (TNBC) compared to non-TNBC cases (Fig. G). On the other hand, EPHB6 mRNA levels were higher in normal breast tissue than in cancerous tissue, with TNBC samples showing significantly elevated EPHB6 expression compared to non-TNBC cases (Fig. H-J). These RNA-level findings are consistent with our protein-level results. We also evaluated EPHB6 expression in axillary lymph nodes. Notably, in nodes without cancer metastasis, prominent EPHB6 expression was detected in the interstitium, indicating its importance for preserving the normal structure and function of the lymph nodes (Fig. A-C). In contrast, upon cancer cell invasion into the lymph nodes, EPHB6 expression was virtually absent within the cancer cells (Fig. A-C). This finding strengthens the hypothesis that reduced EPHB6 expression may be associated with the tumor’s invasive nature and metastatic capacity. Interestingly, in a section of metastatic lymph node, both well-differentiated and poorly differentiated carcinomas were found. Notably, EPHB6 expression was present in well-differentiated carcinomas but absent in poorly differentiated ones. (Fig. D). Nevertheless, further research is needed to validate this observation and explore the underlying mechanisms. We then focused our efforts on a more in-depth exploration of EPHB6 expression in distant breast cancer metastases. In the GSE46141 dataset, we analyzed the expression of EPHB6 at six metastatic sites: liver, breast, lymph nodes, skin, bone, and lung. Our pairwise comparisons revealed a significant finding: the expression level of EPHB6 was significantly lower in hepatic metastatic lesions compared to pulmonary lesions and was also markedly decreased in lymph nodes when compared to the lungs (Supplementary Fig. 9A). Conversely, upon pairwise examination, no significant differences were detected among the remaining metastatic sites (Supplementary Fig. 9A). In the GSE56493 dataset, which also included six metastatic sites of breast cancer (liver, breast, lymph nodes, skin, skeletal muscle, and lung/pleura), we found that EPHB6 expression was significantly lower in hepatic metastatic lesions compared to those in the breast, skin, and lung/pleura (Supplementary Fig. 9B). This observation highlights significant variations in EPHB6 expression across different metastatic sites, suggesting potential differences in tumor behavior or microenvironment. However, pairwise comparisons among the remaining metastatic sites failed to reveal any statistically significant differences (Supplementary Fig. 9B). The GSE56493 dataset provides PAM50 subtype information of metastatic lesions. The metastatic lesions in skin and lymph nodes contain both basal and non-basal samples. Surprisingly, we found that in lymph node metastatic cancer, the expression level of EPHB6 was significantly elevated in basal samples compared to non-basal ones (Supplementary Fig. 9C). This intriguing discovery may shed light on the potential role of EPHB6 in specific tumor subtypes. In contrast, no significant difference in EPHB6 expression was observed between basal and non-basal samples in skin metastatic cancer (Supplementary Fig. 9D). However, given the limitation of the sample size, these preliminary results warrant further validation through larger-scale studies. Using bioinformatics tools, we thoroughly analyzed public breast cancer datasets to identify immune-related prognostic genes. We identified a gene set comprising seven pivotal genes that form an “immune signature”. These genes exhibited strong correlations with different types of immune cells, including T cells and B cells, and were involved in a range of immune processes, suggesting a substantial impact on the immune microenvironment of breast cancer. Based on these genes, we calculated risk scores to categorize patients into high and low-risk groups. Both univariable and multivariable analyses confirmed that the classification into these risk groups serves as an independent prognostic factor. Functional analysis revealed that the differentially expressed genes (DEGs) between these groups are primarily involved in several immune-related pathways, which was further supported by a separate analysis of single-cell data. Remarkably, we discovered that patients in the low-risk group exhibited increased sensitivity to commonly prescribed chemotherapy drugs. Moreover, those who responded positively to immunotherapy had notably lower risk scores compared to non-responders. Although immunotherapy is primarily used for triple-negative breast cancer (TNBC), our findings indirectly suggest the potential for applying immunotherapy to non-TNBC. Pioneering studies conducted by researchers at Fudan University Shanghai Cancer Center have provided valuable insights in this regard. In HER2-positive breast cancer, they identified the immunomodulatory subtype (HER2-IM), which exhibits immune-activating characteristics and is considered suitable for immunotherapy and may respond well to such treatments . For luminal breast cancer, the team discovered that supplementing with tyramine can reshape the immune microenvironment and enhance sensitivity to immunotherapy, opening up a new direction for the immunotherapy of this subtype by enhancing the immune response . These studies have laid a solid foundation for precise immunotherapy in breast cancer, highlighting the significance of formulating individualized treatment plans based on molecular characteristics to improve patient outcomes and are expected to further optimize the treatment strategies for breast cancer. Our research has shown that EPHB6 contributes most significantly to breast cancer OS among immune-related signature genes. However, our knowledge of EPHB6 expression in human tissues is still limited, given that only a handful of studies have been undertaken thus far. In studies focusing on colorectal cancer, it was found that EPHB6 was highly expressed in normal colon tissue, whereas its expression decreased in cancer tissue, particularly in samples exhibiting lymph node metastasis, indicating its potential role in tumor invasiveness and metastasis , . Similarly, in prostate cancer research, it was reported that EphB6 expression was moderate to strong in normal tissue but generally diminished in cancer tissue, often appearing negative or weak . Moreover, in melanoma research, observations revealed that EphB6 was highly expressed in benign nevi but underwent a significant decrease in both melanoma and metastatic tumors, with its expression being nearly absent in the latter . As for gastric cancer, although some studies have demonstrated a positive correlation between EphB6 expression and tumor differentiation, as well as a negative correlation with lymph node metastasis and tumor stage, this relationship has not been universally observed across all studies , . Regarding breast cancer, a previous investigation reported that EphB6 protein was undetectable in three invasive breast cancer cell lines: MDA-MB-231, MDA-MB-435, and BT549 29 . In contrast, substantial EphB6 protein levels were noted in non-invasive cell lines (MCF-7, BT-20, and SkBr3) and normal breast cell lines (MCF-10 A) . Previous research on EPHB6 expression in breast cancer had focused primarily on cellular models, but little is known about EPHB6 expression in human breast tissues. Our study, therefore, for the first time, using IHC to bridge this gap, assessing EPHB6 expression in both benign and malignant breast tissues. Notably, we observed overexpression of EPHB6 protein in fibroadenomas and significantly higher expression levels in adjacent non-cancerous tissues compared to cancer tissues. Intriguingly, EPHB6 expression in IDC was markedly elevated compared to other invasive cancer types, which is consistent with RNA-level analysis from public bulk data. Our findings hint at a potential association between decreased EPHB6 expression and breast cancer progression. Of particular interest, triple-negative breast cancer, renowned for its aggressive nature , exhibited significantly higher EPHB6 expression than other breast cancer types, suggesting that increased EPHB6 expression in breast cancer might correlate with enhanced invasiveness. However, this observation stands in contrast to earlier cell line studies, which suggested that reduced expression of EPHB6 could enhance the invasiveness of breast cancer cells , , . These contradictory conclusions may stem from several sources. Firstly, in vitro cell lines might not comprehensively reflect the intricate nature of primary tumor tissues, resulting in discrepancies with human tissue studies. Secondly, the multifaceted roles of EPHB6 in different cell types and stages of tumor development cannot be overlooked; it may inhibit invasion in some contexts while promoting it in others, depending on its interaction with signaling pathways and the cellular context. Additionally, the dynamic variation of EPHB6 expression during tumor progression, which current cell line models might not fully capture, contributes to the complexity. Importantly, our immunohistochemical analysis emphasizes the intricacy of the human tumor microenvironment, demonstrating EPHB6 expression in both epithelial cells and their surrounding stroma, further highlighting potential contributors to the inconsistent findings regarding its relationship with invasiveness. Thus, to comprehensively elucidate EPHB6 ’s role in breast cancer, future studies should focus on its specific mechanisms within this complex microenvironment. Additionally, we pioneered the confirmation of EPHB6 expression in axillary lymph nodes. In these nodes, EPHB6 is primarily expressed in stroma cells, which are crucial not only for the structural framework of the lymph nodes but also for guiding immune cells to their designated locations. Furthermore, stroma cells play a pivotal role in maintaining immune balance, fostering immune tolerance, and regulating the immune response to potential threats . Interestingly, our study also revealed that upon cancer cell infiltration into the lymph nodes, EPHB6 expression was absent in these cancerous cells. This finding could suggest that the level of EPHB6 expression is linked to the differentiation state and metastatic potential of tumor cells. Its downregulation may be associated with enhanced invasiveness and metastatic capabilities. Regarding the potential of EPHB6 as a therapeutic target for breast cancer, it is noteworthy that previous reports have indicated that EPHB6 enhances tumor sensitivity to DNA-damaging treatments in triple-negative breast cancer (TNBC), potentially by driving tumor-initiating cells into a more active division phase, making them more susceptible to treatment . Consequently, EPHB6 appears to be a promising potential therapeutic target for breast cancer, particularly in the context of TNBC. In conclusion, the study identified a prognostic “immune signature” in breast cancer, with EPHB6 as a key gene linked to tumor behavior and treatment response, suggesting its potential as a therapeutic target for personalized cancer treatment. Limitations of the study This study also has several limitations. Firstly, despite the use of multiple public databases and bioinformatics tools, the results are still contingent on existing datasets, which may contain selection bias and heterogeneity and may limit the generalizability of our findings. Secondly, our research was primarily based on retrospective analysis, which may introduce bias, and future prospective studies will help validate our findings. Additionally, while IHC detection offers insights into the expression pattern of EPHB6 in benign and cancerous breast tissues, a larger sample size and multi-center studies are essential to further substantiate the results. This study also has several limitations. Firstly, despite the use of multiple public databases and bioinformatics tools, the results are still contingent on existing datasets, which may contain selection bias and heterogeneity and may limit the generalizability of our findings. Secondly, our research was primarily based on retrospective analysis, which may introduce bias, and future prospective studies will help validate our findings. Additionally, while IHC detection offers insights into the expression pattern of EPHB6 in benign and cancerous breast tissues, a larger sample size and multi-center studies are essential to further substantiate the results. Data acquisition In our study, we utilized the TCGAbiolinks package to access TCGA-BRCA TPM (Transcripts Per Kilobase Million) data along with corresponding patient clinical profiles. Furthermore, we retrieved the METABRIC breast cancer dataset via cBioPortal ( https://www.cbioportal.org ) , . We applied the following data exclusion criteria: (1) genes with low expression, defined as those having an expression level of zero in more than 10% of the samples; (2) cases with incomplete clinical information; (3) patients with an OS time of less than 30 days; (4) male cases. We downloaded gene expression profile data (GSE65194, GSE21422, GSE20685, and GSE35640) and corresponding clinical information from the public Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/ ). Additionally, we obtained a single-cell dataset (GSE161529) from the GEO database, selecting 13 normal breast tissue samples, 6 Her2-positive breast cancer tissue samples, 17 ER-positive breast cancer tissue samples, and 8 triple-negative breast cancer tissue samples. We also downloaded the IMvigor210 cohort, accessible via the provided link ( http://research-pub.gene.com/IMvigor210CoreBiologies/ ) . To further enrich our dataset, we downloaded two additional GEO datasets: GSE46141 and GSE56493, which contain metastatic breast cancer data from multiple sites. Identification of immune-related prognostic genes in breast cancer We obtained immune and stromal scores for the TCGA-BRCA dataset from the ESTIMATE website ( https://bioinformatics.mdanderson.org/estimate ) . We used the “surv_cutpoint” function within the “survminer” package to determine the optimal threshold, dividing breast cancer patients into high and low immune score groups, and high and low stromal score groups, for survival analysis. Subsequently, we identified differentially expressed genes (DEGs) between the high and low groups for both immune and stromal scores. Additionally, we retrieved genes differentially expressed between breast cancer and normal breast tissue from the GEPIA2 database ( http://gepia2.cancer-pku.cn/ ) . To discover the most predictive gene combination, we applied Lasso regression and the Gaussian mixture model (GMM). To explore the relationship of these genes with immune functions, we utilized the BEST platform ( https://rookieutopia.com/app_direct/BEST ), enabling us to perform tumor immune infiltration, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. These analyses helped to elucidate the role of the identified gene set in immune-related processes . Establishment and validation of the prognostic model We developed a ‘risk score’ by integrating gene expression levels with their respective Lasso regression coefficients. The risk score is calculated as: Risk score = (β1 * X1) + (β2 * X2) + … + (βi * Xi), where Xi is the expression level of each gene, and βi is the corresponding Lasso regression coefficient. To categorize patients into high- and low-risk groups, we utilized the ‘survival’ package in R to determine the optimal cutoff. TCGA data served as our training dataset, while METABRIC data was employed for validation. Furthermore; we developed a nomogram that integrates the risk score and clinical characteristics to predict overall survival (OS). We assessed the predictive accuracy of our model using calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) curves. These statistical methods evaluate the accuracy, discriminatory power, and clinical utility of our model, respectively. Drug sensitivity prediction We utilized the ‘oncoPredict’ package to investigate whether patients in different risk groups have different responses to breast cancer chemotherapy medications. This specific package facilitated our assessment of the sensitivity of agents listed in the GDSC2 (Genomics of Drug Sensitivity in Cancer) database . We employed a ridge regression model, specifically designed for breast cancer transcriptomic data, to evaluate the sensitivity and predict the half-maximal inhibitory concentration (IC50) of drugs for the two risk groups. A significance threshold of p < 0.05 was applied. Transcriptome and clinical datasets were analyzed for information on chemotherapy and immune checkpoint Blockade therapies We analyzed data from the GEO (Gene Expression Omnibus) repository to explore how risk scores correlate with treatment responses in patients. The GSE20685 dataset comprised samples from 327 individuals with breast cancer, among whom 268 received adjuvant chemotherapy and 91 relapsed. Furthermore, the GSE35640 dataset documented the treatment outcomes of metastatic melanoma patients undergoing MAGE A3 immunotherapy. Additionally, the IMvigor210 trial assessed the effectiveness of atezolizumab, a drug targeting the PD-L1 protein, in patients with advanced or metastatic urothelial bladder cancer. Single-cell analysis In this part, we utilized Seurat v4 , adhering to the data quality control guidelines outlined by the ‘scCancer’ package . The “DoubletFinder” package assisted in eliminating doublets from our dataset, while the “Harmony” package facilitated the integration of data from multiple samples. Drawing upon markers identified in previous studies , , we were able to delineate distinct cell subgroups. To distinguish cell subpopulations associated with bulk sample phenotypes, we employed the scissor algorithm (Single-cell identification of subpopulations with bulk sample phenotype correlation) . For this study, the input data consisted of GSE161529 scRNA-seq data and TCGA-BRCA data, with the risk group serving as the phenotype feature that corresponded to the TCGA samples. Consequently, we classified the single cells into Scissor and Scissor groups, representing cells associated with high- and low-risk groups, respectively. By leveraging the “Findmarkers” function, we identified differentially expressed genes (DEGs) between these two cell subgroups, applying the following parameters: min.pct = 0.1, logfc.threshold = 0.25, p-adjust < 0.05. Subsequently, we subjected these DEGs to KEGG pathway analysis using the “clusterProfiler” package . Clinical sample collection In our study, we collected 12 fibroadenoma samples from patients at the Breast and Thyroid Surgery Department of Zibo Maternal and Child Health Hospital. Additionally, 58 clinical breast cancer samples were gathered. Among the breast cancer patients, from 20 of them, we obtained paired paracancerous tissues, ensuring a distance of at least 5 cm from the tumor margin (Table , Supplementary Table ). Furthermore, we sampled one cancerous and one non-cancerous lymph node from each of six patients with axillary lymph node metastasis. To guarantee the quality of our data, we applied stringent criteria for selecting breast cancer patients for the study. Eligible patients were those who did not previously receive any treatment and underwent a modified radical mastectomy for breast cancer. The study was approved by the Ethics Review Committee of Zibo Maternal and Child Health Hospital, all methods were performed in accordance with the relevant guidelines and regulations, and all participants provided written informed consent. Immunohistochemical (IHC) staining and scoring Immunohistochemical experiments were conducted following a standard protocol. Tissue sections embedded in paraffin were first treated with xylene to remove the wax, then rehydrated using a series of ethanol solutions. Antigen retrieval was performed with an EDTA buffer at a pH of 9.0 in a DAKO PT Link device, heated to 97 °C for 20 min. After cooling to 65 °C, the samples were removed and washed with Tris-buffered saline. Endogenous peroxidase activity was inactivated with 3% hydrogen peroxide. The primary antibody used was a mouse polyclonal anti-EphB6 antibody sourced from Abnova, diluted to a 1:1000 ratio. The sections were then incubated with this antibody overnight at 4 °C, followed by a wash in Tris-buffered saline. Subsequently, the sections were treated with a secondary antibody, anti-mouse IgG from Dako, for 20 min at room temperature. The final step was color development using a DAB chromogen for one minute. The slides were evaluated independently by three pathologists for the intensity and distribution of the staining signal. The intensity of IHC staining was scored as negative (score 0), weak (1+), intermediate (2+), and strong (3+). The average Integrated Optical Density (IOD) of three areas randomly selected from the acquired images was analyzed using Image-Pro Plus 6 (Supplementary Table -4). Statistical analysis All statistical analyses and graphs in our study were carried out using R software, version 4.2.2, with the help of specific R packages designed for our analytical needs. We determined overall survival (OS) rates using the Kaplan-Meier method and evaluated differences in these rates with the log-rank test. For nonparametric comparisons, we applied the Wilcoxon test for pairwise analysis and the Kruskal-Wallis test when dealing with multiple groups. This thorough approach enabled us to precisely assess statistical significance within our data set. In our study, we utilized the TCGAbiolinks package to access TCGA-BRCA TPM (Transcripts Per Kilobase Million) data along with corresponding patient clinical profiles. Furthermore, we retrieved the METABRIC breast cancer dataset via cBioPortal ( https://www.cbioportal.org ) , . We applied the following data exclusion criteria: (1) genes with low expression, defined as those having an expression level of zero in more than 10% of the samples; (2) cases with incomplete clinical information; (3) patients with an OS time of less than 30 days; (4) male cases. We downloaded gene expression profile data (GSE65194, GSE21422, GSE20685, and GSE35640) and corresponding clinical information from the public Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/ ). Additionally, we obtained a single-cell dataset (GSE161529) from the GEO database, selecting 13 normal breast tissue samples, 6 Her2-positive breast cancer tissue samples, 17 ER-positive breast cancer tissue samples, and 8 triple-negative breast cancer tissue samples. We also downloaded the IMvigor210 cohort, accessible via the provided link ( http://research-pub.gene.com/IMvigor210CoreBiologies/ ) . To further enrich our dataset, we downloaded two additional GEO datasets: GSE46141 and GSE56493, which contain metastatic breast cancer data from multiple sites. We obtained immune and stromal scores for the TCGA-BRCA dataset from the ESTIMATE website ( https://bioinformatics.mdanderson.org/estimate ) . We used the “surv_cutpoint” function within the “survminer” package to determine the optimal threshold, dividing breast cancer patients into high and low immune score groups, and high and low stromal score groups, for survival analysis. Subsequently, we identified differentially expressed genes (DEGs) between the high and low groups for both immune and stromal scores. Additionally, we retrieved genes differentially expressed between breast cancer and normal breast tissue from the GEPIA2 database ( http://gepia2.cancer-pku.cn/ ) . To discover the most predictive gene combination, we applied Lasso regression and the Gaussian mixture model (GMM). To explore the relationship of these genes with immune functions, we utilized the BEST platform ( https://rookieutopia.com/app_direct/BEST ), enabling us to perform tumor immune infiltration, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. These analyses helped to elucidate the role of the identified gene set in immune-related processes . We developed a ‘risk score’ by integrating gene expression levels with their respective Lasso regression coefficients. The risk score is calculated as: Risk score = (β1 * X1) + (β2 * X2) + … + (βi * Xi), where Xi is the expression level of each gene, and βi is the corresponding Lasso regression coefficient. To categorize patients into high- and low-risk groups, we utilized the ‘survival’ package in R to determine the optimal cutoff. TCGA data served as our training dataset, while METABRIC data was employed for validation. Furthermore; we developed a nomogram that integrates the risk score and clinical characteristics to predict overall survival (OS). We assessed the predictive accuracy of our model using calibration plots, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) curves. These statistical methods evaluate the accuracy, discriminatory power, and clinical utility of our model, respectively. We utilized the ‘oncoPredict’ package to investigate whether patients in different risk groups have different responses to breast cancer chemotherapy medications. This specific package facilitated our assessment of the sensitivity of agents listed in the GDSC2 (Genomics of Drug Sensitivity in Cancer) database . We employed a ridge regression model, specifically designed for breast cancer transcriptomic data, to evaluate the sensitivity and predict the half-maximal inhibitory concentration (IC50) of drugs for the two risk groups. A significance threshold of p < 0.05 was applied. We analyzed data from the GEO (Gene Expression Omnibus) repository to explore how risk scores correlate with treatment responses in patients. The GSE20685 dataset comprised samples from 327 individuals with breast cancer, among whom 268 received adjuvant chemotherapy and 91 relapsed. Furthermore, the GSE35640 dataset documented the treatment outcomes of metastatic melanoma patients undergoing MAGE A3 immunotherapy. Additionally, the IMvigor210 trial assessed the effectiveness of atezolizumab, a drug targeting the PD-L1 protein, in patients with advanced or metastatic urothelial bladder cancer. In this part, we utilized Seurat v4 , adhering to the data quality control guidelines outlined by the ‘scCancer’ package . The “DoubletFinder” package assisted in eliminating doublets from our dataset, while the “Harmony” package facilitated the integration of data from multiple samples. Drawing upon markers identified in previous studies , , we were able to delineate distinct cell subgroups. To distinguish cell subpopulations associated with bulk sample phenotypes, we employed the scissor algorithm (Single-cell identification of subpopulations with bulk sample phenotype correlation) . For this study, the input data consisted of GSE161529 scRNA-seq data and TCGA-BRCA data, with the risk group serving as the phenotype feature that corresponded to the TCGA samples. Consequently, we classified the single cells into Scissor and Scissor groups, representing cells associated with high- and low-risk groups, respectively. By leveraging the “Findmarkers” function, we identified differentially expressed genes (DEGs) between these two cell subgroups, applying the following parameters: min.pct = 0.1, logfc.threshold = 0.25, p-adjust < 0.05. Subsequently, we subjected these DEGs to KEGG pathway analysis using the “clusterProfiler” package . In our study, we collected 12 fibroadenoma samples from patients at the Breast and Thyroid Surgery Department of Zibo Maternal and Child Health Hospital. Additionally, 58 clinical breast cancer samples were gathered. Among the breast cancer patients, from 20 of them, we obtained paired paracancerous tissues, ensuring a distance of at least 5 cm from the tumor margin (Table , Supplementary Table ). Furthermore, we sampled one cancerous and one non-cancerous lymph node from each of six patients with axillary lymph node metastasis. To guarantee the quality of our data, we applied stringent criteria for selecting breast cancer patients for the study. Eligible patients were those who did not previously receive any treatment and underwent a modified radical mastectomy for breast cancer. The study was approved by the Ethics Review Committee of Zibo Maternal and Child Health Hospital, all methods were performed in accordance with the relevant guidelines and regulations, and all participants provided written informed consent. Immunohistochemical experiments were conducted following a standard protocol. Tissue sections embedded in paraffin were first treated with xylene to remove the wax, then rehydrated using a series of ethanol solutions. Antigen retrieval was performed with an EDTA buffer at a pH of 9.0 in a DAKO PT Link device, heated to 97 °C for 20 min. After cooling to 65 °C, the samples were removed and washed with Tris-buffered saline. Endogenous peroxidase activity was inactivated with 3% hydrogen peroxide. The primary antibody used was a mouse polyclonal anti-EphB6 antibody sourced from Abnova, diluted to a 1:1000 ratio. The sections were then incubated with this antibody overnight at 4 °C, followed by a wash in Tris-buffered saline. Subsequently, the sections were treated with a secondary antibody, anti-mouse IgG from Dako, for 20 min at room temperature. The final step was color development using a DAB chromogen for one minute. The slides were evaluated independently by three pathologists for the intensity and distribution of the staining signal. The intensity of IHC staining was scored as negative (score 0), weak (1+), intermediate (2+), and strong (3+). The average Integrated Optical Density (IOD) of three areas randomly selected from the acquired images was analyzed using Image-Pro Plus 6 (Supplementary Table -4). All statistical analyses and graphs in our study were carried out using R software, version 4.2.2, with the help of specific R packages designed for our analytical needs. We determined overall survival (OS) rates using the Kaplan-Meier method and evaluated differences in these rates with the log-rank test. For nonparametric comparisons, we applied the Wilcoxon test for pairwise analysis and the Kruskal-Wallis test when dealing with multiple groups. This thorough approach enabled us to precisely assess statistical significance within our data set. Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 |
A blended knowledge translation initiative to improve colorectal cancer staging [ISRCTN56824239] | dc5a7d73-0ed7-4197-9fc7-f9ea7a006a70 | 1395360 | Pathology[mh] | A significant difference exists between what is known to represent best practice and the actual practice of medicine . Such gaps have been repeatedly documented in surgical practice [ - ]. Unfortunately, traditional continuing professional development (CPD) has not been able to bridge the gap between research and evidence-based guidelines and clinical practice [ - ] and consequently, many have advocated for an improved approach . Davis has advocated for 'knowledge translation', as a way of closing the gap between evidence and practice . Such an approach focuses on situated learning within the actual practice of healthcare, includes all participants involved in healthcare practices and attempts to identify and overcome local barriers that prevent practice change . Our group has focused on identifying and closing a gap in colorectal cancer (CRC) staging in Ontario. Accurate staging of CRC is critical when determining appropriate treatment for patients and when it is poorly done it has a negative impact on patient survival . Optimal CRC staging involves clinician knowledge of the minimum number of lymph nodes (LN) to be assessed, requires that a surgeon perform an appropriate mesenteric resection and a pathologist identify and assess the LNs adequately . In Ontario, where 73% of patients with Stage II CRC were shown to be inadequately staged , the challenge of influencing the practice of over 1000 surgeons and pathologists in multiple institutions is significant. We examined the effectiveness of a multi-pronged strategy attempting to improve CRC staging in this large geographic area. We embarked upon a knowledge translation study in which we adapted the principles of social marketing to influence physician behaviour in the context of a practice element that has both knowledge and technical aspects . In contrast, Soumerai initially described social marketing in the context of changing physician prescribing practices . The elements of the social marketing approach include defining clear educational objectives, focusing programs on specific categories of physicians and opinion leaders, establishing 'messenger' credibility, stimulating physician participation in educational interactions, using concise educational materials and providing positive reinforcement when trying to change physician behaviour. A recent Cochrane Review has suggested that social marketing can change physician behaviour . Embedded in the social marketing model we adapted, was the identification (using Hiss methodology) and utilization of both local and expert opinion leaders' (OL) influence . According to the Hiss construct, local OLs are physicians who 1) encourage learning and enjoy sharing their knowledge; 2) are clinical experts and always seem up-to-date and 3) treat others as equals . Opinion leaders who are influential in inciting change at their local health care institution are considered local to peer Ols . OLs who are considered influential on a provincial or national level are considered 'expert' OLs and their support for evidence is sufficient endorsement to consider adoption . Such expert OLs are often consultants or work out of academic centres . Among surgeons, Young has identified that the concept of the OL, especially on a provincial or national level, is supported and that OLs, are considered influential . Little has been written about how large-scale social marketing that utilizes the influence of local and expert opinion leaders has been performed among specialist physicians. The Cochrane Collaboration suggests that further research is required to determine in what context social marketing and OLs are most likely to influence the practice of their peers . In this paper we describe a knowledge translation intervention that used the principles of social marketing and that utilized the influence of local and expert Ols .
Study design and study population This trial compared formal CME alone and formal CME plus the influence of a local opinion leader plus a toolkit on changing surgeon and pathologist behaviour in the context of LN assessment in CRC staging. It was a cluster-randomized trial with the hospital as the unit of random assignment . The particular design was utilized to minimize the contamination of education materials between intervention arms and enabled measurement of the rate of change in each region (Fig. ) . Most randomized trials do not have outcome data for non-participants. This limits their ability to generalize study results or to determine the impact of Hawthorne effects . A strength of our study is that the number of LN's assessed will be available for all patients in Ontario diagnosed with CRC. Consequently we will also be comparing LN assessment of patients from the study hospitals to those of patients whose LN's were assessed at hospitals which did not participate in our trial. Sample size and power calculation Between 1997 and 2000, 27% of patients had an appropriate number of LNs (minimum 12) examined in their surgical specimens in Ontario . As part of this initiative we enrolled 42 hospitals in Ontario. Twenty-one hospitals were randomized to a formal continuing medical education lecture and the other 21 were randomized to the lecture/OL influence/toolkit arm. The remaining hospitals that did not identify an OL did not participate in the study. This sample size is predicted to have 80% power to detect a difference between the two randomized treatment arms of 27% for CME alone and 54% for CME plus the influence of a local opinion leaders plus toolkit in the proportion of patients having at least 12 nodes examined assuming an average of 3 patients per hospital at the six month assessment and using a two-tailed 5% type I error rate and an intracluster correlation coefficient of 0.1. Note that the assumption that 27% of patients seen at CME alone hospitals will have at least 12 nodes assessed is equivalent to what was seen, overall, by Wright et al. as was the degree of intracluster correlation . A two fold difference between the randomized arms was selected as being clinically relevant and equivalent to the difference found between academic and nonacademic hospitals by Wright et al . The sample size was determined using the approach described by Donner and Klar . Greater power is anticipated to be achieved as the primary analysis is based on the number of nodes examined per patient using the generalized estimating equations extension of Poisson regression to account for between hospital variation in node counts . Opinion leader identification A two-page survey instrument was created based on the OL identification methodology developed by Hiss (Additional file: ) . The wording that was used to describe the three OL characteristics (knowledgeable practitioners, educators, and caring professionals who exhibit a high level of humanist concern) was minimally changed from the original Hiss survey instrument . We then identified OLs with special expertise in CRC using a technique utilized by other investigators who also identified OLs with special expertise [ - ]. Importantly, in Soumerai's, Gifford's, Lomas' and Guadagnoli's study , the OLs (with special expertise) were part of a multi-modal approach that resulted in an improvement in patient care. Sample The OL survey was mailed to 1243 general surgeons and pathologists in Ontario with a stamped addressed envelope (SAE) for their reply. Physicians were identified using the Canadian Medical Directory™ (2001) using the criteria "General Surgeons and Pathologists with and without hospital affiliation". The second mail contact included the survey, SAE and an incentive to complete the survey (draw for a Sony Clie © ™). An electronic mail reminder to fill in the survey, including incentive information, was sent out to 366 physicians (e-mail addresses from the Canadian Medical Directory™). A subset of physicians who had not replied after two mailings had their offices contacted by telephone and if they agreed, a survey was faxed to their office or completed over the phone. The third mail contact again included a SAE, survey, and the same incentive. The final mail contact included the survey, SAE, the same incentive and a flyer with the TNM Staging for colorectal cancer. All forms of contact were coded so that it could be identified which contact had initiated the survey response. Physicians were excluded if their practice did not include any colorectal cancer surgery and if they were practicing in another surgical sub-specialty i.e. cardiac, thoracic, vascular surgery or if they were not currently practicing in Ontario, retired or deceased. Physicians whose surveys were returned with an incorrect address were also excluded. Efforts were made to find the correct address including using the College of Physicians and Surgeons of Ontario (CPSO) website and the Royal College of Physicians and Surgeons of Canada (RCPSC) website. "Refusals" were defined as physicians who sent back the surveys not completed or partially completed. Hospital amalgamation In 1997–2000, we identified 99 hospitals that performed CRC surgery in Ontario. By the time we identified OL in Ontario, a number of hospitals had been amalgamated at the request of the provincial government. Hence at the time of our study, 81 hospitals were performing CRC surgery. Identifying an opinion leader for colorectal cancer In our study, physicians were defined as an OL for CRC if they were recognized at least once in all three OL categories and additionally were identified as a person whose advice was valued on CRC using this algorithm. Forty-two hospitals identified an OL for CRC and 39 centres did not, one of which was an academic centre . The 42 hospitals that identified an OL participated in the education intervention and the 39 that did not were not exposed to an intervention. Importantly, our lack of OL identification in a number of centres is not unique, Young (2003) did not identify local surgical OLs at each hospital in her study of Australian surgeons . Identifying the characteristics of an " Expert OL for CRC " The expert OL was a highly regarded surgeon who was identified (multiple times) as an OL for CRC , worked at an academic centre, is recognized in the surgical community as having expertise in CRC on the basis of multiple formal Continuing Medical Education presentations and publications regarding CRC and for treating a high volume of patients with CRC. Randomization Hospitals that identified OL's were cluster-randomized to one of two arms. The intervention arm included a Formal CME (continuing medical education) lecture plus the influence of the Opinion Leader plus a Toolkit. The control arm was the Formal CME session alone. The cluster randomization design was utilized to minimize the contamination of education materials between intervention arms and enabled measurement of the rate of change in each region (Fig. ) . In addition, hospitals were stratified, prior to random assignment, based on two characteristics, their academic status and their yearly volume of CRC cases (low < 20, high ≥ 20). Our previous work demonstrated that a hospital's designation as an academic or non-academic institution was an important predictor of the number of LNs assessed in CRC . We defined academic centers as those hospitals in which both pathology and surgery residents have regular rotations. The remaining hospitals that did not identify OL for CRC and did not participate in the education sessions constituted the control arm (see Fig ). Intervention All randomized hospitals (n = 42) participated in the formal educational sessions led by the same expert OL for CRC . The sessions emphasized the importance of adequate LN assessment in CRC and consisted of a standardized PowerPoint ® lecture which had previously been tested in a single institution study and an interactive question and answer session . The presentation also included a 'scatter gram' of the median LN counts collected for patients with Stage II CRC (1997–2000) for each hospital in the province. If requested by the institution or an individual surgeon/pathologist, the median LN count for that particular institution was revealed at a later date. Participants in the study were not made aware that they were part of a randomized controlled trial and that CRC LN counts would be reassessed after the formal education sessions and academic detailing had been completed. Opinion leader arm The expert OL for CRC met with all but one of the locally identified OL and discussed the importance of adequate LN assessment, local barriers toward improving LN assessment and possible solutions were discussed (academic detailing). A toolkit was provided at the time of the detailing for the OL which consisted of a binder that had a cover letter, a print-out of the PowerPoint ® slide presentation, a pathology template for CRC, guidelines for what should be included in a pathology report for CRC, 3 copies of a poster with a picture of a colon with a number '12' watermarked over it and 3 pocket cards that reminded the OL what an optimal pathology report for CRC would look like, the AJCC staging and a reminder of the minimum number of LN to assess in a CRC specimen. Further printed information was given to some OLs either during the sessions or after if requested. E-mail and telephone follow-up also occurred with some OLs. Follow-up A follow-up package was sent 6 months following the presentation (regular mail) to the CME plus OL plus toolkit site only. The package included a cover letter from the expert OL for CRC thanking the local OL for their participation in the process and opening the door to further discussion if requested, a peer-reviewed paper on LNs clearing solution and more of the same pocket cards . Ethical Review was obtained from the Sunnybrook and Women's College Health Sciences Centre Research Ethics Review Board to complete this trial. Preliminary results Participation All centres (n = 42) agreed to have the expert OL for CRC come and give the formal CME session. Although the hospitals were enthusiastic about hosting the sessions, the arrangements to coordinate the sessions were time consuming. Ninety-percent (38/42) of these sessions took place over a four-month time period beginning in January 5 th 2004 and all of the sessions were completed by June 17 th 2004 (5.5 months). Twenty-four of the sessions were given in the context of hospital rounds and 18 were formal dinners at local restaurants. In general, the dinner presentations were organized for smaller community hospitals. The sessions varied in length between 50 minutes to 4 hours. Food was paid for by the research group in 20/42 centres. Attendance was generally good with most surgeons, pathologists, and pathology assistants (if the position existed at the hospital) attending at each centre. In addition, medical oncologists, family physicians, residents, fellows and nurses also attended some of the sessions. All but one of the opinion leaders in the academic detailing arm agreed to meet personally with the expert OL for CRC (96%) on an individual basis. These sessions lasted between 15–30 minutes. The local OL who did not meet personally with the expert OL for CRC communicated with the expert OL on the telephone and via electronic mail. Feedback Hospitals and OLs relayed their enthusiasm for the project in a number of different ways. Two centres performed audits on the local LN counts prior to the CME session by the expert OL for CRC . After the session was completed, five centres sent correspondence relaying the positive experience of the session, four centres indicated that they were planning to initiate a multi-disciplinary gastro-intestinal tumour conference and four centres requested further information (particularly with regards to their own LNs counts). Interestingly, two centres that were not visited as part of the study also contacted our group requesting information on how to improve their LN counts in CRC.
This trial compared formal CME alone and formal CME plus the influence of a local opinion leader plus a toolkit on changing surgeon and pathologist behaviour in the context of LN assessment in CRC staging. It was a cluster-randomized trial with the hospital as the unit of random assignment . The particular design was utilized to minimize the contamination of education materials between intervention arms and enabled measurement of the rate of change in each region (Fig. ) . Most randomized trials do not have outcome data for non-participants. This limits their ability to generalize study results or to determine the impact of Hawthorne effects . A strength of our study is that the number of LN's assessed will be available for all patients in Ontario diagnosed with CRC. Consequently we will also be comparing LN assessment of patients from the study hospitals to those of patients whose LN's were assessed at hospitals which did not participate in our trial.
Between 1997 and 2000, 27% of patients had an appropriate number of LNs (minimum 12) examined in their surgical specimens in Ontario . As part of this initiative we enrolled 42 hospitals in Ontario. Twenty-one hospitals were randomized to a formal continuing medical education lecture and the other 21 were randomized to the lecture/OL influence/toolkit arm. The remaining hospitals that did not identify an OL did not participate in the study. This sample size is predicted to have 80% power to detect a difference between the two randomized treatment arms of 27% for CME alone and 54% for CME plus the influence of a local opinion leaders plus toolkit in the proportion of patients having at least 12 nodes examined assuming an average of 3 patients per hospital at the six month assessment and using a two-tailed 5% type I error rate and an intracluster correlation coefficient of 0.1. Note that the assumption that 27% of patients seen at CME alone hospitals will have at least 12 nodes assessed is equivalent to what was seen, overall, by Wright et al. as was the degree of intracluster correlation . A two fold difference between the randomized arms was selected as being clinically relevant and equivalent to the difference found between academic and nonacademic hospitals by Wright et al . The sample size was determined using the approach described by Donner and Klar . Greater power is anticipated to be achieved as the primary analysis is based on the number of nodes examined per patient using the generalized estimating equations extension of Poisson regression to account for between hospital variation in node counts .
A two-page survey instrument was created based on the OL identification methodology developed by Hiss (Additional file: ) . The wording that was used to describe the three OL characteristics (knowledgeable practitioners, educators, and caring professionals who exhibit a high level of humanist concern) was minimally changed from the original Hiss survey instrument . We then identified OLs with special expertise in CRC using a technique utilized by other investigators who also identified OLs with special expertise [ - ]. Importantly, in Soumerai's, Gifford's, Lomas' and Guadagnoli's study , the OLs (with special expertise) were part of a multi-modal approach that resulted in an improvement in patient care.
The OL survey was mailed to 1243 general surgeons and pathologists in Ontario with a stamped addressed envelope (SAE) for their reply. Physicians were identified using the Canadian Medical Directory™ (2001) using the criteria "General Surgeons and Pathologists with and without hospital affiliation". The second mail contact included the survey, SAE and an incentive to complete the survey (draw for a Sony Clie © ™). An electronic mail reminder to fill in the survey, including incentive information, was sent out to 366 physicians (e-mail addresses from the Canadian Medical Directory™). A subset of physicians who had not replied after two mailings had their offices contacted by telephone and if they agreed, a survey was faxed to their office or completed over the phone. The third mail contact again included a SAE, survey, and the same incentive. The final mail contact included the survey, SAE, the same incentive and a flyer with the TNM Staging for colorectal cancer. All forms of contact were coded so that it could be identified which contact had initiated the survey response. Physicians were excluded if their practice did not include any colorectal cancer surgery and if they were practicing in another surgical sub-specialty i.e. cardiac, thoracic, vascular surgery or if they were not currently practicing in Ontario, retired or deceased. Physicians whose surveys were returned with an incorrect address were also excluded. Efforts were made to find the correct address including using the College of Physicians and Surgeons of Ontario (CPSO) website and the Royal College of Physicians and Surgeons of Canada (RCPSC) website. "Refusals" were defined as physicians who sent back the surveys not completed or partially completed.
In 1997–2000, we identified 99 hospitals that performed CRC surgery in Ontario. By the time we identified OL in Ontario, a number of hospitals had been amalgamated at the request of the provincial government. Hence at the time of our study, 81 hospitals were performing CRC surgery.
In our study, physicians were defined as an OL for CRC if they were recognized at least once in all three OL categories and additionally were identified as a person whose advice was valued on CRC using this algorithm. Forty-two hospitals identified an OL for CRC and 39 centres did not, one of which was an academic centre . The 42 hospitals that identified an OL participated in the education intervention and the 39 that did not were not exposed to an intervention. Importantly, our lack of OL identification in a number of centres is not unique, Young (2003) did not identify local surgical OLs at each hospital in her study of Australian surgeons .
Expert OL for CRC " The expert OL was a highly regarded surgeon who was identified (multiple times) as an OL for CRC , worked at an academic centre, is recognized in the surgical community as having expertise in CRC on the basis of multiple formal Continuing Medical Education presentations and publications regarding CRC and for treating a high volume of patients with CRC.
Hospitals that identified OL's were cluster-randomized to one of two arms. The intervention arm included a Formal CME (continuing medical education) lecture plus the influence of the Opinion Leader plus a Toolkit. The control arm was the Formal CME session alone. The cluster randomization design was utilized to minimize the contamination of education materials between intervention arms and enabled measurement of the rate of change in each region (Fig. ) . In addition, hospitals were stratified, prior to random assignment, based on two characteristics, their academic status and their yearly volume of CRC cases (low < 20, high ≥ 20). Our previous work demonstrated that a hospital's designation as an academic or non-academic institution was an important predictor of the number of LNs assessed in CRC . We defined academic centers as those hospitals in which both pathology and surgery residents have regular rotations. The remaining hospitals that did not identify OL for CRC and did not participate in the education sessions constituted the control arm (see Fig ).
All randomized hospitals (n = 42) participated in the formal educational sessions led by the same expert OL for CRC . The sessions emphasized the importance of adequate LN assessment in CRC and consisted of a standardized PowerPoint ® lecture which had previously been tested in a single institution study and an interactive question and answer session . The presentation also included a 'scatter gram' of the median LN counts collected for patients with Stage II CRC (1997–2000) for each hospital in the province. If requested by the institution or an individual surgeon/pathologist, the median LN count for that particular institution was revealed at a later date. Participants in the study were not made aware that they were part of a randomized controlled trial and that CRC LN counts would be reassessed after the formal education sessions and academic detailing had been completed.
The expert OL for CRC met with all but one of the locally identified OL and discussed the importance of adequate LN assessment, local barriers toward improving LN assessment and possible solutions were discussed (academic detailing). A toolkit was provided at the time of the detailing for the OL which consisted of a binder that had a cover letter, a print-out of the PowerPoint ® slide presentation, a pathology template for CRC, guidelines for what should be included in a pathology report for CRC, 3 copies of a poster with a picture of a colon with a number '12' watermarked over it and 3 pocket cards that reminded the OL what an optimal pathology report for CRC would look like, the AJCC staging and a reminder of the minimum number of LN to assess in a CRC specimen. Further printed information was given to some OLs either during the sessions or after if requested. E-mail and telephone follow-up also occurred with some OLs. Follow-up A follow-up package was sent 6 months following the presentation (regular mail) to the CME plus OL plus toolkit site only. The package included a cover letter from the expert OL for CRC thanking the local OL for their participation in the process and opening the door to further discussion if requested, a peer-reviewed paper on LNs clearing solution and more of the same pocket cards . Ethical Review was obtained from the Sunnybrook and Women's College Health Sciences Centre Research Ethics Review Board to complete this trial.
A follow-up package was sent 6 months following the presentation (regular mail) to the CME plus OL plus toolkit site only. The package included a cover letter from the expert OL for CRC thanking the local OL for their participation in the process and opening the door to further discussion if requested, a peer-reviewed paper on LNs clearing solution and more of the same pocket cards . Ethical Review was obtained from the Sunnybrook and Women's College Health Sciences Centre Research Ethics Review Board to complete this trial.
Participation All centres (n = 42) agreed to have the expert OL for CRC come and give the formal CME session. Although the hospitals were enthusiastic about hosting the sessions, the arrangements to coordinate the sessions were time consuming. Ninety-percent (38/42) of these sessions took place over a four-month time period beginning in January 5 th 2004 and all of the sessions were completed by June 17 th 2004 (5.5 months). Twenty-four of the sessions were given in the context of hospital rounds and 18 were formal dinners at local restaurants. In general, the dinner presentations were organized for smaller community hospitals. The sessions varied in length between 50 minutes to 4 hours. Food was paid for by the research group in 20/42 centres. Attendance was generally good with most surgeons, pathologists, and pathology assistants (if the position existed at the hospital) attending at each centre. In addition, medical oncologists, family physicians, residents, fellows and nurses also attended some of the sessions. All but one of the opinion leaders in the academic detailing arm agreed to meet personally with the expert OL for CRC (96%) on an individual basis. These sessions lasted between 15–30 minutes. The local OL who did not meet personally with the expert OL for CRC communicated with the expert OL on the telephone and via electronic mail. Feedback Hospitals and OLs relayed their enthusiasm for the project in a number of different ways. Two centres performed audits on the local LN counts prior to the CME session by the expert OL for CRC . After the session was completed, five centres sent correspondence relaying the positive experience of the session, four centres indicated that they were planning to initiate a multi-disciplinary gastro-intestinal tumour conference and four centres requested further information (particularly with regards to their own LNs counts). Interestingly, two centres that were not visited as part of the study also contacted our group requesting information on how to improve their LN counts in CRC.
All centres (n = 42) agreed to have the expert OL for CRC come and give the formal CME session. Although the hospitals were enthusiastic about hosting the sessions, the arrangements to coordinate the sessions were time consuming. Ninety-percent (38/42) of these sessions took place over a four-month time period beginning in January 5 th 2004 and all of the sessions were completed by June 17 th 2004 (5.5 months). Twenty-four of the sessions were given in the context of hospital rounds and 18 were formal dinners at local restaurants. In general, the dinner presentations were organized for smaller community hospitals. The sessions varied in length between 50 minutes to 4 hours. Food was paid for by the research group in 20/42 centres. Attendance was generally good with most surgeons, pathologists, and pathology assistants (if the position existed at the hospital) attending at each centre. In addition, medical oncologists, family physicians, residents, fellows and nurses also attended some of the sessions. All but one of the opinion leaders in the academic detailing arm agreed to meet personally with the expert OL for CRC (96%) on an individual basis. These sessions lasted between 15–30 minutes. The local OL who did not meet personally with the expert OL for CRC communicated with the expert OL on the telephone and via electronic mail.
Hospitals and OLs relayed their enthusiasm for the project in a number of different ways. Two centres performed audits on the local LN counts prior to the CME session by the expert OL for CRC . After the session was completed, five centres sent correspondence relaying the positive experience of the session, four centres indicated that they were planning to initiate a multi-disciplinary gastro-intestinal tumour conference and four centres requested further information (particularly with regards to their own LNs counts). Interestingly, two centres that were not visited as part of the study also contacted our group requesting information on how to improve their LN counts in CRC.
This study is unique in attempting to incite practice change amongst surgeons and pathologists by using an adapted social marketing model. The intervention utilized the influence of Hiss-criteria OLs for CRC in a large geographic area with diverse practice settings (Table ) [ , , , - ]. Importantly, surgeons have indicated in a number of studies that OLs could be influential on their practice patterns especially at a national level (Simunovic, personal communication 2004). Social marketing has been successfully used to change physician behaviour primarily with respect to physician prescribing practices [ - ]. Our study is unique in that we have adopted this model to change aspects of physician behaviour that are related to a process that has both knowledge and technical elements. We have utilized both the influence of an expert OL for CRC and a local or peer OL for CRC both of whom have different roles during a change intervention. Locock suggests that expert OLs are important in the initial stages of an education intervention when evidence needs to be endorsed and translated into a form that is acceptable to local practitioners . The expert OL is considered to be a "higher authority" who is able to explain and evaluate the evidence . In contrast, local or peer OLs are important in the later phases of implementation during which time they role model new behaviour and give colleagues confidence to initiate change . In the present intervention, the expert OL for CRC personally went to each of the hospitals (n = 42) to present the CME session (endorse the evidence) and detail the local OLs. We feel that the presentation by the expert OL for CRC at each local site was an important aspect of the intervention. It has been demonstrated that when physicians consider adopting an innovation that the meaning of the new information has to be discussed among the local physicians (social construction of knowledge) before it can be enacted [50, 51, 52, 53, 54]. We postulate the presence of the expert OL for CRC when endorsing the new information initiated this discussion for each group and the local OL and will facilitate the process of behaviour change. This multi-pronged intervention required a substantial time and financial commitment to enact. One full-time research assistant was employed to co-ordinate the formal CME sessions, academic detailing and follow-up packages. The expert OL for CRC also dedicated 25% of his clinical time for four months to complete the intervention. Clearly this sort of intervention is resource intense and if it is to become a standard approach to changing physician behaviour then substantial support would be required. There are a number of reasons why this study may not be successful in achieving its endpoint of improved CRC staging. First, during our OL identification process we may not have included a number of new general surgery graduates in our survey mail out and hence, some OL for CRC may not have been identified. Second, our intervention predominantly addressed a knowledge deficit and although we attempted to incite discussion and start the process of the social construction of knowledge, if local barriers were too great (i.e. pathology resource issues) then improving CRC staging may be an insurmountable barrier [55]. However, if the intervention is successful then we may not be able to clearly determine if our intervention alone was the catalyst. A number of other continuing medical education events have occurred in the province (including our own oncology rounds) that focused on accurate staging in CRC. In addition, the provincial Cancer Care Organization has also been recently focusing on improving the care of patients with cancer [56]. To address this issue, we will be collecting LN counts for a number of years (2002, 2003) before the intervention was initiated in 2004 as well as after the intervention was started. Our timeline involves data collection between September and December 2005, and analysis is to start in January 2006. In addition, we plan on conducting qualitative interviews with participants to determine whether our intervention incited any physician behaviour change. Davis has suggested that further research is required to understand how to best facilitate the rapid uptake of evidenced-based knowledge . We have described a knowledge translation initiative that we have implemented across Ontario with the aim of improving colorectal cancer staging. We have used a social marketing approach that included the influence of both peer and expert opinion leaders in an attempt to locally construct knowledge to enable physician behaviour change .
The author(s) declare that they have no competing interests.
FCW helped develop the study design, assisted with statistical analysis and drafted the manuscript. CHLL helped develop the study design, performed statistical analysis and helped draft the manuscript. LDL helped develop the study design, collected and collated the data and helped draft the manuscript. NK helped develop the study design and formulated the randomization and helped draft the manuscript. DPR helped develop the study design and helped draft the manuscript. AJS conceived and helped develop the study design, was the investigator who actually contacted and detailed the Opinion Leaders, helped draft the manuscript and helped with statistical analysis. All authors read and approved the final manuscript.
The pre-publication history for this paper can be accessed here:
Additional file 1 . Click here for file
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Connecting environmental and evolutionary microbiology for the development of new agrobiotechnological tools | b123c899-c6b4-4064-b00b-8d989c8ed6c1 | 10087822 | Microbiology[mh] | The author declares no conflict of interest.
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Presentation of pharmacological content in crime novels between 1890 and 2023 | 66d599e6-387e-4838-bb97-30a2af83e0ba | 11422460 | Pharmacology[mh] | In times of global public health crises like the recent COVID19-pandemic, science communication becomes more and more important (Matta ). Scientific findings lead to concrete action approaches for governments and society (Wirz et al. ). To assure general compliance to such actions in the interest of public health, it is essential that scientific information gets presented in the best comprehensible way. Popular science formats like books have always been a great tool to do so (Sørensen et al. ). They both entertain the reader and give him the possibility to develop a better understanding of certain topics. In this way, books are a valuable part in building connections between the scientific and the general world. Beyond that, science communication also occurs in formats one would not necessarily expect. This includes the most popular book genre: crime novels and thrillers ( https://zipdo.co/statistics/book-sales-by-genre/ , last accessed on 29.01.2024). They often present a variety of drugs to numb or poison people. The presentation of those substances comes frequently along with technical terms suggesting trustworthy information. By being the most accessible way for most people to get in contact with pharmacological information, the stories have the potential to shape the readers image of certain substances and pharmacological principles in general. This could be both a great chance to casually educate them or a potential danger of supplying them with wrong information. Despite the great range and potential influence, little research has been performed on the presentation of pharmacological content in literature. The existing work only focusses on either one disease (Vázquez-Espinosa et al. ) or one specific author (Gerald ). This includes the most successful female crime author of all time, Agatha Christie (Editors of wikipedia.org ). In the book “The Poisonous Pen of Agatha Christie,” Michael Gerald gives a detailed overview on how the former nurse introduced her pharmacological knowledge to her work. As this research has already been performed, we decided to exclude the novels of Christie from our analysis but will link the existing research to our findings in the discussion. The overall aim of our study was to find out how drugs are presented generally in crime novels, also in comparison to other genres like TV series and the reality. Suitable authors of the genre were identified to perform further research. We focused on successful authors with a huge range that at the same time were not yet covered in another analysis. Agatha Christie’s work was already covered in previous studies (Gerald ). Authors from different times and different western countries were included to identify similarities and differences in terms of cultural aspects and time of origin. Table shows our final author selection including their lifetime, their number of copies sold, their most famous character, and in how many languages their work has been translated to. After identifying all crime novels and thrillers written by them, they were read in the German translation. Books for children were not covered. To give the best possible overview, every book of the named authors was read from first to last page. This procedure was adopted to guarantee that every case is part of the analysis, and the shown trends are representative for the author. For the work of Simenon, we had to use another practice as his complete work includes more than 1000 books and short stories. Therefore, the fan page “ https://www.maigret.de ” was used to identify which stories of Simenon have pharmacological content and are, therefore, suitable for our analysis. Statistical analysis In total, 24,895 pages were read, and 88 cases for further analysis were found. This means an average of one case every 283 pages. We found 4 cases in the books of Doyle, 14 in the books of Simenon, 27 in the books of Olsen, 34 in the books of Nesbø, and 9 in the books of Beckett. Figure gives an overview of the reading and analyzation process. A list of all books and page number can be found in Table . Out of 61 books, just 13 did not contain any usable case. Fifteen books contained exactly 1 case, and 33 books—including 5 anthologies—contained at least 2 cases. A case was defined as a scene in which a pharmacological substance is presented and used beyond their medical indication. Therefore, proper usage of substances performed by professionals to treat diseases was not part of our analysis. If a substance appeared more than once in a book, it was still counted as one case as long it was used the same way. It was counted as a new case if there was a relevant change regarding the analyzed parameters. To reveal historical trends, the books were divided into two time categories. All books from the authors born around 1900 or before (Doyle and Simenon) were counted as “old,” whereas books from the later born authors (Beckett, Nesbø, and Olsen) were counted as “new/modern.” This leads to cases between 1890 and 1960 for the older and between 1990 and 2023 for the newer books. For division in time categories, the year of initial release was used. In some cases, this differs from the release date of the German translation that can be found in the references. The cases were drawn out and categorized by the given name, the substance category, substance presentation, way of application, outcome, etiology, gender of offender and victim, whether a mechanism of action was provided, and whether additional information was provided. A fact check of the scenes and further comparison between the authors and the genre was performed after statistical analysis. Fact check and genre comparison For the plausibility check, only information was used the author could have been using too while writing the book. The Poulsson – Lehrbuch der Pharmakologie (“Poulsson – Textbook of Pharmacology”) from 1922 was used to cover the level of knowledge for the older books, whereas modern reference works (Seifert ) and research available on “PubMed” have been used to check the newer ones. For the genre comparison, the work on the German TV series “Tatort” by Ellerbeck and Seifert and Borchert and Seifert was used. Reality comparison has been performed with data of the ”GIZ Nord” (“Poison Information Center North”) and “Gitfnotruf München” (“Poison ermergency call Munich”). In total, 24,895 pages were read, and 88 cases for further analysis were found. This means an average of one case every 283 pages. We found 4 cases in the books of Doyle, 14 in the books of Simenon, 27 in the books of Olsen, 34 in the books of Nesbø, and 9 in the books of Beckett. Figure gives an overview of the reading and analyzation process. A list of all books and page number can be found in Table . Out of 61 books, just 13 did not contain any usable case. Fifteen books contained exactly 1 case, and 33 books—including 5 anthologies—contained at least 2 cases. A case was defined as a scene in which a pharmacological substance is presented and used beyond their medical indication. Therefore, proper usage of substances performed by professionals to treat diseases was not part of our analysis. If a substance appeared more than once in a book, it was still counted as one case as long it was used the same way. It was counted as a new case if there was a relevant change regarding the analyzed parameters. To reveal historical trends, the books were divided into two time categories. All books from the authors born around 1900 or before (Doyle and Simenon) were counted as “old,” whereas books from the later born authors (Beckett, Nesbø, and Olsen) were counted as “new/modern.” This leads to cases between 1890 and 1960 for the older and between 1990 and 2023 for the newer books. For division in time categories, the year of initial release was used. In some cases, this differs from the release date of the German translation that can be found in the references. The cases were drawn out and categorized by the given name, the substance category, substance presentation, way of application, outcome, etiology, gender of offender and victim, whether a mechanism of action was provided, and whether additional information was provided. A fact check of the scenes and further comparison between the authors and the genre was performed after statistical analysis. For the plausibility check, only information was used the author could have been using too while writing the book. The Poulsson – Lehrbuch der Pharmakologie (“Poulsson – Textbook of Pharmacology”) from 1922 was used to cover the level of knowledge for the older books, whereas modern reference works (Seifert ) and research available on “PubMed” have been used to check the newer ones. For the genre comparison, the work on the German TV series “Tatort” by Ellerbeck and Seifert and Borchert and Seifert was used. Reality comparison has been performed with data of the ”GIZ Nord” (“Poison Information Center North”) and “Gitfnotruf München” (“Poison ermergency call Munich”). The designation of the pharmacological substances was different between the analyzed novels. Figure shows the different designation of the pharmacological substances in all novels. Most often, the substances were introduced by naming the active toxin. This was the case for 41% of the findings in total and significantly more in the older novels (Figure ). The usage of colloquial language such as “heart medication” was found in 28.5% of the cases and appeared more often in the newer novels. This was also the case for the lack of a designation with a total count of 16%. Overall, newer novels presented a greater variety of designation which sometimes impeded with the identification of the particular substance. As examples for designation also the mention of the substance group (4.5%), the usage of fictious names (4.5%), the usage of the trade name (4.5%) and the usage of plant name (1%) were found. All substances we found were categorized as visible in Fig. . Hypnotics, often described as “sleeping pills”, were introduced the most often, with 20 mentions overall. Nineteen of those 20 mentions appeared in the newer novels. The usage of substances in the medical world changes over time; the same appeared for the novels. The increase of hypnotic usage in the fictional world reflects the increase of hypnotic usage in the real world. Since the appearance of benzodiazepines in the 1960s, they rapidly became one of the most frequently prescribed substance groups (Wick ). Professionals were pleased to have a presumed safe alternative to the respiratory depressing barbiturates. The discovery of other unwanted effects like addiction some years later led to guidelines to regulate the use. However, they still belong to the most commonly used drugs worldwide (Votaw et al. ). The abuse of benzodiazepines became a serious public health problem and is a relevant topic even nowadays (UNDOC ). By frequently mentioning the misuse of those substances in their novels, modern crime authors potentially raise the awareness for that. The second most found substance category was “not mentioned” with 13 entries. Opioids appeared 8 times. The majority of opioid cases (6) ended up with death, showing how dangerous those substances are also in reality. Opioids are involved in 85% of lethal drug overdoses within the European Union (EMCDDA ). In America, more than 100 people per day die of opioid related overdose ( https://www.cdc.gov/opioids/basics/epidemic.html#:~:text=The%20number%20of%20people%20who ,in%202021%20involved%20an%20opioid., last accessed 01.02.2024). The books again address a serious public health issue here and raise the readers awareness for the danger lies within drug consumption. Indole alkaloids like strychnine appeared exclusively in the older novels with 5 mentions. Also, metals were commonly used in the older novels with 5 mentions compared with one in the modern ones. In nearly every case, the metal used was arsenic, and the indole alkaloid of choice was strychnine. As visible in old pharmacology textbooks like the Poulsson , those two substances were well known also around 1900. The earlier authors seem to stick with substances they already know. In contrast to that, newer novels show a greater variety of substances. Nine different substance categories occur in the older novels, whereas 14 appear in the newer ones. Some agents were used only one single time like thallium in “Takeover” (Olsen ) or rodenticides in “Tiere” (“Animals”) (Beckett ). Solvents appeared 5 times in the modern novels and once in the older ones. Drugs were defined as illegal drugs except for opiates/opioids which were covered in an extra category. Drugs appeared exclusively in the newer novels with 5 mentions, same for gases and bacterial toxins with 3 mentions. Other substances—which means substances that only appeared once and were therefore not categorized separately—were mentioned 7 times in total. This appeared for rodenticides, organophosphates, amyl nitrite, potassium chloride, insulin, propofol, and the toxic ingredients of old matchsticks. Plant toxins were found twice in the new and once in the old novels, same allocation for fictious substances. Animal toxins appeared once for newer and older novels, whereas “heart medication” and cyanide exclusively appeared in the newer novels with two mentions each. An overview of the mention for the substance categories divided into newer and older novels can be found in Figure . The reader also comes in contact with innovations in pharmacology. In the crime novel “Schneemann” (“The Snowman”) by Nesbø , a new kind of pain medication was presented. It was described as a substance from cone snails. The book claimed it as an innovation in the field of pain treatment and as more potent alternative for opioids. Even though the described usage of this substance in the novel was pharmacologically wrong, there was indeed a surge of pain medication research at that time (Safavi-Hemami et al. ). It finally turned out that the drugs could not really been used widely due to huge potential of serious unwanted effects (Löschner et al. ). However, this example shows that some of the newer books introduce current innovations. Overall, a huge variety of pharmacological substances gets presented in crime literature, especially in the newer books. Some serious public health issues get addressed here, and the reader can learn something about newly developed drugs. The older books focused on a smaller selection of substances. The reader here has less opportunity to get in contact with new substances and pharmaceutical innovations. There were various ways of substance presentation that we found in the novels as visible in Fig. . The leadings category was not mentioned with 26%. No big difference was found between older and newer books (Figure ). The second most described presentation forms were tablets (“pills”) with 23% and syringes with 17%. Syringes were exclusively mentioned in the newer novels. In 13% of the cases, the application form was powder; in the older novels, they accounted for a share of 50% and were thereby the most common form of application. Additional ways of application found were “other” with 9%, vessel with liquid 7%, rag soaked with liquid 3%, and exposition to animal with 2%. An example for alternative ways of application described as “other” was the description of gases in the surrounding respiratory air (Nesbø ). Figure shows the application of the substances in all analyzed cases. The most common way of application was oral with 48%, followed by injected with 19%. In 21% of the cases, the way of application remained unclear. In 11%, inhalative application was described, and in 1%, other forms were described. Oral application is not only the most common form in the novels but also in reality (Alqahtani et al. ). It has been even more prominent in the older novels. The commonly used substances in older literature naturally came up in the form of powder and here therefore taken orally. However, the oral way is still the most common form also in the newer novels. The mention of injection has nearly doubled in the newer novels (Figure ). This reflects true pharmacological progress within the last decades. With the advent of disposable syringes in the second half of the twentieth century (Skaftason et al. ) and the scientific progress in the development of biopharmaceuticals ( https://www.pfizercentreone.com/insights-resources/articles/what-are-key-trends-and-developments-injectable-drug-formulation-and , last accessed 01.02.2024), this way of application becomes more and more significant in pharmacotherapy. Again, the newer novels here reflect a real trend in pharmacology which shows that the authors are influenced by scientific developments, at least to a certain degree. Figure shows the outcome of poisoning by percentage value for all cases (a comparison between new and old cases can be found in Figure ). If the target of the person using or delivering the substance was to kill somebody and it succeeded, that was counted as outcome “with death.” If the person survived, it was counted as “with survival.” If a person was intentionally numbed by a substance, this was counted as “with anesthesia,” exceptionally the case the person died. Then this was also counted as outcome “with death.” If the person simply got numbed and survived, it stayed in the category “with anesthesia.” No person was categorized twice. The most common outcome was death with 51%. The survival rate was 11%. Cases of anesthesia were found in 30% of all cases, and in 8% of the cases, the outcome remained unknown. Regarding the outcome, the books partially reflect trends from reality. The role of stunning people with pharmaceuticals, especially injected ones, has noticeably increased in recent literature. In the newer books, the outcome “with anesthesia” appeared in 36% of the cases compared with only 6% in the older ones. An example for that is “Leopard” (“The Leopard”) by Jo Nesbø . Several people get stunned by an injection of a fictious anesthetic similar to ketamine. Also, in reality, it gets more common to stun people with intravenous drugs. Whereas the usage of oral substances has been a common way to target victims in night clubs, it gets more and more widespread to use injections as an alternative ( https://www.theguardian.com/uk-news/2021/oct/19/police-investigate-reports-of-spiking-by-needle-at-nottingham-clubs , last accessed 01.02.2024). Novels might raise the awareness for those new forms of application. Apart from that, the outcome shown in the novels is also source of misinformation. With 72% in the newer and 46% in the older novels, most victims of fictional poisoning died. This stands in contrast to reality. According to GIZ Nord , less than 1% of their registered poisoning cases in 2021 ended up with death. The novels in these cases draw a wrong picture of the danger coming from pharmacological substances. In “Eifersucht” (“The Jealousy Man”) (Nesbø ) and “Die Larve” (“Phantom”) by Nesbø , an overdose of heart medication led to death. Such descriptions might undermine the trust in safe substances and might lower patience adherence to take them. Figure shows the etiology of poisoning with all analyzed cases included. In this category, the reader gets misinformed. In 71.6% of the fictional cases, the poison was delivered by another person and not taken by the victims themselves. Suicidal (13.6%), accidental (8%), and abusive use (6.8%) played a minor role. This stands in contrast to reality. Giftnotruf München is an emergency number that professionals or laypersons can call in case of acute intoxication. They also monitor the etiology of the cases reaching them (Giftnotruf München ). Out of 16,000 poisoning cases in adults in 2022, the most common etiology was by accident with about 50%, followed by suicidal with nearly 30%, followed by abuse with about 10% (Giftnotruf München ). Poison delivery was not even listed as an etiology at all. In reality, the danger to get poisoned at home by accident is much higher than getting poisoned by another individual as incorrectly described in the novels. The readers might get more aware regarding external threat but underestimating the much bigger danger in their daily life. In the age group 14–17 years, the most common etiology surveyed by Giftnotruf München was suicidal with nearly 50% (Giftnotruf München ). This also is not reflected in the books where suicidal pharmaceutical intake plays a minor role. At least the representation of this has increased. Whereas in the older novels, only 6% of the analyzed cases involved suicide, it was 16% percent in the newer novels. However, the shown etiologies differ a lot from reality and are not helpful in raising public awareness for serious dangers. Figure shows the gender distribution of all analyzed cases. The reality comparison is based on a work of Fuhrmeister . A comparison between older and newer novels can be found in Figures and . Regarding gender in poisoning, the books draw a wrong picture of reality. Over all books, the offenders are mainly male (59.7%), whereas more female offenders are involved in real criminal poising cases (53%) (Fuhrmeister ). Also, the victims of poisoning are primarily male in the books (55%), whereas it seems to be nearly even in reality (38% male; 34% female). To a significant extent, the victims’ gender in reality was unclear (28%). In the older books, male had been the victims in 2/3 of all cases. This overrepresentation of men as victims of poisoning may give female readers a wrong security although they are nearly evenly suffering from poisoning cases in reality. Figure shows that if a mechanism of action was provided; it includes all analyzed cases. Among all books, a mechanism of action was not described in 92% of the cases. There was no difference between newer and older novels as shown in Figure . Only in 8% of the cases, a mechanism of action was described. Figure shows if the analyzed cases provided additional information or not. Additional information was defined as pharmacological content such as symptoms, latency times, or dosages. An overview for older and newer novels separately can be found in Figure . Overall, additional pharmacological information was found in 56% of the novels which means that 44% of the cases contained no further information. Figure shows the result of the pharmacological fact check we performed on the fictional cases. To check the information regarding their pharmacological plausibility, we only used data the authors could have been using to while writing the book. For the older cases, mainly the Poulsson – Handbuch der Pharmakologie (“Poulsson – Textbook of pharmacology”) from 1922 was used (Poulsson, E. 1922a). For the plausibility check of the newer cases, we used a current pharmacology reference textbook (Seifert ) and current research data from “PubMed.” Overall, 63% of the cases were plausible; 37% contained, at least minor, inaccuracies. Figure shows that the plausibility decreased over time. In the older books, the rate of correct cases was 72% percent, while it is 60% today. Table shows examples of false presentation. It describes the case and gives a detailed fact check. Table does the same with examples of correct presentation. Figure shows which substances were often source for mistake. Figure gives a comparison between the analyzed authors. Each column represents all cases of this author we checked the plausibility for. The plausible count of cases is colored in yellow; the implausible in red Educating the reader Literature has always been a great tool to educate the readers about topics. As many people are not in contact with advanced pharmacological knowledge daily, the description of those topics in media like books has a substantial impact on how the audience imagines drugs and poisons to work. Despite this opportunity to educate the readers and spread pharmacological knowledge in a thrilling setting, the mechanism of action only got explained in a minority of the novels. In most cases the reader gets no further information on what the substances exactly do to the body and how. If a mechanism of action was described like in “Kakerlaken” (“Cockroaches”) (Nesbø ), the description was very detailed. The reader gets precise information on how an intoxication with carbon dioxide gradually leads to death. This example shows that it is possible for the authors to implement valuable pharmacological education in their literature and leads to the question why they do not do so on a regular basis. When it comes to additional pharmacological information this was also missing in the majority of the analyzed cases. In the older novels, it was more likely to get additional pharmacological information (72% vs. 51%). Also, here, the authors miss the opportunity of expanding the readers knowledge on drugs and poisons. It has been quite common in the older books to give at least some extra information like symptoms in “Die Wahrheit über Bebe Dong” (“The Truth About Bebe Dong”) (Simenon ) or dosage in “Sonntag” (“Sunday”) (Simenon ). In the newer cases, poisoning and drug use are often mentioned in passing. They rarely get described comprehensively like in “Verachtung” (“Journal 64”) (Olsen ) where the reader witnesses the whole process of alkaloid intoxication from the first symptoms to death. Overall, newer authors again miss the opportunity to educate the readers about pharmaceuticals especially compared with the older ones. This may lead to a lesser knowledge about substances among the readers nowadays compared to those in the past. Reality check The fact check performed for our analysis showed that the pharmacological correctness in crime literature decreased over time. Although it is easier than ever before to gain valid information by using online research or getting in contact with experts from all over the world with a mouse-click, modern books were lacking correctness. The most named substances in modern crime novels (hypnotics) were also those with a large error ratio. The same applies for solvents and anesthetics. Common sources for mistakes were false attribution of effect (Olsen /Nesbø ), wrong description of symptoms (Simenon ), or too short latency (Doyle /Nesbø ). Also, wrong antidote use appeared. In “Verachtung” (“Journal 64”) (Olsen ), an unconsciousness caused by propofol was rapidly antagonized by Flumazenil. As they interact with different subunits of the GABA-receptor, this is not possible. In fact, there is no proper antidote for propofol (Keymling et al. ). This leads to a misconception in the readers mind giving him the idea that there are many potent antidots for common anesthetics like propofol. In modern books, hypnotics were often used to commit suicide like in “Natriumchlorid” (“The shadow murders”) (Olsen ), “Verachtung” (“Journal 64”) (Olsen ), or “Der Sohn” “The Son”) (Nesbø ). In fact, suicide with old sleeping substances like barbiturates were common and possible as they could lead to a lethal suppression of the respiratory center in the medulla oblongata. With modern substances like benzodiazepines and non-benzodiazepines (also known as “Z-drugs”), respiratory arrest is hardly possible. The reader gets a wrong picture of those substances here and may therefore reject therapy with those although hypnotics can be helpful, especially in psychiatric emergency situations. Hypnotics are also used together with other substances like alcohol (Beckett or Nesbø ). These combinations are indeed dangerous and could lead to a lethal depression of the respiratory center. However, this danger is not addressed in any of the stories. The reader stays unaware of the danger lies within combining hypnotics and alcohol. Not further classified drugs to numb people by injection were often used in modern crime literature. They work within seconds (Nesbø ), are easy to handle (Beckett ), and are used without any monitoring (Olsen ). This suggestion of monitor-free anesthesia without any big risks is far apart from reality. Famous persons like Michael Jackson ( https://www.health.harvard.edu/blog/propofol-the-drug-that-killed-michael-jackson-201111073772 , last accessed 14.02.204) died of unmonitored injections of propofol. The reader should be educated not to experiment with these drugs under wrong preconditions. However, there were examples of cases where the description was correct and gave the reader the possibility of advancing their pharmacological knowledge. In “Verwesung” (“The calling of the grave”) (Beckett ), we found a correct description of cocaine abuse including symptoms of overdosage and possibly lethal long-term effects. Also, the poisonous effects of plant-based alkaloids were described in great detail in “Verachtung” (“Journal 64”) by Olsen . Moreover, examples of correct hypnotic presentation were found. In “Koma” (“Police”) by Jo Nesbø , a stunning case with a benzodiazepine even includes the mention of adverse drug reactions the following day. Those carefully researched examples show that it is possible for an author to give a realistic picture. This way, the reader can learn facts about pharmacology and get a better understanding of a wide range of substances. As also dangers like death and ADRs are shown in the correct examples, it is unlikely that persons would imitate those. Author comparison and point of view Overall, authors from former centuries wrote more plausible books. This surprised us a lot as careful research was way more difficult in the past centuries. The authors had to consult libraries or professionals which is much more time-consuming than using the internet or artificial intelligence as it is possible for today’s content creators. Why mistakes like the misrepresentation of hypnotics then commonly occur in the modern books has to be part of further research. Maybe also professionals have common misconceptions about particular substances. This would have a negative impact on public health and should be investigated in another study. Although the modern authors did not perform as well as the old ones regarding plausibility, the most correct author by mere numbers was Simon Beckett, a modern author. He often gave detailed information, for example about medical diamorphine use in the UK (Beckett ) or cocaine abuse (Beckett ). The mistakes we found in his books also fall into the categories widely presented incorrectly. In his novel “Die Verlorenen” (“The Lost”) (Beckett ), children get diazepam to numb them for a short time. As diazepam is a long-acting benzodiazepine, this is questionable. Additionally, the use of benzodiazepines in children has always the risk of paradoxical reactions which is not addressed in the book. However, from a pharmacological point of view, Becketts books go in a direction where the reader can learn something about substances and pharmacological principles without being miseducated. The second British author in the analysis (A.C. Doyle) also performed mostly correct leading to the conclusion that British authors were the most accurate in this analysis. The Scandinavians J. Nesbø and J.A. Olsen provided the most examples for this analysis which by mere number increases the chance of finding inaccuracies by a closer look. However, the trend is clear that in those books, the focus was not always on educating the viewer and giving most correct presentation. Overall, the main misconception in the modern books relate to widely known and widely used substances. Most of the readers will get in contact with those substances sooner or later. It is important to draw a realistic picture of those to increase the acceptance for pharmaceuticals in the general population and give them the best possible treatment. Comparison to TV series There has been research done before regarding pharmacological content in fiction. Two current papers discuss the pharmacological content in the most watched German crime TV-Series “Tatort.” Whereas Ellerbeck and Seifert mainly focused on quantitative aspects, Borchert and Seifert concentrated on a reality check. Both is a good basis for comparison with our analysis of the novels as it includes quantitative and qualitative aspects. The “Tatort” seems to have a greater value for the consumer regarding pharmacology than the novels. Although the mechanism of action was also lacking nearly as often as in our analysis, “Tatort” provides additional information more regularly. When it comes to the correctness of this information the TV series also yielded better results. The analysis taken for the TV was slightly different as it also included professional pharmaceutical use to treat symptoms and heal people. However, it seems that more careful research was done in preparation of the TV series than for most of the novels. This breaks with the cliché that books are always more informative and better for education than TV series. Authors might benefit from this, finding out on how research is performed for TV and adopt their own processes, so that more correct information reaches their audience. More suggestions for improvement and an overall assessment of the analyzed parameters can be found in Table . Literature has always been a great tool to educate the readers about topics. As many people are not in contact with advanced pharmacological knowledge daily, the description of those topics in media like books has a substantial impact on how the audience imagines drugs and poisons to work. Despite this opportunity to educate the readers and spread pharmacological knowledge in a thrilling setting, the mechanism of action only got explained in a minority of the novels. In most cases the reader gets no further information on what the substances exactly do to the body and how. If a mechanism of action was described like in “Kakerlaken” (“Cockroaches”) (Nesbø ), the description was very detailed. The reader gets precise information on how an intoxication with carbon dioxide gradually leads to death. This example shows that it is possible for the authors to implement valuable pharmacological education in their literature and leads to the question why they do not do so on a regular basis. When it comes to additional pharmacological information this was also missing in the majority of the analyzed cases. In the older novels, it was more likely to get additional pharmacological information (72% vs. 51%). Also, here, the authors miss the opportunity of expanding the readers knowledge on drugs and poisons. It has been quite common in the older books to give at least some extra information like symptoms in “Die Wahrheit über Bebe Dong” (“The Truth About Bebe Dong”) (Simenon ) or dosage in “Sonntag” (“Sunday”) (Simenon ). In the newer cases, poisoning and drug use are often mentioned in passing. They rarely get described comprehensively like in “Verachtung” (“Journal 64”) (Olsen ) where the reader witnesses the whole process of alkaloid intoxication from the first symptoms to death. Overall, newer authors again miss the opportunity to educate the readers about pharmaceuticals especially compared with the older ones. This may lead to a lesser knowledge about substances among the readers nowadays compared to those in the past. The fact check performed for our analysis showed that the pharmacological correctness in crime literature decreased over time. Although it is easier than ever before to gain valid information by using online research or getting in contact with experts from all over the world with a mouse-click, modern books were lacking correctness. The most named substances in modern crime novels (hypnotics) were also those with a large error ratio. The same applies for solvents and anesthetics. Common sources for mistakes were false attribution of effect (Olsen /Nesbø ), wrong description of symptoms (Simenon ), or too short latency (Doyle /Nesbø ). Also, wrong antidote use appeared. In “Verachtung” (“Journal 64”) (Olsen ), an unconsciousness caused by propofol was rapidly antagonized by Flumazenil. As they interact with different subunits of the GABA-receptor, this is not possible. In fact, there is no proper antidote for propofol (Keymling et al. ). This leads to a misconception in the readers mind giving him the idea that there are many potent antidots for common anesthetics like propofol. In modern books, hypnotics were often used to commit suicide like in “Natriumchlorid” (“The shadow murders”) (Olsen ), “Verachtung” (“Journal 64”) (Olsen ), or “Der Sohn” “The Son”) (Nesbø ). In fact, suicide with old sleeping substances like barbiturates were common and possible as they could lead to a lethal suppression of the respiratory center in the medulla oblongata. With modern substances like benzodiazepines and non-benzodiazepines (also known as “Z-drugs”), respiratory arrest is hardly possible. The reader gets a wrong picture of those substances here and may therefore reject therapy with those although hypnotics can be helpful, especially in psychiatric emergency situations. Hypnotics are also used together with other substances like alcohol (Beckett or Nesbø ). These combinations are indeed dangerous and could lead to a lethal depression of the respiratory center. However, this danger is not addressed in any of the stories. The reader stays unaware of the danger lies within combining hypnotics and alcohol. Not further classified drugs to numb people by injection were often used in modern crime literature. They work within seconds (Nesbø ), are easy to handle (Beckett ), and are used without any monitoring (Olsen ). This suggestion of monitor-free anesthesia without any big risks is far apart from reality. Famous persons like Michael Jackson ( https://www.health.harvard.edu/blog/propofol-the-drug-that-killed-michael-jackson-201111073772 , last accessed 14.02.204) died of unmonitored injections of propofol. The reader should be educated not to experiment with these drugs under wrong preconditions. However, there were examples of cases where the description was correct and gave the reader the possibility of advancing their pharmacological knowledge. In “Verwesung” (“The calling of the grave”) (Beckett ), we found a correct description of cocaine abuse including symptoms of overdosage and possibly lethal long-term effects. Also, the poisonous effects of plant-based alkaloids were described in great detail in “Verachtung” (“Journal 64”) by Olsen . Moreover, examples of correct hypnotic presentation were found. In “Koma” (“Police”) by Jo Nesbø , a stunning case with a benzodiazepine even includes the mention of adverse drug reactions the following day. Those carefully researched examples show that it is possible for an author to give a realistic picture. This way, the reader can learn facts about pharmacology and get a better understanding of a wide range of substances. As also dangers like death and ADRs are shown in the correct examples, it is unlikely that persons would imitate those. Overall, authors from former centuries wrote more plausible books. This surprised us a lot as careful research was way more difficult in the past centuries. The authors had to consult libraries or professionals which is much more time-consuming than using the internet or artificial intelligence as it is possible for today’s content creators. Why mistakes like the misrepresentation of hypnotics then commonly occur in the modern books has to be part of further research. Maybe also professionals have common misconceptions about particular substances. This would have a negative impact on public health and should be investigated in another study. Although the modern authors did not perform as well as the old ones regarding plausibility, the most correct author by mere numbers was Simon Beckett, a modern author. He often gave detailed information, for example about medical diamorphine use in the UK (Beckett ) or cocaine abuse (Beckett ). The mistakes we found in his books also fall into the categories widely presented incorrectly. In his novel “Die Verlorenen” (“The Lost”) (Beckett ), children get diazepam to numb them for a short time. As diazepam is a long-acting benzodiazepine, this is questionable. Additionally, the use of benzodiazepines in children has always the risk of paradoxical reactions which is not addressed in the book. However, from a pharmacological point of view, Becketts books go in a direction where the reader can learn something about substances and pharmacological principles without being miseducated. The second British author in the analysis (A.C. Doyle) also performed mostly correct leading to the conclusion that British authors were the most accurate in this analysis. The Scandinavians J. Nesbø and J.A. Olsen provided the most examples for this analysis which by mere number increases the chance of finding inaccuracies by a closer look. However, the trend is clear that in those books, the focus was not always on educating the viewer and giving most correct presentation. Overall, the main misconception in the modern books relate to widely known and widely used substances. Most of the readers will get in contact with those substances sooner or later. It is important to draw a realistic picture of those to increase the acceptance for pharmaceuticals in the general population and give them the best possible treatment. There has been research done before regarding pharmacological content in fiction. Two current papers discuss the pharmacological content in the most watched German crime TV-Series “Tatort.” Whereas Ellerbeck and Seifert mainly focused on quantitative aspects, Borchert and Seifert concentrated on a reality check. Both is a good basis for comparison with our analysis of the novels as it includes quantitative and qualitative aspects. The “Tatort” seems to have a greater value for the consumer regarding pharmacology than the novels. Although the mechanism of action was also lacking nearly as often as in our analysis, “Tatort” provides additional information more regularly. When it comes to the correctness of this information the TV series also yielded better results. The analysis taken for the TV was slightly different as it also included professional pharmaceutical use to treat symptoms and heal people. However, it seems that more careful research was done in preparation of the TV series than for most of the novels. This breaks with the cliché that books are always more informative and better for education than TV series. Authors might benefit from this, finding out on how research is performed for TV and adopt their own processes, so that more correct information reaches their audience. More suggestions for improvement and an overall assessment of the analyzed parameters can be found in Table . Of course, we could not read all existing crime literature. However, as our findings for the older novels coincide with the results of the Agatha Christie analysis by Gerald, it can reasonably be concluded that they are representative. Gerald as well described a substantial use of arsenic and strychnine in her stories (Gerald ). The metal arsenic even appeared in one quarter of those (Gerald ). Same coincidence with our findings could be found for way of application, with a huge number of cases including oral application rather than injectable ones (Gerald ). Qualitatively, Gerald outlined the detailed descriptions of drug use in her stories (Gerald ). This again matches our results showing that more additional information on drug use was described in the older novels. In our selection, the variety of pharmacological content in crime novels is overall large. The reader gets in contact with multiple substances in many ways of application and presentation. The variety has increased over time showing that some authors like to reflect trends and progress pharmacology has made over the last decades. This especially comes true regarding drugs and hypnotics. Their rise in reality over the past decades is also shown by constant mention in the fictional world. Unfortunately, hypnotics and anesthetics are also the substances which got misrepresented most commonly. The same misconceptions appear repeatedly. When it comes to etiology and gender, the books did not draw a realistic picture. Accidental poisoning and suicide are massively underrepresented. This might switch readers focus from the serious threat of domestic poisoning. Especially older novels also suggested a safer usage of substances by women which does not correspond to reality. Regarding the education of the viewers, there is lots of space for improvement. The mechanism of action is rarely presented, and additional information is also missing quite regularly. The lack of plausible description is potentially dangerous as readers might get false ideas of substances and their action principle in general. Although authors of fictious books have artistic freedom, they should consider the impact they have when presenting drugs to the general public. Great examples provided in some novels and the much higher rate of correct cases in TV series show that this is possible. This could be the first step in the right direction to get better quality novels which educate the readers beyond pure entertainment. Below is the link to the electronic supplementary material. Supplementary file1 (DOCX 1721 KB) |
A cross-sectional study on oral health-care habits and oral-health-related quality-of-life in marginalized persons in Copenhagen | 7a6ac917-15be-434e-bb66-45020700e9e5 | 11302656 | Dental[mh] | Oral health is an integral part of general health and is highly related to social functioning and quality-of-life . Poor oral health thus can have a negative impact on a person’s life. In Denmark, poor oral health has become less frequent during the last decades , but the distribution of the phenomenon is not equal in the population. The social inequality in oral health is thus persisting, and is higher than in many other European countries . The general population has few problems with their teeth and mouth, whereas there are reports of high frequency of poor oral health in socially marginalized persons . Marginalized persons have many both social and health issues including unemployment, mental health issues, and shorter life expectancy. They live on the edge of society battling with among other things addictions and homelessness. Unfortunately, this population uses the oral health-care system to a lower degree than the general population . This is what is referred to as the ‘inverse care law’ and makes the problem even greater. In addition, it has been described how this group, due to their poor oral health, might be stigmatized and excluded from the health-and social systems in society including the labor market . For this reason, efforts have been implemented to improve oral health in the marginalized group. So far, the experiences are not great, with the main challenges being poor oral hygiene and poor use of the dental care system. In Denmark, it has thus been a priority to incorporate these citizens into the dental care system in order to treat them and initiate preventive measures. Unfortunately, the initiatives to incorporate them into the system thus far have failed . An important challenge is the competing health and social issues found in this group , which often results in low prioritization of oral health. If we are to have success in including marginalized persons in the dental care system, it is crucial to know what types of oral problems they face, how it affects them, and what their oral health-care habits are. In this regard, oral-health-related quality-of-life (OHRQoL) seems as a highly relevant parameter to investigate, as it can indicate what challenges the population encounters, and how much the problems impact their lives. Some studies have investigated OHRQoL and oral health-care habits in marginalized populations [ , , ], but there is still much we do not know about this vulnerable group. One of the reasons for the lack of knowledge is the difficulties in including the group in epidemiological studies . We therefore conducted a study with the aim to describe the OHRQoL and oral health-care habits in the most marginalized persons in Copenhagen. The knowledge from this study will be highly relevant when preparing for inclusion of this group in the dental care system or creating other initiatives to improve oral health in marginalized populations, such as prevention programs and actual dental care.
Participants and setting Until 2020, three dental clinics offered free dental services for the most marginalized persons in Copenhagen. The most marginalized persons are people living in the street or in temporary housing who only with great difficulty can use the health-care system including dental care. One of these clinics was part of a more general health-care offer at the Sundholm health-care center in the Southern part of Copenhagen. The clinic had easy access to the target group and a wish to measure OHRQoL in their patients, which made it a good study site. The clinic was in use from 2018–2020 and was staffed with a single dental hygienist, who made clinical examinations including diagnostics of oral diseases and performed preventive dental care. If the dental hygienist diagnosed oral diseases with a need for treatment, the patient was referred to one of the two other clinics offering free dental care for marginalized persons, as they were staffed with dentists. In the period, 212 patients had contact to the clinic and as part of the initial recordings, all patients were asked to fill in a questionnaire on their oral health-care habits and OHRQoL and were potential participants in the study. There were no other inclusion and exclusion criteria applied to be included and the sample was thus based on convenience. The patients willingly participated but did not sign an informed consent. They were pseudo-anonymized, and the data were handled without the researchers knowing the identity of the patient. The project is approved by the Danish Data Protection Agency (514-0658/21-3000) and the local ethical committee at the Faculty of Health, University of Copenhagen (504-0302/22-5000). Methods In this cross-sectional study, oral health-care habits were investigated by asking the participants about their use of the dental care system and their daily oral hygiene. Use of the dental care system was evaluated by having the participant answer when they last had contact with the system (less than 6 months, 6–12 months, more than 1 year – but less than 2, 2–5 years, more than 5 years). For analytical purposes, the following categories were used: contact within 2 years, contact within 2–5 years, and no contact for more than 5 years. The reason for their last visit was also registered (consultation, pain or other oral-related problem, planned treatment, regular check-up, other). The following categories were used for analytical purposes: consultation/regular check-ups, treatment, other reason. The oral hygiene was evaluated by having the participants answer how often they brushed their teeth (never, once in a while – not every week, several times a week – not every day, once a day, two or more times a day). For analytical purposes, the following categories were used: never, once in a while/not every day, daily brushing. If they used toothpaste when brushing was also registered (yes, once in a while, no). The questions on habits were developed by the dental hygienist in the clinic and were not validated before use. The OHRQoL was measured with the 14-item oral-health-impact profile (OHIP-14), which consists of 14 questions related to problems in the oral region . The participants answered how often each problem had occurred during the past month on a scale with six choices and correspondent scores: very often (4), fairly often (3), occasionally (2), hardly ever (1), never (0) or don’t know . To calculate an overall OHIP-14 score for each participant, the scores from the 14 answers are added, thereby giving a score between 0 and 56. A higher score thus indicates a worse quality-of-life. The OHIP-14 score was further dichotomized using the mean OHIP-14 score. OHIP-14 items with score 3 and 4 were considered as experienced problems . The frequency of problems was calculated and reported in percentage of the population having the problems. Besides the oral health-care habits and OHRQoL, the participant’s gender and age were registered. Due to the relatively low number of participants, age was divided into two categories based on the mean age. It was also registered if they smoked (yes/no), if they currently needed general health-care services in the clinic (yes/no), and if they were referred to a dental clinic for treatment (yes/no). Their living condition was registered according to the European Typology of Homelessness (ETHOS) classification and the following categories were used: homeless, temporary housing, housing offer for addicts or mentally ill, own housing. Analyses Analyses were performed using the Statistical Package for the Social Science (SPSS) version 28 and the significance level was 0.05. Descriptive analyses were used to describe the oral health-care habits and quality-of-life in the population. The frequency of problems was illustrated with bar plots. The OHIP-14 score was normally distributed according to the test of skewness and kurtosis and the Kolmogorov-Smirnov test. Bivariate analyses between the OHIP-14 score and the categorical variables for age, gender, living condition, referral, contact to the dentist, and tooth brushing habits were performed using t-tests and ANOVA with post hoc analysis. The difference in frequency of problems between participants referred to dental treatment and participants not referred to treatment was specifically tested, as this gives valuable knowledge on what dentists can expect when receiving such patients in their clinic. Logistic regression analysis was performed with the categorical OHIP-14 variable as an outcome and the variables used in the bivariate analyses as explanatory.
Until 2020, three dental clinics offered free dental services for the most marginalized persons in Copenhagen. The most marginalized persons are people living in the street or in temporary housing who only with great difficulty can use the health-care system including dental care. One of these clinics was part of a more general health-care offer at the Sundholm health-care center in the Southern part of Copenhagen. The clinic had easy access to the target group and a wish to measure OHRQoL in their patients, which made it a good study site. The clinic was in use from 2018–2020 and was staffed with a single dental hygienist, who made clinical examinations including diagnostics of oral diseases and performed preventive dental care. If the dental hygienist diagnosed oral diseases with a need for treatment, the patient was referred to one of the two other clinics offering free dental care for marginalized persons, as they were staffed with dentists. In the period, 212 patients had contact to the clinic and as part of the initial recordings, all patients were asked to fill in a questionnaire on their oral health-care habits and OHRQoL and were potential participants in the study. There were no other inclusion and exclusion criteria applied to be included and the sample was thus based on convenience. The patients willingly participated but did not sign an informed consent. They were pseudo-anonymized, and the data were handled without the researchers knowing the identity of the patient. The project is approved by the Danish Data Protection Agency (514-0658/21-3000) and the local ethical committee at the Faculty of Health, University of Copenhagen (504-0302/22-5000).
In this cross-sectional study, oral health-care habits were investigated by asking the participants about their use of the dental care system and their daily oral hygiene. Use of the dental care system was evaluated by having the participant answer when they last had contact with the system (less than 6 months, 6–12 months, more than 1 year – but less than 2, 2–5 years, more than 5 years). For analytical purposes, the following categories were used: contact within 2 years, contact within 2–5 years, and no contact for more than 5 years. The reason for their last visit was also registered (consultation, pain or other oral-related problem, planned treatment, regular check-up, other). The following categories were used for analytical purposes: consultation/regular check-ups, treatment, other reason. The oral hygiene was evaluated by having the participants answer how often they brushed their teeth (never, once in a while – not every week, several times a week – not every day, once a day, two or more times a day). For analytical purposes, the following categories were used: never, once in a while/not every day, daily brushing. If they used toothpaste when brushing was also registered (yes, once in a while, no). The questions on habits were developed by the dental hygienist in the clinic and were not validated before use. The OHRQoL was measured with the 14-item oral-health-impact profile (OHIP-14), which consists of 14 questions related to problems in the oral region . The participants answered how often each problem had occurred during the past month on a scale with six choices and correspondent scores: very often (4), fairly often (3), occasionally (2), hardly ever (1), never (0) or don’t know . To calculate an overall OHIP-14 score for each participant, the scores from the 14 answers are added, thereby giving a score between 0 and 56. A higher score thus indicates a worse quality-of-life. The OHIP-14 score was further dichotomized using the mean OHIP-14 score. OHIP-14 items with score 3 and 4 were considered as experienced problems . The frequency of problems was calculated and reported in percentage of the population having the problems. Besides the oral health-care habits and OHRQoL, the participant’s gender and age were registered. Due to the relatively low number of participants, age was divided into two categories based on the mean age. It was also registered if they smoked (yes/no), if they currently needed general health-care services in the clinic (yes/no), and if they were referred to a dental clinic for treatment (yes/no). Their living condition was registered according to the European Typology of Homelessness (ETHOS) classification and the following categories were used: homeless, temporary housing, housing offer for addicts or mentally ill, own housing.
Analyses were performed using the Statistical Package for the Social Science (SPSS) version 28 and the significance level was 0.05. Descriptive analyses were used to describe the oral health-care habits and quality-of-life in the population. The frequency of problems was illustrated with bar plots. The OHIP-14 score was normally distributed according to the test of skewness and kurtosis and the Kolmogorov-Smirnov test. Bivariate analyses between the OHIP-14 score and the categorical variables for age, gender, living condition, referral, contact to the dentist, and tooth brushing habits were performed using t-tests and ANOVA with post hoc analysis. The difference in frequency of problems between participants referred to dental treatment and participants not referred to treatment was specifically tested, as this gives valuable knowledge on what dentists can expect when receiving such patients in their clinic. Logistic regression analysis was performed with the categorical OHIP-14 variable as an outcome and the variables used in the bivariate analyses as explanatory.
All of the 212 citizens had age and gender registered and almost all had living conditions, smoking, the need of health-care, and referral status registered ( ). Oral health-care habits and OHRQoL were reported in 186 (88%) and 182 (86%) respectively. Of the participants reporting OHRQoL, none had missing values in any of the OHIP-14 items. The mean age of the participants was 44.40 (SD 12.36) and the distribution of the categorical variables is shown in . Most participants were male, living in temporary housings, were smokers, and did not need general health-care. The participants most often were referred to dental treatment, had not seen a dentist in more than two years, had treatment as their last contact with a dentist, and brushed their teeth frequently with toothpaste. Drop-out analyses between participants filling in and not filling in the OHIP-14 showed no statistical differences in the distribution in any of the explanatory variables. The mean OHIP-14 score in the total population was 24.9 (SD: 13.6). The bivariate analyses showed that most of the groups did not differ significantly in the mean OHIP-14 score ( ). Needing general health-care and being referred to dental treatment was, however, associated with significantly higher OHIP-14 scores compared to not needing general health-care and not being referred to dental treatment. The logistic regression analysis showed that participants needing general health-care had an odds ratio of 2.4 (CI 1.1–4.7) for being in the high OHIP-14 score group compared to participants not needing general health-care ( ). None of the other odds ratios were significant. In the study population, it was found that 73.3% had at least one problem. shows the frequency of experienced problems in the study population for each item. It is seen that pain, chewing difficulties, being self-conscious, tense and embarrassed is the most frequent problems alongside impact on life in general. When comparing participants who were referred and not referred to dental treatment, it is seen that participants who were referred to treatment in most items more frequently had problems ( ). This was especially pronounced for chewing difficulties ( p = 0.04), being self-conscious ( p = 0.29), and being embarrassed ( p = 0.07).
This study investigated the OHRQoL and oral health-care habits in a marginalized population in Copenhagen. The main finding is poor OHRQoL in the group with the most frequent problems being pain, chewing difficulties and aesthetic issues. The participants had low, treatment-oriented use of the dental care system and a high frequency of tooth brushing. Furthermore, participants were often referred for dental treatment. Referral for dental treatment and needing general health-care were associated with poorer OHRQoL. The poor OHRQoL in the participants is not surprising and similar levels of OHIP-14 scores have been reported in other studies [ , , ]. This does, however, not make the finding irrelevant. The more evidence for the oral-related problems in vulnerable people we have and the more knowledge of the reasons for this, the more realistic it is to change the situation and achieve more equality in oral health. Other studies investigating the experienced problems using OHIP-14 in marginalized people have reported the same problems as being the most frequent as the ones in this study [ , , ]. This indicates that oral pain, having trouble eating your food, and aesthetic issues regarding your teeth affects the life in this group to a large degree. From our study, it is noteworthy that the participants that were referred for dental treatment, in general, had more problems related specifically to chewing difficulties and aesthetic problems. This is important knowledge for the clinicians they are referred to. Luckily, it has been found that oral treatment with relatively simple measures can increase marginalized people’s OHRQoL significantly . The association between OHRQoL and the explanatory variables used was very limited. This implies either no association between the variables or to small power to find significant results, which both could be the case in our study. The explanatory variables in our study are relevant, but other relevant variables could have been included. It is especially a limitation that the clinical oral status of the participants was not included since it has been found that high DMFT and periodontal problems can be associated with poor OHRQoL in homeless people . Also, other socioeconomic variables such as ethnicity and length of stay in Denmark could have been relevant to include. Further, even though the OHIP-14 questionnaire is a validated measure, the questions on oral-health habits were not and could have been more in line with international standards, to better compare to other studies. The power in our study is also limited due to the small population size, at least in some of the subgroups. The non-significant findings are, however, not useless. It is interesting that no matter your living condition, gender, age and oral health-care habits, being marginalized is associated with poor OHRQoL. This implies that the target group in general has great oral problems, and it can be difficult to predict which citizens have oral problems based on their oral heal-care habits. This is important knowledge for people working with marginalized persons. The association between needing general health-care and poor OHRQoL indicates that a poor general health status also is reflected in oral health. It has been described how this group has a broad spectrum of health and social issues , which naturally affect their lives. Seen as the view on life also influences the OHRQoL , it is thus not surprising that participants with general health problems report worse OHRQoL. The oral health-care habits investigated in our study is relevant, even though they could have been supplemented with data on their diet. It was not surprising that few participants had contact with the dental care system within the last two years and that the contact most often was related to treatment and not prevention. Other studies have also shown a limited use of the dental care system and several barriers to this in the most marginalized people . Even though other studies also have reported frequent tooth brushing in marginalized groups , it was rather surprising that the group reported frequent tooth brushing and use of toothpaste. The reason for the high frequency of tooth brushing might be true, but it might also reflect the societal expectation that you should report that you brush your teeth; otherwise, there is a risk of being stigmatized. An important aspect to discuss is the representativeness of our results. Because the participants found their way to the health clinic, they might be considered some of the more resourceful marginalized people, which would imply better oral health than the entire target population. On the other hand, an overestimation of problems might be the case as the recruitment was done in a dental care clinic and the participants could have visited the clinic due to oral problems. Further, it is important to note that the setting is rather local, which could question the generalizability of our results. It seems, however, from other studies in other settings, that many of the same issues and challenges are found in marginalized people. We hope that the findings from our study will help to put focus on the troubles of marginalized persons including their challenges in regard to oral health. Quality-of-life was highly affected and improvement in oral health is thus very much needed in the population. Given our results are valid, it seems that even though improvement in daily oral health-care is desirable, increasing the use of the dental care system and receiving oral rehabilitation and preventive measures is an obvious place to start. In this regard, it is relevant that a newly published study has found that an oral health motivation intervention in marginalized people not only led to an increase in the use of the dental care system but also had an effect on the proximity to the labor market . To improve oral health-care habits in marginalized people, it has been suggested to improve the awareness and knowledge in the population and implement supportive systems focusing on holistic and flexible care, outreach, interdisciplinary teams, and effective communication .
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Discovery of Aptamers and the Acceleration of the Development of Targeting Research in Ophthalmology | dc974a77-bd00-47da-92a3-6c1b0aba196d | 10404440 | Ophthalmology[mh] | Ophthalmology is an important clinical specialty that focuses on the physiological and pathological processes of the eye, which may become diseased as a result of internal and external factors. Several approaches have been used to increase the understanding of eye disease and provide effective therapeutic strategies. In recent years, as the development of targeting research in ophthalmology, several proteins have been discovered to participate and play key roles in the disease processes. By enhancing the function of proteins such as vascular endothelial growth factor (VEGF), the course of eye disorders may be modified; for example Using targeting to discover the pathogenesis of eye disorders is another research hotspot; it facilitates a better understanding of the mechanism of disease and contributes to the development of new treatment strategies. Therefore, aptamers were developed to be used for targeting research and edited for various deformations and combinations with other elements. Aptamers have been widely used for their ability to bind to different targets and their functions as chemical antibodies. Since their discovery in 1990, aptamers have also been used in ophthalmology to investigate disease mechanisms and for diagnosis and therapy. The binding of aptamers to various targets has been demonstrated and applied in disease research. In the field of ophthalmology, aptamers are mainly used for targeting therapy. Various aptamers have been discovered and applied to nanomedicine. Therefore, a review of the current research status of aptamers in ophthalmology has become necessary. In the present review, the current research developments of aptamers and their characteristics for targeting in eye disease are introduced. The application of aptamers, encompassing their development, targeting, and mechanism of action in ophthalmology, over the past 10 years has been discussed. Aptamers are short single-stranded ribonucleotides or deoxyribonucleotides. The first aptamer was composed of ribonucleotides, and deoxyribonucleotides were subsequently added. According to McKeague, approximately 68.8% of aptamers comprised ribonucleotides from 1990 to 2007, after which the proportion dropped to 29.5%. Aptamers have a high affinity toward their target and their equilibrium dissociation constants may reach nanomolar levels with the Kd value of aptamers mainly ranging from 1–100nM; several factors such as the template length and selection condition affect this constant. Aptamers recognize various types of targets and undergo various modifications that facilitate connections between aptamers and other carriers, giving aptamers broader biosensor applications than antibodies. These characteristics make aptamers popular for diagnostic innovation and drug development; for example, aptamer-based biosensors have been used in the diagnosis of diabetes, and aptamer-siRNA has been used for cancer therapy. , Other characteristics such as cellular uptake, stability, and low cost are advantages for therapeutic application. However, some characteristics limit the application of aptamers, such as their size determining the high rapid clearance rate for the weights of aptamers lower than the renal filtration threshold, and their single-strand nucleic acid structure being easily degenerated by nuclease. To overcome these limitations, aptamers have been modified by the chemical group or coupled drug carrier. For example, Judith found that aptamers conjugating with polyethylene glycol have an extended circulatory half-life and a reduced rate of urinary elimination. When methyl was added to KH1C12.O2, its stability was extended to 24h while its affinity was not affected. Similarly, hydrophobic F bases improved nuclease resistance ability, and aptamers coupled with F and paclitaxel (Sgc8-F-PTX) had significantly higher stability than Sgc8, perhaps because F bases could bind with albumin to form a stable complex. , Aptamer development was supported by SELEX. The initial single-stranded random oligonucleotides were used to incubate positive and negative targets, resulting in the amplification of a pool of single-stranded random oligonucleotides with high affinity. After several rounds of selection, aptamers with high binding ability were obtained and identified . In this process, the positive targets included proteins, cells, or tissues, and several variations of the SELEX approach were developed to suit different targets and improve processes. In addition, aptamers collected through SELEX always need to be further optimized and modified, and characteristics of aptamers such as affinity, specificity, stability, and internalization have been evaluated for later application. As the primary research structures, the eyeball, ocular adnexa, and orbital cavity include epithelial, bone, vascular, muscle, nervous, and other tissues. These may undergo biological processes common to a range of tissues in other parts of the body, and some pathological changes of ocular tissue are part of systemic disease. Therefore, the results of target-based research and therapy may have similarities for ophthalmology and other disciplines. For example, aptamer AS1411 target nucleolin is located in nucleoli and expressed by various tissue types, including vascular and cancer tissue and could be used for therapy for ophthalmopathy despite its intended use as an anticancer drug. , In contrast, the application of target-based research varies for ocular tissues, since the anterior and posterior segments of the eye differ in their anatomic structures and functions. Target-based research may, therefore, be applied to each segment, such as corneal and fundal staining techniques for diagnosis and administration techniques for therapy. , When aptamers are designed for examination or treatment applications, the target anatomical structure and location, as well as the characteristics of tissues should be considered. For example, anti-VEGF transmission across the cornea is desirable to avoid the discomfort of retrobulbar injections, and carbon dot modification of anti-VEGF aptamer facilitates corneal administration. The blood-aqueous and blood-retinal barriers , tightly restrict the passage of proteins between extra- and intraocular regions, presenting a challenge for the development of intraocular target-based drugs. Aptamer application in ophthalmology is based on the pathogenic mechanisms of eye disorders. The key molecules or cells in the pathogenesis of eye disorders may provide a target for aptamers, and a change in the expression or signal pathway in that target may have a diagnostic and therapeutic effect. To date, several types of aptamers have been developed to cure eye disorders, such as NX1838 for age-related macular degeneration (AMD), S58 for glaucoma, and AS1411 for corneal neovascularization. In addition to the development of aptamers for ophthalmology, those intended for non-ocular diseases have also been used in research on eye disease, as summarized in . Aptamers Applied in Bacterial Keratitis In addition to their use for targeting therapeutic binding sites in eye disease, aptamers have been used in the development of therapeutic drugs. Given the rapid clearance of eye drops from the ocular surface and the challenge of bioactive compounds reaching target tissues from the ocular surface, Jan Willem de Vries et al developed a DNA amphiphiles nanoparticle drug carrier system. This novel system was used to treat bacterial keratitis, and aptamers, in this case, targeted kanamycin or neomycin and were used as linkers between nanoparticles and antibiotics. Aptamers Applied in Glaucoma Glaucoma is a global optic neuropathy characterized by the degeneration of retinal ganglion cells. Aptamers are rarely used clinically for glaucoma therapy, and this application is still under development, but research in this field shows promise. As the most effective therapy for drug-refractory glaucoma, glaucoma filtration surgery, may not always be successful due to conjunctival fibrosis at the incision site promoted by TGF-β binding with TGF-β receptor II. Xie et al developed an aptamer S58 that targets TGF-β receptor II and inhibits the differentiation of tenon’s fibroblasts into myofibroblasts, effectively improving the outcome of glaucoma filtration surgery. In further research, S58 was combined with a chitosan thermo-sensitive gel or exosome, and the results showed that S58 reduced fibrosis in human fibroblasts as well as in a rat glaucoma filtration surgery model. , In addition, recovery after glaucoma infiltration glaucoma is complicated, with several bioprocesses such as angiogenesis, which may affect the outcome of surgery. The anti-VEGF aptamer pegaptanib was the first to be approved by the FDA for use as an inhibitor of angiogenesis, inflammation, or collagen deposition and has been shown to reduce angiogenesis after glaucoma filtration surgery to improve its outcomes. An anti-VEGF aptamer was also used to treat neovascular glaucoma, characterized by massive neovascularization on the iris surface and atrial angle. , Brain-derived neurotrophic factors are nerve growth factors with neuroprotective effects through Tropomyosin receptor kinase B and are significantly lower in aqueous humor, lacrimal fluid, and serum in glaucoma than in the normal eye and may be a biomarker for early glaucoma diagnosis. An aptamer targeting brain-derived neurotrophic factors has been developed to construct a biolayer interferometry-based 3D aptasensor in which aptamers have a detecting function and produce a signal for highly sensitive 3D matrix sensors, achieving low-abundance brain-derived neurotrophic factor detection for early diagnosis of glaucoma. Lipid DNA nanoparticles have been developed for drug delivery to overcome the disadvantages of low drug uptake on the ocular surface. In this system, the aptamer targets drugs and is a linker between drugs and DNA nanoparticles rather than disease-related targets. Schnichels et al used this system to enhance glaucoma drugs based on travoprost-target and brimonidine-target aptamers. , Aptamer Application in AMD The mechanism of AMD is complicated and could be classified into early and late stages, the latter characterized by neovascularization. During angiogenesis, cell factors such as VEGF, a mitogen for endothelial cells, enhance blood vessel formation. While there are several genes in the VEGF family, including VEGF-B, VEGF-C, and placental growth factor, VEGF-A is thought to play a major role in angiogenesis. Aptamers target VEGF develop rapidly since the first aptamer drug pegaptanib was proven to be effective in a clinical trial in 2004. Within the past decade, the applications of pegaptanib have been investigated through large-scale research and meta-analysis, and its therapeutic effects and those of other anti-VEGF drugs, such as monoclonal antibodies, have been tested. The results have shown that monoclonal antibodies such as bevacizumab and ranibizumab performed similarly based on best-corrected visual acuity, while indirect evidence showed that pegaptanib provided less improvement in visual acuity. , Dalvin et al found that anti-VEGF therapy has no association with stroke or death, and a retrospective cohort study revealed that an injection of an anti-VEGF such as pegaptanib did not increase the risk of developing glaucoma. Platelet-derived growth factor (PDGF) regulates angiogenesis and interacts with VEGF, , while PDGF inhibitors serve as a potential therapy for ocular neovascularization. Since aptamers ARC126 and ARC127 have been found to affect several retinal diseases through preclinical trials, anti-PDGF aptamers were developed for clinical usage. E10030 is an anti-platelet-derived growth factor aptamer that has been used in combination with ranibizumab for the treatment of AMD. Phase I and IIb clinical trials have been conducted, and the results have confirmed the efficacy of E10030 and permitted a phase III clinical trial. , Fibroblast growth factor 2 (FGF2) participates in angiogenesis and fibrosis by promoting the proliferation of vascular endothelial cells and stimulating the secretion of VEGF. The aptamer target FGF2 was first developed and used for therapy for the bone disease known as APT-F2P. Since the bioprocess of angiogenesis is similar for eye and bone disease, Yusaku et al used APT-F2P (RBM-007) for retinal disease therapy. Through an angiogenesis mouse model, APT-F2P was found to reduce new vessel formation and subretinal fibrosis, based on which a phase I/IIa clinical study was conducted to further investigate the effect of APT-F2P in AMD. Complement component 5 (C5) mediates inflammation and was thought to participate in the local chronic inflammatory process in AMD. While research on single nucleotide polymorphisms of C5 did not support an association between C5 and AMD, immunolocalization has provided evidence of the C5 complement activation in AMD. , The aptamer targeting C5 (avacincaptad pegol) has been used for AMD therapy, and the results have shown that avacincaptad pegol significantly reduces geographic atrophy in AMD. AS1411 is an aptamer targeting nucleolin with an anti-proliferation effect and acts as an anti-cancer drug, and a phase II clinical trial has shown that it has a therapeutic effect in metastatic renal cell carcinoma. AS1411 was introduced for AMD to suppress the function of endothelial cells and have a therapeutic effect on AMD. This aptamer has been found in animal models to reduce choroidal neovascularization and attenuate the infiltration of macrophages. In addition to fully developed aptamer therapeutics, some newly developed aptamers have a potential therapeutic effect on AMD. C promoter binding factor 1 is involved in Notch signaling and acts as an inhibitor of angiogenesis. VEGF promotes C promoter binding factor 1 proteasomal degradation and suppresses the activation of Notch signaling. An aptamer Apt-3 developed by Tezuka-Kagajo et al targeted C promoter binding factor 1 and active Notch signaling, thus inhibiting angiogenesis. Chandola et al developed an aptamer targeting CD44 (which is overexpressed in retinal pigment epithelium after oxidative stress) that could be transferred to lysosomes under oxidative stress. Since oxidative stress also occurs in AMD, CD44-aptamer could be used for lysosomal delivery of drugs to the retinal pigment epithelium and may have a therapeutic effect on AMD. In addition to therapy, aptamers have also been used to detect biomarkers in AMD, and various detection methods have been established to suit a range of clinical application scenarios. For example, an aptamer-based proteomic technology has been used to detect the biomarkers in the disease and show differential expression of vinculin and CD177 compared with controls. Lynch et al also found different protein expression assays in AMD using aptamer-based technology. An anti-VEGF aptamer has also been used to establish a target-induced dissociation assay using thermophoresis and microarrays, which can detect 0.1 nM of VEGF, , and another has been used to develop an electrochemical aptasensor based on metallo nanoenzyme particles to amplify the VEGF signal to facilitate its detection. Gao et al constructed a biolayer interferometry-based enzyme-linked aptamer sorbent assay based on anti-PDGF-BB, allowing rapid, high-throughput processing and real-time monitoring. The generation of these detection methods indicates the new direction of aptamer application in AMD and the importance of biomarker detection for early diagnosis and therapy of the disease. In addition, current studies have conjugated aptamers with nanoparticles or other elements, further demonstrating the developing trends of application in AMD. Aptamer Application in Diabetic Retinopathy (DR) The development of anti-VEGF aptamer drugs in angiogenesis has led to their use in DR and assessment of their therapeutic effect and safety in this disease. A Phase 3 study of pegaptanib assessed its safety in diabetic macular edema (a complication in DR) and showed that side effects of the drug were mainly mild or moderate and were related to the injection. A network meta-analysis comparing the effects of various anti-VEGF drugs such as aflibercept, ranibizumab, bevacizumab, and pegaptanib showed that anti-VEGF drugs improved vision, but long-term effects remained unclear. Approximately 40% of the patients with diabetic macular edema who underwent anti-VEGF therapy switched to laser surgery. With the development of anti-VEGF drugs, other kinds of aptamer drugs were neglected. Advanced glycation end products were associated with the early phase of DR through VEGF. An aptamer targeting advanced glycation end products was developed and used in DR and was found to prevent abnormalities in electroretinograms and have an inhibitory effect on the early development of DR. , Connective tissue growth factor serves as a biomarker for DR and may be used in early diagnosis. Shunxiang et al developed a BLI-based enzyme-linked aptamer sandwich assay based on connective tissue growth factor-targeting aptamer, which detected connective tissue growth factor at a level of 0.02 M, facilitating the early diagnosis of DR. Lipocalin 1 is another biomarker of DR that is related to its severity, and its detection in tears facilitates the early diagnosis of DR. Gao et al developed an aptamer targeting lipocalin 1 which folds into the B-DNA structure. After being assembled with G-rich DNA fragments and the Thioflavin T mediator, a lipocalin 1-targeting aptamer-based fluorescent aptasensor was developed, with potential application as a convenient detector of lipocalin 1 with high sensitivity and specificity. Aptamer Application in Ocular Tumors As the most common intraocular malignant tumor in adults, uveal melanoma has been well studied, and several biomarkers, such as TRPM4, BAP1, and RBM15B, have been associated with its mechanism and therapy. These biomarkers provide a therapeutic binding target and a potential target for aptamers. CD71 is overexpressed in malignancy, and antibodies such as A24 may compete for receptor binding sites with CD71, inducing CD71 degeneration in adult T-cell leukemia cells. An aptamer XQ-2d has been developed to target CD71 and is used in uveal melanoma therapy. XQ-2d was designed to conjugate with Monomethyl Auristatin E, and it inhibits the progression of uveal melanoma in mouse models. Retinoblastoma is a childhood eye cancer with an incidence of 1:15,000–1:20,000 globally. Aptamers targeting retinoblastoma have been developed over the past 10 years, but their application is still in the experimental stages. Epithelial cell adhesion molecules are cancer stem cell biomarkers since they are overexpressed in most solid cancers. An aptamer targeting epithelial cell adhesion molecules was developed and used in retinoblastoma therapy due to the high quantity of epithelial cell adhesion molecules in retinoblastoma cells. , The aptamer was developed with doxorubicin, which enhanced the targeting of drugs. Aptamers developed with siRNA silence the expression of epithelial cell adhesion molecules and have been used therapeutically. Since high mobility group A is elevated in both pancreatic cancer and retinoblastoma, the aptamer targeting high mobility group A developed via research on the former has been used in retinoblastoma. A nucleolin-targeting aptamer (AS1411) has also been used in retinoblastoma and found to reduce its proliferation. Based on the inhibitory effects of anti-nucleolin and high mobility group A on cancer, Kannan et al constructed two aptamer drugs: NCLap-HMGA2si and NCLAb-HMGAap. The nucleolin-targeting aptamer was developed with high-mobility group A siRNA, and the high-mobility group A targeting aptamer was developed with a nucleolin antibody, respectively, and both had therapeutic effects on retinoblastoma. Challenges and Opportunities There are several reports of cases of aptamer use in research related to eye disorders. However, there are several challenges. On the one hand, only a few types of aptamers are used in ophthalmology. Aptamers for several targets important for the pathogeneses of eye diseases have not been reported. Several original aptamers are not developed for eye disorders, and the specific characteristics of eye disease make it difficult for adopting aptamers in clinical practice. On the other hand, the current aptamer-related drugs used in clinical practice have challenges, including the long period of drug development and their characteristics such as degeneration and affinity. To overcome these challenges, more types of aptamer need to be developed while existing aptamers may be improved to facilitate their application to eye disorders. In addition to their use for targeting therapeutic binding sites in eye disease, aptamers have been used in the development of therapeutic drugs. Given the rapid clearance of eye drops from the ocular surface and the challenge of bioactive compounds reaching target tissues from the ocular surface, Jan Willem de Vries et al developed a DNA amphiphiles nanoparticle drug carrier system. This novel system was used to treat bacterial keratitis, and aptamers, in this case, targeted kanamycin or neomycin and were used as linkers between nanoparticles and antibiotics. Glaucoma is a global optic neuropathy characterized by the degeneration of retinal ganglion cells. Aptamers are rarely used clinically for glaucoma therapy, and this application is still under development, but research in this field shows promise. As the most effective therapy for drug-refractory glaucoma, glaucoma filtration surgery, may not always be successful due to conjunctival fibrosis at the incision site promoted by TGF-β binding with TGF-β receptor II. Xie et al developed an aptamer S58 that targets TGF-β receptor II and inhibits the differentiation of tenon’s fibroblasts into myofibroblasts, effectively improving the outcome of glaucoma filtration surgery. In further research, S58 was combined with a chitosan thermo-sensitive gel or exosome, and the results showed that S58 reduced fibrosis in human fibroblasts as well as in a rat glaucoma filtration surgery model. , In addition, recovery after glaucoma infiltration glaucoma is complicated, with several bioprocesses such as angiogenesis, which may affect the outcome of surgery. The anti-VEGF aptamer pegaptanib was the first to be approved by the FDA for use as an inhibitor of angiogenesis, inflammation, or collagen deposition and has been shown to reduce angiogenesis after glaucoma filtration surgery to improve its outcomes. An anti-VEGF aptamer was also used to treat neovascular glaucoma, characterized by massive neovascularization on the iris surface and atrial angle. , Brain-derived neurotrophic factors are nerve growth factors with neuroprotective effects through Tropomyosin receptor kinase B and are significantly lower in aqueous humor, lacrimal fluid, and serum in glaucoma than in the normal eye and may be a biomarker for early glaucoma diagnosis. An aptamer targeting brain-derived neurotrophic factors has been developed to construct a biolayer interferometry-based 3D aptasensor in which aptamers have a detecting function and produce a signal for highly sensitive 3D matrix sensors, achieving low-abundance brain-derived neurotrophic factor detection for early diagnosis of glaucoma. Lipid DNA nanoparticles have been developed for drug delivery to overcome the disadvantages of low drug uptake on the ocular surface. In this system, the aptamer targets drugs and is a linker between drugs and DNA nanoparticles rather than disease-related targets. Schnichels et al used this system to enhance glaucoma drugs based on travoprost-target and brimonidine-target aptamers. , The mechanism of AMD is complicated and could be classified into early and late stages, the latter characterized by neovascularization. During angiogenesis, cell factors such as VEGF, a mitogen for endothelial cells, enhance blood vessel formation. While there are several genes in the VEGF family, including VEGF-B, VEGF-C, and placental growth factor, VEGF-A is thought to play a major role in angiogenesis. Aptamers target VEGF develop rapidly since the first aptamer drug pegaptanib was proven to be effective in a clinical trial in 2004. Within the past decade, the applications of pegaptanib have been investigated through large-scale research and meta-analysis, and its therapeutic effects and those of other anti-VEGF drugs, such as monoclonal antibodies, have been tested. The results have shown that monoclonal antibodies such as bevacizumab and ranibizumab performed similarly based on best-corrected visual acuity, while indirect evidence showed that pegaptanib provided less improvement in visual acuity. , Dalvin et al found that anti-VEGF therapy has no association with stroke or death, and a retrospective cohort study revealed that an injection of an anti-VEGF such as pegaptanib did not increase the risk of developing glaucoma. Platelet-derived growth factor (PDGF) regulates angiogenesis and interacts with VEGF, , while PDGF inhibitors serve as a potential therapy for ocular neovascularization. Since aptamers ARC126 and ARC127 have been found to affect several retinal diseases through preclinical trials, anti-PDGF aptamers were developed for clinical usage. E10030 is an anti-platelet-derived growth factor aptamer that has been used in combination with ranibizumab for the treatment of AMD. Phase I and IIb clinical trials have been conducted, and the results have confirmed the efficacy of E10030 and permitted a phase III clinical trial. , Fibroblast growth factor 2 (FGF2) participates in angiogenesis and fibrosis by promoting the proliferation of vascular endothelial cells and stimulating the secretion of VEGF. The aptamer target FGF2 was first developed and used for therapy for the bone disease known as APT-F2P. Since the bioprocess of angiogenesis is similar for eye and bone disease, Yusaku et al used APT-F2P (RBM-007) for retinal disease therapy. Through an angiogenesis mouse model, APT-F2P was found to reduce new vessel formation and subretinal fibrosis, based on which a phase I/IIa clinical study was conducted to further investigate the effect of APT-F2P in AMD. Complement component 5 (C5) mediates inflammation and was thought to participate in the local chronic inflammatory process in AMD. While research on single nucleotide polymorphisms of C5 did not support an association between C5 and AMD, immunolocalization has provided evidence of the C5 complement activation in AMD. , The aptamer targeting C5 (avacincaptad pegol) has been used for AMD therapy, and the results have shown that avacincaptad pegol significantly reduces geographic atrophy in AMD. AS1411 is an aptamer targeting nucleolin with an anti-proliferation effect and acts as an anti-cancer drug, and a phase II clinical trial has shown that it has a therapeutic effect in metastatic renal cell carcinoma. AS1411 was introduced for AMD to suppress the function of endothelial cells and have a therapeutic effect on AMD. This aptamer has been found in animal models to reduce choroidal neovascularization and attenuate the infiltration of macrophages. In addition to fully developed aptamer therapeutics, some newly developed aptamers have a potential therapeutic effect on AMD. C promoter binding factor 1 is involved in Notch signaling and acts as an inhibitor of angiogenesis. VEGF promotes C promoter binding factor 1 proteasomal degradation and suppresses the activation of Notch signaling. An aptamer Apt-3 developed by Tezuka-Kagajo et al targeted C promoter binding factor 1 and active Notch signaling, thus inhibiting angiogenesis. Chandola et al developed an aptamer targeting CD44 (which is overexpressed in retinal pigment epithelium after oxidative stress) that could be transferred to lysosomes under oxidative stress. Since oxidative stress also occurs in AMD, CD44-aptamer could be used for lysosomal delivery of drugs to the retinal pigment epithelium and may have a therapeutic effect on AMD. In addition to therapy, aptamers have also been used to detect biomarkers in AMD, and various detection methods have been established to suit a range of clinical application scenarios. For example, an aptamer-based proteomic technology has been used to detect the biomarkers in the disease and show differential expression of vinculin and CD177 compared with controls. Lynch et al also found different protein expression assays in AMD using aptamer-based technology. An anti-VEGF aptamer has also been used to establish a target-induced dissociation assay using thermophoresis and microarrays, which can detect 0.1 nM of VEGF, , and another has been used to develop an electrochemical aptasensor based on metallo nanoenzyme particles to amplify the VEGF signal to facilitate its detection. Gao et al constructed a biolayer interferometry-based enzyme-linked aptamer sorbent assay based on anti-PDGF-BB, allowing rapid, high-throughput processing and real-time monitoring. The generation of these detection methods indicates the new direction of aptamer application in AMD and the importance of biomarker detection for early diagnosis and therapy of the disease. In addition, current studies have conjugated aptamers with nanoparticles or other elements, further demonstrating the developing trends of application in AMD. The development of anti-VEGF aptamer drugs in angiogenesis has led to their use in DR and assessment of their therapeutic effect and safety in this disease. A Phase 3 study of pegaptanib assessed its safety in diabetic macular edema (a complication in DR) and showed that side effects of the drug were mainly mild or moderate and were related to the injection. A network meta-analysis comparing the effects of various anti-VEGF drugs such as aflibercept, ranibizumab, bevacizumab, and pegaptanib showed that anti-VEGF drugs improved vision, but long-term effects remained unclear. Approximately 40% of the patients with diabetic macular edema who underwent anti-VEGF therapy switched to laser surgery. With the development of anti-VEGF drugs, other kinds of aptamer drugs were neglected. Advanced glycation end products were associated with the early phase of DR through VEGF. An aptamer targeting advanced glycation end products was developed and used in DR and was found to prevent abnormalities in electroretinograms and have an inhibitory effect on the early development of DR. , Connective tissue growth factor serves as a biomarker for DR and may be used in early diagnosis. Shunxiang et al developed a BLI-based enzyme-linked aptamer sandwich assay based on connective tissue growth factor-targeting aptamer, which detected connective tissue growth factor at a level of 0.02 M, facilitating the early diagnosis of DR. Lipocalin 1 is another biomarker of DR that is related to its severity, and its detection in tears facilitates the early diagnosis of DR. Gao et al developed an aptamer targeting lipocalin 1 which folds into the B-DNA structure. After being assembled with G-rich DNA fragments and the Thioflavin T mediator, a lipocalin 1-targeting aptamer-based fluorescent aptasensor was developed, with potential application as a convenient detector of lipocalin 1 with high sensitivity and specificity. As the most common intraocular malignant tumor in adults, uveal melanoma has been well studied, and several biomarkers, such as TRPM4, BAP1, and RBM15B, have been associated with its mechanism and therapy. These biomarkers provide a therapeutic binding target and a potential target for aptamers. CD71 is overexpressed in malignancy, and antibodies such as A24 may compete for receptor binding sites with CD71, inducing CD71 degeneration in adult T-cell leukemia cells. An aptamer XQ-2d has been developed to target CD71 and is used in uveal melanoma therapy. XQ-2d was designed to conjugate with Monomethyl Auristatin E, and it inhibits the progression of uveal melanoma in mouse models. Retinoblastoma is a childhood eye cancer with an incidence of 1:15,000–1:20,000 globally. Aptamers targeting retinoblastoma have been developed over the past 10 years, but their application is still in the experimental stages. Epithelial cell adhesion molecules are cancer stem cell biomarkers since they are overexpressed in most solid cancers. An aptamer targeting epithelial cell adhesion molecules was developed and used in retinoblastoma therapy due to the high quantity of epithelial cell adhesion molecules in retinoblastoma cells. , The aptamer was developed with doxorubicin, which enhanced the targeting of drugs. Aptamers developed with siRNA silence the expression of epithelial cell adhesion molecules and have been used therapeutically. Since high mobility group A is elevated in both pancreatic cancer and retinoblastoma, the aptamer targeting high mobility group A developed via research on the former has been used in retinoblastoma. A nucleolin-targeting aptamer (AS1411) has also been used in retinoblastoma and found to reduce its proliferation. Based on the inhibitory effects of anti-nucleolin and high mobility group A on cancer, Kannan et al constructed two aptamer drugs: NCLap-HMGA2si and NCLAb-HMGAap. The nucleolin-targeting aptamer was developed with high-mobility group A siRNA, and the high-mobility group A targeting aptamer was developed with a nucleolin antibody, respectively, and both had therapeutic effects on retinoblastoma. There are several reports of cases of aptamer use in research related to eye disorders. However, there are several challenges. On the one hand, only a few types of aptamers are used in ophthalmology. Aptamers for several targets important for the pathogeneses of eye diseases have not been reported. Several original aptamers are not developed for eye disorders, and the specific characteristics of eye disease make it difficult for adopting aptamers in clinical practice. On the other hand, the current aptamer-related drugs used in clinical practice have challenges, including the long period of drug development and their characteristics such as degeneration and affinity. To overcome these challenges, more types of aptamer need to be developed while existing aptamers may be improved to facilitate their application to eye disorders. In this study, the development of aptamers in ophthalmology was systematically reviewed. Several types of aptamers were used for targeting in drug development or improvement of drug performance for conditions such as glaucoma, AMD, DR, uveal melanoma, and retinoblastoma. Besides, aptamer was also used for the detection of the pathogenesis of eye disorders. The development of aptamers in ophthalmology may lead to further clinical applications in the future. |
Connections between postparotid terminal branches of the facial nerve: An immunohistochemistry study | c0e3f108-92b5-4c25-8719-447a014a7595 | 10098607 | Anatomy[mh] | INTRODUCTION Connections between the five terminal branches of the facial nerve (cranial nerve [cn] VII) have been described since the second half of the nineteenth century. They constitute a structure with multiple connected branches called the “subparotid plexus” (Hovelaque, ; Sappey, ) or “parastenon plexus” (Pons‐Tortella, ). Most authors have used this description and it has served as a basis for different proposed facial nerve classifications (Alomar, ; Bernstein & Nelson, ; Davis et al., ; Katz & Catalano, ; Kitamura & Yamazaki, ; Martínez Pascual et al., ; Myint et al., ; Tzafetta & Terzis, ). Connections between facial nerve branches have been found more frequently in the temporofacial division (TF). This has been attributed to its greater number of branches and its plexiform nature; the cervicofacial division (CF) supplies fewer branches, so connections between them are less common (Davis et al., ; Diamond et al., ; Lineaweaver et al., ; Martínez Pascual et al., ; Pons‐Tortella, ; Salame et al., ; Tansatit et al., ). It has been assumed that the fibers within these connections are motor because the five terminal branches of the facial nerve supply the mimic muscles, and the sensory innervation of the face depends on the trigeminal nerve (cn V) (Shoja et al., ). However, branches of cn VII also communicate with terminal ramifications of cn V in the face: the auriculotemporal (Kwak et al., ; Namking et al., ; Tansatit et al., ), supraorbital (Hwang et al., ; Li et al., ; Martínez Pascual et al., ), infraorbital (Hu et al., ; Hwang et al., ; Martínez Pascual et al., ; Tansatit et al., ), and mental (Hwang et al., ; Kim et al., ; Martínez Pascual et al., ; Touré et al., ) nerves, or the well‐known connection between the lingual nerve and the chorda tympani conveying the sense of taste (Dixon, ; Kwak et al., ; Hwang et al., ; Diamond et al., ; Shoja et al., ; Takezawa & Kageyama, ). Different types of fibers have been proposed to constitute the VII‐V connections: autonomic (Bowden & Mahran, ; Lewy et al., ; Tansatit et al., ), motor (Conley, ; Martin & Helsper, ; Odobescu et al., ) or sensory (Baumel, ; Cobo, Abbate, et al., ; Cobo, Solé‐Magdalena, et al., ; Odobescu et al., ; Yang et al., ). Thus, non‐motor fibers of VII‐V connections could continue to travel through the postparotid facial connections, so not all the fibers inside those connections are necessarily motor type. However, all these studies of the VII‐VII and V‐VII connections are based on anatomical dissection, which does not reveal the real functions of the component fibers. Therefore, the goal of our study is to determine, using specific immunohistochemical techniques, whether the connections between the terminal branches of the facial nerve are purely motor or whether they also carry other types of fiber.
MATERIALS AND METHODS The study was carried out on 13 hemiheads from embalmed adult Caucasian bodies (seven men, five women) from the Body Donations and Dissecting Rooms Centre of the Complutense University of Madrid. The average age of the cadavers was 83 years (range 75–90 years) at the time of death. The authors state that every effort was made to follow all local and international ethical guidelines and laws that pertain to the use of human cadaveric donors in anatomical research (Iwanaga et al., ). 2.1 Microdissection The extrapetrous course of 13 facial nerves (seven right, six left) was dissected from proximal to distal using microsurgical forceps and scissors with the help of surgical loupes (2.5x) (Optimedic®). The facial nerve was dissected and the postparotid terminal facial‐facial connections were identified, sectioned, and extracted for processing. 2.2 Immunohistochemistry Immunohistochemistry was performed in the Section of Anatomy from Department of Neuroscience at the University of Padova and the Department of Immunology, Ophthalmology and ENT at the Complutense University School of Medicine in Madrid. The connections were processed and embedded in paraffin blocks. Transverse sections (6 μm thickness) were cut with a microtome and mounted on slides, deparaffinized, and rehydrated before staining. Antigen retrieval was performed with sodium citrate (pH 6.1) for 20 min at 95°C. The sections were then washed in phosphate‐buffered saline (PBS) and placed in 1% hydrogen peroxide (H 2 O 2 ) in PBS for 10 min at room temperature, and then put into blocking buffer (0.2% bovine serum albumin in PBS) for 1 h at room temperature. After washing with PBS, they were incubated for 24 h at 4°C with the primary antibody anti‐choline acetyl transferase (ChAT) (Gene Tex® [N1N3]; 1:800). A negative control was performed for each different sample. The slides were washed with PBS and incubated with secondary antibody (goat anti‐rabbit, Jackson Immunoreserch®; 1:300) in blocking buffer for 1 h at room temperature. After further washing, color was developed with DAKO chromogen for 30 s. The samples were washed with distilled water and finally counterstained with hematoxylin, dehydrated and mounted. 2.3 Images analysis The immunohistochemical images were photographed under a microscope (Nikon E800M). Motor axons (ChAT positive) (Figure ) were counted in every sample using ImageJ Fiji 1.52p software (National Institutes of Health®) with 20× magnification. The connections were classified on the basis of number of motor fibers: strongly positive (>75% ChAT+ fibers), intermediately positive (50%–75% ChAT+ fibers) and weakly positive (< 50% ChAT+ fibers) (Figures ). 2.4 Statistical analysis Both descriptive and analytical statistics were used; percentages, means, ranges, and standard deviations were collected and compared. A one‐factor experimental design was used to detect significant differences in the average number of fibers with respect to side. The Kolmogorov–Smirnov Test was used to determine the normality of the underlying data distribution. A significance level alpha = 0.05 was used for all tests. SPSS software version 22 (IBM Corporation, Armonk) was used for the analyses.
Microdissection The extrapetrous course of 13 facial nerves (seven right, six left) was dissected from proximal to distal using microsurgical forceps and scissors with the help of surgical loupes (2.5x) (Optimedic®). The facial nerve was dissected and the postparotid terminal facial‐facial connections were identified, sectioned, and extracted for processing.
Immunohistochemistry Immunohistochemistry was performed in the Section of Anatomy from Department of Neuroscience at the University of Padova and the Department of Immunology, Ophthalmology and ENT at the Complutense University School of Medicine in Madrid. The connections were processed and embedded in paraffin blocks. Transverse sections (6 μm thickness) were cut with a microtome and mounted on slides, deparaffinized, and rehydrated before staining. Antigen retrieval was performed with sodium citrate (pH 6.1) for 20 min at 95°C. The sections were then washed in phosphate‐buffered saline (PBS) and placed in 1% hydrogen peroxide (H 2 O 2 ) in PBS for 10 min at room temperature, and then put into blocking buffer (0.2% bovine serum albumin in PBS) for 1 h at room temperature. After washing with PBS, they were incubated for 24 h at 4°C with the primary antibody anti‐choline acetyl transferase (ChAT) (Gene Tex® [N1N3]; 1:800). A negative control was performed for each different sample. The slides were washed with PBS and incubated with secondary antibody (goat anti‐rabbit, Jackson Immunoreserch®; 1:300) in blocking buffer for 1 h at room temperature. After further washing, color was developed with DAKO chromogen for 30 s. The samples were washed with distilled water and finally counterstained with hematoxylin, dehydrated and mounted.
Images analysis The immunohistochemical images were photographed under a microscope (Nikon E800M). Motor axons (ChAT positive) (Figure ) were counted in every sample using ImageJ Fiji 1.52p software (National Institutes of Health®) with 20× magnification. The connections were classified on the basis of number of motor fibers: strongly positive (>75% ChAT+ fibers), intermediately positive (50%–75% ChAT+ fibers) and weakly positive (< 50% ChAT+ fibers) (Figures ).
Statistical analysis Both descriptive and analytical statistics were used; percentages, means, ranges, and standard deviations were collected and compared. A one‐factor experimental design was used to detect significant differences in the average number of fibers with respect to side. The Kolmogorov–Smirnov Test was used to determine the normality of the underlying data distribution. A significance level alpha = 0.05 was used for all tests. SPSS software version 22 (IBM Corporation, Armonk) was used for the analyses.
RESULTS A total of 17 VII‐VII connections were analyzed. These connections were more frequent on the left side (10 connections) than on the right (seven). Nine of the connections were in male specimens while the other eight were in female cadavers. Tables and show the distribution of connections by side and sex respectively. The different types of connections are reported first, followed by a global overview. 3.1 Temporo‐temporal A temporo‐temporal (tt) connection was found in one case. It had 84 fibers, 76.2% (64/84) of them ChAT positive (ChAT+) and the other 23.8% (20/84) ChAT negative (ChAT−). Therefore, this connection was strongly positive (Figure ). 3.2 Temporo‐zygomatic Two temporo‐zygomatic (tz) connections were found. The number of fibers in them totalled 469, and the average was 234 (range 134–335); 46.1% (216/469) were ChAT+ while 53.9% (253/469) were ChAT−. Both tz connections were weakly positive (Figure ). 3.3 Zygomatic‐zygomatic There were two zygomatic‐zygomatic (zz) connections. The number of fibers in them totalled 685, and the average was 343 (259–426); 69.8% (478/685) were ChAT+ and 30.2% (207/685) were ChAT−. One connection was classed as strongly positive while the other was intermediately positive (Figure ). 3.4 Zygomatic‐buccal The zygomatic‐bucal (zb) connection was the most frequent, being found in six cases. Five of the buccal branches (b) arose from the TF division and one from the CF division. The total number of fibers was 1871 and the average was 312 (144–587); 53.9% (1009/1871) were ChAT+ and 46.1% (862/1871) were ChAT−. Five were intermediately positive and the other was weakly positive (Figure ). 3.5 Bucco‐buccal We found just one bucco‐buccal (bb) connection. Both b branches belonged to the TF division. It had 115 fibers, 20% (23/115) of them ChAT− and 80% (92/115) ChAT+, so it was a strongly positive connection (Figure ). 3.6 Bucco‐mandibular There was a bucco‐mandibular (bm) connection in three facial nerves. Two b branches came from the TF division and the other from the CF. The total number of fibers was 858 and the average was 286 (259–322), 68.1% (584/858) of them ChAT+ and 31.9% (274/858) ChAT−. Two connections were intermediately positive while the other was strongly positive (Figure ). 3.7 Mandibulo‐cervical There was a mandibulo‐cervical (mc) connection in two facial nerves. These had the highest number of fibers, averaging 399 (232–566) with a total number of 798, 32.7% (261/798) being ChAT− and 67.3% (537/798) ChAT+. One connection was strongly positive and the other intermediately positive (Figure ). 3.8 Global view The average number of fibers in the VII‐VII connections overall was 287 with a standard deviation of 145.46 (range 84–587), and the average proportion of positive fibers was 63% with a standard deviation of 15% (range 37.7%–91.5%). The average number of fibers on the left side was 319 with a standard deviation of 146.49 (range 134–587), and the average proportion of positive fibers was 58.9% with a standard deviation of 17.2% (range 37.6%–91.5%). In contrast, the average number of fibers in the right side was 241 with a standard deviation of 141.5 (range 84–430), and the average proportion of positive fibers was 68.9% with a standard deviation of 9.82% (range 55.6%–80%) (Figure ). The average number of fibers in males was 302 with a standard deviation of 164.81 (range 84–587) and the average proportion of positive fibers was 61.21% with a standard deviation of 14.03% (range 43.3%–83.2%). The average number of fibers in females was 270 with a standard deviation of 129.3 (range 115–566) and the average proportion of positive fibers was 64.9% with a standard deviation of 17.1% (range 37.6%–91.5%) (Figure ). The distributions of both ChAT+ and ChAT− fibers was normal (Kolmogorov–Smirnov Test p ‐values = 0.821 and 0.871, respectively) and the ANOVA table associated with the one factor experimental design corroborated the hypothesis of equity between the average numbers of positive fibers by side ( p ‐value = 0.429) and of negative fibers by side ( p ‐value = 0.273). Similar results were obtained for sex ( p ‐values = 0.926 for ChAT+ fibers and 0.483 for ChAT− fibers). Therefore, there were no statistically significant side or sex differences. Strongly positive ChAT+ connections were found in 29% of the nerves in the sample (five cases in 17), intermediately positive in 52.94% (nine cases in 17) and weakly positive in 17.65% (three cases in 17).
Temporo‐temporal A temporo‐temporal (tt) connection was found in one case. It had 84 fibers, 76.2% (64/84) of them ChAT positive (ChAT+) and the other 23.8% (20/84) ChAT negative (ChAT−). Therefore, this connection was strongly positive (Figure ).
Temporo‐zygomatic Two temporo‐zygomatic (tz) connections were found. The number of fibers in them totalled 469, and the average was 234 (range 134–335); 46.1% (216/469) were ChAT+ while 53.9% (253/469) were ChAT−. Both tz connections were weakly positive (Figure ).
Zygomatic‐zygomatic There were two zygomatic‐zygomatic (zz) connections. The number of fibers in them totalled 685, and the average was 343 (259–426); 69.8% (478/685) were ChAT+ and 30.2% (207/685) were ChAT−. One connection was classed as strongly positive while the other was intermediately positive (Figure ).
Zygomatic‐buccal The zygomatic‐bucal (zb) connection was the most frequent, being found in six cases. Five of the buccal branches (b) arose from the TF division and one from the CF division. The total number of fibers was 1871 and the average was 312 (144–587); 53.9% (1009/1871) were ChAT+ and 46.1% (862/1871) were ChAT−. Five were intermediately positive and the other was weakly positive (Figure ).
Bucco‐buccal We found just one bucco‐buccal (bb) connection. Both b branches belonged to the TF division. It had 115 fibers, 20% (23/115) of them ChAT− and 80% (92/115) ChAT+, so it was a strongly positive connection (Figure ).
Bucco‐mandibular There was a bucco‐mandibular (bm) connection in three facial nerves. Two b branches came from the TF division and the other from the CF. The total number of fibers was 858 and the average was 286 (259–322), 68.1% (584/858) of them ChAT+ and 31.9% (274/858) ChAT−. Two connections were intermediately positive while the other was strongly positive (Figure ).
Mandibulo‐cervical There was a mandibulo‐cervical (mc) connection in two facial nerves. These had the highest number of fibers, averaging 399 (232–566) with a total number of 798, 32.7% (261/798) being ChAT− and 67.3% (537/798) ChAT+. One connection was strongly positive and the other intermediately positive (Figure ).
Global view The average number of fibers in the VII‐VII connections overall was 287 with a standard deviation of 145.46 (range 84–587), and the average proportion of positive fibers was 63% with a standard deviation of 15% (range 37.7%–91.5%). The average number of fibers on the left side was 319 with a standard deviation of 146.49 (range 134–587), and the average proportion of positive fibers was 58.9% with a standard deviation of 17.2% (range 37.6%–91.5%). In contrast, the average number of fibers in the right side was 241 with a standard deviation of 141.5 (range 84–430), and the average proportion of positive fibers was 68.9% with a standard deviation of 9.82% (range 55.6%–80%) (Figure ). The average number of fibers in males was 302 with a standard deviation of 164.81 (range 84–587) and the average proportion of positive fibers was 61.21% with a standard deviation of 14.03% (range 43.3%–83.2%). The average number of fibers in females was 270 with a standard deviation of 129.3 (range 115–566) and the average proportion of positive fibers was 64.9% with a standard deviation of 17.1% (range 37.6%–91.5%) (Figure ). The distributions of both ChAT+ and ChAT− fibers was normal (Kolmogorov–Smirnov Test p ‐values = 0.821 and 0.871, respectively) and the ANOVA table associated with the one factor experimental design corroborated the hypothesis of equity between the average numbers of positive fibers by side ( p ‐value = 0.429) and of negative fibers by side ( p ‐value = 0.273). Similar results were obtained for sex ( p ‐values = 0.926 for ChAT+ fibers and 0.483 for ChAT− fibers). Therefore, there were no statistically significant side or sex differences. Strongly positive ChAT+ connections were found in 29% of the nerves in the sample (five cases in 17), intermediately positive in 52.94% (nine cases in 17) and weakly positive in 17.65% (three cases in 17).
DISCUSSION Previous studies of VII‐VII connections were based on anatomical dissection, so the real functions of those fibers could not be established. No other immunohistochemical studies of the types of fibers in the postparotid facial connections in humans were found in the literature studied, so our results cannot be compared with others. ChAT antibody has been proved specific/selective for motor axons in peripheral nerves (Castro et al., ; Courties et al., ; Kim et al., ; Lago et al., ; Lago & Navarro, ; Zhou et al., ), even after nerve injury (Castro et al., ; Kim et al., ; Lago et al., ; Lago & Navarro, ; Zhou et al., ). Therefore, it was chosen in this study to establish whether or not the VII‐VII connections are exclusively motor. The results showed that every connection had ChAT+ and ChAT– fibers, so they all contained both motor and non motor fibers. The connection with the highest percentage of ChAT− fibers was the temporo‐zygomatic (53.9%), while the bucco‐buccal had the highest percentage of ChAT+ fibers (80%). This could be because the buccal branches innervate the middle and lower facial thirds, where there are more muscles (Le Louarn, ) than in the upper third (Abramo, ; Abramo et al., ); bucco‐buccal connections could therefore carry a greater motor axonal load. Connections between the sensory terminal ramifications of cn V in the face and the terminal branches of the extrapetrous cn VII have already been described with the auriculotemporal (Kwak et al., ; Namking et al., ; Tansatit et al., ), supraorbital (Hwang et al., ; Li et al., ; Martínez Pascual et al., ), infraorbital (Hu et al., ; Hwang et al., ; Martínez Pascual et al., ; Tansatit et al., ), and mental (Hwang et al., ; Kim et al., ; Martínez Pascual et al., ; Touré et al., ) nerves. The nature of those connections has been discussed by many authors. Some believe they can be autonomic (Bowden & Mahran, ; Lewy et al., ; Tansatit et al., ), some motor (Conley, ; Martin & Helsper, ; Odobescu et al., ) and some sensory (Baumel, ; Cobo, Solé‐Magdalena, et al., ; Odobescu et al., ; Yang et al., ). Thus, assuming that these fibers continue to travel from the V‐VII connection through the rest of the extrapetrous facial nerve, it follows that the terminal branches of the facial nerve and their connections also have non‐motor fibers (Cattaneo & Pavesi, ; Cobo, Solé‐Magdalena, et al., ). Facial muscles typically lack proprioceptors, and facial proprioceptive impulses travel via branches of the trigeminal nerve to the central nervous system (Cattaneo & Pavesi, ; Cobo, Solé‐Magdalena, et al., ). Those propioceptive fibers from the trigeminal nerve in facial‐trigeminal connections could also be conveyed in VII‐VII connections and could innervate sensory structures in facial muscles that substitute for typical muscle spindles in facial proprioception (Cattaneo & Pavesi, ; Cobo, Abbate, et al., ). These findings could explain some of the feelings experienced by a patient with facial palsy after partial recovery, such as painful pressure at some points of the face (e.g. the zygomatic muscles, chin, forehead) (Valls‐Solé, ). Furthermore, muscle mass contraction or synkinesis, both observed in facial palsy patients, could also be related to this mixture of fibers traveling through the multiple connections in the face (Raslan et al., ; Valls‐Solé, ). Indeed, some authors explain synkinesis in terms of activation of latent nervous circuits pre‐existing in the healthy subject (Ton Van & Giot, ). We believe that these preexisting neural circuits can be conveyed by VII‐VII connections. Therefore, we can affirm that the nerve fibers traveling inside the postparotid terminal facial branch connections are not exclusively motor. The nature of the fibers that do not stain for ChAT still needs to be studied using antibodies specific/selective for different types of sensory and autonomic nerves.
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Controlling properties of human neural progenitor cells using 2D and 3D conductive polymer scaffolds | 0b69a4dc-65b4-4c89-b7c0-ed87bdb768b5 | 6925212 | Physiology[mh] | Neurological diseases and injuries are devastating, often resulting in high morbidity and long-term disability due to the limited regenerative ability of endogenous cells – . Stem cell therapy has emerged as a promising treatment approach , because of cells’ ability to proliferate and the potential to differentiate into one or more lineages under appropriate conditions – . Specifically, human induced pluripotent stem cells (hiPSCs) reprogrammed from somatic cells have been successfully differentiated into human neural progenitor cells (hNPCs) , . Transplantation of hNPCs improves functional neurological recovery through increased angiogenesis, dendritic branching and new axonal projections, production of neurotrophic factors, and modulation of the immune system – . However, the success of hNPC transplantation is currently limited by short-term survival of cells and their failure to integrate with the host tissue – . It is crucial to understand how hNPCs are influenced by the microenvironmental cues to sustain their viability and potentially enhance the therapeutic efficacy for nerve repair. The native stem cell niche presents a complex physiochemical microenvironment involving physical (i.e. mechanical stress), chemical (i.e. growth factors), and electrical signals that can dictate stem cell fate and behaviors. Particularly, electrical stimulation plays an important role in biological processes including wound healing, tissue repair, embryogenesis, and remodeling and growth of organisms – . In the clinical setting, electrical treatment has been applied to revive damaged tissues in the neuromuscular system to accelerate the healing of injured tissues such as nerve, bone, ligament, and articular cartilage – . The influence of electrical stimulation on stem cells has been widely reported on a variety of cell types and exposure conditions with regard to cell proliferation, differentiation, migration, and ion channel densities , , – . For instance, human mesenchymal stem cells showed increased proliferation and multi-lineage differentiation potential under long-term exposure to pulsed electromagnetic fields from weeks to a month , , , . Electrical stimulation led to longer neurites and greater branching of neural stem cells cultured under differentiation conditions in vitro , . Previous studies also demonstrated that the electrical signal not only guides the migration of neural stem cells in vivo but also leads to their differentiation ex vivo . Many studies focused on how the electrical field involved with cell mobilization and long-term differentiation in a voltage or time-dependent manner , – . However, there is limited understanding on the effects of the dimensionality of electrical stimulation on hNPCs. Conductive polymers have gained significant interests due to their ability to interface with neural tissues , – . These conductive biomaterials provide a unique platform to study the stem cells function and behaviors electrically. In this study, we have derived scaffolds made of the conductive polymer, polypyrrole (PPy), to understand the effect of changing the dimensionality of electrical stimulating platforms on hNPCs. Specifically, the 2D and 3D PPy scaffolds were electropolymerized and incorporated with hydrogel-immobilized hNPCs. We investigated the physical effect (2D vs 3D) as well as the effect of electrical stimulation on the gene profile of hNPCs. We showed that 2D and 3D electrically-stimulated hNPCs exhibited significant changes in the expression of neurotrophic factors under a brief electrical stimulation. The change in gene expression could be a result of differences in dimensionality of electrical stimulation and nutrient availability associated with the 2D and 3D scaffolds. Neurotrophic factors are known to be important in regulating cell survival, synaptic remodeling and nerve regeneration – . Therefore, the understanding of the interplay between biophysical cues and electrical signals on hNPCs holds great potential for developing promising therapeutic strategies for nerve regeneration in the future.
Differentiation of hiPSCs to hNPCs As described previously, the inhibition by SMAD inhibitors showed effective induction of hiPSCs into hNPCs in the early neuroepithelial progenitor (NEP) phase , . Following a 7-day induction procedure, a majority of the cells were organized into “rosettes” where the levels of PAX6, SOX1, SOX2, and Nestin were highly expressed at 97.8 ± 7.5%, 99.8 ± 0.7%, 96.8 ± 1.9%, and 97 ± 2.3%, respectively (Suppl. Fig. ). PAX6, a neuroectodermal marker , is expressed in the regions of the forebrain that give rise to the cortex and functions in the patterning of the brain . A prior study showed that the overexpression of PAX6 favors neural lineage commitment by differentiation into radial glia and subsequently neurons . SOX1 is also one of the earliest expressed neuroectodermal markers – , and its level of expression increases when NEPs differentiate towards NPCs , . It is a marker for proliferating NPCs with roles in enhancing and maintaining neuroectodermal commitment , . Additionally, SOX2 is highly expressed in proliferating NPCs to maintain neural progenitor identity and is downregulated upon further differentiation to neuronal and glial cells , . Nestin, an intermediate filament protein, expresses exclusively in uncommitted NPCs both in vitro and in vivo , . The downregulation of Nestin results in cell differentiation into neurons or glial cells , . Our immunofluorescent data showed a uniform expression of these markers, indicating the successful differentiation of hiPSCs into hNPCs (Suppl. Fig. ). 2D and 3D hNPCs scaffolds PPy is one of the most thoroughly investigated conductive polymers for biomedical applications due to its ease for fabrication, high electrical conductivity, and excellent biocompatibility , , , , . It is known that electrodeposited polymers that are doped with various agents exhibit altered physical, chemical, and electrical properties . Textured surfaces and porous structures could be produced by different electroplating conditions (e.g. lower temperatures) previously described for planar and tubular surfaces , , . In our study, NaDBS-doped PPy was electroplated at room temperature (Fig. ) which resulted in a smooth surface with a mechanically rigid structure for both 2D and 3D conductive PPy scaffolds (Fig. ). Further inspection showed that the 2D PPy films exhibited a smooth surface morphology (Fig. ). The inside of the 3D PPy tubes was smooth, whereas the outer surface of 3D PPy tubes was slightly uneven microscopically (Fig. ). The cross-sectional images showed crystalline structures that were mechanically rigid and insoluble (Fig. ). Modeling the fields produced by 2D and 3D PPy scaffolds The 2D and 3D conductive PPy scaffolds were connected with external wires that allowed for direct electrical stimulation (Fig. ). Using an electromagnetic field simulation based on the finite element method for modeling, we observed that sites where the external wires were attached showed a greater field strength. The average field strength for 2D and 3D conditions were 53.6 ± 9.5 V/m and 51.1 ± 2.5 V/m, respectively (Fig. ). The majority of area in both the 2D and 3D conductive PPy scaffolds exhibited longitudinally and horizontally uniform field strength (~40 V/m) despite the difference in the physical shape of stimulating platform (Fig. ). Cells were subsequently seeded in those regions with uniform electrical field for both conditions. The Maxwell equation used in this computation employs a homogeneous isotropic medium to model the air and gel, thus not capturing the dimensional variation of the gel’s electrical properties. Moreover, despite the similar electric field strengths, the direction and distribution of the electrical fields are different between the 2D films and 3D tubes. Cells encapsulated in 3D tubes could experience a more unidirectional stimulation signal, whereas cells seeding on 2D films encounter a less uniform stimulation signal due to stronger edge effects. Our stimulating platforms provide a comparable magnitude of electrical stimulation (40 V/m or 0.4 V/cm) to the previous literature. For instance, a carbon nanotube-based scaffold that delivered 0.15 V/cm for 2 ms duration at a frequency of 1 Hz for two weeks re-oriented human mesenchymal stem cells and promoted differentiation towards a cardiac genotype . A graphene-based conductive substrate enhanced the protein synthesis involved in the cell mobility in relation to the cytoskeleton under electrical exposure of 0.045-4.5 V/cm for 32 minutes . Human fibroblasts remained their orientation under one-hour electrical exposure of 2-4 V/cm, but they re-oriented themselves under a stronger electrical field exposure at 7 V/cm . Bone marrow-derived rat mesenchymal stem cells showed no signs of re-alignment with the same electrical setup. Viability of hNPCs on conductive scaffolds After hiPSCs were successfully differentiated into hNPCs, the alginate-immobilized hNPCs were either deposited onto the 2D PPy films or encapsulated into the 3D PPy tubes (Fig. ). The total number of hNPCs (~1 million) and the density of cells in the alginate were identical for both platforms. With 1 hr of electrical stimulation of hNPCs on the 2D and 3D PPy scaffolds with identical electrical field strength, we observed that electrical stimulation alone did not change the viability of the hNPCs based on the lactate dehydrogenase (LDH) and alamar blue assays. The LDH assay showed that the percentage of dead cells was 1.6 ± 0.5% and 3.1 ± 1.2% for hNPCs on 2D PPy films, and 19 ± 4.2% and 16 ± 2.8% for 3D PPy tubes under unstimulated and stimulated conditions, respectively (Fig. ). The alamar blue assay showed that the cell viability was 92 ± 1.1% and 90 ± 2.6% for unstimulated and stimulated hNPCs on 2D PPy films, and unstimulated and stimulated hNPCs in 3D PPy tubes were 56 ± 15% and 52 ± 15%, respectively (Fig. ). Although no significant difference in cell viability resulted from direct electrical stimulation using 2D and 3D scaffolds, we observed that cells on 2D PPy films were more viable compared to the 3D PPy tubes with LDH (unstimulated 2D and 3D cell death: 1.6 ± 0.5% vs 19 ± 4.2%; stimulated 2D and 3D cell death: 3.1 ± 1.2% vs 16 ± 2.8%) and alamar blue assays (unstimulated 2D vs 3D viability: 92 ± 1.1% vs 56 ± 15%; stimulated 2D vs 3D viability: 90 ± 2.6% vs 52 ± 15%). This is likely due to the impermeability of PPy (Fig. ), which only allowed the axial diffusion of nutrients and waste in the 3D tubes, resulting in a decreased viability compared to those cultured on 2D films. These results were further supported by the modeling of oxygen and glucose transport for hNPCs on the 2D and 3D PPy scaffolds. Without cells, oxygen and glucose concentrations for 2D films and 3D tubes reached equilibrium with the surrounding culture solution (Fig. left panels). However, once cells were placed, the 3D scaffolds showed significant nutrient depletion in the tube lumen, whereas the 2D films exhibited minimal changes in oxygen and glucose gradients (Fig. right panels). One limitation associated with modeling cell-incorporated scaffolds is that nutrient consumption was kept at a constant rate, which might not be representative to the real-time cell consumption as the cell survival and subsequent nutrient demand could change over the course of experiments. Another reason for the decreased viability readings from alamar blue assay could be the potential adsorption of reagents in the polymer. Further inspection with live/dead staining showed that hNPCs exhibit the same round cell morphology under unstimulated and stimulated conditions for both 2D and 3D scaffolds (Suppl. Fig. ). Expression changes of electrically stimulated hNPCs in 2D environments Previous studies demonstrate electrical stimulation causes preferential neurite growth, directional cell migration, and long-term differentiation changes , , , , , . Indeed electrical exposure is known to also play a role in induced expression of numerous transcription factors that have great implications in self-renewal and survival, synaptic remodeling, and nerve regeneration – , . We hypothesized that the dimensions of stimulating platforms with identical electrical field would impact these changes in hNPCs. Under the electrical stimulation on 2D PPy films, hNPCs showed an upregulation of gene expression in heparin binding EGF like growth factor (HBEGF), heat shock protein family member 1 (HSPB1), glial cell derived neurotrophic factor (GDNF), brain derived neurotrophic factor (BDNF), and neurotrophin 3 (NTF3) and a downregulation of gene expression in enolase 2 (ENO2). The gene expression of HBEGF, HSPB1, GDNF, BDNF, and NTF3 were 1.8-, 5.7-, 12-, 33-, and 3.2-fold higher in the electrically-stimulated hNPCs compared to the unstimulated group under the identical 2D environment, respectively (Fig. ). These altered genes play a role in multiple important pathways. Previously, the application of a low electrical field causes upregulation and asymmetric distribution of the epidermal growth factor receptor (EGFR) . Low levels of electrical stimulation caused neural cell precursor proliferation and expression of EGF in the brains of rats . Specifically, HBEGF was shown to stimulate the formation of multipotent glial-derived progenitors in the uninjured Zebrafish retina linking its role in the mediation of the EGFR/MAPK signal transduction pathway . The activation of heat shock proteins (HSP) has been hypothesized as a result of physiological stress induced by electrical stimulation . HSPB1 is a member of the HSP family with the ability to interact with components of the actin cytoskeleton and protect against cytoskeletal injury during stress . HSPB1 mutations result in the onset of motor neuropathy present with slowly progressive peroneal muscular atrophy, decreased compound muscle action potentials and sensory nerve action potentials based on electrophysiological evidence – . Neurotrophic factors including GDNF, BDNF, and NTF3 are important regulators in cell fate decisions, axon branching, dendrite pruning, and appropriate patterning of neuronal functions and innervation . They are crucial for the survival, development, and function in the nervous system – , . Changes in the expression levels and activities of neurotrophic factors have great implications in many neurodegenerative diseases including Parkinson disease, Alzheimer disease, and Huntington disease . Expression changes of electrically stimulated hNPCs in 3D environments Similarly, the electrically stimulated hNPCs in 3D PPy tubes showed an increase in gene expression of HBEGF, HSPB1, GDNF, BDNF, and NTF3 where they were 3.8-, 5.8-, 19-, 48-, 5.7-fold higher than unstimulated cells, respectively (Fig. ). Other studies have also demonstrated that electrical stimulation enhanced neurological recovery by modulating the secretion of neurotrophic factors , , – . For example, PPy coated poly(l-lactic acid-co-caprolactone) (PLCL) conduits showed upregulation of genes GDNF, BDNF, and NTF3 on dorsal root ganglia (DRG) cells under electrical stimulation of 100 mV/cm for 4h . Direct stimulation (50–1000 mV/mm) on rat Schwann cells through PPy and chitosan composite also demonstrated an increase in BDNF level in vitro . The hollow composite made of PPy and chitosan with electrical stimulation (3 V, 20 Hz, 1 hr) further promoted transected nerve regeneration and functional recovery in rats for 12 weeks . Our findings show that HBEGF, HSPB1, GDNF, BDNF, and NTF3 were upregulated as a direct result of electrical stimulation regardless the shape of the stimulating platform used. Given the importance of these factors for neurotrophic effects, electrical stimulation on hNPCs through our conductive 2D and 3D scaffolds could provide beneficial therapeutics to potentially treat neurological disorders. Interestingly, electrically-stimulated hNPCs on 2D PPy films showed that the expression of ENO2 was 0.64-fold lower than the unstimulated group, whereas no changes were observed for ENO2 in the hNPCs seeded in 3D PPy tubes under unstimulated and stimulated conditions (Fig. ). No changes in gene expression of VEGF-A were observed for all experimental groups (Fig. ). ENO2 is a hallmark of neuronal lineage related gene in neural stem cells (NSCs) , . VEGF-A is important for angiogenesis, cell proliferation, and plasticity , , . Our results were different from the previous studies that reported highly expressed ENO2 in neural stem cells (NSCs) after 1 week regardless the use of electrical stimulation (5 mV, 0.5 mA, 25 ms intermittent stimulation) on conducting ropes and increased VEGF-A expression of hNPCs on polypyrrole surface (2 V, 1 kHz, 1 h) . These discrepancies in findings could be due to differences in the experimental materials (e.g. cell source, conductive substrate, scaffold shape) and methods (e.g. stimulating parameters, culture conditions) used in the literature. Neural cell adhesion molecule (NCAM), expressed on the cell surface of various cell types like neurons and glial cells , was found to express at similar levels in all samples (Fig. ), suggesting a potential enhancement in cell-cell adhesion, cell proliferation and directional growth, and synaptic plasticity potential – . Expression changes of hNPCs in 2D and 3D environments We further investigated the physical effect of 2D and 3D environment on hNPCs alone. In the long-term (~ 2 weeks), hNCPs stemness varies as function of their surrounding hydrogel stiffness and degradability . In our study, the alginate-immobilized hNPCs that were seeded on the 2D surface showed significantly higher expression of ENO2 without electrical stimulation (Fig. ). Previous literature reported that ENO2 expression increases as a result of 3D culture and is a key glycolytic enzyme , . Our transport modeling indicated that different dimension of cell encapsulation (2D vs 3D) significantly impacts cell survival (Fig. ). Therefore, the physical microenvironment, in the short term, could directly affect the metabolic pathway of hNPCs, which would be important to consider when designing cell-seeded conductive scaffolds. Expression changes of electrically stimulated hNPCs in 2D and 3D environments More importantly, we examined whether the shape of the stimulating platform (2D vs. 3D) was more effective in promoting certain gene expressions in hNPCs during a short period of electrical stimulation. Shown previously, the long-term electrical modulation can effectively bias the differentiation of stem cells preferentially into a certain lineage (neuronal lineage) . Our findings showed that 3D electrically-stimulated hNPCs were more effective in enhancing neurotrophic factor expression namely GDNF and BDNF (Fig. ), whereas 2D electrically-stimulated cells increased gene expression of ENO2 (Fig. ). Interestingly, the 3D field alters GDNF and BDNF to a far greater degree than the 2D field. This finding illustrates that even under the identical field strength for a brief period of time, the shape of stimulating platforms has great implications in eliciting the therapeutic potential of hNPCs. Future work can be conducted to study the long-term effects of the dimensionality of electrical stimulation on changes in hNPCs gene expression and their implications in cell proliferation and differentiation. In this study, we demonstrated the feasibility of fabricating the conductive 2D and 3D PPy scaffolds as platforms to examine the potential dimensional effect of electrical stimulation on hNPCs. Specifically, the 2D and 3D PPy scaffolds with similar material morphologies were used to electrically stimulate hNPCs under identical field strength. Electrical stimulation applied through 2D and 3D conductive scaffolds shared upregulated expression of some common genes that play important roles in signaling self-renewal and survival, synaptic remodeling, and nerve regeneration despite differences in the physical shapes of the stimulating platform. The physical 2D and 3D culturing conditions alone also affected the NPC gene expression related to cell proliferation and metabolic pathways. Importantly, the 3D electrically-stimulated cells were more effective in promoting expression of neurotrophic factors and the 2D stimulated conditions showed increased gene expression that is important for cell-cell adhesion, neuronal differentiation, and metabolic maintenance. In addition to different stimulating platforms, the nutrient availability associated with 2D and 3D scaffolds was also likely to contribute changes in the expression of neurotrophic factors. Overall, our study demonstrated the significance in manipulating the physical culture conditions with brief electrical stimulation that resulted in profound effects reflected by the gene expression profile of hNPCs. Thus, the dimension of stimulating platforms used to apply electrical stimulation proved to be important for modulating expression changes of hNPCs depending on their metabolic states. This discovery can be important in implementing engineering strategies to manipulate the microenvironment to obtain desired therapeutic effects from stem cells.
As described previously, the inhibition by SMAD inhibitors showed effective induction of hiPSCs into hNPCs in the early neuroepithelial progenitor (NEP) phase , . Following a 7-day induction procedure, a majority of the cells were organized into “rosettes” where the levels of PAX6, SOX1, SOX2, and Nestin were highly expressed at 97.8 ± 7.5%, 99.8 ± 0.7%, 96.8 ± 1.9%, and 97 ± 2.3%, respectively (Suppl. Fig. ). PAX6, a neuroectodermal marker , is expressed in the regions of the forebrain that give rise to the cortex and functions in the patterning of the brain . A prior study showed that the overexpression of PAX6 favors neural lineage commitment by differentiation into radial glia and subsequently neurons . SOX1 is also one of the earliest expressed neuroectodermal markers – , and its level of expression increases when NEPs differentiate towards NPCs , . It is a marker for proliferating NPCs with roles in enhancing and maintaining neuroectodermal commitment , . Additionally, SOX2 is highly expressed in proliferating NPCs to maintain neural progenitor identity and is downregulated upon further differentiation to neuronal and glial cells , . Nestin, an intermediate filament protein, expresses exclusively in uncommitted NPCs both in vitro and in vivo , . The downregulation of Nestin results in cell differentiation into neurons or glial cells , . Our immunofluorescent data showed a uniform expression of these markers, indicating the successful differentiation of hiPSCs into hNPCs (Suppl. Fig. ).
PPy is one of the most thoroughly investigated conductive polymers for biomedical applications due to its ease for fabrication, high electrical conductivity, and excellent biocompatibility , , , , . It is known that electrodeposited polymers that are doped with various agents exhibit altered physical, chemical, and electrical properties . Textured surfaces and porous structures could be produced by different electroplating conditions (e.g. lower temperatures) previously described for planar and tubular surfaces , , . In our study, NaDBS-doped PPy was electroplated at room temperature (Fig. ) which resulted in a smooth surface with a mechanically rigid structure for both 2D and 3D conductive PPy scaffolds (Fig. ). Further inspection showed that the 2D PPy films exhibited a smooth surface morphology (Fig. ). The inside of the 3D PPy tubes was smooth, whereas the outer surface of 3D PPy tubes was slightly uneven microscopically (Fig. ). The cross-sectional images showed crystalline structures that were mechanically rigid and insoluble (Fig. ).
The 2D and 3D conductive PPy scaffolds were connected with external wires that allowed for direct electrical stimulation (Fig. ). Using an electromagnetic field simulation based on the finite element method for modeling, we observed that sites where the external wires were attached showed a greater field strength. The average field strength for 2D and 3D conditions were 53.6 ± 9.5 V/m and 51.1 ± 2.5 V/m, respectively (Fig. ). The majority of area in both the 2D and 3D conductive PPy scaffolds exhibited longitudinally and horizontally uniform field strength (~40 V/m) despite the difference in the physical shape of stimulating platform (Fig. ). Cells were subsequently seeded in those regions with uniform electrical field for both conditions. The Maxwell equation used in this computation employs a homogeneous isotropic medium to model the air and gel, thus not capturing the dimensional variation of the gel’s electrical properties. Moreover, despite the similar electric field strengths, the direction and distribution of the electrical fields are different between the 2D films and 3D tubes. Cells encapsulated in 3D tubes could experience a more unidirectional stimulation signal, whereas cells seeding on 2D films encounter a less uniform stimulation signal due to stronger edge effects. Our stimulating platforms provide a comparable magnitude of electrical stimulation (40 V/m or 0.4 V/cm) to the previous literature. For instance, a carbon nanotube-based scaffold that delivered 0.15 V/cm for 2 ms duration at a frequency of 1 Hz for two weeks re-oriented human mesenchymal stem cells and promoted differentiation towards a cardiac genotype . A graphene-based conductive substrate enhanced the protein synthesis involved in the cell mobility in relation to the cytoskeleton under electrical exposure of 0.045-4.5 V/cm for 32 minutes . Human fibroblasts remained their orientation under one-hour electrical exposure of 2-4 V/cm, but they re-oriented themselves under a stronger electrical field exposure at 7 V/cm . Bone marrow-derived rat mesenchymal stem cells showed no signs of re-alignment with the same electrical setup.
After hiPSCs were successfully differentiated into hNPCs, the alginate-immobilized hNPCs were either deposited onto the 2D PPy films or encapsulated into the 3D PPy tubes (Fig. ). The total number of hNPCs (~1 million) and the density of cells in the alginate were identical for both platforms. With 1 hr of electrical stimulation of hNPCs on the 2D and 3D PPy scaffolds with identical electrical field strength, we observed that electrical stimulation alone did not change the viability of the hNPCs based on the lactate dehydrogenase (LDH) and alamar blue assays. The LDH assay showed that the percentage of dead cells was 1.6 ± 0.5% and 3.1 ± 1.2% for hNPCs on 2D PPy films, and 19 ± 4.2% and 16 ± 2.8% for 3D PPy tubes under unstimulated and stimulated conditions, respectively (Fig. ). The alamar blue assay showed that the cell viability was 92 ± 1.1% and 90 ± 2.6% for unstimulated and stimulated hNPCs on 2D PPy films, and unstimulated and stimulated hNPCs in 3D PPy tubes were 56 ± 15% and 52 ± 15%, respectively (Fig. ). Although no significant difference in cell viability resulted from direct electrical stimulation using 2D and 3D scaffolds, we observed that cells on 2D PPy films were more viable compared to the 3D PPy tubes with LDH (unstimulated 2D and 3D cell death: 1.6 ± 0.5% vs 19 ± 4.2%; stimulated 2D and 3D cell death: 3.1 ± 1.2% vs 16 ± 2.8%) and alamar blue assays (unstimulated 2D vs 3D viability: 92 ± 1.1% vs 56 ± 15%; stimulated 2D vs 3D viability: 90 ± 2.6% vs 52 ± 15%). This is likely due to the impermeability of PPy (Fig. ), which only allowed the axial diffusion of nutrients and waste in the 3D tubes, resulting in a decreased viability compared to those cultured on 2D films. These results were further supported by the modeling of oxygen and glucose transport for hNPCs on the 2D and 3D PPy scaffolds. Without cells, oxygen and glucose concentrations for 2D films and 3D tubes reached equilibrium with the surrounding culture solution (Fig. left panels). However, once cells were placed, the 3D scaffolds showed significant nutrient depletion in the tube lumen, whereas the 2D films exhibited minimal changes in oxygen and glucose gradients (Fig. right panels). One limitation associated with modeling cell-incorporated scaffolds is that nutrient consumption was kept at a constant rate, which might not be representative to the real-time cell consumption as the cell survival and subsequent nutrient demand could change over the course of experiments. Another reason for the decreased viability readings from alamar blue assay could be the potential adsorption of reagents in the polymer. Further inspection with live/dead staining showed that hNPCs exhibit the same round cell morphology under unstimulated and stimulated conditions for both 2D and 3D scaffolds (Suppl. Fig. ).
Previous studies demonstrate electrical stimulation causes preferential neurite growth, directional cell migration, and long-term differentiation changes , , , , , . Indeed electrical exposure is known to also play a role in induced expression of numerous transcription factors that have great implications in self-renewal and survival, synaptic remodeling, and nerve regeneration – , . We hypothesized that the dimensions of stimulating platforms with identical electrical field would impact these changes in hNPCs. Under the electrical stimulation on 2D PPy films, hNPCs showed an upregulation of gene expression in heparin binding EGF like growth factor (HBEGF), heat shock protein family member 1 (HSPB1), glial cell derived neurotrophic factor (GDNF), brain derived neurotrophic factor (BDNF), and neurotrophin 3 (NTF3) and a downregulation of gene expression in enolase 2 (ENO2). The gene expression of HBEGF, HSPB1, GDNF, BDNF, and NTF3 were 1.8-, 5.7-, 12-, 33-, and 3.2-fold higher in the electrically-stimulated hNPCs compared to the unstimulated group under the identical 2D environment, respectively (Fig. ). These altered genes play a role in multiple important pathways. Previously, the application of a low electrical field causes upregulation and asymmetric distribution of the epidermal growth factor receptor (EGFR) . Low levels of electrical stimulation caused neural cell precursor proliferation and expression of EGF in the brains of rats . Specifically, HBEGF was shown to stimulate the formation of multipotent glial-derived progenitors in the uninjured Zebrafish retina linking its role in the mediation of the EGFR/MAPK signal transduction pathway . The activation of heat shock proteins (HSP) has been hypothesized as a result of physiological stress induced by electrical stimulation . HSPB1 is a member of the HSP family with the ability to interact with components of the actin cytoskeleton and protect against cytoskeletal injury during stress . HSPB1 mutations result in the onset of motor neuropathy present with slowly progressive peroneal muscular atrophy, decreased compound muscle action potentials and sensory nerve action potentials based on electrophysiological evidence – . Neurotrophic factors including GDNF, BDNF, and NTF3 are important regulators in cell fate decisions, axon branching, dendrite pruning, and appropriate patterning of neuronal functions and innervation . They are crucial for the survival, development, and function in the nervous system – , . Changes in the expression levels and activities of neurotrophic factors have great implications in many neurodegenerative diseases including Parkinson disease, Alzheimer disease, and Huntington disease .
Similarly, the electrically stimulated hNPCs in 3D PPy tubes showed an increase in gene expression of HBEGF, HSPB1, GDNF, BDNF, and NTF3 where they were 3.8-, 5.8-, 19-, 48-, 5.7-fold higher than unstimulated cells, respectively (Fig. ). Other studies have also demonstrated that electrical stimulation enhanced neurological recovery by modulating the secretion of neurotrophic factors , , – . For example, PPy coated poly(l-lactic acid-co-caprolactone) (PLCL) conduits showed upregulation of genes GDNF, BDNF, and NTF3 on dorsal root ganglia (DRG) cells under electrical stimulation of 100 mV/cm for 4h . Direct stimulation (50–1000 mV/mm) on rat Schwann cells through PPy and chitosan composite also demonstrated an increase in BDNF level in vitro . The hollow composite made of PPy and chitosan with electrical stimulation (3 V, 20 Hz, 1 hr) further promoted transected nerve regeneration and functional recovery in rats for 12 weeks . Our findings show that HBEGF, HSPB1, GDNF, BDNF, and NTF3 were upregulated as a direct result of electrical stimulation regardless the shape of the stimulating platform used. Given the importance of these factors for neurotrophic effects, electrical stimulation on hNPCs through our conductive 2D and 3D scaffolds could provide beneficial therapeutics to potentially treat neurological disorders. Interestingly, electrically-stimulated hNPCs on 2D PPy films showed that the expression of ENO2 was 0.64-fold lower than the unstimulated group, whereas no changes were observed for ENO2 in the hNPCs seeded in 3D PPy tubes under unstimulated and stimulated conditions (Fig. ). No changes in gene expression of VEGF-A were observed for all experimental groups (Fig. ). ENO2 is a hallmark of neuronal lineage related gene in neural stem cells (NSCs) , . VEGF-A is important for angiogenesis, cell proliferation, and plasticity , , . Our results were different from the previous studies that reported highly expressed ENO2 in neural stem cells (NSCs) after 1 week regardless the use of electrical stimulation (5 mV, 0.5 mA, 25 ms intermittent stimulation) on conducting ropes and increased VEGF-A expression of hNPCs on polypyrrole surface (2 V, 1 kHz, 1 h) . These discrepancies in findings could be due to differences in the experimental materials (e.g. cell source, conductive substrate, scaffold shape) and methods (e.g. stimulating parameters, culture conditions) used in the literature. Neural cell adhesion molecule (NCAM), expressed on the cell surface of various cell types like neurons and glial cells , was found to express at similar levels in all samples (Fig. ), suggesting a potential enhancement in cell-cell adhesion, cell proliferation and directional growth, and synaptic plasticity potential – .
We further investigated the physical effect of 2D and 3D environment on hNPCs alone. In the long-term (~ 2 weeks), hNCPs stemness varies as function of their surrounding hydrogel stiffness and degradability . In our study, the alginate-immobilized hNPCs that were seeded on the 2D surface showed significantly higher expression of ENO2 without electrical stimulation (Fig. ). Previous literature reported that ENO2 expression increases as a result of 3D culture and is a key glycolytic enzyme , . Our transport modeling indicated that different dimension of cell encapsulation (2D vs 3D) significantly impacts cell survival (Fig. ). Therefore, the physical microenvironment, in the short term, could directly affect the metabolic pathway of hNPCs, which would be important to consider when designing cell-seeded conductive scaffolds.
More importantly, we examined whether the shape of the stimulating platform (2D vs. 3D) was more effective in promoting certain gene expressions in hNPCs during a short period of electrical stimulation. Shown previously, the long-term electrical modulation can effectively bias the differentiation of stem cells preferentially into a certain lineage (neuronal lineage) . Our findings showed that 3D electrically-stimulated hNPCs were more effective in enhancing neurotrophic factor expression namely GDNF and BDNF (Fig. ), whereas 2D electrically-stimulated cells increased gene expression of ENO2 (Fig. ). Interestingly, the 3D field alters GDNF and BDNF to a far greater degree than the 2D field. This finding illustrates that even under the identical field strength for a brief period of time, the shape of stimulating platforms has great implications in eliciting the therapeutic potential of hNPCs. Future work can be conducted to study the long-term effects of the dimensionality of electrical stimulation on changes in hNPCs gene expression and their implications in cell proliferation and differentiation. In this study, we demonstrated the feasibility of fabricating the conductive 2D and 3D PPy scaffolds as platforms to examine the potential dimensional effect of electrical stimulation on hNPCs. Specifically, the 2D and 3D PPy scaffolds with similar material morphologies were used to electrically stimulate hNPCs under identical field strength. Electrical stimulation applied through 2D and 3D conductive scaffolds shared upregulated expression of some common genes that play important roles in signaling self-renewal and survival, synaptic remodeling, and nerve regeneration despite differences in the physical shapes of the stimulating platform. The physical 2D and 3D culturing conditions alone also affected the NPC gene expression related to cell proliferation and metabolic pathways. Importantly, the 3D electrically-stimulated cells were more effective in promoting expression of neurotrophic factors and the 2D stimulated conditions showed increased gene expression that is important for cell-cell adhesion, neuronal differentiation, and metabolic maintenance. In addition to different stimulating platforms, the nutrient availability associated with 2D and 3D scaffolds was also likely to contribute changes in the expression of neurotrophic factors. Overall, our study demonstrated the significance in manipulating the physical culture conditions with brief electrical stimulation that resulted in profound effects reflected by the gene expression profile of hNPCs. Thus, the dimension of stimulating platforms used to apply electrical stimulation proved to be important for modulating expression changes of hNPCs depending on their metabolic states. This discovery can be important in implementing engineering strategies to manipulate the microenvironment to obtain desired therapeutic effects from stem cells.
Fabrication of conductive scaffolds For 2D PPy conductive films, the electroplating PPy solution was doped with sodium dodecylbenzenesulfonate (NaDBS) which was then electroplated onto prepared indium tin oxide (ITO) slides at 2 mA/cm2 as previously described , , (Fig. ). After removal from the ITO, the electroplated-PPy was washed with DI H 2 O. It was sandwiched between polydimethylsiloxane (PDMS; Sylgard, Dow) slab and a chamber slide to form cell chambers on top of the 2D PPy film (Lab-Tek, Thermo Fisher) (Fig. ). The PDMS slab was used to flatten out the 2D PPy films and prevent potential leakage from subsequent cell culture experiments. Wires were attached to the 2D PPy (length: 3 cm, width: 1.2 cm, thickness: 0.25 mm) outside of the chambers. The individual chamber dimension was 1.1 cm in length and 0.9 cm in width. For the 3D PPy conductive tubes, PPy was electroplated onto a 14G Nickel-Chromium Alloy wire at 2 mA/cm 2 for 2 hrs (Fig. ). The 3D PPy tubes were then gently detached from the plating wire with the following dimensions: 1.63 mm inner diameter, 15 mm length, and 0.4 mm in wall thickness. All scaffolds were electroplated with 0.2 M NaDBS and 0.2 M PPy (Sigma Aldrich) at room temperature. To disassociate scaffolds from underlying substrates, −10 V was applied between the substrate and the reference platinum mesh for 2 min via the function generator (E3641A, Agilent) in PBS. All scaffolds were then mechanically removed from the substrates and sterilized under UV light prior to use . The conductivity was measured to be 57.8 ± 4.2 S/m using the direct current (d.c.) four-point probe method with a Keithley 2400 Source Meter 45 at room temperature. Physical dimensions of scaffolds were measured by a caliper. Differentiation of hiPSCs to hNPCs The differentiation of hiPSCs to hNPCs was generated using defined conditions with modifications to previously reported protocols , . The NPC differentiation medium was made of 50% DMEM/F12 (Thermo Fisher Scientific), 50% Neurobasal (Thermo Fisher Scientific), 1% N2-Max (R&D Systems), 2% B27 (Thermo Fisher Scientific), 1% non-essential amino acids (NEAA) (Fisher), 1% GlutaMax (Fisher), 0.1 mM Mercaptoethanol (Sigma), and 1% penicillin/streptomycin (P/S) (Fisher) supplemented with SMAD inhibitors (i.e. 1 μM Dorsomorphin and SB431542). The NPC maintenance medium consisted of differentiation medium supplemented with bFGF (20 ng/ml) (Fisher) and EGF (20 ng/ml) (Fisher) without SMAD inhibitors. On day 0, iPSCs (~80–90% confluency) were washed with PBS without Ca 2+ and Mg 2+ , followed by addition of NPC differentiation medium for 7 days (4 mL per 6-well) under standard culture conditions (37 °C, 5% CO 2 ). Medium was replaced every 24 hr. On day 7, after the induction procedure, hNPCs were washed with PBS, and Accutase (1 ml per well) was added to detach the cells. After 5 min, cells were detached from the plate surface under gentle dislodging. All cells were collected into medium made of DMEM/F12 with the RhoA/ROCK inhibitor and spun down at 1,200 rpm for 5 min at room temperature. The number of cells was determined using a hemocytometer. hNPCs were used between passages 1–3. Electrically-stimulation of hNPC-seeded conductive scaffolds Cell density in alginate was kept consistent for both the 2D and 3D conditions. 25,000 cells/ul hNPCs were encapsulated in 1% alginate solution. The solution was dispensed onto the individual chambers of 2D PPy films or encapsulated into the 3D PPy tubes. The thickness of hydrogel on 2D PPy films was 1.5 mm and the radial diameter in 3D PPy tubes was 1.63 mm as measured by a caliper. The hydrogel-immobilized cell solution was also deposited into 48-well plate as controls. The cross-linked solution containing NPC maintenance medium and 1%CaCl 2 supplemented by the RhoA/ROCK inhibitor was added to all scaffolds under standard culture conditions. New medium was added to all conditions the next day. The NPC-seeded 2D and 3D conductive scaffolds were electrically stimulated to achieve identical electric field strength (~40 V/m) (Fig. ). After a 1-hr stimulation, all samples were incubated for 24 hrs before analysis. Electromagnetic finite element method (FEM) simulation Electromagnetic field computation was conducted with physical dimensions and electrical properties described in the 2D and 3D PPy scaffolds (i.e. electrical resistivity of connection ~0.007 Ωcm and experimental conductivity 57.8 S/m ). Electromagnetic simulations were performed on ANSYS HFSS using the finite element method (FEM) solver with the model subdivided into many small subsections in the form of tetrahedra. A solution is found such that the interrelated fields within these tetrahedra satisfy the Maxwell’s Equations across inter-element boundaries. Specifically, the electric field E is solved using the equation [12pt]{minimal}
$$ (_{r}} {})-{k}_{0}^{\,2}{{ }}_{r}\,{}=-j { }_{0}{}}}_{source}$$ ∇ × ( 1 μ r ∇ × E ) − k 0 2 ϵ r E = − j ω μ 0 J ⃗ s o u r c e , where [12pt]{minimal}
$${k}_{0}^{2}=^{2}}{{c}^{2}}$$ k 0 2 = ω 2 c 2 , and [12pt]{minimal}
$${{ }}_{r}$$ ϵ r , μ r are the relative permittivity and permeability respectively. This equation makes no approximation from Maxwell’s Equations, thus accurately capturing the electromagnetic field within the model. At each iterative calculation, the fields and associated S-matrix is generated, with the next iteration minimizing the field errors with an adaptive mesh refinement process. A solution is found when Δ S max is smaller than the target, which is set to be 0.05% for high precision. Nutrient molecule transport finite element method (FEM) simulation Nutrient molecules transport simulations were performed on COMSOL Multiphysics using the finite element method (FEM) solver, with the model subdivided into many small subsections. A solution is found such that the nutrient concentrations within these subsections satisfy the steady-state reaction-diffusion equations. Specifically, concentration C i is solved using the equation ∇ ( D i ∇ C i ) = R i , where D i is the diffusion coefficient for the i th nutrient, and R i is the nutrient consumption rate by the cell culture. Concentration for oxygen and glucose at the hydrogel boundary were set to be the same as in the cell culture medium provided by the manufacture. Diffusion coefficients for oxygen and glucose are set to be 2.5 × 10 −9 m 2 /s and 1 × 10 −9 m 2 /s, respectively . Cell numbers from experiments and cell consumption rate per cell values (oxygen and glucose) from previous literature were used for modeling 2D PPy film sheet and 3D PPy tube. Cell viability For the lactate dehydrogenase (LDH) (Pierce, Thermo Fisher Scientific) assay, the positive control was a sample medium collected from cells that were lysed with a buffer reagent provided by the manufacturer. The negative control was medium from cells cultured on a tissue culture plate under standard culture conditions. Supernatant from unstimulated and stimulated cells in 2D and 3D PPy scaffolds were also collected. Supernatant from all conditions was then mixed with the reaction mixture and later added with the stop solution. The LDH activity was measured by the Spectra Max M2 plate reader (Molecular Devices) at an absorbance of 490 nm and 680 nm, based on the manufacturer’s protocol. For the alamar blue assay, the positive control was cells cultured on a tissue culture plate under standard culture conditions, whereas the negative control was lysed cells. A 10% alamar blue reagent (DAL1025, Thermo Fisher Scientific) was added to each culture condition including the unstimulated and stimulated cells in the 2D and 3D PPy scaffolds. The activity from the alamar blue assay was quantified with the plate reader by monitoring the absorbance of the reagent at 570 nm while using 600 nm as a reference wavelength based on the manufacturer’s protocol. Live/Dead assay was used to stain cells based on the manufacturer protocol (L3224, Thermo Fisher Scientific). Immunofluorescence staining Cells were fixed with 4% formaldehyde followed by PBS washes, permeabilized with 0.1% Triton X-100 for 10 min, and incubated in blocking solution (PBS, 1% normal goat serum) for 30 min. Samples were incubated with primary antibodies (PAX6: 42-6600, SOX1: AF3369, SOX2: AF2018, Nestin: ABD69MI; Fisher Scientific) at a dilution of 1:100-1:300 for 1 hr and washed twice for 5 min with PBS to remove residues. Another incubation with secondary antibodies (Alexa Fluor 555: A27039, Alexa Fluor 488: A-11008; Thermo Fisher Scientific) at a dilution of 1:1000 for 1 hr was used, followed by PBS washes for 5 min. DAPI (1:1000, D9542, Sigma-Aldrich) was added for nuclear staining. Images were obtained using a Keyence BZ-X710 microscope equipped with full BZ acquisition and analysis software. Quantitative gene expression The quantitative real-time polymerase chain reaction (qRT-PCR) was performed using the RNeasy Mini Kit (Qiagen) based on the manufacturer’s protocol. The iScript cDNA Synthesis Kit (Bio-Rad) was used for cDNA synthesis. The QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific) was used to perform quantitative real-time PCR. Taq polymerase and Taqman primers (Thermo Fisher Scientific) glyceraldehyde-3-phosphate dehydrogenase ( GAPDH Hs02786624_g1), neural cell adhesion molecule 1 ( NCAM1 Hs00941830_m1), heparin binding EGF like growth factor ( HBEGF Hs00181813_m1), heat shock protein family member 1 ( HSPB1 Hs00356629_g1), enolase 2 ( ENO2 Hs00157360_m1), vascular endothelial growth factor A ( VEGF-A Hs00900055_m1), glial cell derived neurotrophic factor ( GDNF Hs01931883_s1), brain derived neurotrophic factor ( BDNF Hs02718934_s1), and neurotrophin 3 ( NTF3 Hs00267375_s1) for formed the PCR reaction mixtures. The Delta-Delta CT method was utilized for analysis with the GAPDH housekeeping gene and alginate-immobilized hNPCs on tissue culture wells as references. Statistical analysis Sample pairs were analyzed using the Student’s t-test. Multiple samples were evaluated with one-way or two-way analysis of variance (ANOVA) followed by Tukey and multiple comparisons using GraphPad Prism software (San Diego, CA). A p value of <0.05 was accepted as statistically significant for all analyses.
For 2D PPy conductive films, the electroplating PPy solution was doped with sodium dodecylbenzenesulfonate (NaDBS) which was then electroplated onto prepared indium tin oxide (ITO) slides at 2 mA/cm2 as previously described , , (Fig. ). After removal from the ITO, the electroplated-PPy was washed with DI H 2 O. It was sandwiched between polydimethylsiloxane (PDMS; Sylgard, Dow) slab and a chamber slide to form cell chambers on top of the 2D PPy film (Lab-Tek, Thermo Fisher) (Fig. ). The PDMS slab was used to flatten out the 2D PPy films and prevent potential leakage from subsequent cell culture experiments. Wires were attached to the 2D PPy (length: 3 cm, width: 1.2 cm, thickness: 0.25 mm) outside of the chambers. The individual chamber dimension was 1.1 cm in length and 0.9 cm in width. For the 3D PPy conductive tubes, PPy was electroplated onto a 14G Nickel-Chromium Alloy wire at 2 mA/cm 2 for 2 hrs (Fig. ). The 3D PPy tubes were then gently detached from the plating wire with the following dimensions: 1.63 mm inner diameter, 15 mm length, and 0.4 mm in wall thickness. All scaffolds were electroplated with 0.2 M NaDBS and 0.2 M PPy (Sigma Aldrich) at room temperature. To disassociate scaffolds from underlying substrates, −10 V was applied between the substrate and the reference platinum mesh for 2 min via the function generator (E3641A, Agilent) in PBS. All scaffolds were then mechanically removed from the substrates and sterilized under UV light prior to use . The conductivity was measured to be 57.8 ± 4.2 S/m using the direct current (d.c.) four-point probe method with a Keithley 2400 Source Meter 45 at room temperature. Physical dimensions of scaffolds were measured by a caliper.
The differentiation of hiPSCs to hNPCs was generated using defined conditions with modifications to previously reported protocols , . The NPC differentiation medium was made of 50% DMEM/F12 (Thermo Fisher Scientific), 50% Neurobasal (Thermo Fisher Scientific), 1% N2-Max (R&D Systems), 2% B27 (Thermo Fisher Scientific), 1% non-essential amino acids (NEAA) (Fisher), 1% GlutaMax (Fisher), 0.1 mM Mercaptoethanol (Sigma), and 1% penicillin/streptomycin (P/S) (Fisher) supplemented with SMAD inhibitors (i.e. 1 μM Dorsomorphin and SB431542). The NPC maintenance medium consisted of differentiation medium supplemented with bFGF (20 ng/ml) (Fisher) and EGF (20 ng/ml) (Fisher) without SMAD inhibitors. On day 0, iPSCs (~80–90% confluency) were washed with PBS without Ca 2+ and Mg 2+ , followed by addition of NPC differentiation medium for 7 days (4 mL per 6-well) under standard culture conditions (37 °C, 5% CO 2 ). Medium was replaced every 24 hr. On day 7, after the induction procedure, hNPCs were washed with PBS, and Accutase (1 ml per well) was added to detach the cells. After 5 min, cells were detached from the plate surface under gentle dislodging. All cells were collected into medium made of DMEM/F12 with the RhoA/ROCK inhibitor and spun down at 1,200 rpm for 5 min at room temperature. The number of cells was determined using a hemocytometer. hNPCs were used between passages 1–3.
Cell density in alginate was kept consistent for both the 2D and 3D conditions. 25,000 cells/ul hNPCs were encapsulated in 1% alginate solution. The solution was dispensed onto the individual chambers of 2D PPy films or encapsulated into the 3D PPy tubes. The thickness of hydrogel on 2D PPy films was 1.5 mm and the radial diameter in 3D PPy tubes was 1.63 mm as measured by a caliper. The hydrogel-immobilized cell solution was also deposited into 48-well plate as controls. The cross-linked solution containing NPC maintenance medium and 1%CaCl 2 supplemented by the RhoA/ROCK inhibitor was added to all scaffolds under standard culture conditions. New medium was added to all conditions the next day. The NPC-seeded 2D and 3D conductive scaffolds were electrically stimulated to achieve identical electric field strength (~40 V/m) (Fig. ). After a 1-hr stimulation, all samples were incubated for 24 hrs before analysis.
Electromagnetic field computation was conducted with physical dimensions and electrical properties described in the 2D and 3D PPy scaffolds (i.e. electrical resistivity of connection ~0.007 Ωcm and experimental conductivity 57.8 S/m ). Electromagnetic simulations were performed on ANSYS HFSS using the finite element method (FEM) solver with the model subdivided into many small subsections in the form of tetrahedra. A solution is found such that the interrelated fields within these tetrahedra satisfy the Maxwell’s Equations across inter-element boundaries. Specifically, the electric field E is solved using the equation [12pt]{minimal}
$$ (_{r}} {})-{k}_{0}^{\,2}{{ }}_{r}\,{}=-j { }_{0}{}}}_{source}$$ ∇ × ( 1 μ r ∇ × E ) − k 0 2 ϵ r E = − j ω μ 0 J ⃗ s o u r c e , where [12pt]{minimal}
$${k}_{0}^{2}=^{2}}{{c}^{2}}$$ k 0 2 = ω 2 c 2 , and [12pt]{minimal}
$${{ }}_{r}$$ ϵ r , μ r are the relative permittivity and permeability respectively. This equation makes no approximation from Maxwell’s Equations, thus accurately capturing the electromagnetic field within the model. At each iterative calculation, the fields and associated S-matrix is generated, with the next iteration minimizing the field errors with an adaptive mesh refinement process. A solution is found when Δ S max is smaller than the target, which is set to be 0.05% for high precision.
Nutrient molecules transport simulations were performed on COMSOL Multiphysics using the finite element method (FEM) solver, with the model subdivided into many small subsections. A solution is found such that the nutrient concentrations within these subsections satisfy the steady-state reaction-diffusion equations. Specifically, concentration C i is solved using the equation ∇ ( D i ∇ C i ) = R i , where D i is the diffusion coefficient for the i th nutrient, and R i is the nutrient consumption rate by the cell culture. Concentration for oxygen and glucose at the hydrogel boundary were set to be the same as in the cell culture medium provided by the manufacture. Diffusion coefficients for oxygen and glucose are set to be 2.5 × 10 −9 m 2 /s and 1 × 10 −9 m 2 /s, respectively . Cell numbers from experiments and cell consumption rate per cell values (oxygen and glucose) from previous literature were used for modeling 2D PPy film sheet and 3D PPy tube.
For the lactate dehydrogenase (LDH) (Pierce, Thermo Fisher Scientific) assay, the positive control was a sample medium collected from cells that were lysed with a buffer reagent provided by the manufacturer. The negative control was medium from cells cultured on a tissue culture plate under standard culture conditions. Supernatant from unstimulated and stimulated cells in 2D and 3D PPy scaffolds were also collected. Supernatant from all conditions was then mixed with the reaction mixture and later added with the stop solution. The LDH activity was measured by the Spectra Max M2 plate reader (Molecular Devices) at an absorbance of 490 nm and 680 nm, based on the manufacturer’s protocol. For the alamar blue assay, the positive control was cells cultured on a tissue culture plate under standard culture conditions, whereas the negative control was lysed cells. A 10% alamar blue reagent (DAL1025, Thermo Fisher Scientific) was added to each culture condition including the unstimulated and stimulated cells in the 2D and 3D PPy scaffolds. The activity from the alamar blue assay was quantified with the plate reader by monitoring the absorbance of the reagent at 570 nm while using 600 nm as a reference wavelength based on the manufacturer’s protocol. Live/Dead assay was used to stain cells based on the manufacturer protocol (L3224, Thermo Fisher Scientific).
Cells were fixed with 4% formaldehyde followed by PBS washes, permeabilized with 0.1% Triton X-100 for 10 min, and incubated in blocking solution (PBS, 1% normal goat serum) for 30 min. Samples were incubated with primary antibodies (PAX6: 42-6600, SOX1: AF3369, SOX2: AF2018, Nestin: ABD69MI; Fisher Scientific) at a dilution of 1:100-1:300 for 1 hr and washed twice for 5 min with PBS to remove residues. Another incubation with secondary antibodies (Alexa Fluor 555: A27039, Alexa Fluor 488: A-11008; Thermo Fisher Scientific) at a dilution of 1:1000 for 1 hr was used, followed by PBS washes for 5 min. DAPI (1:1000, D9542, Sigma-Aldrich) was added for nuclear staining. Images were obtained using a Keyence BZ-X710 microscope equipped with full BZ acquisition and analysis software.
The quantitative real-time polymerase chain reaction (qRT-PCR) was performed using the RNeasy Mini Kit (Qiagen) based on the manufacturer’s protocol. The iScript cDNA Synthesis Kit (Bio-Rad) was used for cDNA synthesis. The QuantStudio 6 Flex Real-Time PCR System (Thermo Fisher Scientific) was used to perform quantitative real-time PCR. Taq polymerase and Taqman primers (Thermo Fisher Scientific) glyceraldehyde-3-phosphate dehydrogenase ( GAPDH Hs02786624_g1), neural cell adhesion molecule 1 ( NCAM1 Hs00941830_m1), heparin binding EGF like growth factor ( HBEGF Hs00181813_m1), heat shock protein family member 1 ( HSPB1 Hs00356629_g1), enolase 2 ( ENO2 Hs00157360_m1), vascular endothelial growth factor A ( VEGF-A Hs00900055_m1), glial cell derived neurotrophic factor ( GDNF Hs01931883_s1), brain derived neurotrophic factor ( BDNF Hs02718934_s1), and neurotrophin 3 ( NTF3 Hs00267375_s1) for formed the PCR reaction mixtures. The Delta-Delta CT method was utilized for analysis with the GAPDH housekeeping gene and alginate-immobilized hNPCs on tissue culture wells as references.
Sample pairs were analyzed using the Student’s t-test. Multiple samples were evaluated with one-way or two-way analysis of variance (ANOVA) followed by Tukey and multiple comparisons using GraphPad Prism software (San Diego, CA). A p value of <0.05 was accepted as statistically significant for all analyses.
Supplementary information
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Environmental microbiology going computational—Predictive ecology and unpredicted discoveries | 67905c48-0d55-4e51-b4c2-10278140f7e0 | 10092848 | Microbiology[mh] | The fields of microbial ecology and environmental microbiology are producing loads of data, mainly nucleic acid sequence data due to the extensive use of amplicon sequencing and metagenomics, and an increasing use of transcriptomics. To increase our understanding of microorganisms in terrestrial ecosystems, multiple, concerted efforts to collect large numbers of samples for analyses of microbial communities were initiated already more than 15 years ago (Fierer & Jackson, ; Lozupone & Knight, ) but have really exploded the last years, with The Earth Microbiome Project Consortium being one of the first major endeavours for bacteria across all biomes (Thompson et al., ) and the work by Tedersoo et al. ( ) for soil fungi. The majority of the investigations have a biogeography focus based on a single sampling occasion and the word ‘global’ is frequently used in the titles of these soil microbial catalogues and surveys (Bahram et al., ; Delgado‐Baquerizo et al., ; Gobbi et al., ). Similar efforts have been done for many other biomes. Although largely descriptive, they have contributed to a better understanding of microbial diversity and the distribution of microbial taxa and their functions at an unprecedented spatial scale. Further, correlative analyses have indicted direct or indirect drivers of the observed patterns as well as the role of microbial communities for ecosystem functioning (Bahram et al., ; Delgado‐Baquerizo et al., ; Garland et al., ). The massive amount of complex data is not only an opportunity but also a major challenge when it comes to meaningful interpretation. The field of computational biology, being the intersection of computer science and biology, is rapidly expanding and developing new methods for this purpose. Artificial intelligence (AI), including machine learning (ML) and to some extent also deep learning (DL) methods are promising for dealing with big data in microbial ecology and environmental microbiology (Ghannam & Techtmann, ; McElhinney et al., ). Especially ML approaches are increasingly adopted by ecologists and many of these methods will soon become routine tools for analyses of complex microbial omics data. They can be used to categorize and finds patterns in uncategorized data as well as analyse data that we know how to categorize. There are several advantages to using ML methods in microbiome studies, for example, they can deal with non‐linear relationships, make better use of the full depth of high‐dimensional data, and can be used to build predictive models based on environmental and community data. Predictive modelling is very attractive in microbial ecology. Among the ML methods, random forests have become frequently applied in microbiome studies in the last decade (Jones et al., ; Ryo & Rillig, ). It is predominantly used for the identification of the best predictors for a given response variable and has for example been used to rank the environmental variables determining the major microbial phyla in wetlands (Bahram et al., ) and the diversity of ammonia oxidizing archaea across European soils (Saghaï et al., ), as well as the relative importance of biotic and abiotic controls of nitrous oxide emissions from agricultural soils (Jones et al., ). Random forest modelling can be very useful when studying remote areas that are difficult to sample, as exemplified by climate projections on microbial communities in the Antarctic Ocean (Tonelli et al., ). RF models can also show how predictions change over the range of each individual predictor variable, thereby giving the possibility to identify thresholds or tipping points (Apley & Zhu, ; Saghaï et al., ). Already in 2012, artificial neural networks were used to incorporate interactions among community members in models for predictions of microbial community composition in time and space based on environmental data (Larsen et al., ). A similar approach was used to predict the maize rhizosphere community at different plant development stages or growth conditions (García‐Jiménez et al., ). This type of approach can potentially assist in the microbiome engineering of important crops. However, with sequencing costs being relatively cheap, there is an increasing interest in using AI and microbiome data for microbiome‐based diagnostics as a means to address environmental challenges and advance management practices (McElhinney et al., ). Two recent examples of the latter are the use of soil microbiome data to predict the propensity for specific plant diseases in agriculture (Yuan et al., ) and soil health metrics (Wilhelm et al., ), which can be laborious and expensive to measure. Combining ML and microbiome data has further shown promising in environmental monitoring, tracing of contaminants and predictions of environmental quality (Sperlea et al., ; Techtmann & Hazen, ; Wheeler, ), which allows us to move away from indicator taxa or microbial biomarkers and instead use the full breath of information encompassed by the microbial community in a given site or sample.
The large amounts of genetic data and corresponding meta‐data generated in microbiome studies are real treasures, especially when it comes to metagenomes and metatranscriptomes, and only a fraction of the information available has been explored. This data can be used for meta‐analyses to increase the scale of the study, but more importantly, it can be used to address other questions than those posed by the researchers that collected the original data. Making use of already published genome or sequence data in microbial ecology is not a new idea (Jones & Hallin, ) but now we have increasing possibilities to mine extremely large data sets (Coelho et al., ). Even more exciting are the possibilities to combine different types of data and information to go beyond the microbiome data. Integration of knowledge from diverse fields of research and the combination of microbiome data with other data from different sources have the potential to result in unexpected and unpredictable results, as well as new discoveries. A recent example of re‐using and combining data is the work by Ke et al. ( ), who reanalyzed data in published datasets on the effects of pesticide application on soil microbial communities combined with information on the physical and chemical properties of the pesticides. By developing a ML model, they were able to show that physical pesticide properties largely explain the ecological impact of the pesticide. This information can guide the design of pesticide molecules to minimize environmental risk. In the field of precision agriculture, researchers have proposed the integration of AI and nanotechnology with disparate datasets to enable the design of nanoscale agrochemicals for sustainable food production (Zhang et al., ). In another study, geographic and meteorological data as well plant‐traits, land‐use type and microbial community data were used in a ML‐based prediction of grassland degradation, which is a multi‐factorial phenomenon not easily captured by a few variables (Yan et al., ). Combining datasets and using computational approaches can also be used to develop new diagnostic tools. For example, de Andrade et al. ( ) suggest the development of a soil quality index based on soil microbiome data, crop productivity and a range of abiotic environmental factors to improve crop production systems using AI. Data‐driven research relying on large, multiple, complex datasets and computational methods and capacity, as exemplified above, indicates a new paradigm in microbial ecology, and ecology in general (McCallen et al., ). We can anticipate new insights, similar to the leaps taken after advanced bioinformatics and multi‐omics approaches became an integral part of microbial ecology research. Microbial ecology and environmental microbiology will follow the trajectory in life sciences and become increasingly computationally demanding, focusing on larger and also more complex sets of information. We are already seeing the laboratories being sparsely populated while students, postdocs, and researchers spend increasing amount of time in front of their computers organizing and analysing data. My crystal ball says that a shift towards a data‐driven rather than an experimental‐driven and data generating science, that depends on complex, big data, and advanced technologies, will be a game changer in microbial ecology and environmental microbiology. This development is already putting pressure on management, storage and sharing of data. Data‐driven microbial ecology research where different types of data are combined to consider the multidimensionality of ecosystems further suggests that students and researchers not only need to enhance their computational skills, but also skills in working interdisciplinary. Nevertheless, important discoveries should ideally be followed by experimental approaches to test hypothesis, determine causal relationships, and verify mechanisms. Already, experimental validation is definitely a bottleneck to close the circle in microbial ecology research and, although my crystal ball is a bit hazy here, it looks like this will become an even greater bottleneck in the era of big data and data‐drivenresearch in microbial ecology.
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The influence of cooling on biomechanical time since death estimations using ovine brain tissue | 9687523b-9f0c-418c-9446-f50348e516c9 | 11490522 | Pathology[mh] | The value of post-mortem biomechanical analyses of brain tissue for forensic time since death estimation has recently been demonstrated using ovine tissue . By employing cerebellar samples, it was possible to distinguish immediately post-mortem samples from those stored at 20 °C for one to four days with a sensitivity and specificity of 90% and 92%, respectively . However, the inability to distinguish between biomechanical properties of brain tissue across days two to four limited the forensic value of the proposed rheological analyses of brain tissue at 20 °C. Lower temperatures generally prolong the degradation of biological tissues . Hence, at lower temperatures, biomechanical analyses of brain tissue for time since death estimations might be promising even beyond day one. From both a forensic and broader scientific perspective, it is of interest to compare the previous observations at 20 °C to a storage temperature of 4 °C, using the same setup. From a practical perspective, 20 °C is a sensible assumption when the body is located in an interior temperature controlled environment. In the morgue, cadavers are commonly stored at 4 °C between admission and autopsy to limit degradation effects. For forensic time since death analyses, an ambient temperature of 4 °C is relevant when bodies are found outside during the colder months of the year. Moreover, the temperature of 4 °C corresponds to the year-round water temperature at the bottom of stagnant waters, such as lakes where bodies (or heads in dismemberment cases) are occasionally disposed after homicides . For biomechanical basic research, brain samples are commonly stored at approximately 4 °C between retrieval and further use to prevent degradation . Post-mortem analyses of the biomechanical properties of brain tissue over a time frame of several days after death remain scarce . This scarcity is due to the fact that tissue degradation is commonly undesired for biomechanical analyses. Predominantly, biomechanical research on brain tissue aims at obtaining lifelike properties to allow for an accurate simulation of load deformation properties in head impact scenarios . Hence, researchers strive to keep the post-mortem intervals (PMIs) to a minimum, with a recommendation to stay within a few hours between death and biomechanical analysis . Measuring the mechanical properties of soft tissues is challenging due to their malleability, requiring specialized devices . Rheology is commonly employed to assess these properties, focusing on viscoelastic characteristics in tissues like the brain , liver , kidney , and muscle . Oscillatory rheology efficiently measures a sample’s storage modulus (S mod ), loss modulus (L mod ), and complex shear modulus (CS mod ). The S mod indicates elasticity, reflecting the material’s energy storage ability, while the L mod indicates viscosity, signifying energy dissipation characteristics. The CS mod combines both, representing the material’s resistance to deformation . With tissue decomposition, there’s a progressive loss in deformation resistance, leading to a simultaneous reduction in all three moduli . This study aimed to provide forensically and scientifically relevant biomechanical data on brain tissue over a time frame of four days post-mortem at 4 °C. Emphasis was placed on establishing cut-off values that link the biomechanical properties to indicative points in time post-mortem based on their practical relevance for forensic investigators. The hypothesis posits that, compared to the post-mortem storage temperature of 20 °C, storage at 4 °C improves the resolution beyond day one of time since death classification possible from rheological analysis. Tissue collection and preparation Ovine full brains ( n = 30), including the medulla, were retrieved within two hours of sacrifice. The sheep were sacrificed for meat by throat slitting, and the brains were considered a waste product. Therefore, no ethical approval was required for this study. Immediately after retrieval, the brains were submerged in phosphate-buffered saline (PBS) to rinse off debris from blood and the retrieval process. Subsequently, the brains were placed in containers with freshly prepared PBS at 4 °C until mechanical testing. The day 0 tests were completed within four hours after sacrificing. The maximum sample size per brain region and testing day was 12 and 6 for paired samples (e.g., frontal lobe samples) and unpaired samples (e.g., pons samples), respectively. For each paired brain region, an equal ratio of left and right samples was ensured. Just before mechanical testing, samples were punched from eight different brain regions using a biopsy punch with a diameter of 10 mm. For cerebral samples, sagittal brain slices were cut with a microtome blade and an 8-mm-thick laser-cut acrylic stencil. This process created a medial brain slice, including the deep brain structures, from which frontal lobe (FL), parietal lobe (PL), as well as anterior (ADB) and posterior deep brain (PDB) samples were punched according to Fig. A. Similarly, the stencil was used to produce lateral slices of the cerebellum, from which a sample (CB) was punched (Fig. B). From the midbrain area, the left superior colliculus (SC) sample was punched from posterior to anterior (Fig. D). Likewise, pons (P) and medulla (M) samples were prepared (Fig. D). After punching, the sample height was adjusted to 5 mm using a customized mold and a microtome blade. Each day of testing utilised new samples, no sample was tested twice. The comparative data for samples stored at 20 °C (Fig. C, E) were taken from our previous work , for which the exact same testing protocol was used. Biomechanical testing Biomechanical testing was conducted using a rheometer (MCR302; Anton Paar, Graz, Austria). The tissues were placed into the apparatus under an axial preload of 0.1 N to ensure contact surface adhesion and were given 100 s to relieve any residual stresses. To reduce slippage, sandpaper was inserted between the base plate of the rheometer and the samples and the contact surface of the measuring tool was sandblasted (Fig. A). The rheometer was calibrated using PBS and all tests were performed in PBS at 20 °C (Fig. B). A peak angular shear strain of 0.03 [rad] at 3 Hz, with a continued 0.1 N compression force, was applied for a total of 50 cycles. This approach followed the methodology outlined in our previous study . Data analysis The measured S mod , L mod , and CS mod of the tissues were analysed using Microsoft Excel Version 16.74 (Microsoft Corporation, Redmond, USA) and GraphPad Prism version 9 (GraphPad Software, La Jolla, USA) for statistical analyses and data visualization. The Kolmogorov-Smirnov test was employed to assess the data for Gaussian distribution. Depending on the normality distribution, either ordinary one-way ANOVA tests, including Tukey’s multiple comparisons, or Kruskal-Wallis tests, including Dunn’s multiple comparisons, were applied when at least three groups were present. For cases with only two groups, parametric t-tests and nonparametric Mann-Whitney U-tests were applied for parametric and nonparametric data, respectively. P-values ≤ 0.05 were considered statistically significant. Side comparisons between the cerebral hemispheres of different brains, as well as a comparison between the M and P samples, were conducted to determine whether the respective samples could be pooled for further analyses. The data from all corresponding samples of all tested days were then compared. Receiver Operator Characteristic (ROC) curves with a 95% confidence interval were generated from the group comparisons between the testing days, focusing on significant differences from day 0. Specifically, all testing days with no significant difference from day 0, including day 0, were grouped against all remaining testing days starting from the first day to significantly differ from day 0. The cut-off values with the highest positive likelihood ratio were selected from the computed results. In cases where the highest positive likelihood ratio was present more than once, the one with the highest sensitivity value was chosen. Ovine full brains ( n = 30), including the medulla, were retrieved within two hours of sacrifice. The sheep were sacrificed for meat by throat slitting, and the brains were considered a waste product. Therefore, no ethical approval was required for this study. Immediately after retrieval, the brains were submerged in phosphate-buffered saline (PBS) to rinse off debris from blood and the retrieval process. Subsequently, the brains were placed in containers with freshly prepared PBS at 4 °C until mechanical testing. The day 0 tests were completed within four hours after sacrificing. The maximum sample size per brain region and testing day was 12 and 6 for paired samples (e.g., frontal lobe samples) and unpaired samples (e.g., pons samples), respectively. For each paired brain region, an equal ratio of left and right samples was ensured. Just before mechanical testing, samples were punched from eight different brain regions using a biopsy punch with a diameter of 10 mm. For cerebral samples, sagittal brain slices were cut with a microtome blade and an 8-mm-thick laser-cut acrylic stencil. This process created a medial brain slice, including the deep brain structures, from which frontal lobe (FL), parietal lobe (PL), as well as anterior (ADB) and posterior deep brain (PDB) samples were punched according to Fig. A. Similarly, the stencil was used to produce lateral slices of the cerebellum, from which a sample (CB) was punched (Fig. B). From the midbrain area, the left superior colliculus (SC) sample was punched from posterior to anterior (Fig. D). Likewise, pons (P) and medulla (M) samples were prepared (Fig. D). After punching, the sample height was adjusted to 5 mm using a customized mold and a microtome blade. Each day of testing utilised new samples, no sample was tested twice. The comparative data for samples stored at 20 °C (Fig. C, E) were taken from our previous work , for which the exact same testing protocol was used. Biomechanical testing was conducted using a rheometer (MCR302; Anton Paar, Graz, Austria). The tissues were placed into the apparatus under an axial preload of 0.1 N to ensure contact surface adhesion and were given 100 s to relieve any residual stresses. To reduce slippage, sandpaper was inserted between the base plate of the rheometer and the samples and the contact surface of the measuring tool was sandblasted (Fig. A). The rheometer was calibrated using PBS and all tests were performed in PBS at 20 °C (Fig. B). A peak angular shear strain of 0.03 [rad] at 3 Hz, with a continued 0.1 N compression force, was applied for a total of 50 cycles. This approach followed the methodology outlined in our previous study . The measured S mod , L mod , and CS mod of the tissues were analysed using Microsoft Excel Version 16.74 (Microsoft Corporation, Redmond, USA) and GraphPad Prism version 9 (GraphPad Software, La Jolla, USA) for statistical analyses and data visualization. The Kolmogorov-Smirnov test was employed to assess the data for Gaussian distribution. Depending on the normality distribution, either ordinary one-way ANOVA tests, including Tukey’s multiple comparisons, or Kruskal-Wallis tests, including Dunn’s multiple comparisons, were applied when at least three groups were present. For cases with only two groups, parametric t-tests and nonparametric Mann-Whitney U-tests were applied for parametric and nonparametric data, respectively. P-values ≤ 0.05 were considered statistically significant. Side comparisons between the cerebral hemispheres of different brains, as well as a comparison between the M and P samples, were conducted to determine whether the respective samples could be pooled for further analyses. The data from all corresponding samples of all tested days were then compared. Receiver Operator Characteristic (ROC) curves with a 95% confidence interval were generated from the group comparisons between the testing days, focusing on significant differences from day 0. Specifically, all testing days with no significant difference from day 0, including day 0, were grouped against all remaining testing days starting from the first day to significantly differ from day 0. The cut-off values with the highest positive likelihood ratio were selected from the computed results. In cases where the highest positive likelihood ratio was present more than once, the one with the highest sensitivity value was chosen. Day 0 comparisons Pooling of left and right hemisphere samples from different brains, as well as the M&P samples, was performed as no statistically significant differences were observed across the hemispheres. A test matrix of all successfully tested samples per day and region and a graphical representation of all statistically significant differences among the tested brain regions and biomechanical properties is provided in Tables and . The trends of the investigated biomechanical properties over the five testing days were region-specific, exhibiting differences in rheological behaviour (Fig. ). In particular, the CB samples showed an abrupt decrease to a plateau; the M&P samples had a gradual decrease, and ADB samples showed minimal degradation of shear modulus. None of the brain regions showed statistically significant differences between day 0 and day 1 samples for any of the investigated biomechanical properties. The ADB and PDB samples revealed no significant differences for any of the comparisons between day 0 and 4. Day 2 samples were significantly different from day 0 samples for the S mod of the PL ( p = 0.035) and the CB ( p = 0.008), as well as the CS mod of the CB ( p = 0.009). Day 3 samples exhibited significant differences from day 0 for the S mod and CS mod of the CB (S mod : p = 0.005; CS mod : p = 0.005) and M&P samples (S mod : p = 0.046; CS mod : p = 0.046). For the L mod , the day 0 and 3 comparison only revealed statistically significant differences for the CB ( p = 0.049). On day 4, samples significantly differed in S mod and CS mod from day 0 samples for the PL (S mod : p = 0.012; CS mod : p = 0.027), CB (S mod : p = 0.004; CS mod : p < 0.001), M&P (S mod : p = 0.004; CS mod : p = 0.007), and the SC (S mod : p = 0.033; CS mod : p = 0.049). Day 4 and day 0 samples of the FL also significantly differed in their S mod ( p = 0.024). L mod was only significantly different for the CB samples between days 0 and 4 ( p = 0.024). Comparisons between the remaining testing days Day 1 values of the CB samples were significantly different in all tested biomechanical properties from day 2 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p = 0.005), day 3 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p = 0.001), and day 4 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p < 0.001). Additionally, the day 1 and 4 comparison was significantly different for the S mod of the M&P samples ( p = 0.046). Receiver operator characteristic curves The results of the ROC curve analyses are detailed in Table . Representatively, the grouping and curves for the CS mod data are illustrated in Fig. . A PMI of at least two days could be determined with fair to excellent diagnostic ability using PL and CB samples. With M&P and CB samples, a PMI of at least three days could be diagnosed with fair to good diagnostic ability. A PMI of at least four days could be detected with poor to good diagnostic ability using FL, SC and PL samples. Comparison of 4 and 20 °C data The comparison of data with storage temperatures of 4 and 20 °C revealed region-specific results (Table ). For example, the CS mod of the ADB was significantly different for each individual testing day, while for the M&P samples, it remained indistinguishable throughout all testing days. Pooling of left and right hemisphere samples from different brains, as well as the M&P samples, was performed as no statistically significant differences were observed across the hemispheres. A test matrix of all successfully tested samples per day and region and a graphical representation of all statistically significant differences among the tested brain regions and biomechanical properties is provided in Tables and . The trends of the investigated biomechanical properties over the five testing days were region-specific, exhibiting differences in rheological behaviour (Fig. ). In particular, the CB samples showed an abrupt decrease to a plateau; the M&P samples had a gradual decrease, and ADB samples showed minimal degradation of shear modulus. None of the brain regions showed statistically significant differences between day 0 and day 1 samples for any of the investigated biomechanical properties. The ADB and PDB samples revealed no significant differences for any of the comparisons between day 0 and 4. Day 2 samples were significantly different from day 0 samples for the S mod of the PL ( p = 0.035) and the CB ( p = 0.008), as well as the CS mod of the CB ( p = 0.009). Day 3 samples exhibited significant differences from day 0 for the S mod and CS mod of the CB (S mod : p = 0.005; CS mod : p = 0.005) and M&P samples (S mod : p = 0.046; CS mod : p = 0.046). For the L mod , the day 0 and 3 comparison only revealed statistically significant differences for the CB ( p = 0.049). On day 4, samples significantly differed in S mod and CS mod from day 0 samples for the PL (S mod : p = 0.012; CS mod : p = 0.027), CB (S mod : p = 0.004; CS mod : p < 0.001), M&P (S mod : p = 0.004; CS mod : p = 0.007), and the SC (S mod : p = 0.033; CS mod : p = 0.049). Day 4 and day 0 samples of the FL also significantly differed in their S mod ( p = 0.024). L mod was only significantly different for the CB samples between days 0 and 4 ( p = 0.024). Day 1 values of the CB samples were significantly different in all tested biomechanical properties from day 2 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p = 0.005), day 3 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p = 0.001), and day 4 (S mod : p < 0.001; CS mod : p < 0.001; L mod : p < 0.001). Additionally, the day 1 and 4 comparison was significantly different for the S mod of the M&P samples ( p = 0.046). The results of the ROC curve analyses are detailed in Table . Representatively, the grouping and curves for the CS mod data are illustrated in Fig. . A PMI of at least two days could be determined with fair to excellent diagnostic ability using PL and CB samples. With M&P and CB samples, a PMI of at least three days could be diagnosed with fair to good diagnostic ability. A PMI of at least four days could be detected with poor to good diagnostic ability using FL, SC and PL samples. The comparison of data with storage temperatures of 4 and 20 °C revealed region-specific results (Table ). For example, the CS mod of the ADB was significantly different for each individual testing day, while for the M&P samples, it remained indistinguishable throughout all testing days. The potential of measuring brain tissue mechanics for forensic time since death estimations was recently demonstrated . However, the approach showed limited resolution in time since death prediction after 24 h. Screening for notable differences between day 0 (‘fresh samples’) and the subsequent testing days is of paramount importance. Comparisons between different testing days beyond day 0, such as between days 1 and 2, are valuable for detecting points in time with marked biomechanical changes. However, they offer limited practical value for forensic time since death estimations. When storing the brains at 20 °C between death and the mechanical testing, the most prominent differences were observed between fresh samples and samples with a PMI of one day . As a result, day 0 samples could be distinguished from samples with a PMI of at least one day with high sensitivity and specificity . This study used tissue preparation and testing conditions identical to our previous study . The only change was the storage temperature, which was lowered to 4 °C immediately after retrieval of the brains following animal sacrifice. Low temperature storage slows down biomechanical changes after death At a post-mortem storage temperature of 20 °C, the FL, ADB, CB, and SC significantly differed from the day 0 values after one day post-mortem in all investigated biomechanical properties . Three days post-mortem, all brain regions examined in the study significantly differed from the day 0 values at 20 °C in all biomechanical properties . At 4 °C, the biomechanical changes were much slower. Sample storage at 4 °C for one day did not significantly alter the investigated biomechanical properties of brain tissue. This implies that biomechanical analyses for time since death estimations of brain tissue could be delayed for at least 24 h, potentially even 48 h, by maintaining constant cooling at 4 °C. In practice, this could enable forensic investigators to delay biomechanical analyses for at least a couple of hours, for instance, when other tasks must be prioritized. Beyond that, the tissues could be transferred to a specialized laboratory in a moist 4 °C environment if the forensic team on site is unable to perform the biomechanical analyses immediately. However, it remains unclear if the delayed onset of degradation observed only applies when the tissues are transferred to a 4 °C environment in a fresh state or if it also occurs if initiated at a later stage. This question remains to be addressed in future research. The course of the curves for the investigated biomechanical properties was examined to determine whether general trends apply among the different sampling regions. However, the curves’ progression was region-specific, likely linked to underlying structural differences, including variations in cell types and the white-to-grey matter ratio. As observed at 20 °C, the CB samples exhibited a distinct drop in the investigated biomechanical properties, followed by a slow decline to reach a plateau . At 4 °C, this significant drop was delayed by one day compared to storage at 20 °C. However, it is important to note that cool storage does not imply a simple one-day time delay for biomechanical changes observed at 20 °C storage. For instance, the FL and ADB samples were among the earliest to differ from day 0 samples after just one day post-mortem at 20 °C , but at 4 °C, they were among the more stable sample regions. Diagnostic ability of PMIs of at least two days at 4 °C using cerebellar samples From a practical perspective, forensic investigators require cut-off values to estimate the time since death with high diagnostic ability. Broadly, the diagnostic ability of ROC curves based on the AUC can be categorized as random (AUC: 0.5–0.6), poor (0.6–0.7), fair (0.7–0.8), good (0.8–0.9), and excellent (0.9–1.0) . However, ROC analyses should be interpreted beyond AUC labels . This study revealed that, when using CB samples stored at 4 °C, a PMI of at least two days could be determined with excellent diagnostic ability when reaching CS mod values below 1435 Pa or S mod values below 1313 Pa. A PMI of at least three days could be determined with good diagnostic ability using a L mod cut-off value of 415 Pa for the CB. For a PMI of at least four days, a good diagnostic ability was achieved using a CS mod cut-off value of 1656 Pa for the SC. In conclusion, the hypothesis that cooling at 4 °C extends the value of biomechanical time since death analyses beyond day one after death, compared to storage at 20 °C, can be accepted. However, in contrast to the results at 20 °C, at 4 °C, it was impossible to differentiate samples with a PMI of one day from fresh samples. Therefore, cooling not only extends the value of biomechanical time since death estimations but also lowers the diagnostic value of the method in the very early post-mortem phase, as the biomechanical properties are kept stable. Importantly, the diagnostic abilities stated above require a constant sample temperature for the given intervals. From a practical standpoint, the tissue temperature post-mortem usually varies over time due to different external influences such as exposure to sunlight or the transfer of body parts between places by the perpetrator. Future investigations should explore to what extent the given diagnostic abilities stated here are lowered under varying degrees of temperature variation throughout the given time frames. Although the diagnostic ability of the CS mod of the SC samples for PMIs of at least four days was good, further analyses are warranted due to the limited number of samples that fell below the cut-off value of 1656 Pa in the given dataset. None of the investigated biomechanical properties of the deep brain samples showed significant differences from day zero within the four testing days post-mortem at a storage temperature of 4 °C. Therefore, future studies should consider extending the analyzed PMI interval of the ADB and PDB at 4 °C to determine their points in time of marked tissue degradation, which are associated with biomechanical changes. Temperature as a confounder Importantly, this study highlighted the temperature sensitivity of the given method. Thus, for biomechanical analyses to be meaningful, knowledge of the temperature curve at the crime scene throughout the past hours to days is crucial. Temperature is a common confounder for forensic time since death estimation and also applies to the established nomogram method of Henssge . Measuring both the ambient temperature and the rectal temperature of the deceased is a standard procedure in every crime scene investigation. Furthermore, local meteorological services can assist in supplying the necessary temperature data to cover the gap between the presumed time of death and the data acquired during the forensic investigation at the scene. When comparing the properties at 4 and 20 °C, the temperature sensitivity was brain region-dependent. It ranged from significant differences throughout all the four testing days in the CS mod values of the ADB samples to no significant differences for any of the tested properties in M&P samples. Especially considering the fair diagnostic ability of M&P samples to determine a PMI of at least three days at 4 °C, its temperature stability between 4 and 20 °C makes it a promising sampling region for biomechanical time since death analyses. Outlook The potential use of biomechanical testing for forensic time since death estimation was demonstrated on ovine tissues. As a next step, the findings should be verified on human tissues. So far, the method has been explored at 4 and 20 °C, representing relevant temperatures from a practical perspective. As it seems to be impractical to test each and every temperature value, interpolation might be an option to fill the gaps after some other relevant temperature values have been investigated, e.g. around the human body temperature. Moreover, different body tissues should be explored applying the here stated protocol as their varying tissue structure and location will cause them to biomechanically respond at different times post-mortem, thereby extending the use of biomechanical analyses for time since death estimations beyond the data stated for brain tissue. Limitations Firstly, this study had limitations in sample population size. However, increasing the population size is unlikely to improve ROC values, which are the major tool for assessing classification potential. Secondly, this study was conducted on ovine tissues. Although the findings provide a thorough starting point for analyses on human samples, the cut-off values should be verified on human tissues to be valid for forensic purposes. Thirdly, differences in brain size and concomitantly in sampling regions may have contributed to the standard deviations of the presented biomechanical properties, as sample harvesting may have slightly varied each time. Fourthly, it was initially intended to use brains only from healthy sheep in this study. However, as the brains were not tested for medical conditions, unknown (veterinary) pathological alterations invisible upon gross inspection might have influenced the investigated biomechanical properties. Fifthly, handling times within the 24-hour intervals might have varied by minutes. Sixthly, the PBS solution used for sample storage between retrieval and testing might have impacted the results, for example, through tissue swelling. At a post-mortem storage temperature of 20 °C, the FL, ADB, CB, and SC significantly differed from the day 0 values after one day post-mortem in all investigated biomechanical properties . Three days post-mortem, all brain regions examined in the study significantly differed from the day 0 values at 20 °C in all biomechanical properties . At 4 °C, the biomechanical changes were much slower. Sample storage at 4 °C for one day did not significantly alter the investigated biomechanical properties of brain tissue. This implies that biomechanical analyses for time since death estimations of brain tissue could be delayed for at least 24 h, potentially even 48 h, by maintaining constant cooling at 4 °C. In practice, this could enable forensic investigators to delay biomechanical analyses for at least a couple of hours, for instance, when other tasks must be prioritized. Beyond that, the tissues could be transferred to a specialized laboratory in a moist 4 °C environment if the forensic team on site is unable to perform the biomechanical analyses immediately. However, it remains unclear if the delayed onset of degradation observed only applies when the tissues are transferred to a 4 °C environment in a fresh state or if it also occurs if initiated at a later stage. This question remains to be addressed in future research. The course of the curves for the investigated biomechanical properties was examined to determine whether general trends apply among the different sampling regions. However, the curves’ progression was region-specific, likely linked to underlying structural differences, including variations in cell types and the white-to-grey matter ratio. As observed at 20 °C, the CB samples exhibited a distinct drop in the investigated biomechanical properties, followed by a slow decline to reach a plateau . At 4 °C, this significant drop was delayed by one day compared to storage at 20 °C. However, it is important to note that cool storage does not imply a simple one-day time delay for biomechanical changes observed at 20 °C storage. For instance, the FL and ADB samples were among the earliest to differ from day 0 samples after just one day post-mortem at 20 °C , but at 4 °C, they were among the more stable sample regions. From a practical perspective, forensic investigators require cut-off values to estimate the time since death with high diagnostic ability. Broadly, the diagnostic ability of ROC curves based on the AUC can be categorized as random (AUC: 0.5–0.6), poor (0.6–0.7), fair (0.7–0.8), good (0.8–0.9), and excellent (0.9–1.0) . However, ROC analyses should be interpreted beyond AUC labels . This study revealed that, when using CB samples stored at 4 °C, a PMI of at least two days could be determined with excellent diagnostic ability when reaching CS mod values below 1435 Pa or S mod values below 1313 Pa. A PMI of at least three days could be determined with good diagnostic ability using a L mod cut-off value of 415 Pa for the CB. For a PMI of at least four days, a good diagnostic ability was achieved using a CS mod cut-off value of 1656 Pa for the SC. In conclusion, the hypothesis that cooling at 4 °C extends the value of biomechanical time since death analyses beyond day one after death, compared to storage at 20 °C, can be accepted. However, in contrast to the results at 20 °C, at 4 °C, it was impossible to differentiate samples with a PMI of one day from fresh samples. Therefore, cooling not only extends the value of biomechanical time since death estimations but also lowers the diagnostic value of the method in the very early post-mortem phase, as the biomechanical properties are kept stable. Importantly, the diagnostic abilities stated above require a constant sample temperature for the given intervals. From a practical standpoint, the tissue temperature post-mortem usually varies over time due to different external influences such as exposure to sunlight or the transfer of body parts between places by the perpetrator. Future investigations should explore to what extent the given diagnostic abilities stated here are lowered under varying degrees of temperature variation throughout the given time frames. Although the diagnostic ability of the CS mod of the SC samples for PMIs of at least four days was good, further analyses are warranted due to the limited number of samples that fell below the cut-off value of 1656 Pa in the given dataset. None of the investigated biomechanical properties of the deep brain samples showed significant differences from day zero within the four testing days post-mortem at a storage temperature of 4 °C. Therefore, future studies should consider extending the analyzed PMI interval of the ADB and PDB at 4 °C to determine their points in time of marked tissue degradation, which are associated with biomechanical changes. Importantly, this study highlighted the temperature sensitivity of the given method. Thus, for biomechanical analyses to be meaningful, knowledge of the temperature curve at the crime scene throughout the past hours to days is crucial. Temperature is a common confounder for forensic time since death estimation and also applies to the established nomogram method of Henssge . Measuring both the ambient temperature and the rectal temperature of the deceased is a standard procedure in every crime scene investigation. Furthermore, local meteorological services can assist in supplying the necessary temperature data to cover the gap between the presumed time of death and the data acquired during the forensic investigation at the scene. When comparing the properties at 4 and 20 °C, the temperature sensitivity was brain region-dependent. It ranged from significant differences throughout all the four testing days in the CS mod values of the ADB samples to no significant differences for any of the tested properties in M&P samples. Especially considering the fair diagnostic ability of M&P samples to determine a PMI of at least three days at 4 °C, its temperature stability between 4 and 20 °C makes it a promising sampling region for biomechanical time since death analyses. The potential use of biomechanical testing for forensic time since death estimation was demonstrated on ovine tissues. As a next step, the findings should be verified on human tissues. So far, the method has been explored at 4 and 20 °C, representing relevant temperatures from a practical perspective. As it seems to be impractical to test each and every temperature value, interpolation might be an option to fill the gaps after some other relevant temperature values have been investigated, e.g. around the human body temperature. Moreover, different body tissues should be explored applying the here stated protocol as their varying tissue structure and location will cause them to biomechanically respond at different times post-mortem, thereby extending the use of biomechanical analyses for time since death estimations beyond the data stated for brain tissue. Firstly, this study had limitations in sample population size. However, increasing the population size is unlikely to improve ROC values, which are the major tool for assessing classification potential. Secondly, this study was conducted on ovine tissues. Although the findings provide a thorough starting point for analyses on human samples, the cut-off values should be verified on human tissues to be valid for forensic purposes. Thirdly, differences in brain size and concomitantly in sampling regions may have contributed to the standard deviations of the presented biomechanical properties, as sample harvesting may have slightly varied each time. Fourthly, it was initially intended to use brains only from healthy sheep in this study. However, as the brains were not tested for medical conditions, unknown (veterinary) pathological alterations invisible upon gross inspection might have influenced the investigated biomechanical properties. Fifthly, handling times within the 24-hour intervals might have varied by minutes. Sixthly, the PBS solution used for sample storage between retrieval and testing might have impacted the results, for example, through tissue swelling. The storage, loss, and complex shear modulus of eight different ovine brain regions remained stable for at least one day post-mortem at 4 °C. Beyond this point, the biomechanical properties changed in a brain region-specific manner. A post-mortem interval of at least two days could be determined with excellent diagnostic ability using cut-off values of 1435 Pa and 1313 Pa for the complex shear modulus and the storage modulus in cerebellar samples, respectively. However, it is essential to consider the post-mortem temperature as a confounder, recognizing considerable region-specific differences in its impact. |
International practice patterns of dyslipidemia management in patients with chronic kidney disease under nephrology care: is it time to review guideline recommendations? | fceea79d-3f0d-45f6-bcd8-393dfa4aca76 | 10210460 | Internal Medicine[mh] | Patients with chronic kidney disease (CKD) have an extremely high cardiovascular disease (CVD) burden, which increases as CKD progresses. CKD may represent the kidney manifestation of the systemic impact of vascular disease under the influence of exposure to risk factors such as dyslipidemia. Despite the lack of evidence of benefit from lipid-lowering therapies (LLT) to reduce the progression of CKD, dyslipidemia is considered a modifiable CVD risk factor in this high-risk population , and LLT has been shown to reduce the risk of atherosclerotic cardiovascular events . Based on the analysis of the evidence specific to CKD patients , the 2012 Kidney Disease: Improving Global Outcomes (KDIGO) Clinical Practice Guideline for Lipid Management in CKD recommended conducting a lipid profile upon diagnosis for CKD to establish the diagnosis of severe hypercholesterolemia and/or hypertriglyceridemia and potentially rule out a remediable (secondary) cause if present. These global nephrology guidelines also recommend that all CKD patients ≥ 50 years, and high-risk younger adult patients, should be treated with a statin with or without ezetimibe regardless of lipid levels. In addition, the guidelines did not recommend a follow-up measurement of lipid levels for most patients. These recommendations were based on the results of several clinical studies but principally the SHARP trial results and two meta-analyses . By contrast, different cardiology society guidelines worldwide have provided LDL-cholesterol (LDL-C) targets for CKD patients according to CKD stages and cardiovascular (CV) patients’ risk, which range from < 55 mg/dL for those considered very high risk (CKD stage 4–5) moving to < 70 mg/dL for those at high risk (CKD 3a-3b) and rising to a maximum of 189 mg/dL for those CKD patients between 40–75 years old and with a 10-year atherosclerotic CVD risk of ≥ 7.5% . However, international variations in practice patterns and adherence to these guidelines have not been described until the present. To evaluate the implementation of these recommendations in real-world clinical practice, we aimed to assess current practice patterns for lipid management in an international cohort of non-dialysis CKD patients under nephrology care. Objectives include describing the prevalence and intensity of statin/ezetimibe prescription, achieved levels of LDL-C, and clinicians’ perceptions of LDL-C goals.
Aim, design, and study setting With this multinational cross-sectional analysis of baseline data from the Chronic Kidney Disease Outcomes and Practice Patterns Study (CKDopps), we aimed to demonstrate the variation between clinical practices regarding lipid management in CKD-non-dialysis patients, including prescription patterns, achieved LDL-C levels, and nephrologists’ targets for LDL-C. Data source The CKDopps is an ongoing prospective cohort study of Stage 3–5 CKD (eGFR < 60 ml/min) patients treated in nephrologist-led CKD clinics in Brazil, France, Germany, and the United States (US) (2013–2019). Unfortunately, data from Japan were unavailable at the time of this analysis. CKDopps sites were randomly selected from CKD clinics after stratification by region and clinic profile (academic vs. private). The criteria used for clinic selection regarding the geographic region, key clinic characteristics, inclusion and exclusion criteria, and study design, details, and objectives have previously been published . No clinical data were collected beyond those performed as part of usual care, as the aim is to evaluate standard nephrology clinic practices. One exception was laboratory measurements in France, where a standard set of urine and blood tests was requested at baseline, including lipids. CKDopps was approved by national and/or local ethics committees, and patient consent was obtained as required by local ethics regulations. Cardiovascular disease and lipids therapy stratification We categorized all cardiovascular diseases as either atherosclerotic CVD (ASCVD) or non-atherosclerotic CVD (referred to as “other CVD”, meaning CVD that is not atherosclerotic). ASCVD was defined by the following diagnoses/events and procedures: angina (stable or unstable), acute myocardial infarction, transient ischemic attack, claudication/rest pain, aortic aneurysm, stroke (ischemic), renal artery stenting and/or angioplasty, cardiac catheterization, coronary angioplasty, coronary bypass graft, carotid endarterectomy, angiogram, arterial bypass surgery, coronary angiogram, percutaneous transluminal angioplasty, and renal angioplasty and/or stenting. Other CVD was defined by the following diagnoses/events and procedures: cardiac arrest/sudden death, congestive heart failure, cardiomyopathy, valvular heart disease, atrial fibrillation, other arrhythmia, pericarditis and/or tamponade, deep vein thrombosis, tachycardia, pulmonary edema due to exogenous fluid, cerebral hemorrhage, ischemic brain damage/anoxic encephalopathy, hemorrhage from a ruptured vascular aneurysm, valve repair or replacement, aortic aneurysm repair, cardioversion, defibrillator placement, pacemaker placement, and pericardial procedure . The composite CV risk is based on comorbidity burden (any history of coronary disease, diabetes, or ischemic stroke) and age. In addition, LLT intensity was categorized into two categories: atorvastatin and rosuvastatin were classified as high intensity, and all other statins were categorized as low intensity: simvastatin, lovastatin, pravastatin, fluvastatin, cerivastatin, and pitavastatin. This classification was chosen due to the lack of statin doses in the CKDopps database. Thus, the definition suggested by most guidelines of considering statin doses to classify them as low vs. moderate vs. high intensity could not be applied here. Statistical analysis We reported the mean or percentages of patient characteristics at enrollment into CKDopps. These are presented for socio-demographics, laboratory values, dyslipidemia prescriptions, and comorbidities, all presented by CKD stage and country. For LDL-C levels, we also presented the results stratified based on a composite measure of CV risk: diabetes, any history of coronary disease, and ischemic stroke and further stratified by age < 50 versus age ≥ 50. The CV risk factors were based on some of the factors listed in the KDIGO recommendations regarding statin use among patients aged 18–49, such as a) known coronary disease (myocardial infarction or coronary revascularization), b) diabetes mellitus, c) prior ischemic stroke and, d) estimated 10-year incidence of coronary death or non-fatal myocardial infarction > 10% . We assessed country-level patterns of care for lipid management, including (a) prevalence and intensity of statin use (high intensity: atorvastatin and rosuvastatin; low intensity: all other statins), (b) frequency of lipid testing, (c) mean LDL-C levels during CKD progression, (d) the distribution of LDL-C by statin use, and (e) nephrologist-reported LDL-C goal upper limits. Models were adjusted for CV risk factor, CKD stage, country, sex, and age. Statins were classified as high intensity (atorvastatin or rosuvastatin) and low intensity (all other types). Linear and logistic regression models were used to obtain p values for comparisons of LDL-C levels and the prevalence of statin and/or ezetimibe treatments. In addition, comparisons were made between age groups (< or ≥ 50), countries, and CKD stages. Linear regression models were used on the mean LDL-C by treatment (including statin intensity), country, and CKD stage. Models used generalized estimating equations with an exchangeable working correlation structure to account for patient clustering by the clinic.
With this multinational cross-sectional analysis of baseline data from the Chronic Kidney Disease Outcomes and Practice Patterns Study (CKDopps), we aimed to demonstrate the variation between clinical practices regarding lipid management in CKD-non-dialysis patients, including prescription patterns, achieved LDL-C levels, and nephrologists’ targets for LDL-C.
The CKDopps is an ongoing prospective cohort study of Stage 3–5 CKD (eGFR < 60 ml/min) patients treated in nephrologist-led CKD clinics in Brazil, France, Germany, and the United States (US) (2013–2019). Unfortunately, data from Japan were unavailable at the time of this analysis. CKDopps sites were randomly selected from CKD clinics after stratification by region and clinic profile (academic vs. private). The criteria used for clinic selection regarding the geographic region, key clinic characteristics, inclusion and exclusion criteria, and study design, details, and objectives have previously been published . No clinical data were collected beyond those performed as part of usual care, as the aim is to evaluate standard nephrology clinic practices. One exception was laboratory measurements in France, where a standard set of urine and blood tests was requested at baseline, including lipids. CKDopps was approved by national and/or local ethics committees, and patient consent was obtained as required by local ethics regulations.
We categorized all cardiovascular diseases as either atherosclerotic CVD (ASCVD) or non-atherosclerotic CVD (referred to as “other CVD”, meaning CVD that is not atherosclerotic). ASCVD was defined by the following diagnoses/events and procedures: angina (stable or unstable), acute myocardial infarction, transient ischemic attack, claudication/rest pain, aortic aneurysm, stroke (ischemic), renal artery stenting and/or angioplasty, cardiac catheterization, coronary angioplasty, coronary bypass graft, carotid endarterectomy, angiogram, arterial bypass surgery, coronary angiogram, percutaneous transluminal angioplasty, and renal angioplasty and/or stenting. Other CVD was defined by the following diagnoses/events and procedures: cardiac arrest/sudden death, congestive heart failure, cardiomyopathy, valvular heart disease, atrial fibrillation, other arrhythmia, pericarditis and/or tamponade, deep vein thrombosis, tachycardia, pulmonary edema due to exogenous fluid, cerebral hemorrhage, ischemic brain damage/anoxic encephalopathy, hemorrhage from a ruptured vascular aneurysm, valve repair or replacement, aortic aneurysm repair, cardioversion, defibrillator placement, pacemaker placement, and pericardial procedure . The composite CV risk is based on comorbidity burden (any history of coronary disease, diabetes, or ischemic stroke) and age. In addition, LLT intensity was categorized into two categories: atorvastatin and rosuvastatin were classified as high intensity, and all other statins were categorized as low intensity: simvastatin, lovastatin, pravastatin, fluvastatin, cerivastatin, and pitavastatin. This classification was chosen due to the lack of statin doses in the CKDopps database. Thus, the definition suggested by most guidelines of considering statin doses to classify them as low vs. moderate vs. high intensity could not be applied here.
We reported the mean or percentages of patient characteristics at enrollment into CKDopps. These are presented for socio-demographics, laboratory values, dyslipidemia prescriptions, and comorbidities, all presented by CKD stage and country. For LDL-C levels, we also presented the results stratified based on a composite measure of CV risk: diabetes, any history of coronary disease, and ischemic stroke and further stratified by age < 50 versus age ≥ 50. The CV risk factors were based on some of the factors listed in the KDIGO recommendations regarding statin use among patients aged 18–49, such as a) known coronary disease (myocardial infarction or coronary revascularization), b) diabetes mellitus, c) prior ischemic stroke and, d) estimated 10-year incidence of coronary death or non-fatal myocardial infarction > 10% . We assessed country-level patterns of care for lipid management, including (a) prevalence and intensity of statin use (high intensity: atorvastatin and rosuvastatin; low intensity: all other statins), (b) frequency of lipid testing, (c) mean LDL-C levels during CKD progression, (d) the distribution of LDL-C by statin use, and (e) nephrologist-reported LDL-C goal upper limits. Models were adjusted for CV risk factor, CKD stage, country, sex, and age. Statins were classified as high intensity (atorvastatin or rosuvastatin) and low intensity (all other types). Linear and logistic regression models were used to obtain p values for comparisons of LDL-C levels and the prevalence of statin and/or ezetimibe treatments. In addition, comparisons were made between age groups (< or ≥ 50), countries, and CKD stages. Linear regression models were used on the mean LDL-C by treatment (including statin intensity), country, and CKD stage. Models used generalized estimating equations with an exchangeable working correlation structure to account for patient clustering by the clinic.
We analyzed 8,194 CKD patients in Brazil (912), France (2,969), Germany (2,761), and the US (1,552) (Table ). The patients were generally similar, but there was some variation by country. Patients from Brazil were usually younger, more often Black, and had more peripheral artery disease. Patients from France had less severe disease (more CKD stage 3 than stage 4), a slightly higher smoking prevalence, and were prescribed ezetimibe more often. Patients from Germany were generally older and had higher HDL-C levels, LDL-C levels, and prevalence of cardiovascular diseases. US patients had lower HDL-C, LDL-C, and hemoglobin levels and a higher prevalence of diabetes. Within each country, the percentage of CKD patients who were female, diabetic, or had high triglyceride levels was higher in stages 4/5 than in stage 3. In contrast, hemoglobin and LDL-C levels tended to be lower in stages 4/5. Overall statin use was similar by country and CKD stage, but the types of statins differed between countries (Fig. A). Among statin users, patients in France and the US used more high-intensity statins (39% and 30% overall) than patients in Brazil (9%) and Germany (4%). Patients with ASCVD, diabetes, or peripheral artery disease had slightly higher statin use within each country, but there was no consistent pattern in the use of high- versus low-intensity statins between patients with versus without these comorbidities (Supplemental Fig. ; see file Supplementary Fig. ). Statin use was higher among patients over the age of 50 compared to patients under the age of 50. Within these age groups, statin use was higher among patients with CV comorbidities or diabetes (Fig. B). Outside Germany, where high-intensity statin use was rare, high-intensity statin use was also generally higher among patients aged 50 + and with CV comorbidities. The upper limit of fasting LDL-C goals by nephrologists varied from country to country (Fig. ). Consistent with the higher LDL-C levels found among their patients, 50–53% (depending on CKD stage) of the German nephrologists surveyed specified an upper LDL-C level of 130 or 160 mg/dL, compared to 13–18% of US nephrologists, 27–33% of French nephrologists, and 41–47% of Brazilian nephrologists. No US nephrologists specified an upper LDL-C limit of 160; only 3–6% of Brazilian and French nephrologists did, while 15–21% of German nephrologists selected this high level. Only 7–17% of nephrologists believed that LDL-C should be < 70 mg/dL, and 38- 68% would choose LDL < 100 mg/dl as a threshold. Within each country, the adjusted difference in mean LDL-C between high- and low-intensity statin categories never exceeded 5.5 mg/dL and was statistically significant only in France. In contrast, the combined high and low categories had an adjusted mean LDL-C that was always significantly lower than the “no statin use” category: -7.6 mg/dL for Brazil ( p -value = 0.019), -25.8 for France ( p -value < 0.001), -19.9 for Germany ( p -value < 0.001), and -21.2 for the US ( p -value < 0.001) (Supplemental Fig. ; see file Supplementary Fig. ). The statin intensity-by-country interaction p-value (6 degrees of freedom) was 0.015, implying that mean LDL-C may vary by country and statin intensity and that the effect of statin intensity may differ across the countries. In each country, LDL-C levels were higher among patients not treated with statins (Fig. ). There was no consistent trend in LDL-C across patients with different eGFR levels (Fig. and Supplemental Fig. ; see file Supplementary Fig. ). German patients had higher LDL-C levels, and US patients had lower LDL-C levels across all eGFR levels independent of serum albumin levels. These observations did not vary by the status of comorbidities such as ASCVD, diabetes, or peripheral artery disease (Supplemental Fig. ; see file Supplementary Fig. ).
In the present study, although there were no major differences in demographic and clinic characteristics between countries, there was a substantial variation in dyslipidemia management across geographies. A similar pattern of LLT underutilization across countries and CKD stages was observed, and different statins (high vs. low intensity) were prescribed in each country. In this group of CKD patients under nephrology care, LDL-C was lower among treated patients and differed significantly by country, with the highest LDL-C levels detected in Germany and the lowest in the US. Also, statin use was higher among patients over 50 and in patients with CV comorbidities or diabetes. These findings reflect a low adherence to evidence-based recommendations in real-world nephrological practice. It is important to mention that, in part, this low-adherence may be a result of the differences in access to treatment due to insurance coverage of medications, particularly in the US. At the patient level, LDL-C did not vary significantly by CKD stage, regardless of statin use. LDL-C levels were also consistently higher for non-statin users in each country (+ 22 mg/dL overall in adjusted models), while low-intensity statin users had higher LDL-C levels than high-intensity statin users (+ 4 mg/dL overall in adjusted models). Different results were also demonstrated in the literature. The Pravastatin Pooling Project demonstrated pravastatin, in our study considered as a low-intensity statin, reduced LDL-C levels by 47.9 ± 24.1 mg/dL and triglyceride levels by 17.3 ± 56.3 mg/dL and raised HDL cholesterol by 2.3 ± 6.0 mg/dL at 12 months . On the other hand, in the Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER), rosuvastatin (high-intensity statin) reduced LDL-C by 52% . It is important to remember that patients with moderate to advanced CKD present a mixed dyslipidemia pattern, with a combination of hypertriglyceridemia, low levels of HDL cholesterol, and variable levels of LDL cholesterol and total cholesterol . In general, the progression of CKD to later stages impacts the lipid profile’s composition, resulting in a more atherogenic profile . Because of the combination of this atherogenic dyslipidemia profile with multiple comorbidities and extremely high CV risk, cardiology guidelines tend to recommend an aggressive and inclusive treatment regimen with statins in patients with CKD not on dialysis. However, all dialysis studies failed to demonstrate a significant reduction in cardiovascular events or mortality with LLT despite significant LDL cholesterol lowering, regardless of different treatment strategies applied . In contrast, the overall and non-dialysis subgroup analysis of the SHARP trial supports the aggressive treatment for CKD non-dialysis patients to reduce CV events. Recently, the International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) and International Study of Comparative Health Effectiveness with Medical and Invasive Approaches—Chronic Kidney Disease (ISCHEMIA-CKD) trials found similar effects in reducing all-cause death or myocardial infarction between initial invasive management compared to initial conservative management, which includes aggressive LDL-C therapies as a standard of care, of patients with chronic coronary disease and moderate to severe ischemia on stress testing without or with advanced CKD . Also, a post-hoc analysis of the Aggressive Lipid-Lowering Initiation Abates New Cardiac Events (ALLIANCE) Study demonstrated that in patients with coronary heart disease and CKD, intensive LLT with higher doses of atorvastatin to achieve a target < 80 mg/dL reduced the relative risk of time to the first cardiovascular event by 28% in patients with CKD (HR, 0.72; 95% CI, 0.54 to 0.97; P = 0.02) and 11% in patients without CKD (HR, 0.89; 95% CI, 0.74 to 1.07; P = 0.3) . In combination, these studies provide additional evidence to the potential benefits of LLT in CKD patients and raises the question: should nephrologists adopt the guidelines from other areas and redefine triggers and targets for LLT? On the other hand, the CKD-REIN study found that lipid goal achievement was not associated with risk of fatal/non-fatal atheromatous CVD or non-atheromatous CVD in patients with non-dialysis CKD . Safety considerations may also temper the use of intensive/high-dose LLT in patients with CKD, as statin-related toxicity is dose-related. An observational study in the general population demonstrated that in comparison with atorvastatin, rosuvastatin was associated with an increased risk of hematuria (HR, 1.08; 95% confidence interval [95% CI], 1.04 to 1.11), proteinuria (HR, 1.17; 95% CI, 1.10 to 1.25), and kidney failure with replacement therapy (HR, 1.15; 95% CI, 1.02 to 1.30) . The risk was higher with a higher rosuvastatin dose . Among patients with eGFR < 30 ml/min per 1.73 m 2 , 44% were prescribed daily high dose rosuvastatin (20 or 40 mg daily), which exceeds the FDA’s recommended 10 mg daily dose. These findings suggest the need for caution in prescribing and monitoring rosuvastatin, especially in patients receiving high doses or who have severe CKD. In this case, the difference in doses of statin LLT seems to influence patient outcomes . Another important point to be considered regarding safety, is the potential statins have of inducing rhabdomyolysis , because in patients with CKD it is important to avoid measures that could exacerbate kidney disfunction. Individualized treatment is a keystone to minimize those safety issues and improve outcomes in our patients. Our study demonstrated that a substantial proportion of hyperlipidemic CKD patients are not receiving LLT, and 7–23% of untreated patients in each country had LDL-C ≥ 160 mg/dL. The kidney-focused KDIGO guidelines recommend no lipid goals or follow-up lipid testing, instead espousing a ‘fire-and-forget’ strategy of fixed-dose, moderate-intensity statin, or statin-ezetimibe therapy . In contrast, the American Heart Association/American College of Cardiology (AHA/ACC) guidelines utilize LDL-based and ASCVD-risk-based thresholds for statin therapy among CKD patients but also do not stipulate treatment goals; they recommend a moderate-intensity statin alone or combined with ezetimibe for adults 40–75 years of age with LDL-C 70–189 mg/dL (1.7–4.8 mmol/L) who are at 10-year atherosclerotic CVD risk of ≥ 7.5% . Conversely, European and UK guidelines recommends treat-to-goals strategies. For example, the European Society of Cardiology/European Atherosclerosis Society (ESC/EAS) guidelines distinguish patients with G3a-3b as high risk, and eGFR G4-5ND as very high risk, with a treatment goal of ≥ 50% LDL-C reduction from baseline and an LDL-C goal of < 1.8 mmol/L (< 70 mg/dL) for high-risk patients, and a goal of < 1.4 mmol/L (< 55 mg/dL) for very high-risk patients . The UK Renal Association guidelines recommend goals for total cholesterol (≤ 4 mmol/L), LDL (≤ 2 mmol/L), and non-HDL (≤ 2.5 mmol/L) . Our CKDopps nephrologist survey demonstrated the most common LDL-C goal was < 100 mg/dL across regions, regardless of CKD stage, but only 8–19% of nephrologists would aim for < 70 mg/dL for G4-5 patients, as per the current ESC guidelines for ‘very high risk’ patients. LDL-C levels did not appear to vary with eGFR in our analysis. The CKD-REIN study previously demonstrated that only 45% of ‘high-risk’ patients and 29–38% of patients at ‘very high risk’ achieved the LDL-C goal, based on the 2016 ESC/EAS guidelines, which recommended less aggressive targets than the current guidelines . In the current study, overall statin use ranged from 51–61% of patients in countries included in this analysis. These findings are similar to a recent Canadian cross-sectional study of CKD patients, in which approximately 63% of statin-eligible patients were taking a statin . This study also demonstrated CKD patients had about five times the odds of receiving statin therapy for secondary vs. primary prevention. Patients planning for conservative care had lower odds of being prescribed a statin than patients planning for dialysis . There are several possible reasons why nephrologists may not prescribe statins for CKD patients, particularly for primary prevention. Respondents to a Canadian nephrologist survey cited some reasons, including disagreement with KDIGO guidelines in favor of a patient-individualized approach that considers life expectancy and the cause of CKD . For example, for older patients with limited life expectancy, some nephrologists were concerned with the lack of evidence of benefit with statins, higher risk of adverse effects, and increased pill burden. The AHA/ACC does indicate it may be reasonable to stop statin therapy among patients > 75 years of age who have functional decline, multimorbidity, frailty, or reduced life expectancy . While the SHARP trial did show evidence of a benefit for statin plus ezetimibe among the subgroup of CKD patients > 70 years of age (risk ratio 0.78, 95% CI 0.65–0.89) , there remains uncertainty about the benefit-risk ratio of statin use for primary prevention in people > 70 years of age in the general population. Our study has some limitations. First, there is some heterogeneity in study protocols. For example, in France, lab data were drawn according to a country-specific protocol and, therefore, not included in the analysis of lipid monitoring which may compromise the results’ generalizability. Another limitation of this study is the absence of statin dose data, which made necessary an adjustment on the statin intensity classification compared to what is suggested by the guidelines. On the other hand, this study’s strengths are that this is a large, international cohort in academic and community settings and, therefore, may reflect the real-world dyslipidemia management in CKD patients under nephrology care. In conclusion, there is substantial variation in practice patterns regarding lipid-lowering therapies across countries but not across CKD stages. Patients on LLT have lower LDL-C, yet in contrast to the evidence-based guideline recommendations, a significant proportion of CKD patients with dyslipidemia managed by nephrologists are not receiving LLT. Despite the literature supporting LLT in the CKD population with care in dose prescription, our study suggests that the nephrology community needs to review the recommendations and improve the implementation of these guidelines in clinical practice, which may lead to a reduction in the burden of CVD in the CKD population. Further comparative effectiveness studies assessing the effects of a ‘fire-and-forget’ strategy vs. a treat-to-target strategy on patient outcomes are needed to inform the optimal approach to lipid management in patients with non-dialysis CKD.
Additional file 1: Supplementary Figure 1. Prevalence and intensity of statin use by country and other patient strata. Atorvastatin and rosuvastatin are categorized as high intensity; all other statins are categorized as low intensity: simvastatin, lovastatin, pravastatin, fluvastatin, cerivastatin, and pitavastatin. Additional file 2: Supplementary Figure 2. Mean LDL-C during CKD progression, by country and other patient strata. Additional file 3: Supplementary Figure 3. Distribution of LDL-C (mg/dL) by statin use and by other patient strata. Additional file 4: Supplementary Figure 4. Adjusted mean LDL-C (mg/dL) by country and statin use. Legend: LDL-C levels adjusted to average age, sex, CKD stage, and comorbid risk status through a linear regression model.
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Double-stem Hairpin Probe and Ultrasensitive Colorimetric Detection of Cancer-related Nucleic Acids | d3cc70b8-aa35-466a-8be9-f71710364d88 | 4737720 | Pathology[mh] | With advances in molecular biology, nucleic acids (DNA and RNA) detection has been routinely identified as a highly-valued tool for disease monitoring and genetic disorders screening, , which can provide valuable information on biological research, medical science and clinical diagnosis. Especially in the diagnosis and treatment of malignant tumors, oncogene and tumor suppressor gene closely associated with tumor progression are often present at a very low concentration, and their expression levels may provide useful clues for clinical application as well as anticancer drug development. Moreover, gene mutations and change in gene expressing levels often are the early molecular events, and the tumor therapy at the early stage is successful in more than 95 percent of cases. Accordingly, nucleic acid detection has been a topic of significant interest, where various amplification strategies, including polymerase chain reaction (PCR), were employed to interrogate nucleic acid levels. - However, each sensing method has its own advantages and disadvantages with respect to simplicity, sensitivity, operational simplicity, design flexibility and cost. For example, the inherent drawbacks of PCR, such as expensive instruments, complicated procedure, false positive results, and skilled technician, hamper its practical applications in some extent. Further efforts are still needed to address the serious clinical challenge. Additionally, to perform the public and periodic disease screening, it is equally important to simplify the signaling probe design, to reduce the dependence on the medical instruments and to decrease the assay cost, because these improvements can make the sensing platform more readily available and affordable to the people especially in the underdeveloped areas. Thus, development of reliable, convenient and cost-effective screening tools (e.g., visual inspection without any instrument) for nucleic acids detection still remains imperative. Out of the various sensing DNA probes, molecular beacon (MB) is the most attractive probe for DNA detection due to its operation convenience without separation and better specificity than linear DNA probe originating from its hairpin structure. Conceptually, fluorescent MB is a single-strand nucleic acid probe with the terminally-attached fluorophore and quencher, where the loop portion contains the sequence complementary to target DNA (usually 15-30 bases) and the stem consists of two self-complementary fragments (5-7 bases). In the absence of the target, a stem-loop structure holds the terminal fluorophore/quencher pair in proximity and the fluorescence is quenched. The hybridization of target DNA to loop portion can force the fluorophore and quencher moieties to separate, inducing the fluorescence restoration and producing the detectable signal. In essence, one target DNA only causes the opening of one MB. Namely, the target DNA is detected in a one-to-one manner, and the detection sensitivity of MB is only partially successful. , Therefore, to improve further the assay performance, MB, as well as the analogous hairpin probe, was combined with various amplification techniques, for example, hybridization chain reaction, nicking enzyme signal amplification, exonuclease-aided target recycling, strand displacement amplification (SDA), , and rolling circle amplification (RCA). Although considerable research efforts on the innovation and potential application of MBs have been made to implement the amplification detection of nucleic acids, MB-based sensing techniques still suffer from some inherent limitations in some aspects. For example, DNA sticky-end pairing between molecular beacons sometimes takes place especially when long self-complementary base fragments are involved. , In this case, not only is no fluorescence signal detected even if increasing the target DNA concentration but also non-fluorescent hairpin probe-based sensing systems are unsuccessfully constructed. More stable intramolecular hybridization of hairpin probes is expected to improve the detection specificity and endows the probe with the addition design flexibility, but intermolecular sticky-end pairing is more likely to occur. Therefore, up to now, no MB or analogous hairpin probe with a long stem has been reported. This seems to be a challenging yet promising stepping stone toward achieving synergetic effect of hairpin probes and efficient signal amplification strategies for a variety of new diagnostic screening and biomarker discovery applications. The discovery of the horseradish peroxidase (HRP) mimicking hemin/G-quadruplex DNAzyme and related studies provide a good chance for developing a powerful biosensor. , The hemin/G-quadruplex complex, as one fascinating DNAzyme, possesses several attractive features superior to protein enzymes, such as high thermal stability, simple synthesis, low cost and easy modification. Significantly, DNAzyme sequence can be delicately programmed to implement the unique function, for example, being woven into the common nucleic acid sequence to construct a catalytic DNA biosensing probe or DNA biosensing nanowires , and being split into two or more separate molecules to achieved the expected objectives. , Thus, the catalytic utility of G-quadruplex DNAzyme can be compatible with different amplification techniques in a controlled and predictive fashion, leading to several impressive biosensing systems on the basis of nicking enzyme-assisted DNA replication, RCA, , and PCR. In this contribution, using p53 cancer suppressor gene as a model analyte, a novel double-stem-contained hairpin probe (DHP) (essentially label-free MB containing very stable stems) was developed for the ultrasensitive colorimetric detection of DNA hybridization. Into the DHP, we simultaneously introduced a binding site of nicking enzyme and two stems, one of which consisted of long G-rich fragment and its complementary fragment. Contrary to the conventional view that the strong base pairing of hairpin probes readily causes the formation of intermolecular hybridization-based DNA duplexes, , no intermolecular interaction among DHPs occurs. Thus, although only two types of label-free oligonucleotides are involved in the colorimetric sensing system, target binding can easily induce cascade amplification via forcing the DHP to undergo a large-amplitude conformational transition and generates a copious amount of horseradish peroxidase (HRP)-mimicking DNAzyme. This enzyme can catalyze the oxidation of ABTS by H 2 O 2 to a green colored product ABTS• + , producing an exponentially amplified colorimetric signal and improving the intrinsic assay specificity of hairpin probes. As a result, as low as 1 fM p53 gene can be detected and point mutations are easily identified by the naked eye. As a proof-of-concept study, the advanced capabilities of DHP together with the intriguing properties, such as cost-saving and easy construction, are expected to promote the application of hairpin probes in basic research and medical diagnosis.
Materials and reagents Nt. BbvCI endonuclease, Klenow Fragment (3'-5' exo-) polymerase and low DNA ladder were ordered from New England Biolabs (USA) Ltd, while deoxynucleotide triphosphates (dNTPs) were purchased from Dingguo Changsheng Biotechnology Co., Ltd (Beijing, China). The 25 mM tris-buffer (100 mM NaCl, 50 mM KAc, 10 mM MgAc 2 and 1 mM DTT, pH 8.2) was used as the reaction solution. Hemin and ABTS were supplied by Sigma-Aldrich Co. LLC, and H 2 O 2 was from Xilong Chemical Co., Ltd. All chemicals were of analytical reagent grade and used as received unless otherwise stated. Double-distilled water, purified by a Kerton lab MINI water purification system (UK) with electrical resistivity of 18.25 MΩ, was used throughout this study. Oligonucleotide strands designed in this study were synthesized and PAGE-purified by Invitrogen Bio Inc. (Shanghai, China). Their sequences are listed in Table , and the secondary structure of DHP (seen in Figure ) was determined by the online “mfold” program ( http://mfold.rna.albany.edu /). The stock solution of oligonucleotides was prepared in 1× TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0) and stored at 4 ℃ before usage. Instruments Absorbance measurements were taken using a UV-2700 spectrophotometer (Shimadzu, Japan) in the wavelength range of 380-500 nm at room temperature, and the absorption value at 417 nm was recorded to evaluate the proposed assay performance and to quantify target molecules in samples. pH value was determined by a pHS-3C digital pH meter (Ohaus Instrument Plant, Shanghai, China), and the reaction temperature was controlled by a TU-200 Block Heater (Yiheng Co. Ltd., Shanghai, China). Canon D3200 was used to visualize the resulting solution. DHP-based sensing procedure Prior to experiments, DHP was heated to 90 ℃ for 5 min and allowed to cool down to room temperature slowly. Subsequently, 16 μL of tris-buffer, 3 μ of 5 μM DHP, 3 μL of 5 μM P2 (the primer optimization is shown in Figure ), and 3 μL of p53 gene at varied concentrations were thoroughly mixed and the hybridization was allowed to proceed at room temperature for 1 h. Then 1 µL of 10 mM dNTPs, 0.5 µL of 5 U/µL Klenow Fragment (3'-5' exo - ) polymerase, and 0.5 µL of 10 U/µL Nt. BbvCI endonuclease were consecutively added to the resulting mixture to launch the amplification reaction at 37 ℃ for 40 min with gentle vortex. Followed by incubation at 80 ℃ for 20 min to terminate the activity of enzymes as recommended by the manufacturer, a droplet of 20 μM hemin (3 µL, dissolved by DMSO) was injected and incubated at 37 ℃ for another 1 h to form the DNAzymes. Finally, 82.5 µL of 2× HEPES buffer (50 mM HEPES, 20 mM KCl, 0.4 M NaCl, 2% DMSO, 0.1% Triton X-100, pH =5.2), 5 µL of 18 mM ABTS, and 2.5 µL of 4 mM H 2 O 2 were added to the reaction solution to initiate the catalytic reaction. Notably, the volume of the isothermal amplification reaction and the final oxidation reaction are 30 μL and 120 μL, respectively. We calculated the concentration of DHP, P2, target DNA, and hemin from the 30-µL solution, while the concentration of ABTS and H 2 O 2 mentioned in the text was that in 120-µL solution. After 30-min incubation, the absorption spectra of resulting samples were collected. Unless otherwise specified, the experiments were carried out under identical conditions except for only one issue of interest when investigating the factors that influence the assay performance of the present colorimetric sensing system. Asymmetric PCR amplifications Genomic DNA was extracted from the clinical revelant human lung cancer cell line A549 by the universal Genomic DNA exaction kit (from Takara Biotechnology Co. Ltd.) when the cells were cultured to desired density. Asymmetric PCR adopted frequently to generate the single-stranded target strand besides the double-stranded DNA was performed to amplify the codon 273 of p53 gene. The following primers designed with the help of Primer Premier 5.0 software were used: Sense primer 1: 5'-GCTTTGAGGTGCGTGTTT-3'; Anti-sense primer 1: 5'-GTGAGGCTCCCCTTTCTT-3'. Briefly, asymmetric amplification was achieved by thermal cycling for 30 cycles in a total volume of 50 μL of 1× PCR buffer containing 1 μM Forward primer, 0.2 μM Reverse primer, 5 U of Taq polymerase, 0.15 μM dNTP mixture, and 3.4 μg of genomic DNA. Each PCR cycle was initiated by 5 min of denaturation at 94 ℃, followed by 30 s at 94℃, 30 s at 55℃, 55 s at 72 ℃, and then a final extension at 72 ℃ within a time-period of 7 min. Finally, 12% native-PAGE gel electrophoresis was used to verify the amplified products. For control asymmetric PCR amplification, another pair of primers (Sense primer 2: 5'-GAGGTAAGCAAGCAGGACA-3'; Anti-sense primer 2: 5'-GCAAGGAAAGGTGATAAAAGT-3') were used. The amplification experiment was conducted under identical conditions as described above.
Nt. BbvCI endonuclease, Klenow Fragment (3'-5' exo-) polymerase and low DNA ladder were ordered from New England Biolabs (USA) Ltd, while deoxynucleotide triphosphates (dNTPs) were purchased from Dingguo Changsheng Biotechnology Co., Ltd (Beijing, China). The 25 mM tris-buffer (100 mM NaCl, 50 mM KAc, 10 mM MgAc 2 and 1 mM DTT, pH 8.2) was used as the reaction solution. Hemin and ABTS were supplied by Sigma-Aldrich Co. LLC, and H 2 O 2 was from Xilong Chemical Co., Ltd. All chemicals were of analytical reagent grade and used as received unless otherwise stated. Double-distilled water, purified by a Kerton lab MINI water purification system (UK) with electrical resistivity of 18.25 MΩ, was used throughout this study. Oligonucleotide strands designed in this study were synthesized and PAGE-purified by Invitrogen Bio Inc. (Shanghai, China). Their sequences are listed in Table , and the secondary structure of DHP (seen in Figure ) was determined by the online “mfold” program ( http://mfold.rna.albany.edu /). The stock solution of oligonucleotides was prepared in 1× TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0) and stored at 4 ℃ before usage.
Absorbance measurements were taken using a UV-2700 spectrophotometer (Shimadzu, Japan) in the wavelength range of 380-500 nm at room temperature, and the absorption value at 417 nm was recorded to evaluate the proposed assay performance and to quantify target molecules in samples. pH value was determined by a pHS-3C digital pH meter (Ohaus Instrument Plant, Shanghai, China), and the reaction temperature was controlled by a TU-200 Block Heater (Yiheng Co. Ltd., Shanghai, China). Canon D3200 was used to visualize the resulting solution.
Prior to experiments, DHP was heated to 90 ℃ for 5 min and allowed to cool down to room temperature slowly. Subsequently, 16 μL of tris-buffer, 3 μ of 5 μM DHP, 3 μL of 5 μM P2 (the primer optimization is shown in Figure ), and 3 μL of p53 gene at varied concentrations were thoroughly mixed and the hybridization was allowed to proceed at room temperature for 1 h. Then 1 µL of 10 mM dNTPs, 0.5 µL of 5 U/µL Klenow Fragment (3'-5' exo - ) polymerase, and 0.5 µL of 10 U/µL Nt. BbvCI endonuclease were consecutively added to the resulting mixture to launch the amplification reaction at 37 ℃ for 40 min with gentle vortex. Followed by incubation at 80 ℃ for 20 min to terminate the activity of enzymes as recommended by the manufacturer, a droplet of 20 μM hemin (3 µL, dissolved by DMSO) was injected and incubated at 37 ℃ for another 1 h to form the DNAzymes. Finally, 82.5 µL of 2× HEPES buffer (50 mM HEPES, 20 mM KCl, 0.4 M NaCl, 2% DMSO, 0.1% Triton X-100, pH =5.2), 5 µL of 18 mM ABTS, and 2.5 µL of 4 mM H 2 O 2 were added to the reaction solution to initiate the catalytic reaction. Notably, the volume of the isothermal amplification reaction and the final oxidation reaction are 30 μL and 120 μL, respectively. We calculated the concentration of DHP, P2, target DNA, and hemin from the 30-µL solution, while the concentration of ABTS and H 2 O 2 mentioned in the text was that in 120-µL solution. After 30-min incubation, the absorption spectra of resulting samples were collected. Unless otherwise specified, the experiments were carried out under identical conditions except for only one issue of interest when investigating the factors that influence the assay performance of the present colorimetric sensing system.
Genomic DNA was extracted from the clinical revelant human lung cancer cell line A549 by the universal Genomic DNA exaction kit (from Takara Biotechnology Co. Ltd.) when the cells were cultured to desired density. Asymmetric PCR adopted frequently to generate the single-stranded target strand besides the double-stranded DNA was performed to amplify the codon 273 of p53 gene. The following primers designed with the help of Primer Premier 5.0 software were used: Sense primer 1: 5'-GCTTTGAGGTGCGTGTTT-3'; Anti-sense primer 1: 5'-GTGAGGCTCCCCTTTCTT-3'. Briefly, asymmetric amplification was achieved by thermal cycling for 30 cycles in a total volume of 50 μL of 1× PCR buffer containing 1 μM Forward primer, 0.2 μM Reverse primer, 5 U of Taq polymerase, 0.15 μM dNTP mixture, and 3.4 μg of genomic DNA. Each PCR cycle was initiated by 5 min of denaturation at 94 ℃, followed by 30 s at 94℃, 30 s at 55℃, 55 s at 72 ℃, and then a final extension at 72 ℃ within a time-period of 7 min. Finally, 12% native-PAGE gel electrophoresis was used to verify the amplified products. For control asymmetric PCR amplification, another pair of primers (Sense primer 2: 5'-GAGGTAAGCAAGCAGGACA-3'; Anti-sense primer 2: 5'-GCAAGGAAAGGTGATAAAAGT-3') were used. The amplification experiment was conducted under identical conditions as described above.
The design of DHP and working principle In the present study, to execute the multifunctional signal amplification, the DHP is designed to contain four regions: G-quadruplex sequence, nicking endonuclease-binding site, polymerization primer-binding fragment and target DNA recognition segment. The base sequence of each region of DHP is illustrated in Table , while its secondary structure is shown in Figure (mentioned above). DHP is abbreviated from double-stem-contained hairpin probe, containing stem I and stem II as its name implies. One can see that, for DHP, polymerization primer-binding site is locked by stem I, G-quadruplex fragment is locked by its complementary fragment (forming the stem II), and only a half of nicking endonuclease-binding site is involved. Thus, the DHP-based sensing system does not exhibit obvious absorption peak in the UV-vis spectrum. Note that the proposed DHP does not form the sticky-end pairing-based dimer but folds into a unique hairpin structure with two stems containing 25 base pairs. This is an important achievement that can be met without resort (supporting data seen below), establishing the molecular foundation of the present colorimetric assay strategy. The working principle of DHP for the colorimetric detection of DNA hybridization is illustrated in Scheme . In the absence of target, because the DHP were tightly locked by stem I and stem II, the primer could not bind to DHP and G-quadruplex structure is incapable of being formed. Thus, the subsequent enzymatic reaction and signaling do not occur. In contrast, when target gene hybridizes with DHP (step ①), the rigid duplex helix gives rise to a configuration change of DHP and open the hairpin structure of stem I, facilitating the binding of DHP to P2. With the aid of polymerase (step ②), the 3' end of P2 is allowed to extend on DHP and the stem II is completely unfolded. Thus, besides the hybridized target is displaced, the G-rich fragment is released and folds into the G-quadruplex structure, and perfect recognition site of Nt. BbvCI is formed, executing a large-amplitude conformational transition. In the step ③, nicking reaction leads to the generation of new primer and induces the subsequent polymerization, as well as the displacement of pre-replicated G-rich fragment. The nicking, polymerization and displacement can be repeated continuously, resulting in the accumulation of G-quadruplex molecules. Upon addition of hemin, the G-quadruplex can bind to hemin and forms the DNAzyme that has the catalytic activity similar to horseradish peroxidase, catalyzing the oxidation of ABTS by H 2 O 2 and producing the amplified colorimetric signal (step ④). Moreover, the displaced target DNA obtained from the step ② can in turn induce the next round of hybridization, polymerization, nicking and signal conversion, amplifying further the target DNA hybridization event (step ⑤). As a result, an exponentially amplified colorimetric signal is expected to be achieved, enabling the reliable detection of trace target elements. By the way, besides mentioned-above exceptional structural features of DHP, no any signal loss occurs for the present colorimetric sensing system compared with traditional nicking/polymerization-based amplification assays. , Specifically, as illustrated in Scheme S1, the G-quadruplex fragments constantly generated from step ③ are not consumed by hybridizing with DHPs for two reasons: 1) The dual-stem structure makes the DHP stable enough so that it is not easy to open it; 2) even if DHP is opened by displaced G-rich fragments, the G-quadruplex fragment locked by stem II could be released and form an equal amount of DNAzyme. Thus, the likely signal loss is completely circumvented. To demonstrate this important mechanism, Ns with the same base sequence as the nicked/displaced G-quadruplex strand was designed (seen in Table ), and the corresponding experiments were performed under identical conditions. The measured data were collected and analyzed in Figure . Feasibility of the proposed DHP for target DNA detection Since the DHP is a novel hairpin probe with very stable stems, the feasibility of colorimetric sensing strategy should be verified at the initial stage. For this purpose, the DNA colorimetric assay and different control experiments were performed, and the measured data are shown in Figure A. One can see that there is no obvious difference in absorption spectrum between lines a, b and c, indicating that the DHP can tightly self-lock due to the introduction of its two stems and no free DNA-quadruplex fragment exists even if target DNA was added. In the presence of polymerase, as illustrated in the difference between line d and line e, only a slight absorption peak increase is observed. Excitingly, compared with line f, a dramatic absorption increase is seen in line g where nicking enzyme existed, suggesting that a large number of G-quadruplexes were generated during the autonomous polymerization/scission/displacement cycle and formed the expected catalytic DNAzyme in the presence of hemin. Thus, the optical signal of the proposed colorimetric sensing system can reflect the existence of DNA target. Apparently, three different sensing systems are studied in this section: non-amplification system (system I, line b and c), polymerization amplification system (system II, line d and e), and polymerization/nicking amplification system (system III, line f and g). To obtain the accurate comparative data on the assay performance of sensing systems involved, the optical signals, including the background-subtracted absorption intensity and absorption peak ratio of the target sample to blank, were quantitatively evaluated, and the detailed results are shown in Figure B. The system III (namely, the proposed colorimetric assay) exhibits the most desirable sensing performance. In fact, this optical signal changing trend can be observed by the naked eye. Figure C displays the representative photographs corresponding to different samples depicted in Figure A. We can see that a remarkable color change occurs in sample g, while all other samples are almost colorless, strongly further convincing that the DHP is rationally designed to execute the amplification detection of target DNA. In the contribution, we for the first time proposed the DHP with a unique hairpin structure and developed a new amplification sensing system via combining with polymerization and nicking. Although this probe has the self-complementary 25-base fragment, it does not form the sticky-end pairing-based dimer. To confirm the unpredictable molecular structure of DHP and the utility of polymerase and endonuclease, native polyacrylamide gel electrophoresis (PAGE) was used to explore the mechanism of the designed sensing system. The experimental results are represented in Figure . Optimization of experimental conditions In order to achieve the best sensing performance, the effect of the hemin concentration, enzymatic reaction time and H 2 O 2 incubation time were investigated, respectively. The ration of A/A 0 was adopted to evaluate the sensing ability, where A and A 0 represent the absorption peak in the presence and absence of target DNA, respectively. As illustrated in Figure A, the value of A/A 0 first increased with the increase of hemin concentration. The maximal ratio value was achieved when hemin at 2 μM was employed. Then, signal decreased at higher concentration. This is reasonable. In the low hemin concentration range, more hemin molecules can produce more DNAzyme units responsible for the higher signal. However, when the concentration of hemin is more than 2 μM, the background increases and deteriorates the assay performance. Thus, we chose 2 μM as the favorable one for subsequent experiments. The enzymatic reaction time is explored as shown in Figure B. The absorption ratio of the solution increases with the increase of reaction time up to 40 min and then levels off. Therefore, the period of 40 min is preferred for the isothermal amplification. The influence of H 2 O 2 incubation time can be seen in Figure C, and the A/A 0 is found to increase with the incubation time increase and almost reaches equilibrium at 30 min. Thus, we chose 30 min for ABTS oxidation. Analytical performance of DHP Once possessing the capability to accurately recognize and quantify disease-related genes, especially those associated with cancers, the new biosensing probe would hold considerable promise for early disease diagnosis and monitoring of treatment progress. To evaluate the utility of DHP with unique structural features, different concentrations of target DNA ranging from 0 to 200 nM were prepared and analyzed by this colorimetric sensing system. The UV-vis absorption spectra are collected in Figure A, while the corresponding absorption peak is recorded in Figure B. It could be seen that an obvious monotonic increase in absorption intensity is observed when increasing target concentration from 0 and 150 nM, and no obvious signal change could be achieved even at the higher target concentration, for example, 200 nM. Excitingly, as low as 1 fM target DNA, equal to the DNA levels in physiological samples, can still induce a detectable signal compared to the blank sample, and thus we define it as the limit of detection (LOD), representing an impressive improvement in term of assay sensitivity. For example, two classical catalytic beacons in the literature reports , only offer the detection limit of 2 nM and 200 nM, respectively. Namely, the DHP-based colorimetric sensing system can achieve over 6 or 8 orders of magnitude improvement in the detection sensitivity. More details on the sensitivity comparisons with other impressive previously-reported signal amplification strategies, including the methods based on the versatile nanomaterials and electrochemical measurement that is well known to be an extremely sensitive signaling technique, are provided in Table . It is clear and unambiguous that the newly-proposed DHP colorimetric assay can offer a very exciting LOD at least 20 times lower than the literature values. , - The measured data demonstrates that this homogenous signaling platform is efficient for ultrasensitive colorimetric detection of DNA hybridization. It is worth pointing out that, compared with these sensing systems, , - besides desirable LOD, the dynamic response range is substantially widened, including two linear calibration curves different from each other in the low and high target concentration. Figure C displays a good linear relationship between the peak absorption value (Y) and the logarithmic concentration of target DNA (X) in the range from 1.0 fM to 1 nM with a calibration curve fitted to the equation: Y= 0.340+ 0.0049 LogX (R 2 = 0.9910). Figure D presents the linear dynamic response to target DNA in the concentration range from 1 nM to 150 nM, and the regression equation can be expressed as Y= 0.2905+ 0.0043X (R 2 = 0.9964). It should be easy to understand two different linear relationships. On the whole, two types of reactions can contribute to the detectable signal: primary target DNA hybridization (step ①) and subsequent amplification (steps ②, ③ and ⑤). The former plays a major role in signal conversion in the high target concentration range, while the latter is largely responsible in the low target concentration range. Since there is the difference in signaling process between high and low concentration ranges, two different linear relationships could be obtained. Detection specificity Gene mutation is a very common phenomenon occurred frequently in some biological events. A large number of human diseases have been known to originate from gene mutation, and the information on gene mutation is expected to provide direct insight into molecular mechanisms of some diseases and to promote the targeted therapy. Thus, reliably distinguishing mutant target DNA from the wild type one is of great significance. To evaluate the detection specificity of the current colorimetric sensing system, different target DNAs, including complementary target DNA (T), single-base mutant DNA (MT1), two-bases mutant DNA (MT2), and three-base mutant DNA (MT3), were detected under identical experimental conditions, and the measured data are comparatively depicted in Figure . As can be seen, mutations existing in every target DNA induce a substantial decrease in signal intensity. Specifically, if the optical signal triggered by complementary target gene is defined as 100%, the signal intensity corresponding to MT1, MT2, and MT3 are 33.6%, 16.4%, and 1.9%, respectively, reflecting that the newly-proposed DHP possesses an excellent specificity. Clearly, the capability to distinguish the single-base mismatched targets has been fundamentally improved compared with literature values (about 75% and 95% ) offered respectively by common MB and adapted one (LMB). More excitingly, as shown in Figure Inset, all mutant target DNAs can be easily visualized by the naked eye according to the distinct color changes. Note that the MT1 is the mutant type DNA identified as one of the oncogenes, and the reliable identification of MT1 indicates the potential application of DHP in clinical settings to a certain extent. Undoubtedly, the excellent analytical performance achieved should be attributed to the unique DHP and efficient signaling scheme to amplify DNA hybridization event. Several issues should be mentioned: stem I that inhibits the primer binding, stem II that locks the folding of pre-incorporated G-rich fragment into DNAzyme and binding site for nicking endonuclease responsible for the successive generation of new primer. In this case, besides the low background in the absence of target DNA, the synergetic effect of nicking and polymerization causes the target DNA cycle and in turn the exponential accumulation of DNAzyme products, and no any signal loss occurs, enabling the detection of trace targets. Meanwhile, stem I and stem II enhance the stability of DHP hairpin in a cooperative manner, making the detection specificity higher. Essentially, all the distinct advantages are based on the successful design of DHP. In fact, DHP is a more stable hairpin probe than common MB to some degree, but it is never reported because of the difficulty of obtaining the highly stable intramolecular hairpin. The functional fragments of DHP are shown in Scheme S2. Its part I consisting of loop and stem I is similar to the classical MB, and part II have Stem II and ss (single-stranded) fragment. While the ss fragment severs as the bridge between the stem I and stem II and stabilizes further the part I, the stem can be opened by target DNA hybridization, but stem II is still in the close state (no signal detected in line c of Figure A). On the basis of theoretical analysis and our own experience, when each of oligonucleotides contains more than 9 complementary base pairs, the dimer via intermolecular interaction is easily formed. Thus, the construction of two stem-contained DHP with 25 base pairs is a very inspiring achievement in the development of DNA sensing probe. Presumably, the stem II is a unique double-stranded fragment (rather than a common ds DNA) composed of a G-quadruplex sequence and its complementary segment and promotes the intramolecular hybridization. The present study is expected to give invaluable insight into the DNA probe design and clinic genetic diagnosis. Target DNA detection in human serum samples To verify the potential application of the proposed DHP to complex biological samples, we conducted the recovery tests by adding varying amounts of target DNA into the sensing system containing 1% human serum (kindly provided by Fuzhou general hospital of Nanjing military command). As demonstrated in Table , the recoveries for the spiked target DNA are in the range of 99-106%, suggesting that the developed DHP is a promising tool for possible applications since human serum is one of the most challenging media with a variety of proteins and other serious interference.
In the present study, to execute the multifunctional signal amplification, the DHP is designed to contain four regions: G-quadruplex sequence, nicking endonuclease-binding site, polymerization primer-binding fragment and target DNA recognition segment. The base sequence of each region of DHP is illustrated in Table , while its secondary structure is shown in Figure (mentioned above). DHP is abbreviated from double-stem-contained hairpin probe, containing stem I and stem II as its name implies. One can see that, for DHP, polymerization primer-binding site is locked by stem I, G-quadruplex fragment is locked by its complementary fragment (forming the stem II), and only a half of nicking endonuclease-binding site is involved. Thus, the DHP-based sensing system does not exhibit obvious absorption peak in the UV-vis spectrum. Note that the proposed DHP does not form the sticky-end pairing-based dimer but folds into a unique hairpin structure with two stems containing 25 base pairs. This is an important achievement that can be met without resort (supporting data seen below), establishing the molecular foundation of the present colorimetric assay strategy. The working principle of DHP for the colorimetric detection of DNA hybridization is illustrated in Scheme . In the absence of target, because the DHP were tightly locked by stem I and stem II, the primer could not bind to DHP and G-quadruplex structure is incapable of being formed. Thus, the subsequent enzymatic reaction and signaling do not occur. In contrast, when target gene hybridizes with DHP (step ①), the rigid duplex helix gives rise to a configuration change of DHP and open the hairpin structure of stem I, facilitating the binding of DHP to P2. With the aid of polymerase (step ②), the 3' end of P2 is allowed to extend on DHP and the stem II is completely unfolded. Thus, besides the hybridized target is displaced, the G-rich fragment is released and folds into the G-quadruplex structure, and perfect recognition site of Nt. BbvCI is formed, executing a large-amplitude conformational transition. In the step ③, nicking reaction leads to the generation of new primer and induces the subsequent polymerization, as well as the displacement of pre-replicated G-rich fragment. The nicking, polymerization and displacement can be repeated continuously, resulting in the accumulation of G-quadruplex molecules. Upon addition of hemin, the G-quadruplex can bind to hemin and forms the DNAzyme that has the catalytic activity similar to horseradish peroxidase, catalyzing the oxidation of ABTS by H 2 O 2 and producing the amplified colorimetric signal (step ④). Moreover, the displaced target DNA obtained from the step ② can in turn induce the next round of hybridization, polymerization, nicking and signal conversion, amplifying further the target DNA hybridization event (step ⑤). As a result, an exponentially amplified colorimetric signal is expected to be achieved, enabling the reliable detection of trace target elements. By the way, besides mentioned-above exceptional structural features of DHP, no any signal loss occurs for the present colorimetric sensing system compared with traditional nicking/polymerization-based amplification assays. , Specifically, as illustrated in Scheme S1, the G-quadruplex fragments constantly generated from step ③ are not consumed by hybridizing with DHPs for two reasons: 1) The dual-stem structure makes the DHP stable enough so that it is not easy to open it; 2) even if DHP is opened by displaced G-rich fragments, the G-quadruplex fragment locked by stem II could be released and form an equal amount of DNAzyme. Thus, the likely signal loss is completely circumvented. To demonstrate this important mechanism, Ns with the same base sequence as the nicked/displaced G-quadruplex strand was designed (seen in Table ), and the corresponding experiments were performed under identical conditions. The measured data were collected and analyzed in Figure .
Since the DHP is a novel hairpin probe with very stable stems, the feasibility of colorimetric sensing strategy should be verified at the initial stage. For this purpose, the DNA colorimetric assay and different control experiments were performed, and the measured data are shown in Figure A. One can see that there is no obvious difference in absorption spectrum between lines a, b and c, indicating that the DHP can tightly self-lock due to the introduction of its two stems and no free DNA-quadruplex fragment exists even if target DNA was added. In the presence of polymerase, as illustrated in the difference between line d and line e, only a slight absorption peak increase is observed. Excitingly, compared with line f, a dramatic absorption increase is seen in line g where nicking enzyme existed, suggesting that a large number of G-quadruplexes were generated during the autonomous polymerization/scission/displacement cycle and formed the expected catalytic DNAzyme in the presence of hemin. Thus, the optical signal of the proposed colorimetric sensing system can reflect the existence of DNA target. Apparently, three different sensing systems are studied in this section: non-amplification system (system I, line b and c), polymerization amplification system (system II, line d and e), and polymerization/nicking amplification system (system III, line f and g). To obtain the accurate comparative data on the assay performance of sensing systems involved, the optical signals, including the background-subtracted absorption intensity and absorption peak ratio of the target sample to blank, were quantitatively evaluated, and the detailed results are shown in Figure B. The system III (namely, the proposed colorimetric assay) exhibits the most desirable sensing performance. In fact, this optical signal changing trend can be observed by the naked eye. Figure C displays the representative photographs corresponding to different samples depicted in Figure A. We can see that a remarkable color change occurs in sample g, while all other samples are almost colorless, strongly further convincing that the DHP is rationally designed to execute the amplification detection of target DNA. In the contribution, we for the first time proposed the DHP with a unique hairpin structure and developed a new amplification sensing system via combining with polymerization and nicking. Although this probe has the self-complementary 25-base fragment, it does not form the sticky-end pairing-based dimer. To confirm the unpredictable molecular structure of DHP and the utility of polymerase and endonuclease, native polyacrylamide gel electrophoresis (PAGE) was used to explore the mechanism of the designed sensing system. The experimental results are represented in Figure .
In order to achieve the best sensing performance, the effect of the hemin concentration, enzymatic reaction time and H 2 O 2 incubation time were investigated, respectively. The ration of A/A 0 was adopted to evaluate the sensing ability, where A and A 0 represent the absorption peak in the presence and absence of target DNA, respectively. As illustrated in Figure A, the value of A/A 0 first increased with the increase of hemin concentration. The maximal ratio value was achieved when hemin at 2 μM was employed. Then, signal decreased at higher concentration. This is reasonable. In the low hemin concentration range, more hemin molecules can produce more DNAzyme units responsible for the higher signal. However, when the concentration of hemin is more than 2 μM, the background increases and deteriorates the assay performance. Thus, we chose 2 μM as the favorable one for subsequent experiments. The enzymatic reaction time is explored as shown in Figure B. The absorption ratio of the solution increases with the increase of reaction time up to 40 min and then levels off. Therefore, the period of 40 min is preferred for the isothermal amplification. The influence of H 2 O 2 incubation time can be seen in Figure C, and the A/A 0 is found to increase with the incubation time increase and almost reaches equilibrium at 30 min. Thus, we chose 30 min for ABTS oxidation.
Once possessing the capability to accurately recognize and quantify disease-related genes, especially those associated with cancers, the new biosensing probe would hold considerable promise for early disease diagnosis and monitoring of treatment progress. To evaluate the utility of DHP with unique structural features, different concentrations of target DNA ranging from 0 to 200 nM were prepared and analyzed by this colorimetric sensing system. The UV-vis absorption spectra are collected in Figure A, while the corresponding absorption peak is recorded in Figure B. It could be seen that an obvious monotonic increase in absorption intensity is observed when increasing target concentration from 0 and 150 nM, and no obvious signal change could be achieved even at the higher target concentration, for example, 200 nM. Excitingly, as low as 1 fM target DNA, equal to the DNA levels in physiological samples, can still induce a detectable signal compared to the blank sample, and thus we define it as the limit of detection (LOD), representing an impressive improvement in term of assay sensitivity. For example, two classical catalytic beacons in the literature reports , only offer the detection limit of 2 nM and 200 nM, respectively. Namely, the DHP-based colorimetric sensing system can achieve over 6 or 8 orders of magnitude improvement in the detection sensitivity. More details on the sensitivity comparisons with other impressive previously-reported signal amplification strategies, including the methods based on the versatile nanomaterials and electrochemical measurement that is well known to be an extremely sensitive signaling technique, are provided in Table . It is clear and unambiguous that the newly-proposed DHP colorimetric assay can offer a very exciting LOD at least 20 times lower than the literature values. , - The measured data demonstrates that this homogenous signaling platform is efficient for ultrasensitive colorimetric detection of DNA hybridization. It is worth pointing out that, compared with these sensing systems, , - besides desirable LOD, the dynamic response range is substantially widened, including two linear calibration curves different from each other in the low and high target concentration. Figure C displays a good linear relationship between the peak absorption value (Y) and the logarithmic concentration of target DNA (X) in the range from 1.0 fM to 1 nM with a calibration curve fitted to the equation: Y= 0.340+ 0.0049 LogX (R 2 = 0.9910). Figure D presents the linear dynamic response to target DNA in the concentration range from 1 nM to 150 nM, and the regression equation can be expressed as Y= 0.2905+ 0.0043X (R 2 = 0.9964). It should be easy to understand two different linear relationships. On the whole, two types of reactions can contribute to the detectable signal: primary target DNA hybridization (step ①) and subsequent amplification (steps ②, ③ and ⑤). The former plays a major role in signal conversion in the high target concentration range, while the latter is largely responsible in the low target concentration range. Since there is the difference in signaling process between high and low concentration ranges, two different linear relationships could be obtained.
Gene mutation is a very common phenomenon occurred frequently in some biological events. A large number of human diseases have been known to originate from gene mutation, and the information on gene mutation is expected to provide direct insight into molecular mechanisms of some diseases and to promote the targeted therapy. Thus, reliably distinguishing mutant target DNA from the wild type one is of great significance. To evaluate the detection specificity of the current colorimetric sensing system, different target DNAs, including complementary target DNA (T), single-base mutant DNA (MT1), two-bases mutant DNA (MT2), and three-base mutant DNA (MT3), were detected under identical experimental conditions, and the measured data are comparatively depicted in Figure . As can be seen, mutations existing in every target DNA induce a substantial decrease in signal intensity. Specifically, if the optical signal triggered by complementary target gene is defined as 100%, the signal intensity corresponding to MT1, MT2, and MT3 are 33.6%, 16.4%, and 1.9%, respectively, reflecting that the newly-proposed DHP possesses an excellent specificity. Clearly, the capability to distinguish the single-base mismatched targets has been fundamentally improved compared with literature values (about 75% and 95% ) offered respectively by common MB and adapted one (LMB). More excitingly, as shown in Figure Inset, all mutant target DNAs can be easily visualized by the naked eye according to the distinct color changes. Note that the MT1 is the mutant type DNA identified as one of the oncogenes, and the reliable identification of MT1 indicates the potential application of DHP in clinical settings to a certain extent. Undoubtedly, the excellent analytical performance achieved should be attributed to the unique DHP and efficient signaling scheme to amplify DNA hybridization event. Several issues should be mentioned: stem I that inhibits the primer binding, stem II that locks the folding of pre-incorporated G-rich fragment into DNAzyme and binding site for nicking endonuclease responsible for the successive generation of new primer. In this case, besides the low background in the absence of target DNA, the synergetic effect of nicking and polymerization causes the target DNA cycle and in turn the exponential accumulation of DNAzyme products, and no any signal loss occurs, enabling the detection of trace targets. Meanwhile, stem I and stem II enhance the stability of DHP hairpin in a cooperative manner, making the detection specificity higher. Essentially, all the distinct advantages are based on the successful design of DHP. In fact, DHP is a more stable hairpin probe than common MB to some degree, but it is never reported because of the difficulty of obtaining the highly stable intramolecular hairpin. The functional fragments of DHP are shown in Scheme S2. Its part I consisting of loop and stem I is similar to the classical MB, and part II have Stem II and ss (single-stranded) fragment. While the ss fragment severs as the bridge between the stem I and stem II and stabilizes further the part I, the stem can be opened by target DNA hybridization, but stem II is still in the close state (no signal detected in line c of Figure A). On the basis of theoretical analysis and our own experience, when each of oligonucleotides contains more than 9 complementary base pairs, the dimer via intermolecular interaction is easily formed. Thus, the construction of two stem-contained DHP with 25 base pairs is a very inspiring achievement in the development of DNA sensing probe. Presumably, the stem II is a unique double-stranded fragment (rather than a common ds DNA) composed of a G-quadruplex sequence and its complementary segment and promotes the intramolecular hybridization. The present study is expected to give invaluable insight into the DNA probe design and clinic genetic diagnosis.
To verify the potential application of the proposed DHP to complex biological samples, we conducted the recovery tests by adding varying amounts of target DNA into the sensing system containing 1% human serum (kindly provided by Fuzhou general hospital of Nanjing military command). As demonstrated in Table , the recoveries for the spiked target DNA are in the range of 99-106%, suggesting that the developed DHP is a promising tool for possible applications since human serum is one of the most challenging media with a variety of proteins and other serious interference.
In summary, a facile DHP for colorimetric screening of p53 gene has been proposed, into which a G-rich fragment and a cleavable restriction site for Nt. BbvCI are easily introduced. The DHP exclusively folds into an extremely stable hairpin structure consisting of double stems, indicating the exceptional characteristics distinct from classical MB. As a result, the DHP-based colorimetric sensing system can execute the exponential amplification of target DNA hybridization and offers the dramatically-improved detection sensitivity, enabling the ultrasensitive p53 gene detection. Moreover, the unparalleled detection specificity is obtained compared with the traditional MB, and the point mutation occurring in target DNA is able to be visualized by the naked eye. Besides, the DHP has several outstanding advantages of easy synthesis, simple operation and low cost. The impressive research advances, as well as the innovative design of sensing probe as a proof-of-concept, are expected to benefit the development of multifunctional probes for various important purposes and would create a great potential for the clinical diagnosis of genetic diseases.
Schemes S1-S2, Figures S1-S5. Click here for additional data file.
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Assessing microbial diversity in soil samples along the Potomac River: implications for environmental health | 0ed9648c-0461-42cd-8536-a7c564944637 | 10714937 | Microbiology[mh] | The Potomac River, renowned for its rich historical significance, flows through the Mid-Atlantic region of the USA, traversing the Potomac Highlands before draining into the Chesapeake Bay. The river contains a drainage area of about 14,500 square miles and is approximately 405 miles long. The Potomac basin stretches across parts of four states (Maryland, Pennsylvania, Virginia, and West Virginia) as well as the District of Columbia. The Potomac basin is the second largest watershed in the Chesapeake Bay watershed ( ). This includes the land areas where water drains toward the mouth of the Potomac, such as the Anacostia River (8.5 miles long), which empties into the Potomac River at Hains Point in Washington, DC ( , ). The watershed contains a large population, mostly located in the Washington metropolitan area, with forest being the largest land use and agriculture and urban areas being the second largest land uses in the upper and lower basins, respectively. Human population growth, industrialization, and urbanization have caused a drastic increase in pollution levels within the Potomac basin ( ). Washington, DC, has a long history of water pollution, with the Potomac and Anacostia rivers subjected to chemical pollution for over 200 years. The Anacostia River, in particular, is one of the top 10 most polluted rivers in the USA, containing sewage, metals, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) ( ). Excessive nutrient inputs (mainly nitrogen from nonpoint sources) have caused the eutrophication of surface waters ( ). The Potomac River is also plagued by high bacterial growth due to sewage runoff and improper waste disposal, leading to the river being used as a sewage drain ( ). These poor waste management practices and the resulting bacterial growth have led to the formation of cyanobacteria blooms in years of drought and low river volume. The blooms deplete oxygen levels (hypoxic bottom-water dissolved oxygen) and result in the rivers being considered unswimmable and unfishable ( , , ), as confirmed by the Potomac Conservancy (2020), which gave the river a grade of B ( ). These human-influenced increases in waste and nutrient loads (including discharge from sewage treatment plants, atmospheric deposition, and urban/agricultural runoff) have all negatively impacted the Potomac basin. In response to these issues, recent initiatives have been launched to maintain the cleanliness and health of the Potomac River, including the Clean Rivers Project, which aims to reduce combined sewer overflows and increase community monitoring of pollutants and toxins ( ). Sewer separation is just one component of the plan to mitigate combined sewer overflows to the Potomac River and is part of the larger project to clean all three waterways in the District. There has also been a heightened level of community monitoring of pollutants and toxins in the Potomac River, particularly through the efforts of the Interstate Commission on the Potomac River Basin (ICPRB). This increased scrutiny has provided valuable insights into the health of the river and helped to further galvanize support for the protection and preservation of this important waterway. In line with these efforts, this study aims to investigate the current environmental health of the Potomac River region in the DC metro area via a PCR amplicon study of soil samples from various locations along the basin. Soil hosts a wide range of microorganisms that play crucial roles in the ecosystem, and this is especially true for freshwater ecosystems like the Potomac River. The microbial communities present in soil have been shown to be a marker of and have a significant impact on the overall health of these ecosystems. By examining the soil samples collected along the Potomac River, we can gain valuable insights into the connection between soil microbes and the health of the river basin. The findings of this research have the potential to inform management practices aimed at maintaining and improving the health of the Potomac River for future generations.
Sample collection The river soil samples were collected in 50-mL sterile conical tubes, in triplicate, at a distance of 3–5 m from the banks of the Potomac River and a 6-inch depth from the soil surface. Ethanol and paper towels were used interchangeably between each soil sample collection to ensure clean, sterile tools. Samples were transported to the laboratory within an hour of collection and stored in a −20°C refrigerator until further processed. Physiochemical measurements Relative nitrogen, phosphorus, and potassium levels were measured using a LaMotte NPK Soil Test Kit. Approximately 0.5 g of soil was extracted for each sample, and the nitrogen, phosphorus, and potassium levels were recorded as specified in the kit procedure. The pH of each sample was collected using a Soil Condition Meter. The soil meter probe was inserted directly into the soil sample and allowed to equilibrate for 1 min prior to recording the sample pH. DNA extraction The tubes were ultrasonicated for 1 min each to achieve cell disruption. Extraction was completed using a Qiagen DNeasy PowerSoil Kit protocol ( ). Approximately 0.25 g of each soil sample was weighed and recorded. To achieve cell disruption, the samples were ultrasonicated for 1 min each. Samples were then stored at −20°C until PCR was performed. NanoDrop was used to confirm the quality and concentration of the DNA obtained from the soil samples (Table S1). PCR/gel electrophoresis DNA products were PCR amplified using primers “515F–806R” targeting the V4 region of the 16S SSU rRNA—used by the Earth Microbiome Project ( ). Primer sequences are as follows: 515F (Parada)–806R (Apprill), F: GTGYCAGCMGCCGCGGTAA; R: GGACTACNVGGGTWTCTAAT. Primers and primer constructs were designed by Greg Caporaso ( , ). Modifications to primer degeneracy were done by the labs of Jed Furhman ( ) and Amy Apprill ( ). Forward-barcoded constructs were redesigned by Walters ( ). Amplification conditions were performed in a 25-µL reaction volume and consisted of 13 µL of nuclease-free water, 10 µL of 2× PCR master mix, 0.5 µL forward primer, 0.5 µL reverse primer, and 1 µL soil DNA. The thermal cycle was programmed for 120 s at 94°C for initial denaturation, followed by 35 cycles of 45 s at 94°C for denaturation, 60 s at 50°C for annealing, 90 s at 72°C for extension, and a final extension at 72°C for 10 min. PCR products were examined by gel electrophoresis at 100 V for 45 min in a 1% (w/v) agarose gel with ethidium bromide in 1× TAE buffer and compared to a 1-kb DNA ladder (Fig. S1). 16S rRNA amplicon sequencing and analysis After demultiplexing to assign reads to samples at the New York Genome Center, the resulting FASTQ files were placed in the CyVerse Discovery Environment so that sequences could be analyzed in the DNA Subway Purple Line ( , ), which is a graphic user interface for QIIME2. Using the demultiplexed sequence counts summary (Fig. S2), low-quality sequences were trimmed to position 243 (TruncLenF: 243, TruncLenR: 243). After trimming, samples were rarified (rarification depth Min: 1, Max: 5,000), with sampling depths based on the frequency per sample data (Fig. S3). Operational taxonomy unit (OTU) tables were then generated by matching to the Silva (16S/18S rRNA) database. Statistics and analysis The Marker Data Profiling (MDP) module in MicrobiomeAnalyst ( , ) was used to further process the OTU tables generated by DNA Subway. An overview of the library size revealed two sample outliers with <10 read counts (YD1 and CP3; Fig. S4). These samples were removed from further grouped analyses. To remove low-quality or uninformative features, data filtering was done using a low count filter (minimum count = 4, 20% sample prevalence cutoff) and a low variance filter (10% removed based on inter-quantile range). To deal with the variations in sample depth and the sparsity of the data, normalization (total sum scaling) was applied. Using this data set, alpha diversity, beta diversity, pie chart, dendrogram, and abundance bar graphs were all generated.
The river soil samples were collected in 50-mL sterile conical tubes, in triplicate, at a distance of 3–5 m from the banks of the Potomac River and a 6-inch depth from the soil surface. Ethanol and paper towels were used interchangeably between each soil sample collection to ensure clean, sterile tools. Samples were transported to the laboratory within an hour of collection and stored in a −20°C refrigerator until further processed.
Relative nitrogen, phosphorus, and potassium levels were measured using a LaMotte NPK Soil Test Kit. Approximately 0.5 g of soil was extracted for each sample, and the nitrogen, phosphorus, and potassium levels were recorded as specified in the kit procedure. The pH of each sample was collected using a Soil Condition Meter. The soil meter probe was inserted directly into the soil sample and allowed to equilibrate for 1 min prior to recording the sample pH.
The tubes were ultrasonicated for 1 min each to achieve cell disruption. Extraction was completed using a Qiagen DNeasy PowerSoil Kit protocol ( ). Approximately 0.25 g of each soil sample was weighed and recorded. To achieve cell disruption, the samples were ultrasonicated for 1 min each. Samples were then stored at −20°C until PCR was performed. NanoDrop was used to confirm the quality and concentration of the DNA obtained from the soil samples (Table S1).
DNA products were PCR amplified using primers “515F–806R” targeting the V4 region of the 16S SSU rRNA—used by the Earth Microbiome Project ( ). Primer sequences are as follows: 515F (Parada)–806R (Apprill), F: GTGYCAGCMGCCGCGGTAA; R: GGACTACNVGGGTWTCTAAT. Primers and primer constructs were designed by Greg Caporaso ( , ). Modifications to primer degeneracy were done by the labs of Jed Furhman ( ) and Amy Apprill ( ). Forward-barcoded constructs were redesigned by Walters ( ). Amplification conditions were performed in a 25-µL reaction volume and consisted of 13 µL of nuclease-free water, 10 µL of 2× PCR master mix, 0.5 µL forward primer, 0.5 µL reverse primer, and 1 µL soil DNA. The thermal cycle was programmed for 120 s at 94°C for initial denaturation, followed by 35 cycles of 45 s at 94°C for denaturation, 60 s at 50°C for annealing, 90 s at 72°C for extension, and a final extension at 72°C for 10 min. PCR products were examined by gel electrophoresis at 100 V for 45 min in a 1% (w/v) agarose gel with ethidium bromide in 1× TAE buffer and compared to a 1-kb DNA ladder (Fig. S1).
After demultiplexing to assign reads to samples at the New York Genome Center, the resulting FASTQ files were placed in the CyVerse Discovery Environment so that sequences could be analyzed in the DNA Subway Purple Line ( , ), which is a graphic user interface for QIIME2. Using the demultiplexed sequence counts summary (Fig. S2), low-quality sequences were trimmed to position 243 (TruncLenF: 243, TruncLenR: 243). After trimming, samples were rarified (rarification depth Min: 1, Max: 5,000), with sampling depths based on the frequency per sample data (Fig. S3). Operational taxonomy unit (OTU) tables were then generated by matching to the Silva (16S/18S rRNA) database.
The Marker Data Profiling (MDP) module in MicrobiomeAnalyst ( , ) was used to further process the OTU tables generated by DNA Subway. An overview of the library size revealed two sample outliers with <10 read counts (YD1 and CP3; Fig. S4). These samples were removed from further grouped analyses. To remove low-quality or uninformative features, data filtering was done using a low count filter (minimum count = 4, 20% sample prevalence cutoff) and a low variance filter (10% removed based on inter-quantile range). To deal with the variations in sample depth and the sparsity of the data, normalization (total sum scaling) was applied. Using this data set, alpha diversity, beta diversity, pie chart, dendrogram, and abundance bar graphs were all generated.
Sample collection and study site characteristics Soil samples were collected in September 2021 from four locations/sites within the Potomac watershed ( ). The four sites, namely, OO, YD, YW, and CP, are each located at different points along the Potomac River, within the boundary of Washington, DC ( ). Sampling was performed during a period in which the average temperature was 73°F and the average rainfall was 0.3 inches ( https://www.weather.gov/ ; Fig. S5). In this period, the season was characterized as dry; however, for the 2 days between the collection of the samples, there was light rain in the region. These sites were chosen as they lay along a portion of the river still heavily impacted by combined sewer overflows (CSOs) ( ). Washington, DC, has been making progress in cleaning up the Anacostia and Potomac rivers through the court-mandated project known as Clean Rivers ( ). The project consists of 18 miles of underground tunnels designed to capture CSO before it reaches the rivers. One important tunnel, the “Potomac River Tunnel,” has still yet to be constructed, leaving much of the DC river region—namely, the sampled areas—polluted ( ). Soil physiochemical measurements The physiochemical measurements ( ) of the soil samples collected along the Potomac River revealed that relative nitrogen levels were 20 ppm or below in all samples. The relative phosphorus levels ranged from 4 to 10 ppm, while all potassium levels were 80 ppm or above. In addition, the pH levels of the soil samples collected along the Potomac River ranged from pH 6.8 to 8.4, with the majority of samples being neutral to slightly basic. DNA quality and amplification DNA samples obtained in the extraction protocol were of good yield (>20 ng/µL) and quality (260/280 value >1.8). The measurements of isolated DNA, for quality and quantity, are presented in Table S1. Expected amplification was obtained in almost all samples—exhibiting strong bands as visualized with an agarose gel (Fig. S1). This suggests some error in the processing of samples YD1 and CP3, and they should be distinguished as outliers. Microbial diversity and community profiling The amplified DNA from these four sites was analyzed via Illumina HiSeq paired-end sequencing, generating 29,164 clean reads (average 2,430 per sample; range from 1,426 to 4,367) and 666 OTUs (defined at 97% sequence similarity). More detailed summary statistics of the sequences can be found in the supplemental material. Samples YD3 and CP3, which had reads of 10 and 0, respectively, match samples found not amplified via PCR (Fig. S1 and S2) and were removed as outliers from further data analysis. The distribution of microbial alpha diversity indices is visualized in . Overall, the mean values in alpha diversity indices varied among samples grouped by collection site along the river; however, these differences were not statistically significant (ANOVA, P > 0.05). Notably, communities sampled from a small tidal channel parallel to the main river body (DC Wharf; OO) showed higher mean alpha diversity when compared to all other samples. Principal coordinates analysis [PCoA, =multidimensional scaling (MDS)] of the normalized OTUs based on Bray-Curtis distances ( ) also showed a separation between soil samples collected along the main river body (CP, YD, and YW) versus those collected along the parallel channel (OO); this observation is reinforced through dendrogram analysis (Bray-Curtis distances, Ward clustering; ). Among the identified OTUs, members of bacteria were predominant (98.05%), and a small number of OTUs were classified in the domain of archaea (1.95%). Identification of the OTUs at finer taxonomic levels yielded 73 phyla, 167 classes, 417 orders, 705 families, 1,439 genera, and 570 species. At the phylum level, Proteobacteria was dominant (39.0%), followed by Acidobacteria (14.0%), Actinobacteria (14.0%), Chloroflexi (8.0%), Verrucomicrobia (7.0%), Bacteroidetes (6.0%), Planctomycetes (5.0%), Cyanobacteria (2.0%), Gemmatimonadetes (1.0%), and Firmicutes (1.0%); these top 10 bacterial phyla constituted 96% of the total OTUs ( ). Among Proteobacteria , the class Gammaproteobacteria was predominant (47.5%), followed by Alphaproteobacteria (38.3%), and Deltaproteobacteria (14.2%; ); among Acidobacteria , subgroup 6 predominates (48.74%), with a noticeable presence of subgroup 4 (18.75%; ). Microbial composition analysis Core microbiome threshold analysis at the family level revealed the top shared/identified taxa to be Burkholderiaceae , Nitrosomonadaceae , Pedosphaeraceae , Xanthobacteraceae , metagenome, Pirellulaceae , Methyloligellaceae , Pyrinomonadaceae , Gaiellaceae , and Solirubacteraceae ( ). Site-specific distribution of microbial composition Grouped percent abundance data ( ) highlights taxon abundance differences (genus level) based on the sampling site. Detailed box plot comparisons ( ) show that Haliscomenobacter , Pseudomonas , Devosia , Luteolibacter , Ilumatobacter , Nitrospira , Steriodobacter , and Myxococcales (Blrii41 ) were found in higher abundance in location OO compared to the other sites. Acinetobacter and Pseudoxanthomonas were also found in higher abundance, together at sites OO and CP. Pirellula , Nocardioides, Gaiella , and MND1 were, instead, found in high abundance in sites along the upper stretch of the river (YW and YD). All correlation tables can be found in Table S2.
Soil samples were collected in September 2021 from four locations/sites within the Potomac watershed ( ). The four sites, namely, OO, YD, YW, and CP, are each located at different points along the Potomac River, within the boundary of Washington, DC ( ). Sampling was performed during a period in which the average temperature was 73°F and the average rainfall was 0.3 inches ( https://www.weather.gov/ ; Fig. S5). In this period, the season was characterized as dry; however, for the 2 days between the collection of the samples, there was light rain in the region. These sites were chosen as they lay along a portion of the river still heavily impacted by combined sewer overflows (CSOs) ( ). Washington, DC, has been making progress in cleaning up the Anacostia and Potomac rivers through the court-mandated project known as Clean Rivers ( ). The project consists of 18 miles of underground tunnels designed to capture CSO before it reaches the rivers. One important tunnel, the “Potomac River Tunnel,” has still yet to be constructed, leaving much of the DC river region—namely, the sampled areas—polluted ( ).
The physiochemical measurements ( ) of the soil samples collected along the Potomac River revealed that relative nitrogen levels were 20 ppm or below in all samples. The relative phosphorus levels ranged from 4 to 10 ppm, while all potassium levels were 80 ppm or above. In addition, the pH levels of the soil samples collected along the Potomac River ranged from pH 6.8 to 8.4, with the majority of samples being neutral to slightly basic.
DNA samples obtained in the extraction protocol were of good yield (>20 ng/µL) and quality (260/280 value >1.8). The measurements of isolated DNA, for quality and quantity, are presented in Table S1. Expected amplification was obtained in almost all samples—exhibiting strong bands as visualized with an agarose gel (Fig. S1). This suggests some error in the processing of samples YD1 and CP3, and they should be distinguished as outliers.
The amplified DNA from these four sites was analyzed via Illumina HiSeq paired-end sequencing, generating 29,164 clean reads (average 2,430 per sample; range from 1,426 to 4,367) and 666 OTUs (defined at 97% sequence similarity). More detailed summary statistics of the sequences can be found in the supplemental material. Samples YD3 and CP3, which had reads of 10 and 0, respectively, match samples found not amplified via PCR (Fig. S1 and S2) and were removed as outliers from further data analysis. The distribution of microbial alpha diversity indices is visualized in . Overall, the mean values in alpha diversity indices varied among samples grouped by collection site along the river; however, these differences were not statistically significant (ANOVA, P > 0.05). Notably, communities sampled from a small tidal channel parallel to the main river body (DC Wharf; OO) showed higher mean alpha diversity when compared to all other samples. Principal coordinates analysis [PCoA, =multidimensional scaling (MDS)] of the normalized OTUs based on Bray-Curtis distances ( ) also showed a separation between soil samples collected along the main river body (CP, YD, and YW) versus those collected along the parallel channel (OO); this observation is reinforced through dendrogram analysis (Bray-Curtis distances, Ward clustering; ). Among the identified OTUs, members of bacteria were predominant (98.05%), and a small number of OTUs were classified in the domain of archaea (1.95%). Identification of the OTUs at finer taxonomic levels yielded 73 phyla, 167 classes, 417 orders, 705 families, 1,439 genera, and 570 species. At the phylum level, Proteobacteria was dominant (39.0%), followed by Acidobacteria (14.0%), Actinobacteria (14.0%), Chloroflexi (8.0%), Verrucomicrobia (7.0%), Bacteroidetes (6.0%), Planctomycetes (5.0%), Cyanobacteria (2.0%), Gemmatimonadetes (1.0%), and Firmicutes (1.0%); these top 10 bacterial phyla constituted 96% of the total OTUs ( ). Among Proteobacteria , the class Gammaproteobacteria was predominant (47.5%), followed by Alphaproteobacteria (38.3%), and Deltaproteobacteria (14.2%; ); among Acidobacteria , subgroup 6 predominates (48.74%), with a noticeable presence of subgroup 4 (18.75%; ).
Core microbiome threshold analysis at the family level revealed the top shared/identified taxa to be Burkholderiaceae , Nitrosomonadaceae , Pedosphaeraceae , Xanthobacteraceae , metagenome, Pirellulaceae , Methyloligellaceae , Pyrinomonadaceae , Gaiellaceae , and Solirubacteraceae ( ).
Grouped percent abundance data ( ) highlights taxon abundance differences (genus level) based on the sampling site. Detailed box plot comparisons ( ) show that Haliscomenobacter , Pseudomonas , Devosia , Luteolibacter , Ilumatobacter , Nitrospira , Steriodobacter , and Myxococcales (Blrii41 ) were found in higher abundance in location OO compared to the other sites. Acinetobacter and Pseudoxanthomonas were also found in higher abundance, together at sites OO and CP. Pirellula , Nocardioides, Gaiella , and MND1 were, instead, found in high abundance in sites along the upper stretch of the river (YW and YD). All correlation tables can be found in Table S2.
The present study reports physiochemical and bacterial information at the phylum and subgroup levels of soil collected along the DC metro region of the Potomac River as a means to relay information pertaining to the environmental health of the river basin. Though soil nitrogen, phosphorous, and potassium (NPK) levels can vary depending on the specific environmental context and the types of plants or organisms present, all measured samples had relatively low nitrogen levels, low-medium phosphorous levels, and high potassium levels. Soil samples with low nitrogen levels, ranging from 20 ppm or below, and medium to low levels of phosphorus, ranging from 4 to 10 ppm, signal limited plant growth and productivity, which could lead to a decrease in overall biodiversity ( , ). High levels of potassium, above 80 ppm, can indicate that excess fertilizer or manure application has occurred, leading to eutrophication in nearby waterways ( ). The group patterns of the soil microbial data from all samples ( ) displayed variation in alpha diversity indices among samples but without significant differences ( ). However, the DC Wharf site samples showed higher mean alpha diversity, indicating potential variations in microbial community composition between sites. The PCoA and dendrogram analyses ( ) revealed separation between samples collected along the main river body versus those collected along a small tidal channel, indicating possible discrepancies in human impact, water retention, and tidal/current effects. These patterns also corresponded to differences in soil phosphorous levels, with the samples collected along the tidal channel having slightly lower levels of phosphorous than those collected from the main river ( ). The top taxa shared among all sampling sites match typical 16S rRNA-based analyses of phylum diversity found in soil, marine, and wastewater samples ( ) ( , ). In particular, Proteobacteria, Actinobacteria , and Acidobacterium are well represented and often account for 90% of cultivated soil bacteria ( ) ( ) . Proteobacteria is a diverse group of bacteria that is found in a variety of aquatic and terrestrial environments. This phylum is a major contributor to the microbial communities in the Potomac River basin and is likely responsible for the cycling of organic matter, nitrogen, and other essential elements. Actinobacteria and Acidobacterium are a group of bacteria that are typically associated with soil and are thought to play an important role in the decomposition of organic matter nutrient cycling processes. Proteobacteria (gamma), Actinobacteria , and Acidobacterium (subgroup 6) ( ) have been reported to thrive in soil with low levels of nitrogen ( , ). These findings are consistent with the physicochemical results obtained from the soil samples collected along the Potomac River ( ), which showed low levels of nitrogen across all sites. The abundance of these bacterial groups in the soil samples may be attributed to their ability to utilize alternative sources of nitrogen, such as organic matter, or to their capacity to fix atmospheric nitrogen ( ). The presence of these bacteria is expected, but it confirms that the soil is impacted by human activities ( , ). The significant presence of the phylum Chloroflexi in the samples may also indicate a shift in the environmental health of the river ( ). Certain Chloroflexi bacteria are associated with halophilic and thermophilic environments, and their presence could suggest that the Potomac River basin is facing increased hydrological stress. Chloroflexi are known to be involved in organohalide respiration and have potential roles in the bioremediation of chlorinated compounds ( )—noted due to historic PCB pollution in the Chesapeake Bay region ( ). Chloroflexi also play an important role in activated sludge water treatment plants ( , ), and the presence of these bacteria may also be indicative of changes in the river basin’s nutrient cycle. Chloroflexi are known for their ability to break down organic matter, and their presence suggests that there may be an increase in the amount of organic matter entering the river basin. The identified taxa (family level; ) shared among all samples note the strong presence of Burkholderiaceae , Nitrosomonadaceae, and Pedosphaeraceae . These taxa are indicative of nitrogen cycling and an environment with by-products of sewage and agricultural runoff ( , ). Burkholderiaceae has been positively correlated with aerobic chemoheterotrophy, aromatic compound degradation, and ureolysis. Xanthobacteraceae and Methyloligellaceae are typically found in environments with high levels of carbon, which could be due to the abundance of urban settings present along the Potomac River basin ( ). Pirellulaceae , Pyrinomonadaceae , Sphingomonadaceae , and Saprospiraceae are known to be associated with soil, marine sediments, and biofilms ( , Sphingomonadaceae , Solibacteraceae , and Nitrosomonadaceae have all been positively correlated with aerobic nitrite oxidation, aerobic ammonia oxidation, and nitrification (all P < 0.05) ( ). The abundance of these bacterial taxa is possibly an indication of elevated levels of urbanization and industrial activity in the vicinity. Taxon set analysis (Fig. S6), which compares environmental taxon sets to the shared family-level taxa, suggests that these top taxa are strongly correlated with agricultural pollution, organochlorine pesticide contamination, and bromochloromethane pollution. Though many features found in all of the samples were associated with urban settings, notes differences in taxon abundance found based on sampling sites, and these differences correspond to environmental differences as supported by multivariate analyses (Fig. S7). For instance, genus-level taxa, such as Acinetobacter and Pseudoxanthomonas, were more abundant in samples from sites OO and CP, whereas Pirellula , Nocardioides , Gaiella , and MND1 were more abundant in samples from sites YW and YD. Haliscomenobacter , Pseudomonas , Devosia , Luteolibacter , Ilumatobacter , Nitrospira , Steriodobacter , and Myxococcales (Blrii41 ) were more abundant in samples from site OO. Taxa highly represented from sites YW and YD play a central role in carbon cycling through methane and plant and algal degradation, while taxa from sites OO and CP are involved in complex carbon utilization and activated sludge sites. While our sampling was primarily focused on identifying dominant microbial species in the region, we recognize that the scale and design of our sampling might not have captured the full range of community patchiness. Future endeavors in this region could benefit from a more intensive sampling strategy, specifically targeting the nuances of community composition patchiness driven by both natural and anthropogenic factors. Conclusion This research provides valuable insights into the microbial diversity and community composition of soil samples collected from various locations along the urbanized stretch of the Potomac River. Our findings underscore the notable variations in microbial community structure and diversity across different sampling sites, emphasizing the influence of environmental factors on microbial abundance. We identified specific bacterial taxa associated with high levels of urbanization, waste sites, and agricultural pollution. Additionally, the study brings attention to potential disparities in human impact among the soil samples. These contribute to a better understanding of the complex interplay between urbanization and soil microbial communities along the Potomac River. Further research is warranted to more comprehensively explore the impacts of soil health and microbial diversity in this region, with the aim of informing effective strategies for maintaining and improving the health of this vital waterway for future generations.
This research provides valuable insights into the microbial diversity and community composition of soil samples collected from various locations along the urbanized stretch of the Potomac River. Our findings underscore the notable variations in microbial community structure and diversity across different sampling sites, emphasizing the influence of environmental factors on microbial abundance. We identified specific bacterial taxa associated with high levels of urbanization, waste sites, and agricultural pollution. Additionally, the study brings attention to potential disparities in human impact among the soil samples. These contribute to a better understanding of the complex interplay between urbanization and soil microbial communities along the Potomac River. Further research is warranted to more comprehensively explore the impacts of soil health and microbial diversity in this region, with the aim of informing effective strategies for maintaining and improving the health of this vital waterway for future generations.
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Early postoperative laboratory parameters are predictive of initial treatment failure in acute septic arthritis of the knee and shoulder joint | 157ecc0c-99bf-4555-aba7-eddedef43bd4 | 10199901 | Debridement[mh] | Septic arthritis presents an orthopedic emergency with high mortality, and if treated delayed it can cause irreversible bone and cartilage destruction – . The annual incidence ranges from 4 to 10 per 100.000, with an increasing trend over the last two decades – . The knee is most commonly affected followed by the shoulder, and infections are either caused hematogenous, iatrogenous, or posttraumatic , , . Several studies have identified risk factors for septic arthritis of native joints such as rheumatoid arthritis, osteoarthritis, immunosuppression, concurrent infection, diabetes mellitus, or intraarticular corticosteroid injections , – . Diagnosis is based on patient history, physical examination, laboratory values, imaging, and synovial fluid aspiration. Bloodwork ideally includes C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), a complete blood cell count, metabolic panel, and blood cultures before initiation of antibiotic treatment. Further, arthrocentesis with synovial fluid white cell count (WCC), gram strain, crystal analysis, PCR, and cultures are performed as standard , , . The most frequent pathogen in synovial fluid cultures is Staphylococcus aureus , followed by streptococcal species , , . Patients with septic arthritis are usually treated with irrigation and debridement either through arthroscopy or open arthrotomy, in combination with culture-adapted antibiotic therapy, but currently no joint specific treatment algorithms exist, and study results are equivocal regarding optimal surgical techniques , , , , , . Failure rates of a single intervention remain high, and in 11 to 40% of all patients more than one debridement is needed to eradicate the infection , , , – . So far, few studies have addressed the risk factors for failure of a single surgical debridement – . To our knowledge, no study has yet analyzed the time courses of laboratory values during treatment of septic arthritis and their influence on reoperation rates. Therefore, the current study aimed to identify clinical as well as early serological risk factors for treatment failure and additionally to develop predictive models for prognosis of single surgical intervention failure.
Patients In this case–control study data was collected retrospectively from all patients treated with arthroscopy or arthrotomy for septic monoarthritis of the native knee or shoulder joint at our institution between 2003 and 2018. We excluded patients with a diagnosis of osteomyelitis or periprosthetic infections, intra-articular foreign bodies, and all patients younger than 18 years (Fig. ). Initial diagnosis based on clinical presentation, inflammatory markers, imaging, and joint aspiration, and had to be confirmed by a positive culture of the joint fluid or by histopathological examination. 249 patients were included in the final analysis. Demographics We collected demographic data as presented in Table , and pre- and postoperative laboratory findings as presented in Table . The Charlson Comorbidity Index (CCI) was used to summarize comorbidities. Further, surgery type (arthroscopy or arthrotomy) and duration were recorded. Severity of osteoarthritis was graded via the Kellgren and Lawrence classification based on available radiographs , and the Gächter classification was used to grade intra-articular inflammation . Treatment Patients underwent joint punctures at our emergency department at initial presentation, two samples were sent for microbiological analysis. Antibiotic therapy with Cefazolin was initiated immediately after joint aspiration, and in case of penicillin allergy clindamycin was administered instead. Surgery was performed within 24 h, and at least three more tissue as well as fluid samples were taken during surgery and sent for histological and microbiological analysis. As soon as culture and antibiogram results were available, therapy was adjusted in consultation with the department of infectious diseases. Two weeks of i.v. antibiotics were followed by four additional weeks of oral administration. The decision for arthroscopy or open arthrotomy was left to the executing consultant orthopedic surgeon. For the shoulder arthrotomy, an anterior deltopectoral approach with subscapularis tenotomy was the method of choice. For the shoulder arthroscopy, either three standard portals (posterior, anterosuperior, and lateral portal) or four standard portals (posterior, anterosuperior, anterolateral, and posterolateral portal) were used. For knee arthrotomy, a medial parapatellar approach was chosen. In case of knee arthroscopy either three (anterolateral, anteromedial, and superomedial) or four portals (anterolateral, anteromedial, superomedial, superolateral) were used. All surgical procedures included synovectomy, debridement, and joint irrigation with sterile physiological sodium saline solution to an extent determined by the surgeon, as well as microbiological and histopathological sampling. No local antibiotics were administered intraoperatively. One or two suction drains were routinely employed per joint and usually removed five days postoperatively. Treatment failure was defined as the need for more than one surgical procedure for infection eradication, and suspected in case of elevated inflammatory markers, joint pain, limited range of motion or purulent swelling. In case of suspected failure, patients underwent another surgery within less than 48 h. Patients underwent examinations and blood testing in an outpatient setting at two and six weeks, and at three, six and twelve months after surgery, and were readmitted and underwent another debridement in case of suspected reinfection. The total median follow-up time was 32 months, with 25%- and 75%-percentiles at 5.8 and 70.0 months respectively. This study was approved by the ethics committee of the Medical University of Vienna (identification number 1296/2019). All research was performed in accordance with relevant guidelines and regulations, and informed consent was obtained from all patients. Statistics Continuous variables were described using mean and standard deviation and compared via t-tests, or non-parametrical Mann–Whitney-U testing if any conditions for the t-test were not fulfilled. Binary and categorical variables were described via percentages and compared by Chi-squared testing, or Fischer’s exact test for less than five observations. In terms of model development, we first chose all significant demographic variables from univariate analysis, except for Kellgren-Lawrence classifications and surgery types due to a lack of data. Laboratory parameters whose postoperative decline differed significantly between groups were additionally included. All continuous variables used for score development were transformed to dichotomous variables by calculating cutoffs based on the respective Youden index. All variables were then weighted based on their relative risk for failure of a single irrigation and debridement. We assessed performance via receiver operating characteristic (ROC) curves. The Cochran-Armitage trend test was used to evaluate the correlation between score values and the need for repeated surgery. All tests were calculated in their two-sided version with a p-value of < 0.05 considered as significant. The analysis was performed using SPSS Version 28 (IBM Corp., Armonk, NY, USA).
In this case–control study data was collected retrospectively from all patients treated with arthroscopy or arthrotomy for septic monoarthritis of the native knee or shoulder joint at our institution between 2003 and 2018. We excluded patients with a diagnosis of osteomyelitis or periprosthetic infections, intra-articular foreign bodies, and all patients younger than 18 years (Fig. ). Initial diagnosis based on clinical presentation, inflammatory markers, imaging, and joint aspiration, and had to be confirmed by a positive culture of the joint fluid or by histopathological examination. 249 patients were included in the final analysis.
We collected demographic data as presented in Table , and pre- and postoperative laboratory findings as presented in Table . The Charlson Comorbidity Index (CCI) was used to summarize comorbidities. Further, surgery type (arthroscopy or arthrotomy) and duration were recorded. Severity of osteoarthritis was graded via the Kellgren and Lawrence classification based on available radiographs , and the Gächter classification was used to grade intra-articular inflammation .
Patients underwent joint punctures at our emergency department at initial presentation, two samples were sent for microbiological analysis. Antibiotic therapy with Cefazolin was initiated immediately after joint aspiration, and in case of penicillin allergy clindamycin was administered instead. Surgery was performed within 24 h, and at least three more tissue as well as fluid samples were taken during surgery and sent for histological and microbiological analysis. As soon as culture and antibiogram results were available, therapy was adjusted in consultation with the department of infectious diseases. Two weeks of i.v. antibiotics were followed by four additional weeks of oral administration. The decision for arthroscopy or open arthrotomy was left to the executing consultant orthopedic surgeon. For the shoulder arthrotomy, an anterior deltopectoral approach with subscapularis tenotomy was the method of choice. For the shoulder arthroscopy, either three standard portals (posterior, anterosuperior, and lateral portal) or four standard portals (posterior, anterosuperior, anterolateral, and posterolateral portal) were used. For knee arthrotomy, a medial parapatellar approach was chosen. In case of knee arthroscopy either three (anterolateral, anteromedial, and superomedial) or four portals (anterolateral, anteromedial, superomedial, superolateral) were used. All surgical procedures included synovectomy, debridement, and joint irrigation with sterile physiological sodium saline solution to an extent determined by the surgeon, as well as microbiological and histopathological sampling. No local antibiotics were administered intraoperatively. One or two suction drains were routinely employed per joint and usually removed five days postoperatively. Treatment failure was defined as the need for more than one surgical procedure for infection eradication, and suspected in case of elevated inflammatory markers, joint pain, limited range of motion or purulent swelling. In case of suspected failure, patients underwent another surgery within less than 48 h. Patients underwent examinations and blood testing in an outpatient setting at two and six weeks, and at three, six and twelve months after surgery, and were readmitted and underwent another debridement in case of suspected reinfection. The total median follow-up time was 32 months, with 25%- and 75%-percentiles at 5.8 and 70.0 months respectively. This study was approved by the ethics committee of the Medical University of Vienna (identification number 1296/2019). All research was performed in accordance with relevant guidelines and regulations, and informed consent was obtained from all patients.
Continuous variables were described using mean and standard deviation and compared via t-tests, or non-parametrical Mann–Whitney-U testing if any conditions for the t-test were not fulfilled. Binary and categorical variables were described via percentages and compared by Chi-squared testing, or Fischer’s exact test for less than five observations. In terms of model development, we first chose all significant demographic variables from univariate analysis, except for Kellgren-Lawrence classifications and surgery types due to a lack of data. Laboratory parameters whose postoperative decline differed significantly between groups were additionally included. All continuous variables used for score development were transformed to dichotomous variables by calculating cutoffs based on the respective Youden index. All variables were then weighted based on their relative risk for failure of a single irrigation and debridement. We assessed performance via receiver operating characteristic (ROC) curves. The Cochran-Armitage trend test was used to evaluate the correlation between score values and the need for repeated surgery. All tests were calculated in their two-sided version with a p-value of < 0.05 considered as significant. The analysis was performed using SPSS Version 28 (IBM Corp., Armonk, NY, USA).
Univariate analysis 249 patients with septic monoarthritis, including 194 knee (77.9%) and 55 shoulder joints (22.1%) were analyzed in total. Sixty-five (26.1%) experienced failure of a single surgical debridement (25.3% of shoulders, 29.1% of knees). Median follow-up for the single-surgery group was 34 months, and 21 for the failed single-surgery group, respectively. Median time to second surgery was 15 days. Infectious etiology could be retraced in 141 patients, including 61 iatrogenic (56.5%), 46 hematogenic (42.6%), and one traumatic case (1.2%). There were no significant differences regarding gender, age, BMI, fever at admission, Gächter score, and surgery duration between successful and failed single surgical debridement (p > 0.05). Higher CCI scores were significantly associated with the need for repeated surgery (p = 0.025). Further, longer symptom duration (p = 0.003) and severe osteoarthritis, as reflected by high grades of the Kellgren-Lawrence classification (cf. Figure ), were significantly associated with failure of a single debridement (p = 0.013). Table summarizes the results in detail. Of the 65 patients experiencing treatment failure, 39 (60%) were successfully reoperated, 18 (27.7%) required further surgical interventions for septic arthritis, 4 (6.2%) presented with impaired wound healing, 3 (4.6%) died in the postoperative course, 2 (3.1%) were admitted to the ICU for septic shock. One (1.5%) knee arthrodesis was performed. Surgical technique In total 89 arthrotomies (35.7%; 35 shoulders, 54 knees) and 160 arthroscopies (64.3%; 20 shoulders, 140 knees) were performed. The surgical technique had a significant impact on shoulder joints, with failure rates of 50.0% for arthroscopy compared to 17.1% for arthrotomy (p = 0.01). The comparison of baseline characteristics between both treatment strategies showed a significantly higher percentage of female patients (50.6% vs. 36.2%, p = 0.04), a higher mean age (67.0 vs. 59.3 years, p = 0.003), as well as a higher CCI in the arthrotomy group (4.28 vs. 3.09, p < 0.001). Arthroscopy was performed more frequently in knee joints (60.7 vs. 87.5%, p < 0.001), and average Gächter scores were higher in the arthrotomy group (p = 0.011). Microbiological analysis Positive cultures were found in 37.9% in the successful single debridement group, and in 66.15% in the failure group respectively (p < 0.01). In patients in whom no pathogens could be detected, the diagnosis was confirmed by intraoperative histopathological examination. Staphylococcus aureus infections showed no significant influence on treatment failure (p = 0.187). Methicillin-resistant Staphylococcus aureus (MRSA) infections were not separately analyzed, as there were too few cases (cf. Figure ). Postoperative laboratory parameters CRP values on the third and fifth postoperative day were significantly higher in the treatment failure group. Neutrophilic granulocytes three days after surgery, and hemoglobin levels before discharge showed a significant difference in absolute as well as relative measures (cf. Table and Fig. ). Score development Two different SYNC (Symptom duration, Neutrophilic granulocytes, Charlson comorbidity index, 3rd day CRP, 5th day CRP) scoring systems were developed: the SYNC3 includes influencing factors that are known as early as day 3 after surgery, the SYNC5 is a modified version additionally including CRP drop between admission and the fifth postoperative day. Calculated weights for each of the variables are given in Table . The first score reached an AUC of 0.80 (p < 0.001, CI = [0.69 0.91]), the second had an AUC of 0.845 (p < 0.001, CI = [0.72 0.97]) , and both can be considered as excellent in terms of discrimination. Corresponding ROCs are shown in Fig. . Positive correlation of risk score categories and failure rates was underlined by the Cochran-Armitage trend test with p < 0.0001 for both scores. Patients were grouped into low, intermediate, and high risk of failure based on their score results (cf. Figure ). Additionally, a website for score calculation was created ( www.ortho-score.com ). Discussion Septic arthritis of large joints is potentially life-threatening, and requires repeated intervention if a single irrigation and debridement was not sufficient to control the infection to prevent further joint destruction . To the best of our knowledge, we evaluated the largest patient cohort on risk factors for failure of a single arthroscopy or arthrotomy for septic arthritis to date – , . A new scoring system for treatment failure risk estimation was created based on symptom duration, CCI, bacterial culture results, postoperative change in CRP, and change in neutrophilic granulocytes. This is the first study to demonstrate that higher postoperative CRP and neutrophilic granulocyte levels only a few days after initial surgical intervention, as well as slow decrease of absolute and relative CRP and neutrophile values are significant risk factors for failure of a single surgical intervention. The direct proportionality of absolute and relative changes in this study highlight the known physiological exponential course of CRP and neutrophil levels , . Consequently, it was sufficient to include one of the two progression parameters into the SYNC scores. The predictions were based on symptom duration, CCI, bacterial culture results, and absolute CRP and neutrophilic granulocyte changes by the third postoperative day, achieving an AUC of 0.80. Including additional information on the CRP change from admission to the fifth postoperative day further increased the AUC to an excellent 0.85. However, as there was not enough data available for internal validation, external validation is required before our scoring systems can be used in clinical practice. In our cohort 65 patients (26%) had a suspected reinfection with consequent need for further surgical treatment. These numbers are comparable to recent studies, which described rates between 11 and 40% , , , – . In terms of surgical technique, arthroscopy was the preferred method in case of knee infection (72%) and arthrotomy was chosen for the majority of shoulder infections (64%). No significant differences regarding failure rates were observed for knee infections. Though, we found a trend towards better results after arthroscopy, which is consistent with current literature, indicating that knee arthroscopy reduces reoperation rates while improving postoperative range of motion . Shoulder arthroscopy was associated with a higher failure rate in our study, yet current evidence does not provide a clear indication of the superiority of one surgical method over the another. Failure rates in current literature range from 5.6 to 100%, and Abdelmalek et al. found higher reoperation rates in arthroscopy in comparison to arthrotomy for the treatment of native shoulder septic arthritis, Acosta-Olivo et al. report a tendency towards lower reinfection rates for arthroscopy, and Memon et al. did not demonstrate the superiority of either method , , , , , . We observed a trend towards lower Gächter classes in patients treated with arthroscopy compared to arthrotomy, but no difference in Gächter stages regarding the risk of failure. This underlines previous findings, indicating that patients with a higher Gächter classification are more likely to benefit from arthrotomy than from arthroscopy, and appropriate choice of surgical procedure can help minimize the risk of failure . Our study yielded positive microbiological cultures of joint aspirate for almost half of all cases, twice as frequent and therefore significantly more common in the failure group, in which infection was confirmed histologically. The current body of evidence highlights that negative microbiological cultures occur in 12–50% of cases despite strong clinical suspicion of septic arthritis, especially if crystals or clotting are present – , . The sensitivity of bacterial culture reportedly ranges between 75–95%, which might decrease in case of atypical organisms or antibiotic treatment before joint aspiration, and in 9–14% of cases the pathogen can only be detected through additional blood cultures , . This underlines the necessity for a more comprehensive approach to diagnosis including clinical, radiological, and histological evidence , . In the presented cohort, Staphylococcus aureus was the most common pathogen and accounted for 49% of all organisms, similar to previous reports ranging between 37–56% , , – . Patients with Staphylococcus aureus infections showed no significantly higher failure rate in our study. However, current data on this topic is ambiguous: some studies found a significant association , , , whilst others did not , . Different rates of MRSA infections might explain the contradicting findings. In our cohort, there were only four MRSA cases, and therefore too few to draw conclusions and far fewer than reported in comparable studies , , . Geographical differences in the presence of MRSA might explain the inconsistent findings . The current study confirms previous observations that symptom duration and CCI are risk factors for failure of a single surgical intervention. However, none of the analyzed single comorbidities was associated with intervention failure , , . Further, we found a significant difference of about 1 mg/dl in Hb levels at discharge or before reoperation between successful and failed single surgical intervention groups. This might be explained though a more radical synovectomy, and therefor increased blood loss, for patients suffering from a more severe infection, but a more detailed assessment of postoperative Hb levels is needed. As of today, there exists no guideline on how to decide whether or when to repeat irrigation and debridement in patients with suspected persistent infection, and there is currently no uniform definition of treatment failure . The median time to second surgery was 15 days within our cohort, but for the majority of patients classified as high risk, repeated surgery was correctly predicted 10 days earlier than that. This indicates that levels and changes of infection parameters only a few days after initial surgery already need to be considered as risk factors for treatment failure, instead of drawing conclusions from them only after more extended periods of watchful waiting. Therefore, a faster decision for return to operating room, reinforced by score results, could potentially prevent further joint destruction, and preserve functionality. As for patients in the intermediate risk group, the indication for earlier and more frequent follow-ups may be made. The current study has some limitations: First, although it is based on the largest dataset of risk factors for shoulder and knee arthritides in current literature, its sample size still is comparatively small. Including the two most commonly affected large joints on the one hand increased sample size, but on the other hand neglect joint specific pathophysiology or treatment response. Our data quality was also limited by the retrospective data collection, with consecutive incompleteness and missing randomisation. No functional parameters could be considered due to insufficient documentation, and information on the administration of antibiotics prior to hospital admission was not available. Second, as there were not enough data for internal validation, there is a clear risk of overfitting for our predictive scores, which needs to be taken into consideration when applying them in clinical practice. Third, in terms of surgical approaches, decisions were made based on the opinion of the consultant orthopedic surgeon. In summary, the course of CRP and neutrophil granulocytes between admission and the fifth postoperative day, in combination with CCI, symptom duration, and bacterial culture results can help predict the need for further surgical intervention earlier and more accurately. Moreover, a decrease in hemoglobin and high Kellgren-Lawrence grading as factors significantly associated with more than one surgery.
249 patients with septic monoarthritis, including 194 knee (77.9%) and 55 shoulder joints (22.1%) were analyzed in total. Sixty-five (26.1%) experienced failure of a single surgical debridement (25.3% of shoulders, 29.1% of knees). Median follow-up for the single-surgery group was 34 months, and 21 for the failed single-surgery group, respectively. Median time to second surgery was 15 days. Infectious etiology could be retraced in 141 patients, including 61 iatrogenic (56.5%), 46 hematogenic (42.6%), and one traumatic case (1.2%). There were no significant differences regarding gender, age, BMI, fever at admission, Gächter score, and surgery duration between successful and failed single surgical debridement (p > 0.05). Higher CCI scores were significantly associated with the need for repeated surgery (p = 0.025). Further, longer symptom duration (p = 0.003) and severe osteoarthritis, as reflected by high grades of the Kellgren-Lawrence classification (cf. Figure ), were significantly associated with failure of a single debridement (p = 0.013). Table summarizes the results in detail. Of the 65 patients experiencing treatment failure, 39 (60%) were successfully reoperated, 18 (27.7%) required further surgical interventions for septic arthritis, 4 (6.2%) presented with impaired wound healing, 3 (4.6%) died in the postoperative course, 2 (3.1%) were admitted to the ICU for septic shock. One (1.5%) knee arthrodesis was performed.
In total 89 arthrotomies (35.7%; 35 shoulders, 54 knees) and 160 arthroscopies (64.3%; 20 shoulders, 140 knees) were performed. The surgical technique had a significant impact on shoulder joints, with failure rates of 50.0% for arthroscopy compared to 17.1% for arthrotomy (p = 0.01). The comparison of baseline characteristics between both treatment strategies showed a significantly higher percentage of female patients (50.6% vs. 36.2%, p = 0.04), a higher mean age (67.0 vs. 59.3 years, p = 0.003), as well as a higher CCI in the arthrotomy group (4.28 vs. 3.09, p < 0.001). Arthroscopy was performed more frequently in knee joints (60.7 vs. 87.5%, p < 0.001), and average Gächter scores were higher in the arthrotomy group (p = 0.011).
Positive cultures were found in 37.9% in the successful single debridement group, and in 66.15% in the failure group respectively (p < 0.01). In patients in whom no pathogens could be detected, the diagnosis was confirmed by intraoperative histopathological examination. Staphylococcus aureus infections showed no significant influence on treatment failure (p = 0.187). Methicillin-resistant Staphylococcus aureus (MRSA) infections were not separately analyzed, as there were too few cases (cf. Figure ).
CRP values on the third and fifth postoperative day were significantly higher in the treatment failure group. Neutrophilic granulocytes three days after surgery, and hemoglobin levels before discharge showed a significant difference in absolute as well as relative measures (cf. Table and Fig. ).
Two different SYNC (Symptom duration, Neutrophilic granulocytes, Charlson comorbidity index, 3rd day CRP, 5th day CRP) scoring systems were developed: the SYNC3 includes influencing factors that are known as early as day 3 after surgery, the SYNC5 is a modified version additionally including CRP drop between admission and the fifth postoperative day. Calculated weights for each of the variables are given in Table . The first score reached an AUC of 0.80 (p < 0.001, CI = [0.69 0.91]), the second had an AUC of 0.845 (p < 0.001, CI = [0.72 0.97]) , and both can be considered as excellent in terms of discrimination. Corresponding ROCs are shown in Fig. . Positive correlation of risk score categories and failure rates was underlined by the Cochran-Armitage trend test with p < 0.0001 for both scores. Patients were grouped into low, intermediate, and high risk of failure based on their score results (cf. Figure ). Additionally, a website for score calculation was created ( www.ortho-score.com ).
Septic arthritis of large joints is potentially life-threatening, and requires repeated intervention if a single irrigation and debridement was not sufficient to control the infection to prevent further joint destruction . To the best of our knowledge, we evaluated the largest patient cohort on risk factors for failure of a single arthroscopy or arthrotomy for septic arthritis to date – , . A new scoring system for treatment failure risk estimation was created based on symptom duration, CCI, bacterial culture results, postoperative change in CRP, and change in neutrophilic granulocytes. This is the first study to demonstrate that higher postoperative CRP and neutrophilic granulocyte levels only a few days after initial surgical intervention, as well as slow decrease of absolute and relative CRP and neutrophile values are significant risk factors for failure of a single surgical intervention. The direct proportionality of absolute and relative changes in this study highlight the known physiological exponential course of CRP and neutrophil levels , . Consequently, it was sufficient to include one of the two progression parameters into the SYNC scores. The predictions were based on symptom duration, CCI, bacterial culture results, and absolute CRP and neutrophilic granulocyte changes by the third postoperative day, achieving an AUC of 0.80. Including additional information on the CRP change from admission to the fifth postoperative day further increased the AUC to an excellent 0.85. However, as there was not enough data available for internal validation, external validation is required before our scoring systems can be used in clinical practice. In our cohort 65 patients (26%) had a suspected reinfection with consequent need for further surgical treatment. These numbers are comparable to recent studies, which described rates between 11 and 40% , , , – . In terms of surgical technique, arthroscopy was the preferred method in case of knee infection (72%) and arthrotomy was chosen for the majority of shoulder infections (64%). No significant differences regarding failure rates were observed for knee infections. Though, we found a trend towards better results after arthroscopy, which is consistent with current literature, indicating that knee arthroscopy reduces reoperation rates while improving postoperative range of motion . Shoulder arthroscopy was associated with a higher failure rate in our study, yet current evidence does not provide a clear indication of the superiority of one surgical method over the another. Failure rates in current literature range from 5.6 to 100%, and Abdelmalek et al. found higher reoperation rates in arthroscopy in comparison to arthrotomy for the treatment of native shoulder septic arthritis, Acosta-Olivo et al. report a tendency towards lower reinfection rates for arthroscopy, and Memon et al. did not demonstrate the superiority of either method , , , , , . We observed a trend towards lower Gächter classes in patients treated with arthroscopy compared to arthrotomy, but no difference in Gächter stages regarding the risk of failure. This underlines previous findings, indicating that patients with a higher Gächter classification are more likely to benefit from arthrotomy than from arthroscopy, and appropriate choice of surgical procedure can help minimize the risk of failure . Our study yielded positive microbiological cultures of joint aspirate for almost half of all cases, twice as frequent and therefore significantly more common in the failure group, in which infection was confirmed histologically. The current body of evidence highlights that negative microbiological cultures occur in 12–50% of cases despite strong clinical suspicion of septic arthritis, especially if crystals or clotting are present – , . The sensitivity of bacterial culture reportedly ranges between 75–95%, which might decrease in case of atypical organisms or antibiotic treatment before joint aspiration, and in 9–14% of cases the pathogen can only be detected through additional blood cultures , . This underlines the necessity for a more comprehensive approach to diagnosis including clinical, radiological, and histological evidence , . In the presented cohort, Staphylococcus aureus was the most common pathogen and accounted for 49% of all organisms, similar to previous reports ranging between 37–56% , , – . Patients with Staphylococcus aureus infections showed no significantly higher failure rate in our study. However, current data on this topic is ambiguous: some studies found a significant association , , , whilst others did not , . Different rates of MRSA infections might explain the contradicting findings. In our cohort, there were only four MRSA cases, and therefore too few to draw conclusions and far fewer than reported in comparable studies , , . Geographical differences in the presence of MRSA might explain the inconsistent findings . The current study confirms previous observations that symptom duration and CCI are risk factors for failure of a single surgical intervention. However, none of the analyzed single comorbidities was associated with intervention failure , , . Further, we found a significant difference of about 1 mg/dl in Hb levels at discharge or before reoperation between successful and failed single surgical intervention groups. This might be explained though a more radical synovectomy, and therefor increased blood loss, for patients suffering from a more severe infection, but a more detailed assessment of postoperative Hb levels is needed. As of today, there exists no guideline on how to decide whether or when to repeat irrigation and debridement in patients with suspected persistent infection, and there is currently no uniform definition of treatment failure . The median time to second surgery was 15 days within our cohort, but for the majority of patients classified as high risk, repeated surgery was correctly predicted 10 days earlier than that. This indicates that levels and changes of infection parameters only a few days after initial surgery already need to be considered as risk factors for treatment failure, instead of drawing conclusions from them only after more extended periods of watchful waiting. Therefore, a faster decision for return to operating room, reinforced by score results, could potentially prevent further joint destruction, and preserve functionality. As for patients in the intermediate risk group, the indication for earlier and more frequent follow-ups may be made. The current study has some limitations: First, although it is based on the largest dataset of risk factors for shoulder and knee arthritides in current literature, its sample size still is comparatively small. Including the two most commonly affected large joints on the one hand increased sample size, but on the other hand neglect joint specific pathophysiology or treatment response. Our data quality was also limited by the retrospective data collection, with consecutive incompleteness and missing randomisation. No functional parameters could be considered due to insufficient documentation, and information on the administration of antibiotics prior to hospital admission was not available. Second, as there were not enough data for internal validation, there is a clear risk of overfitting for our predictive scores, which needs to be taken into consideration when applying them in clinical practice. Third, in terms of surgical approaches, decisions were made based on the opinion of the consultant orthopedic surgeon. In summary, the course of CRP and neutrophil granulocytes between admission and the fifth postoperative day, in combination with CCI, symptom duration, and bacterial culture results can help predict the need for further surgical intervention earlier and more accurately. Moreover, a decrease in hemoglobin and high Kellgren-Lawrence grading as factors significantly associated with more than one surgery.
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Diversity and community distribution of soil bacterial in the Yellow River irrigation area of Ningxia, China | 33f273e4-9aeb-41fa-b24c-0007be916f61 | 11441701 | Microbiology[mh] | The global population is increasing and has now reached 7 billion . Experts speculate that the global population will reach 9.5 billion by 2050, which will put enormous pressure on food supply worldwide. FAO (2013) reported that the food deficit will be 70% in the coming decades . To address this problem, soils are planted with successive crops, which depletes nutrient reserves, leads to a negative nutrient balance, and causes soil degradation. Soil microorganisms are the drivers of material transformation and nutrient cycling in soil, which are crucial for carbon storage, plant growth, and the protection of other organisms, especially from pathogens . Numerous studies have demonstrated the critical role of soil microbial diversity in soil functions, including the carbon-nitrogen cycle, pathogen management, and bioremediation. Specific soil microbial groups can restrain soil-borne plant pathogens . As the most diverse and abundant group of soil microorganisms, bacteria are ubiquitous owing to their ability to evolve and survive in all types of environments . Soil bacteria are involved in most soil ecological processes, such as geochemical cycles, energy flow, and information transfer . Soil bacteria are sensitive to environmental changes, and their community composition and diversity respond rapidly to changes in environmental conditions, making them an important indicator for assessing the quality of the soil environment . A good soil bacterial structure and higher bacterial diversity can increase bacterial activity and improve the physicochemical properties of soil and the contribution to soil nutrient cycling. Therefore, understanding the changes in soil bacterial community composition under different environmental conditions systematically is a necessity. In agroecosystems, soil bacteria are a major class of microorganisms that keep soils healthy and productive . Soil bacteria perform important functions in the soil, breaking down organic residues from enzymes released in the soil. Many bacteria secrete enzymes in the soil to increase the solubility and bioavailability of phosphorus. Most soil bacteria perform better in well-oxygenated soils with a neutral pH. Nitrogen is often lacking in soils. Bacteria provide nitrogen to plants in large quantities. However, some studies have shown that soil bacterial communities are profoundly influenced by changes in soil conditions. For example, soil pH has been considered to influence bacterial community composition and has also been used for the large-scale prediction of bacterial diversity . Changes in the soil nitrogen concentration exert a significant effect on the structure and composition of the bacterial community . In addition, soil moisture, plant diversity, and soil type have been shown to be associated with changes in bacterial communities . Importantly, there is ample evidence that bacterial communities respond directly or indirectly to soil environmental changes. In other words, fertilization, changes in pH, and changes in farming patterns have been shown to affect soil bacterial communities. Thus, a deeper understanding of how bacterial communities respond to soil conditions is important for evaluating agroecosystem processes. Yinchuan Plain, commonly referred to as Ningxia Plain, is the political, economic, and cultural center of the Ningxia Province. Situated in the middle of Ningxia Province on the two banks of the Yellow River, it comprises a typical alluvial plain formed by long-term siltation from the Yellow River . It is an important crop production area in Ningxia as well as the primary irrigation area of the Yellow River, which is crucial for preserving ecological security in northwest China and has a history of more than 2000 years . Unfortunately, the physicochemical and microbiological properties of the soil have fundamentally changed owing to long-term planting, irrigation, fertilization, and crop planting, adversely affecting the development of the ecological environment and agriculture. Therefore, research on soil bacteria can help us better understand the soil properties and soil quality conditions in the irrigation area. To gain insights into soil biochemical processes in irrigation areas, we used soil samples from a typical irrigated area in the Ningxia Plain and examined soil bacterial changes and diversity. Our specific objectives were (i) elucidating changes in the composition and diversity of the soil bacterial community in the irrigated area and (ii) defining the relationship between soil bacterial communities and soil physicochemical properties.
Study area The study area is situated in Yinchuan Plain (37°46’~39°23’N, 105°45’~106°56’E), with a surface area of 7615 km 2 , spanning approximately 165 km from north to south and 60 km from east to west. Although the Yinchuan Plain lies in the arid inland temperate zone, with an average annual precipitation of less than 200 mm, average annual temperature of 8.3°C, and annual evaporation of nearly 2000 mm, the Yellow River flows through obliquely with a flow of approximately 280 km, carrying around 32.5 billion m 3 of transit water annually . Moreover, the Yinchuan Plain has annual sunshine of up to 3000 h, with abundant agricultural natural resources such as light, heat, water, and soil. These factors make it an important irrigated agricultural area in northwest China. Corn, wheat, rice, fruits, vegetables, and other crops produced in the Ningxia Plain have high and stable yields and good quality. Soil collection From July to October of 2020 to 2021, we collected 147 soil samples from eight areas irrigated by the Yellow River across the Yinchuan Plain, including Huinong District, Pingluo County, Yinchuan City, Helan County, Yongning County, Lingwu City, Litong District, and Qingtongxia City. Representative fields were chosen for each irrigated site based on the field area, soil type, and crop planting conditions. In each sample site, samples were collected at 10~15 points using the S-shaped or the quincunx sampling method at 0 to 20 cm depth. Three plot replicates were established at each site. Following this, the apparent root system was removed, and 2 kg of the mixed soil samples was reserved using the quartering method. Next, 100 g and 400 g of soil samples were stored in the refrigerator. After the samples were brought back to the laboratory, 100 g of the soil samples were stored at -80°C in a refrigerator for the soil bacterial diversity test, and 400 g of the samples were stored at 4°C in a refrigerator for testing the content of ammonium nitrogen and nitrate nitrogen in soil. The remaining 1.5 kg of samples were stored in a large valve bag for examining the physicochemical properties after air drying and screening. Geographic information, including the latitude, longitude, and altitude for each sample site was recorded by GPS (GM977-GPS, Shanghai, China), and the specific information of each sampling region is listed in . Soil physicochemical properties The physical properties of the soil samples were assessed using soil argrochemistry analysis . Soil pH was measured using a pH meter (soil: water = 1:5 (w:v)) (Mettler FE28-Standard desktop, Shanghai, China). Soil moisture was measured using the Sartorius MA 100 moisture test apparatus. Soil bulk density and field capacity were measured using the cutting ring method. The total salt content was measured using a conductivity meter (INESA DDS-307, USA). Soil organic matter was measured using potassium dichromate (K 2 Cr 2 O 7 ). Total nitrogen was measured using an automatic azotometer (GL-500, Shandong, China). Total and available phosphorus were measured using the molybdenum-antimony anticolorimetric method. A flame photometer for used for measuring total and available potassium . NH 4 + -N and NO 3 − -N were assayed using an ultraviolet spectrophotometer . Illumina sequencing analysis of 16S rRNA gene amplicons Soil DNA was extracted from all 147 samples using HiPure Soil DNA Kits (or HiPure Stool DNA Kits) (Magen, Guangzhou, China) according to the manufacturer’s protocol. A NanoDrop Micro Spectrophotometer (NanoDrop 2000, Thermo Fisher Technology, USA) and agarose gel electrophoresis were used to determine the concentration, purity, and integrity of DNA. PCR of the V3-V4 region of 16S rDNA gene was performed using primers 341F (5’- CCT ACG GGN GGC WGC AG -3’) and 806R (5’ - GGACTACHVGGGTATCTAAT -3’) to study the bacterial communities. For PCR, we used 5 μL of 10× KOD Buffer, 5 μL of 2.5 mM dNTPs, 1.5 μL of each primer (5 μM), 1 μL of KOD Polymerase, and 100 ng of template DNA (Guangzhou, China). The representative sequences were classified into organisms by a naive Bayesian model using the RDP Classifier based on SILVA Database (version 132),with the confidence threshold value of 0.8. Statistical analysis The correlation among the abundance of soil bacterial communities, environmental factors, and the composition of bacterial species was analyzed on the platform by Guangzhou Gene Denovo Biotechnology Co., Ltd (Guangzhou, China). Data were analyzed using R (4.3.1). Chao1 and Shannon indexes were calculated for alpha diversity (Caporaso & Gregory, 2010). Non-metric multi-dimensional scaling (NMDS) of UniFrac distances was conducted, and the results were plotted in R (4.3.1). Redundancy analysis (RDA) was used to visualize the relationship between microbial communities and environmental variables. The differences in bacterial communities between eight regions were assessed using one-way ANOVA, followed by Tukey’s honestly significant difference post hoc test. Statistical analyses were performed using SPSS25.0 (IBM, Armonk, NY, USA) and the vegan package in R(4.3.1).
The study area is situated in Yinchuan Plain (37°46’~39°23’N, 105°45’~106°56’E), with a surface area of 7615 km 2 , spanning approximately 165 km from north to south and 60 km from east to west. Although the Yinchuan Plain lies in the arid inland temperate zone, with an average annual precipitation of less than 200 mm, average annual temperature of 8.3°C, and annual evaporation of nearly 2000 mm, the Yellow River flows through obliquely with a flow of approximately 280 km, carrying around 32.5 billion m 3 of transit water annually . Moreover, the Yinchuan Plain has annual sunshine of up to 3000 h, with abundant agricultural natural resources such as light, heat, water, and soil. These factors make it an important irrigated agricultural area in northwest China. Corn, wheat, rice, fruits, vegetables, and other crops produced in the Ningxia Plain have high and stable yields and good quality.
From July to October of 2020 to 2021, we collected 147 soil samples from eight areas irrigated by the Yellow River across the Yinchuan Plain, including Huinong District, Pingluo County, Yinchuan City, Helan County, Yongning County, Lingwu City, Litong District, and Qingtongxia City. Representative fields were chosen for each irrigated site based on the field area, soil type, and crop planting conditions. In each sample site, samples were collected at 10~15 points using the S-shaped or the quincunx sampling method at 0 to 20 cm depth. Three plot replicates were established at each site. Following this, the apparent root system was removed, and 2 kg of the mixed soil samples was reserved using the quartering method. Next, 100 g and 400 g of soil samples were stored in the refrigerator. After the samples were brought back to the laboratory, 100 g of the soil samples were stored at -80°C in a refrigerator for the soil bacterial diversity test, and 400 g of the samples were stored at 4°C in a refrigerator for testing the content of ammonium nitrogen and nitrate nitrogen in soil. The remaining 1.5 kg of samples were stored in a large valve bag for examining the physicochemical properties after air drying and screening. Geographic information, including the latitude, longitude, and altitude for each sample site was recorded by GPS (GM977-GPS, Shanghai, China), and the specific information of each sampling region is listed in .
The physical properties of the soil samples were assessed using soil argrochemistry analysis . Soil pH was measured using a pH meter (soil: water = 1:5 (w:v)) (Mettler FE28-Standard desktop, Shanghai, China). Soil moisture was measured using the Sartorius MA 100 moisture test apparatus. Soil bulk density and field capacity were measured using the cutting ring method. The total salt content was measured using a conductivity meter (INESA DDS-307, USA). Soil organic matter was measured using potassium dichromate (K 2 Cr 2 O 7 ). Total nitrogen was measured using an automatic azotometer (GL-500, Shandong, China). Total and available phosphorus were measured using the molybdenum-antimony anticolorimetric method. A flame photometer for used for measuring total and available potassium . NH 4 + -N and NO 3 − -N were assayed using an ultraviolet spectrophotometer .
Soil DNA was extracted from all 147 samples using HiPure Soil DNA Kits (or HiPure Stool DNA Kits) (Magen, Guangzhou, China) according to the manufacturer’s protocol. A NanoDrop Micro Spectrophotometer (NanoDrop 2000, Thermo Fisher Technology, USA) and agarose gel electrophoresis were used to determine the concentration, purity, and integrity of DNA. PCR of the V3-V4 region of 16S rDNA gene was performed using primers 341F (5’- CCT ACG GGN GGC WGC AG -3’) and 806R (5’ - GGACTACHVGGGTATCTAAT -3’) to study the bacterial communities. For PCR, we used 5 μL of 10× KOD Buffer, 5 μL of 2.5 mM dNTPs, 1.5 μL of each primer (5 μM), 1 μL of KOD Polymerase, and 100 ng of template DNA (Guangzhou, China). The representative sequences were classified into organisms by a naive Bayesian model using the RDP Classifier based on SILVA Database (version 132),with the confidence threshold value of 0.8.
The correlation among the abundance of soil bacterial communities, environmental factors, and the composition of bacterial species was analyzed on the platform by Guangzhou Gene Denovo Biotechnology Co., Ltd (Guangzhou, China). Data were analyzed using R (4.3.1). Chao1 and Shannon indexes were calculated for alpha diversity (Caporaso & Gregory, 2010). Non-metric multi-dimensional scaling (NMDS) of UniFrac distances was conducted, and the results were plotted in R (4.3.1). Redundancy analysis (RDA) was used to visualize the relationship between microbial communities and environmental variables. The differences in bacterial communities between eight regions were assessed using one-way ANOVA, followed by Tukey’s honestly significant difference post hoc test. Statistical analyses were performed using SPSS25.0 (IBM, Armonk, NY, USA) and the vegan package in R(4.3.1).
Physicochemical properties of soil samples Various physicochemical variables were used to characterize the soil environment. Among the different soil physicochemical variables , the pH values of the eight regions were weakly alkaline , and the total nitrogen, total phosphorus, and total potassium contents in the soil differed significantly. However, the trend in variation was essentially the same. The highest total nitrogen was observed in soil from HN, and the lowest was observed in soil from HL. PL had the highest soil moisture content and field capacity, followed by HN and QTX, and YC had the lowest. The ammonium nitrogen content was highest in soil from YN and lowest in soil from YC, and the nitrate nitrogen content was highest in soil from PL and HL and lowest in soil from HN. The available phosphorus and potassium contents were highest in LTQ and lowest in YC and YN. The soil organic matter content was highest in HN and lowest in YC and HL. Bacterial community structure We classified the top 10 operational taxonomic units (OTUs) bacteria among soil bacterial communities in different regions based on the phylum and class to identify the dominant bacterial communities in different fields . In all soil samples obtained from Yellow River irrigation areas, at the phylum level, bacterial profiles were dominated by Proteobacteria (23%), Bacteroidetes (16.4%), Acidobacteriota (15.2%), Planctomycetes (9.4%), Chloroflexi (9.8%), Actinobacteria (8.6%), Gemmatimonadetes (6.1%), Verrucomicrobia (4.6%), Patescibacteria (4.9%), and Nitrospirae (1.5%). At the class level, Bacteroidetes (20.87%) were predominant, followed by Blastocatellia_Subgroup_4 (11.31%), Gammaproteobacteria (10.09%), Alphaproteobacteria (6.50%), and Anaerolineae (5.10%); other classes had an abundance less than 5% . Among the eight areas, LW had the highest relative abundance of Proteobacteria (28.64%), followed by YC (26.15%), PL (23.84%), HL (22.61%), HN (21.30%), YN (21.16%), QTX (20.76%), and LTQ (19.52%). In the LW sample site, the relative abundance of Bacteroidetes (18.85%) was the second-highest, followed by the abundance of Acidobacteriota (11.98%), Chloroflexi (9.87), Planctomycetes (5.41%), Patescibacteria (4.99%), Gemmatimonadetes (4.22%), Verrucomicrobia (4.44%), Actinobacteria (4.09%), and Nitrospirae (1.21%). Overall, the relative abundance of Verrucomicrobia and Acidobacteriota in QTX was the highest, that of Gemmatimonadetes in YN was the highest, and those of Actinobacteria, Patescibacteria, and Nitrospirae in YC were the highest. At the class level, the relative abundance of Bacteroidetes was the highest in LTQ (20.87%), followed by that in LW (16.98%), PL (16.64%), QTX (15.59%), HL (15.28%), YN (13.26%), YC (12.60), and HN (11.91%). Gammaproteobacteria was the second-most abundant, ranging from 13.25% in LW to 9.63% in HN. In general, LTQ had the highest relative abundance of Bacteroidetes (20.87%). QTX had the highest relative abundance of Blastocatellia_Subgroup_4. LW had the highest relative abundance of Alphaproteobacteria. YC had the highest relative abundance of Anaerolineae. PL had the highest relative abundance of Gammaproteobacteria. HN had the highest relative abundances of Phycisphaera, Deltaproteobacteria, Verrucomicrobia, Deltaproteobacteria, and Subgroup_6 . Soil bacterial diversity The soil bacterial diversity varied significantly across the eight sample sites, with YN and LW having higher Chao1 indexes than other sample plots . The ACE index of YN was significantly higher than that of other sample; however, the values did not differ significantly . The Shannon indexes of soil bacteria in HL and YN were higher than those in HN, YC, LW, QTX, and LTQ . The Good’scoverage index, which reflects the sequencing depth, indicated that the similarity of all samples in this study was more than 97%,”showing homogeneous sequencing coverage across samples. Therefore, the findings can accurately represent the community characteristics of soil bacteria in different analysis and indicate the actual bacterial distribution of each sample . The similarity in the soil bacterial community structures in the Ningxia Plain was examined in this study based on the non-metric multidimensional scaling analysis (NMDS) method. The stress value of NMDS was 0.113 (<0.2), indicating that the analytical results precisely reflected the composition differences in soil bacterial communities in the different farmlands in Ningxia . The result indicated significant differences in the soil bacterium types and bacterial community composition across different regions (R 2 = 0.13, p<0.001). The sample points between PL and YC showed significant differences and minor similarities. The differences in soil samples between the LTQ and QTX regions were minor, and the bacterial communities were largely similar. Relation between soil physicochemical properties and soil bacteria We analyzed the relationship between bacterial community composition and edaphic factors through redundancy analysis. As shown in , collectively, the cumulative squared Pearson’s correlation coefficient of the first two axes was 85.14%, which can better depict the relation between dominant bacteria and edaphic factors. The soil moisture content, organic matter, and total nitrogen had a significant impact on the soil bacterial community . Additionally, at the phylum level, the soil moisture content was positively correlated with Patescibacteria and was negatively correlated with Planctomycetes, Gemmatimonadetes, and Acidobacteriota, the soil organic matter content and pH value were positively correlated with the abundance of Planctomycetes, the total salt content was positively correlated with the abundance of Bacteroidetes.
Various physicochemical variables were used to characterize the soil environment. Among the different soil physicochemical variables , the pH values of the eight regions were weakly alkaline , and the total nitrogen, total phosphorus, and total potassium contents in the soil differed significantly. However, the trend in variation was essentially the same. The highest total nitrogen was observed in soil from HN, and the lowest was observed in soil from HL. PL had the highest soil moisture content and field capacity, followed by HN and QTX, and YC had the lowest. The ammonium nitrogen content was highest in soil from YN and lowest in soil from YC, and the nitrate nitrogen content was highest in soil from PL and HL and lowest in soil from HN. The available phosphorus and potassium contents were highest in LTQ and lowest in YC and YN. The soil organic matter content was highest in HN and lowest in YC and HL.
We classified the top 10 operational taxonomic units (OTUs) bacteria among soil bacterial communities in different regions based on the phylum and class to identify the dominant bacterial communities in different fields . In all soil samples obtained from Yellow River irrigation areas, at the phylum level, bacterial profiles were dominated by Proteobacteria (23%), Bacteroidetes (16.4%), Acidobacteriota (15.2%), Planctomycetes (9.4%), Chloroflexi (9.8%), Actinobacteria (8.6%), Gemmatimonadetes (6.1%), Verrucomicrobia (4.6%), Patescibacteria (4.9%), and Nitrospirae (1.5%). At the class level, Bacteroidetes (20.87%) were predominant, followed by Blastocatellia_Subgroup_4 (11.31%), Gammaproteobacteria (10.09%), Alphaproteobacteria (6.50%), and Anaerolineae (5.10%); other classes had an abundance less than 5% . Among the eight areas, LW had the highest relative abundance of Proteobacteria (28.64%), followed by YC (26.15%), PL (23.84%), HL (22.61%), HN (21.30%), YN (21.16%), QTX (20.76%), and LTQ (19.52%). In the LW sample site, the relative abundance of Bacteroidetes (18.85%) was the second-highest, followed by the abundance of Acidobacteriota (11.98%), Chloroflexi (9.87), Planctomycetes (5.41%), Patescibacteria (4.99%), Gemmatimonadetes (4.22%), Verrucomicrobia (4.44%), Actinobacteria (4.09%), and Nitrospirae (1.21%). Overall, the relative abundance of Verrucomicrobia and Acidobacteriota in QTX was the highest, that of Gemmatimonadetes in YN was the highest, and those of Actinobacteria, Patescibacteria, and Nitrospirae in YC were the highest. At the class level, the relative abundance of Bacteroidetes was the highest in LTQ (20.87%), followed by that in LW (16.98%), PL (16.64%), QTX (15.59%), HL (15.28%), YN (13.26%), YC (12.60), and HN (11.91%). Gammaproteobacteria was the second-most abundant, ranging from 13.25% in LW to 9.63% in HN. In general, LTQ had the highest relative abundance of Bacteroidetes (20.87%). QTX had the highest relative abundance of Blastocatellia_Subgroup_4. LW had the highest relative abundance of Alphaproteobacteria. YC had the highest relative abundance of Anaerolineae. PL had the highest relative abundance of Gammaproteobacteria. HN had the highest relative abundances of Phycisphaera, Deltaproteobacteria, Verrucomicrobia, Deltaproteobacteria, and Subgroup_6 .
The soil bacterial diversity varied significantly across the eight sample sites, with YN and LW having higher Chao1 indexes than other sample plots . The ACE index of YN was significantly higher than that of other sample; however, the values did not differ significantly . The Shannon indexes of soil bacteria in HL and YN were higher than those in HN, YC, LW, QTX, and LTQ . The Good’scoverage index, which reflects the sequencing depth, indicated that the similarity of all samples in this study was more than 97%,”showing homogeneous sequencing coverage across samples. Therefore, the findings can accurately represent the community characteristics of soil bacteria in different analysis and indicate the actual bacterial distribution of each sample . The similarity in the soil bacterial community structures in the Ningxia Plain was examined in this study based on the non-metric multidimensional scaling analysis (NMDS) method. The stress value of NMDS was 0.113 (<0.2), indicating that the analytical results precisely reflected the composition differences in soil bacterial communities in the different farmlands in Ningxia . The result indicated significant differences in the soil bacterium types and bacterial community composition across different regions (R 2 = 0.13, p<0.001). The sample points between PL and YC showed significant differences and minor similarities. The differences in soil samples between the LTQ and QTX regions were minor, and the bacterial communities were largely similar.
We analyzed the relationship between bacterial community composition and edaphic factors through redundancy analysis. As shown in , collectively, the cumulative squared Pearson’s correlation coefficient of the first two axes was 85.14%, which can better depict the relation between dominant bacteria and edaphic factors. The soil moisture content, organic matter, and total nitrogen had a significant impact on the soil bacterial community . Additionally, at the phylum level, the soil moisture content was positively correlated with Patescibacteria and was negatively correlated with Planctomycetes, Gemmatimonadetes, and Acidobacteriota, the soil organic matter content and pH value were positively correlated with the abundance of Planctomycetes, the total salt content was positively correlated with the abundance of Bacteroidetes.
Soil bacteria are a major group of microorganisms that keep soils healthy and productive. In our study, we identified the bacterial community in the Yellow River irrigation area using the microbial diversity analysis and found that the moisture, organic matter, and total nitrogen contents were the primary factors influencing the bacterial community in the Yellow River irrigation area in Ningxia, China. The findings of this study provide strong evidence for the evaluation and management of soil quality in the Yellow River irrigation area in Ningxia province. Soil physicochemical properties Soil and water quality plays an important role in the Yellow River irrigation area. A better understanding of soil and water quality will help irrigators efficiently manage their crops . In this study, the eight regions had a high pH, which may have negatively affected nutrient absorption from the soil. Additionally, soil properties, especially ammonium nitrogen, nitrate nitrogen, total phosphorus, and available phosphorus levels, were significantly different among the sample sites. These may result in the abundance of bacterial taxa in different sample sites and also indicate that bacterial communities have a relatively stable survival environment to ensure function. Bacteria response to yellow river irrigation area The composition of the soil bacterial community can reflect changes in soil quality . In our study, despite the obvious differences in the spatial scale and environmental conditions among the eight regions, some conditions are relatively similar. For example, the soil in the eight regions had a high moisture and total nitrogen content. These may result in an abundance of bacterial diversity and relatively stable compositions. At the phylum level, Proteobacteria (23%), Bacteroidetes (16.4%), and Acidobacteriota (15.2%) were the dominant groups, with a relatively high abundance in the study area, which is consistent with findings from previous studies. This indicated an absolute superiority of Proteobacteria in the bacterial community structure in farmland soil . Proteobacteria, as the most important bacterial group and one of the most abundant soil microorganisms, has been shown to be a dominant community in farmland and mining areas . Its metabolic activity is the most prominent bacterial activity in the soil. At the class level, the dominant bacteria (Gemmatimonadetes and Alphaproteobacteria) are Proteobacteria as well, which emphasizes the essential role of Proteobacteria in the bacterial community structure of farmland soils. Generally, members of Proteobacteria are present widely in various types of soil . Therefore, we confirmed that certain bacterial taxa are not unique to the Yellow River irrigation area, and their relative abundance values are simply different. A higher relative abundance of Proteobacteria is observed in LW and YN, followed by that in YC, with a lower abundance in LTQ and QTX. Previous findings on Proteobacteria (which can be used as indicators of the nutrient content) indicated that increasing Proteobacteria abundance may be beneficial for improving crop yield . The higher Proteobacteria abundance in LW and YN in our study could be beneficial for the improvement of the soil nutrient content and yield. Soil bacteria are the principal microorganisms that keep soil healthy and productive. Soil bacterial diversity is critical to the integrity of soil ecosystems and long-term soil sustainability . The difference in bacterial community structures is also considered to influence the diversity of soil bacteria; the greater the diversity of the soil bacterial community, the more stable the soil ecosystem. In this study, the Shannon indexes of soil bacteria in HL and YN were higher than those in other regions. Interestingly, the Chao1, Shannon, and ACE indexes are similar in the eight regions, even though the physical and chemical properties of the soil, such as the total nitrogen, total phosphorus, and available phosphorus levels were significantly different. This may be attributed to the long-term application of fertilizers and the presence of soil nutrients that have a strong filtration effect on soil bacteria . Soil bacteria are reportedly more sensitive to N and P enrichment; for example, changes in NH 4 + -N and NO 3 — N content can explain the effects of the bacterial community . Moreover, soil bacterial diversity is primarily controlled by factors such as pH. The soil samples used in this study were alkaline (pH > 7.0); this may be resulting the less influence of pH on bacterial communities in the Yellow River irrigation area. Meanwhile, the heterogeneity of the physical and chemical properties of soil samples is also an important factor affecting soil bacterial diversity . The plausible explanation is that the eight regions have similar soil types and soil pH, because of which the pH value considerably exceeds the suitable range (<5.5) for bacterial growth. Thus, the soil properties of the Yellow River irrigation area are in a relatively balanced state, and the difference in soil bacterial diversity in the eight regions could be used as an important reference for the management of soil quality in the Yellow River irrigation area. In addition, some studies have revealed that β diversity can also indicate differences in soil bacterial composition among agriculture systems . Also, some plants are known to affect bacterial communities in the soil, and the diversity of such plants is often used to predict the β diversity of soil bacterial communities . In our study, the composition of bacterial communities at the phyla level differed in the PL and YC regions, whereas the LTQ and QTX regions showed similarities in bacterial communities. This could be attributed to the proximity of the latter two regions and the similarity in soil conditions. The sample points in PL and YC showed significant differences and minor similarities, which could be attributed to similar soil conditions and crops . The crops in PL were dominated by wheat, apart from rice and corn; this could explain the variations in the bacterial communities in PL and YC. Previous studies have shown that soil bacteria can aggregate in response to different environmental factors , which is not consistent with our conclusions. This could be attributed to the selection of different variables in the study. Although we could not determine the factors influencing the difference in diversity, this difference could help us understand the variations in soil parameters in the different regions in the irrigation area. Abundance of bacterial communities based on the environmental variables For the sustainable production of field crops, food security, and economic prosperity, healthy and productive soil is a necessity , and nutrient availability and soil quality preservation are both considerably influenced by soil microorganisms . Soil properties (total salt, total nitrogen, and soil organic matter) were found to be the most important factors affecting the abundance and diversity of bacterial phyla, which is consistent with the results of other large-scale studies . In this study, the soil moisture content, organic matter, and total nitrogen are significant physicochemical factors influencing crop plantation in the yellow river irrigation area. Soil moisture content is the primary factor affecting the composition of bacterial communities. If the soil moisture content is reduced, it can inhibit aerobic microbial growth and promote the growth of certain anaerobic microorganisms, such as Chloroflexi, which are denitrifying bacteria . The soil water content also limits the decomposition of soil organic matter. Soil pH can serve as a precise predictor of bacterial community composition . All bacterial species can grow well in acidic pH values. Previous studies have shown that soil pH significantly affects the abundance of Actinobacteria, Gemmatimonadetes, Acidobacteriota, and Chloroflexi . The importance of soil pH in influencing bacterial structure and composition has been demonstrated in various studies conducted on different agricultural soils . Alterations in soil pH can potentially affect the nitrogen content in the soil because the initial transformation of nitrogen in the soil-plant system is affected by the concentration of ammonium and nitrate nitrogen. Organic nitrogen mineralization alters the pH value by depleting H + during ammonification or releasing H + during nitrification , indicating the important role of pH in influencing the bacterial community. In our study, the pH was alkaline and exerted lesser influence on bacterial communities; however, an obvious correlation exists among soil moisture, organic matter, total nitrogen, and the abundance of Patescibacteria, Planctomycetes, Gemmatimonadetes, and Acidobacteriota, indicating that changes in soil organic matter and nitrogen content are closely related to variations in bacterial communities during cultivation. The findings of our study indicate that soil bacteria play a major role in mediating nitrogen fixation, nitrification, denitrification, and ammonification .
Soil and water quality plays an important role in the Yellow River irrigation area. A better understanding of soil and water quality will help irrigators efficiently manage their crops . In this study, the eight regions had a high pH, which may have negatively affected nutrient absorption from the soil. Additionally, soil properties, especially ammonium nitrogen, nitrate nitrogen, total phosphorus, and available phosphorus levels, were significantly different among the sample sites. These may result in the abundance of bacterial taxa in different sample sites and also indicate that bacterial communities have a relatively stable survival environment to ensure function.
The composition of the soil bacterial community can reflect changes in soil quality . In our study, despite the obvious differences in the spatial scale and environmental conditions among the eight regions, some conditions are relatively similar. For example, the soil in the eight regions had a high moisture and total nitrogen content. These may result in an abundance of bacterial diversity and relatively stable compositions. At the phylum level, Proteobacteria (23%), Bacteroidetes (16.4%), and Acidobacteriota (15.2%) were the dominant groups, with a relatively high abundance in the study area, which is consistent with findings from previous studies. This indicated an absolute superiority of Proteobacteria in the bacterial community structure in farmland soil . Proteobacteria, as the most important bacterial group and one of the most abundant soil microorganisms, has been shown to be a dominant community in farmland and mining areas . Its metabolic activity is the most prominent bacterial activity in the soil. At the class level, the dominant bacteria (Gemmatimonadetes and Alphaproteobacteria) are Proteobacteria as well, which emphasizes the essential role of Proteobacteria in the bacterial community structure of farmland soils. Generally, members of Proteobacteria are present widely in various types of soil . Therefore, we confirmed that certain bacterial taxa are not unique to the Yellow River irrigation area, and their relative abundance values are simply different. A higher relative abundance of Proteobacteria is observed in LW and YN, followed by that in YC, with a lower abundance in LTQ and QTX. Previous findings on Proteobacteria (which can be used as indicators of the nutrient content) indicated that increasing Proteobacteria abundance may be beneficial for improving crop yield . The higher Proteobacteria abundance in LW and YN in our study could be beneficial for the improvement of the soil nutrient content and yield. Soil bacteria are the principal microorganisms that keep soil healthy and productive. Soil bacterial diversity is critical to the integrity of soil ecosystems and long-term soil sustainability . The difference in bacterial community structures is also considered to influence the diversity of soil bacteria; the greater the diversity of the soil bacterial community, the more stable the soil ecosystem. In this study, the Shannon indexes of soil bacteria in HL and YN were higher than those in other regions. Interestingly, the Chao1, Shannon, and ACE indexes are similar in the eight regions, even though the physical and chemical properties of the soil, such as the total nitrogen, total phosphorus, and available phosphorus levels were significantly different. This may be attributed to the long-term application of fertilizers and the presence of soil nutrients that have a strong filtration effect on soil bacteria . Soil bacteria are reportedly more sensitive to N and P enrichment; for example, changes in NH 4 + -N and NO 3 — N content can explain the effects of the bacterial community . Moreover, soil bacterial diversity is primarily controlled by factors such as pH. The soil samples used in this study were alkaline (pH > 7.0); this may be resulting the less influence of pH on bacterial communities in the Yellow River irrigation area. Meanwhile, the heterogeneity of the physical and chemical properties of soil samples is also an important factor affecting soil bacterial diversity . The plausible explanation is that the eight regions have similar soil types and soil pH, because of which the pH value considerably exceeds the suitable range (<5.5) for bacterial growth. Thus, the soil properties of the Yellow River irrigation area are in a relatively balanced state, and the difference in soil bacterial diversity in the eight regions could be used as an important reference for the management of soil quality in the Yellow River irrigation area. In addition, some studies have revealed that β diversity can also indicate differences in soil bacterial composition among agriculture systems . Also, some plants are known to affect bacterial communities in the soil, and the diversity of such plants is often used to predict the β diversity of soil bacterial communities . In our study, the composition of bacterial communities at the phyla level differed in the PL and YC regions, whereas the LTQ and QTX regions showed similarities in bacterial communities. This could be attributed to the proximity of the latter two regions and the similarity in soil conditions. The sample points in PL and YC showed significant differences and minor similarities, which could be attributed to similar soil conditions and crops . The crops in PL were dominated by wheat, apart from rice and corn; this could explain the variations in the bacterial communities in PL and YC. Previous studies have shown that soil bacteria can aggregate in response to different environmental factors , which is not consistent with our conclusions. This could be attributed to the selection of different variables in the study. Although we could not determine the factors influencing the difference in diversity, this difference could help us understand the variations in soil parameters in the different regions in the irrigation area.
For the sustainable production of field crops, food security, and economic prosperity, healthy and productive soil is a necessity , and nutrient availability and soil quality preservation are both considerably influenced by soil microorganisms . Soil properties (total salt, total nitrogen, and soil organic matter) were found to be the most important factors affecting the abundance and diversity of bacterial phyla, which is consistent with the results of other large-scale studies . In this study, the soil moisture content, organic matter, and total nitrogen are significant physicochemical factors influencing crop plantation in the yellow river irrigation area. Soil moisture content is the primary factor affecting the composition of bacterial communities. If the soil moisture content is reduced, it can inhibit aerobic microbial growth and promote the growth of certain anaerobic microorganisms, such as Chloroflexi, which are denitrifying bacteria . The soil water content also limits the decomposition of soil organic matter. Soil pH can serve as a precise predictor of bacterial community composition . All bacterial species can grow well in acidic pH values. Previous studies have shown that soil pH significantly affects the abundance of Actinobacteria, Gemmatimonadetes, Acidobacteriota, and Chloroflexi . The importance of soil pH in influencing bacterial structure and composition has been demonstrated in various studies conducted on different agricultural soils . Alterations in soil pH can potentially affect the nitrogen content in the soil because the initial transformation of nitrogen in the soil-plant system is affected by the concentration of ammonium and nitrate nitrogen. Organic nitrogen mineralization alters the pH value by depleting H + during ammonification or releasing H + during nitrification , indicating the important role of pH in influencing the bacterial community. In our study, the pH was alkaline and exerted lesser influence on bacterial communities; however, an obvious correlation exists among soil moisture, organic matter, total nitrogen, and the abundance of Patescibacteria, Planctomycetes, Gemmatimonadetes, and Acidobacteriota, indicating that changes in soil organic matter and nitrogen content are closely related to variations in bacterial communities during cultivation. The findings of our study indicate that soil bacteria play a major role in mediating nitrogen fixation, nitrification, denitrification, and ammonification .
The bacterial community composition in the soil from eight irrigation areas in northwestern China was significantly different. Bacterial communities tend to be similar in soils with similar physicochemical properties. Soil moisture was positively correlated with the abundance of Patescibacteria and negatively correlated with the abundance of Planctomycetes, Gemmatimonadetes, and Acidobacteriota. Soil organic matter and pH value were positively correlated with the abundance of Planctomycetes. The total salt content was positively correlated with Bacteroidetes abundance. Soil moisture, organic matter content, and total nitrogen were the primary factors that influenced the bacterial community composition in the Yellow River irrigation area. The results of this study will help elucidate the functional contributions of soil bacterial communities to the soil ecosystem and predict the potential function of soil quality in the future, which has gained importance owing to continuous climate change and increasing land-use intensity.
S1 File Physical and chemical property data. (XLSX) S2 File Composition of soil bacterial community at phylum level. (XLS) S3 File Composition of soil bacterial community at class level. (XLS) S4 File α diversity comparison of soil bacteria data. (XLS) S5 File NMDS analysis data. (XLS) S6 File Correlation analysis between phylum bacteria and physicochemical properties. (XLS)
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Determination of Priorities for Lung Transplant Education for Pulmonary and Critical Care Medicine Fellows | 7b76b1e9-f81a-4cd2-80bd-195d8a50f849 | 11734675 | Internal Medicine[mh] | Study Design We developed expert consensus on lung transplantation topics and subtopics (“items”) for a graduating PCCM fellow through modified electronic Delphi methodology from July 2023 to October 2023. The modified electronic Delphi methodology was chosen because it is a systematic way to elicit expert consensus in an area without clear data . Our study conforms to the Delphi reporting guidelines as outlined by the CREDES (Conducting and Reporting of Delphi Studies) tool . This study was deemed exempt by the Mayo Clinic Institutional Review Board. Panelist Selection Our panelists were a group of transplant pulmonologists from academic medical centers with an interest in medical education from the United States and Europe. Panelists were self-identified after a recruitment e-mail was sent to the American College of Chest Physicians Transplant Network listserv and to a separate group of International Society for Heart Lung Transplantation network members interested in lung transplant education. Panelists received personalized questionnaire links for each Delphi round. Preserving anonymity was not always possible, because several panelists included other interested colleagues in their reply to our recruitment e-mail. The information provided to the panelists at the time of recruitment was a brief description of the study and learner level (“for a graduating PCCM fellow, not lung transplant fellow”), intended plans for the data generated, and expectations for participation. Panelists were expected to complete up to three survey rounds, review feedback between rounds, and provide information about their clinical roles. Survey Design and Iterative Feedback We used Qualtrics to survey our panelists. Panelists were asked to rank items as “must know” (MK), “nice to know” (NK), or “not necessary to know” (NN) for a graduating PCCM fellow. Consensus was defined as having ≥50% of responses as MK. If an item had tied responses that included MK, it was submitted for reranking in the subsequent round. Closing criteria a priori was decided to be three rounds. Weekly reminder e-mails were sent during each round. For round 1, we created a list of items based on senior author expertise (one lung transplantation fellowship–trained PCCM physician/associate program director of a lung transplantation fellowship/3 yr in practice; one PCCM physician/associate program director of a PCCM fellowship/7 yr in practice), and the ABIM/ACGME core competencies. Panelists were also given the opportunity to suggest new items in this round only. Between the first and second rounds, panelists were provided e-mail feedback on 1 ) round 1 response rate, 2 ) items that did not achieve consensus, and 3 ) transplantation-related ABIM and ACGME competencies for PCCM fellows. Summary statistics for how the group ranked items in this round were not provided. All new items generated were reviewed by the authors for duplication, relevance to learner level, clarity, and uniqueness to transplantation medicine before being considered for ranking in round 2. This additional step was taken by the authors as a quality control measure outside of usual Delphi practice to streamline the survey experience. In round 2, panelists were asked to rerank any items from round 1 that had tied MK responses and those new items after author review. Between the second and third rounds, panelists were provided e-mail feedback on 1 ) round 2 response rate and 2 ) items that did not achieve consensus. Summary statistics for how the group ranked items in this round were not provided. In round 3, panelists were asked to rerank items that had tied MK responses in round 2. Response rate was defined as having opened the questionnaire link and/or a partially completed questionnaire. Completion rate was defined as 100% completion of the questionnaire. We developed expert consensus on lung transplantation topics and subtopics (“items”) for a graduating PCCM fellow through modified electronic Delphi methodology from July 2023 to October 2023. The modified electronic Delphi methodology was chosen because it is a systematic way to elicit expert consensus in an area without clear data . Our study conforms to the Delphi reporting guidelines as outlined by the CREDES (Conducting and Reporting of Delphi Studies) tool . This study was deemed exempt by the Mayo Clinic Institutional Review Board. Our panelists were a group of transplant pulmonologists from academic medical centers with an interest in medical education from the United States and Europe. Panelists were self-identified after a recruitment e-mail was sent to the American College of Chest Physicians Transplant Network listserv and to a separate group of International Society for Heart Lung Transplantation network members interested in lung transplant education. Panelists received personalized questionnaire links for each Delphi round. Preserving anonymity was not always possible, because several panelists included other interested colleagues in their reply to our recruitment e-mail. The information provided to the panelists at the time of recruitment was a brief description of the study and learner level (“for a graduating PCCM fellow, not lung transplant fellow”), intended plans for the data generated, and expectations for participation. Panelists were expected to complete up to three survey rounds, review feedback between rounds, and provide information about their clinical roles. We used Qualtrics to survey our panelists. Panelists were asked to rank items as “must know” (MK), “nice to know” (NK), or “not necessary to know” (NN) for a graduating PCCM fellow. Consensus was defined as having ≥50% of responses as MK. If an item had tied responses that included MK, it was submitted for reranking in the subsequent round. Closing criteria a priori was decided to be three rounds. Weekly reminder e-mails were sent during each round. For round 1, we created a list of items based on senior author expertise (one lung transplantation fellowship–trained PCCM physician/associate program director of a lung transplantation fellowship/3 yr in practice; one PCCM physician/associate program director of a PCCM fellowship/7 yr in practice), and the ABIM/ACGME core competencies. Panelists were also given the opportunity to suggest new items in this round only. Between the first and second rounds, panelists were provided e-mail feedback on 1 ) round 1 response rate, 2 ) items that did not achieve consensus, and 3 ) transplantation-related ABIM and ACGME competencies for PCCM fellows. Summary statistics for how the group ranked items in this round were not provided. All new items generated were reviewed by the authors for duplication, relevance to learner level, clarity, and uniqueness to transplantation medicine before being considered for ranking in round 2. This additional step was taken by the authors as a quality control measure outside of usual Delphi practice to streamline the survey experience. In round 2, panelists were asked to rerank any items from round 1 that had tied MK responses and those new items after author review. Between the second and third rounds, panelists were provided e-mail feedback on 1 ) round 2 response rate and 2 ) items that did not achieve consensus. Summary statistics for how the group ranked items in this round were not provided. In round 3, panelists were asked to rerank items that had tied MK responses in round 2. Response rate was defined as having opened the questionnaire link and/or a partially completed questionnaire. Completion rate was defined as 100% completion of the questionnaire. Panelists A total of 33 panelists were sent questionnaire links in each round, and there were 25 unique panelists who participated in one or more rounds. The 23 panelists from round 1 responded to the item on location of practice. Panelists represented 12 unique institutions in the United States and 3 from Europe. Of the 22 respondents to the item on educational leadership role, 17 (77%) identified as core faculty members and 1 identified as an assistant program director of a PCCM fellowship . Round 1 In round 1, the response rate was 70% ( n = 23), and the completion rate was 96% ( n = 22). The initial eight topics and 30 subtopics are provided in Appendix E1 in the online supplement. All topics achieved “must know” consensus in this round except “transplant immunology” (50% MK, 50% NK), which was submitted for reranking, and “allograft donation and procurement” (59% NK, 27% NN), which was discarded. Three subtopics had tied MK responses: “response to allograft” (50% MK, 50% NK), “type of listing (41% MK, 41% NK), and “recurrence of native disease” (41% MK, 41% NK). “Response to allograft” was intentionally discarded from reranking because of vagueness of the term in relation to the new items suggested under transplant immunology. The other two subtopics were inadvertently omitted from the round 2 questionnaire. Five subtopics had majority responses that were not MK and were also discarded (“highly HLA sensitized patients,” “donor evaluation and types,” “ ex vivo lung perfusion,” “overview of surgical techniques,” and “lymphoproliferative disorders”). Last, one subtopic that did achieve “must know” consensus (“normal immune response”) was intentionally discarded because of vagueness of the term in relation to the new items suggested under transplant immunology . In this first round, a total of 82 new items were suggested (Appendix E2), with most under the topics of transplant immunology (22 items) and evaluation of a lung transplant candidate (10 items). After author review, 19 new subtopics were selected for reranking after consolidation in addition to the previous topic of “transplant immunology” (Appendix E3). Examples of our consolidation included, under the topic of “complications,” “long-term complications” was suggested (too vague); “heart failure,” and “osteoporosis” were suggested but also span many areas of pulmonary medicine (uniqueness); and “CLAD” (chronic lung allograft dysfunction) and “chronic rejection” were suggested (duplication). Round 2 In round 2, the response rate was 67% ( n = 22), and the completion rate was 100%. Twenty of the panelists participated in round 1. The topic of “transplant immunology” and 15 subtopics achieved MK consensus. Two subtopics had tied responses and were submitted for reranking: “predictors of prolonged wait time” (45% MK, 45% NK) and “thoracoabdominal normothermic regional perfusion (TA-NRP)” (45% NK, 45% NN). The latter was unintentionally included in reranking despite not having an MK tied response. Two subtopics were intentionally discarded: “UNOS [United Network for Organ Sharing] allocation system” (50% NK, 14% NN) and “thoracic compartment syndrome” (MK majority of 40.9% less than the prespecified consensus cutoff of 50%). Round 3 In round 3, the response rate was 58% ( n = 19), and the completion rate was 100%. Sixteen of the panelists had participated in both prior rounds. Of the two items in this round, neither achieved MK consensus; “predictors of prolonged wait time” had a tied response (47% MK, 47% NK), and “TA-NRP” had a 53% majority response of NN. The final list of 7 “must know” topics and 36 subtopics is shown in . A total of 33 panelists were sent questionnaire links in each round, and there were 25 unique panelists who participated in one or more rounds. The 23 panelists from round 1 responded to the item on location of practice. Panelists represented 12 unique institutions in the United States and 3 from Europe. Of the 22 respondents to the item on educational leadership role, 17 (77%) identified as core faculty members and 1 identified as an assistant program director of a PCCM fellowship . In round 1, the response rate was 70% ( n = 23), and the completion rate was 96% ( n = 22). The initial eight topics and 30 subtopics are provided in Appendix E1 in the online supplement. All topics achieved “must know” consensus in this round except “transplant immunology” (50% MK, 50% NK), which was submitted for reranking, and “allograft donation and procurement” (59% NK, 27% NN), which was discarded. Three subtopics had tied MK responses: “response to allograft” (50% MK, 50% NK), “type of listing (41% MK, 41% NK), and “recurrence of native disease” (41% MK, 41% NK). “Response to allograft” was intentionally discarded from reranking because of vagueness of the term in relation to the new items suggested under transplant immunology. The other two subtopics were inadvertently omitted from the round 2 questionnaire. Five subtopics had majority responses that were not MK and were also discarded (“highly HLA sensitized patients,” “donor evaluation and types,” “ ex vivo lung perfusion,” “overview of surgical techniques,” and “lymphoproliferative disorders”). Last, one subtopic that did achieve “must know” consensus (“normal immune response”) was intentionally discarded because of vagueness of the term in relation to the new items suggested under transplant immunology . In this first round, a total of 82 new items were suggested (Appendix E2), with most under the topics of transplant immunology (22 items) and evaluation of a lung transplant candidate (10 items). After author review, 19 new subtopics were selected for reranking after consolidation in addition to the previous topic of “transplant immunology” (Appendix E3). Examples of our consolidation included, under the topic of “complications,” “long-term complications” was suggested (too vague); “heart failure,” and “osteoporosis” were suggested but also span many areas of pulmonary medicine (uniqueness); and “CLAD” (chronic lung allograft dysfunction) and “chronic rejection” were suggested (duplication). In round 2, the response rate was 67% ( n = 22), and the completion rate was 100%. Twenty of the panelists participated in round 1. The topic of “transplant immunology” and 15 subtopics achieved MK consensus. Two subtopics had tied responses and were submitted for reranking: “predictors of prolonged wait time” (45% MK, 45% NK) and “thoracoabdominal normothermic regional perfusion (TA-NRP)” (45% NK, 45% NN). The latter was unintentionally included in reranking despite not having an MK tied response. Two subtopics were intentionally discarded: “UNOS [United Network for Organ Sharing] allocation system” (50% NK, 14% NN) and “thoracic compartment syndrome” (MK majority of 40.9% less than the prespecified consensus cutoff of 50%). In round 3, the response rate was 58% ( n = 19), and the completion rate was 100%. Sixteen of the panelists had participated in both prior rounds. Of the two items in this round, neither achieved MK consensus; “predictors of prolonged wait time” had a tied response (47% MK, 47% NK), and “TA-NRP” had a 53% majority response of NN. The final list of 7 “must know” topics and 36 subtopics is shown in . Through modified electronic Delphi methodology, we created a content outline of 7 “must know” topics and 36 subtopics in lung transplantation for graduating PCCM fellows that serves as a starting point for future curriculum development. This content outline is comprehensive, reflects current practice, and fulfills a gap in the sparse lung transplantation education literature . Our results suggest that transplant pulmonologists expect graduating PCCM fellows to have a more nuanced understanding of transplantation topics than suggested by current ABIM/ACGME standards. When comparing our results with these current standards , it is evident that our content outline clarifies important details. This clarification can cue PCCM educators to high-yield transplantation topics to add to their fellowship curriculum and can be particularly helpful in cases where no transplant curriculum exists in part because of lack of faculty training or resources . Most of the items not included in the final content outline (Appendix E4) pertain to details on listing, surgery, or rare complications that are appropriate exclusions, considering the scope of practice of a general pulmonologist. One notable exception is “lymphoproliferative disorders,” which fits in the ABIM “neoplastic complications” category. However, creating a new curriculum for as broad an outline as this is a time-intensive process, and it may not be feasible to deliver this within the scope of a balanced PCCM training program. Some may argue that a curricular footprint this broad in transplantation is not necessary, given small representation on the current board certification examination. Regarding the former, we suggest starting with a more condensed list of 4 topics and 11 subtopics for reasons described below. We argue regarding the latter that the growing patient population of surviving lung transplant recipients does warrant increased training during fellowship and that standardized examinations have limitations, including not always reflecting real-world practice. Several aspects of our study design may have contributed to this broad outline. First, there were no general pulmonologists on our expert panel, which may have led to selection bias regarding the nature and difficulty of items ranked as “must know”; a content expert panel may be generally unfamiliar with the educational needs of less specialized learners. Second, we used a percentage agreement cutoff of ≥50% to define consensus. Although the range of percentage agreement cutoffs reported in a meta-analysis of consensus studies varied from 50% to 97%, the median was higher at 75% . Our choice of using a lower cutoff meant more items were included in the final outline than if a higher threshold had been used. If we were to apply a threshold of 75% on the final outline, this would result in a list of 4 topics and 11 subtopics . The advantage of this is a more realistic starting point for curriculum development, but it does result in deviation from standard Delphi methodology. Last, we did not provide complete summary statistics of how the group ranked items between rounds, so panelists were unaware of the extent of agreement on items. It is possible that had we provided this information and additional opportunity for feedback, fewer items would have been included in the final outline. Although this is a deviation from Delphi methodology, we believed that because most items achieved consensus in the first round, they did not need to be reconsidered, especially given that reconsideration of old items along with new items would have led to significant survey length and potentially lower completion rates. Future Directions More work is needed to determine optimal instructional design for lung transplantation topics. Given that only 8% of PCCM program directors reported use of online modules for lung transplantation , we believe that this avenue should be explored further. Online self-paced modules may solve the problem of limited protected didactic time to cover a broad content outline. Given the effort required to create new curriculum to address this, it is reasonable to consider sharing content with the caveat that transplantation medicine is highly institution specific . Little is also known about trainee perspectives on lung transplantation education. The 2016 needs assessment was reflective of program directors’ opinions only. Data regarding ILD education show that there may be differences in how trainees rate their own ability levels relative to how program directors perceive trainees’ ability levels. Strengths Our study has several strengths. It is the first, to our knowledge, to describe the creation of a lung transplantation content outline for PCCM fellows in a scholarly fashion, filling a gap in the literature. It has high survey response/completion rates with low attrition between rounds. We had geographic diversity within our expert panel spanning 7 of 11 Organ Procurement Organization regions in the United States. Most panelists were also involved in trainee education in some capacity. Last, we report on most of the 13 elements considered to be “high quality” for a medical education Delphi study . Limitations In addition to the limitations described above regarding lack of general pulmonologists on the panel, a low percentage agreement cutoff, and the nature of feedback provided, we describe a few others. There is overlap in multiple subtopics under the infections topic. We assume that the spirit of each subtopic is different, but more opportunities for panelists to provide feedback during the survey phase would have confirmed this. For example, for “EBV/CMV serostatus,” we infer that it is important to know how this affects the risk of Epstein-Barr virus/cytomegalovirus infection or reactivation relative to “infections <1 year post-transplant,” and we assume it is important to recognize that overall immunosuppression is greatest in the first year and that most opportunistic infections occur during this time. Our panelists were self-identified, and our cohort included European providers who may have different opinions on knowledge requirements, given training pathways differing from those in the United States. Last, because of clerical error, two subtopics that had tied MK responses were inadvertently excluded from reranking (“type of listing” and “recurrence of native disease”) in the second round. Educator discretion should be used when considering these items in curriculum development. Conclusion We identified 7 topics and 36 subtopics in lung transplantation deemed to be “must know” topics for a graduating PCCM fellow through electronic modified Delphi methodology by a panel of self-identified lung transplantation experts. The findings serve as a starting point for future curriculum development. More work is needed to determine optimal instructional design for lung transplantation topics. Given that only 8% of PCCM program directors reported use of online modules for lung transplantation , we believe that this avenue should be explored further. Online self-paced modules may solve the problem of limited protected didactic time to cover a broad content outline. Given the effort required to create new curriculum to address this, it is reasonable to consider sharing content with the caveat that transplantation medicine is highly institution specific . Little is also known about trainee perspectives on lung transplantation education. The 2016 needs assessment was reflective of program directors’ opinions only. Data regarding ILD education show that there may be differences in how trainees rate their own ability levels relative to how program directors perceive trainees’ ability levels. Our study has several strengths. It is the first, to our knowledge, to describe the creation of a lung transplantation content outline for PCCM fellows in a scholarly fashion, filling a gap in the literature. It has high survey response/completion rates with low attrition between rounds. We had geographic diversity within our expert panel spanning 7 of 11 Organ Procurement Organization regions in the United States. Most panelists were also involved in trainee education in some capacity. Last, we report on most of the 13 elements considered to be “high quality” for a medical education Delphi study . In addition to the limitations described above regarding lack of general pulmonologists on the panel, a low percentage agreement cutoff, and the nature of feedback provided, we describe a few others. There is overlap in multiple subtopics under the infections topic. We assume that the spirit of each subtopic is different, but more opportunities for panelists to provide feedback during the survey phase would have confirmed this. For example, for “EBV/CMV serostatus,” we infer that it is important to know how this affects the risk of Epstein-Barr virus/cytomegalovirus infection or reactivation relative to “infections <1 year post-transplant,” and we assume it is important to recognize that overall immunosuppression is greatest in the first year and that most opportunistic infections occur during this time. Our panelists were self-identified, and our cohort included European providers who may have different opinions on knowledge requirements, given training pathways differing from those in the United States. Last, because of clerical error, two subtopics that had tied MK responses were inadvertently excluded from reranking (“type of listing” and “recurrence of native disease”) in the second round. Educator discretion should be used when considering these items in curriculum development. We identified 7 topics and 36 subtopics in lung transplantation deemed to be “must know” topics for a graduating PCCM fellow through electronic modified Delphi methodology by a panel of self-identified lung transplantation experts. The findings serve as a starting point for future curriculum development. 10.34197/ats-scholar.2024-0046OC Data Supplement |
Spray-Congealing and Wet-Sieving as Alternative Processes for Engineering of Inhalation Carrier Particles: Comparison of Surface Properties, Blending and | ede2135a-6cf0-4281-8df1-611e4b419e74 | 8217042 | Pharmacology[mh] | In dry powder inhalation (DPI), drugs are delivered as solid particles to the lung. In order to reach the lower respiratory airways, the drug particles have to be in the size range of 0.5/1.0 to 5.0 μm . Due to their very large surface to volume ratio, the particles in the aforementioned size range, are cohesive and possess poor powder flow. The flowability and dispersion of the inhaled active pharmaceutical ingredient (API) particles can be improved by specifically tailoring their properties (e.g., to free-flowing large porous particles) or blending with excipients. Traditionally, the drug particles are blended with coarse excipient ones (Dv 0.5 ≥ 20 μm) in a practice known as adhesive mixing. Adhesive mixing aims to attach the smaller API particles onto the surface of larger excipient ones. Likewise, the excipient functions as a ‘carrier’ and such formulations are called carrier-based DPI formulations. α-lactose monohydrate (α-LH) particles are typical DPI carriers presenting a tomahawk shape and a mean particle size (Dv 0.5 ) between 50 μm and 250 μm, depending on the device used. α-LH can be blended solely with the API, forming binary blends or can be mixed with the drug and other excipient particles that are added in order to improve the aerosolization. These excipient particles, presenting a size smaller than the coarse carrier, are usually known as fines. Excipient fines are usually magnesium stearate or lactose particles alone or in a mixture. Fine particles are known to aid the performance of DPIs by a variety of mechanisms . Although α-LH has been typically used as a carrier, its complex solid state, encompassing 2 anomeric forms, 2 anhydrous polymorphs and 1 hydrate of its α-anomer as well as an amorphous phase makes engineering of lactose particles quite challenging. Moreover, high temperature engineering processes cannot be applied to lactose due to its degradation upon melting. Thus, D-mannitol, a sugar approved for inhalation , is regarded as a good alternative to lactose. D-mannitol crystals exist as two polymorphs (the α- and β-forms) with very similar thermodynamic behavior that are monotropically related, and a metastable form enantiotropically (δ-form) related to the β-polymorph. Although, an amorphous phase and a hemi-hydrate of the β-polymorph are known, these forms cannot be easily obtained under ambient conditions. Moreover, D-mannitol does not degrade upon melting offering the possibility to process it at high temperatures. Thus, D-mannitol has been extensively studied as a potential carrier for DPIs in recent years . In 2017, Merck has started commercializing a grade of D-mannitol intended to be used as a carrier in DPI formulations . During inhalation, carrier particles will impact the upper respiratory tract and get swallowed or expectorated. Thus, although drug particles need to attach with sufficient force to the carrier surface to be properly handled during manufacturing, and in particular to facilitate dose metering, the attachment also has to be loose enough to allow drug detachment during inhalation. DPI formulations are commonly delivered using inhalation devices that rely on the inspiratory forces of patients to fluidize the powder and promote detachment. Hence, when designing excipient particles for inhalation a combination of factors related to the carrier and API combination as well as type of inhalation device and its dependency on the patient inspiratory force, should be considered . Often, excipient particles lack the most adequate characteristics when obtained from primary manufacturing and have to be further engineered. Therefore, in the present work, we aim to explore innovative engineering strategies that allow the production of D-mannitol particles, which have adequate characteristics, to be successfully applied as carriers for DPI. Wet-sieving, commonly used in soil analysis , and previously used by Adi et al . to fractionate lactose particles intended for inhalation , was selected to engineer D-mannitol. During wet-sieving, powder particles are washed with an anti-solvent and fractionated. Thus, wet-sieving was used for removing the variable amount of fine particles present in the raw excipient powder. Spray-congealing (also known as spray-chilling or spray-cooling), which is a melt-based technique able to produce well-defined spherical particles , was also applied to engineer D-mannitol. In this process, molten D-mannitol was atomized into droplets through a bi-fluid nozzle and sprayed into a cooling chamber where the melt quickly solidified forming solid microparticles. The technique was selected due to its known ability to produce free-flowing particles with a diameter between 50 and 500 μm. To evaluate the impact of engineering on particle properties, D-mannitol powders were characterized concerning their solid-state, micromeritics and flowability. Afterwards, D-mannitol was blended (in binary and ternary mixtures) in low doses (1 wt%) with an inhaled corticosteroid (i.e., beclomethasone dipropionate). The obtained blends were tested in combination with a reservoir inhaler (NEXThaler®) and the aerosolization performance of the distinct particles of D-mannitol was evaluated, accordingly. Whenever relevant, the performance of the D-mannitol particles was compared to that of α-LH engineered by the same techniques. Eventually, it was possible to understand the applicability of wet-sieving and spray-congealing in producing novel D-mannitol carriers for DPI delivery.
Materials D-mannitol (Pearlitol® 300 DC) was purchased from Roquette (France) and α-LH (CapsuLac® 60 and InhaLac® 120) was obtained from Meggle (Germany). The model API, beclomethasone dipropionate (BDP) with a mean particle size of 1.05 μm was provided by Chiesi Pharmaceutici S.p.A, Italy. Magnesium Stearate (MgSt) as well as acetone were purchased from Merck KGaA, Germany. Particle Engineering Surface Processing Via Wet-Sieving The experimental set-up used for wet-sieving in the present study was based on the work by Robertson et al . . A standard vibratory sieve shaker (AS200, Retsch, Germany), as schematically shown in Fig. was used to wet-sieve the particles of D-mannitol. Before wet-sieving, D-mannitol and acetone (anti-solvent) were mixed in a 1:2 wt% ratio and placed in an ultrasonic bath for 5 min. The resulting mixture was transferred to a 100 μm sieve (top of the tower) and the vibration intensity was set to 0.2. The wet-sieving of the powder was then carried out by consecutively rinsing the sample with acetone (400 ml for 20 g of powder) as the tower was vibrating. When the process was finished, the washed material was transferred to a filter paper and placed under a fume hood for 24 h in order to let the material dry. α-LH (CapsuLac®60) was also engineered using the same procedure as a control/reference for comparison. Spray-Congealing The particles of D-mannitol were also engineered via spray-congealing (4 M8-TriX spray-congealer, ProCepT, Belgium). In this process, D-mannitol was first placed in an oven at 190°C and once a melt was obtained this was transferred to a heated vessel kept at 200°C. The molten fluid was pumped at 20.0 ± 1.4 g/min from the vessel to a heated bi-fluid nozzle (diameter 1.2 mm) and atomized (0.44 bar) into a glass tower chilled at −10°C, using a nitrogen flow of 0.6 m 3 /min. The solidified particles were separated from the air stream using a cyclone set at a pressure drop of 13 mbar and collected in a glass vessel at 13°C (Fig. ). Characterization of the Engineered Powders Scanning Electron Microscopy (SEM) The powder samples were observed using scanning electron microscopy (SEM). For this, the particles were sputtered with gold-palladium and then examined using a Zeiss Ultra 55 scanning microscope (Zeiss, Germany), operating at 5 kV. Particle Size Distribution The particle size distribution (PSD) was determined using laser light diffraction (HELOS/KR, Sympatec GmbH, Germany). A dry dispersing system (Rodos, Sympatec) and a vibrating chute (Vibri, Sympatec) were used for powder dispersion. The powders were analyzed using a primary dispersion pressure of 1.0 bar and using the R2 (0.45–87.50 μm) and R5 (4.5–875.0 μm) optical modes. The measurements were triggered once an optical concentration of 0.5% was achieved. The resulting volumetric particle size distributions were calculated and analyzed using Windox 5 software (Sympatec GmbH, Germany). Particle Solid-State The solid-state of the particles was characterized by differential scanning calorimetry (DSC 204F1 Phoenix®, Netzsch GmbH, Germany) and wide-angle X-ray scattering (WAXS, S3-MICRO camera, Bruker AXS GmbH, Germany). For the DSC analysis, 10–12 mg sample were weighed into an aluminum pan and crimped with a pierced lid. The samples were heated from 25 to 200°C at a rate of 10°C/min using pure nitrogen as purging gas at a flow rate of 20 mL/min. The DSC data analysis was conducted with Proteus Thermal Analysis software (Netzsch GmbH, Germany). For the WAXS analysis, the powder samples were filled into 2 mm glass capillaries and analyzed under constant rotation (9 rpm) between the angular range of 17 and 27° 2θ during 600 s at 30 counts/s (22 ± 2°C). Determination of the Specific Surface Area and Bulk Roughness Nitrogen gas adsorption (TriStar II 3020, Micromeretics, USA) was used to determine the specific surface area of the powders. Before analysis, the samples were treated under vacuum (VacPrep 061, Micromeritics, USA) overnight at room temperature (22 ± 2°C). A 5-point analysis was performed using a nitrogen relative pressure (p/p 0 ) between 0.06–0.20 and the Brunauer – Emmett – Teller (BET) adsorption theory was used to calculate the specific surface area (SSA BET ). The bulk roughness (BR) of the different D-mannitol particles was calculated as the ratio between the SSA BET and the theoretical specific surface area (SSA sv ) calculated based on the particle size volume-distribution assuming spherical particles (Eq. ) . 1 [12pt]{minimal}
$$ {}_{}=}_{} } $$ SSA SV = 6 D sv × ρ The D sv is the Sauter mean diameter determined by laser diffraction as described above in the relevant section and ρ is the true density of the particles. The true density was calculated as the ratio between the mass of particles and their respective volume. The particle volume was determined by helium pycnometry (AccuPyc II 1340, Micromeritics, USA), using 20 purges at 19.5 psi with an equilibration rate of 0.0050 psi/min. Powder Flowability The flowability of the powders was measured using a FT4 Powder Rheometer (Freeman Technology, UK). An appropriate amount of sample was placed in a 1 ml cell in order to fill it. A standard conditioning cycle was applied using a 23.5 mm blade moving down a helical path in order to generate a uniform low packing powder bed. Afterwards, the surplus of powder was removed by splitting the cell and the blade was replaced by a 24 mm shear cell. The powder was pre-consolidated at 9 kPa and then sheared at 7, 6, 5, 4, and 3 kPa. The flowability parameters of the powders were obtained from the Mohr’s stress circles. The major principal (δ 1 ) and unconfined yield (δ c ) stresses are the highest values at which the larger and smaller Mohr’s stress intercept the x axis. The cohesion (Coh) is the point of intersection of the yield locus (normal stress = 0). The flow function coefficient (ffc) is the ratio between the major principal stress and the unconfined yield stress. The angle of internal friction (AIF eff ) was determined from the effective yield locus. Evaluation of Powder Performance for Dry Powder Inhalation To evaluate the applicability of the D-mannitol powders as carriers for inhalation, the particles were blended with BDP (Dv 0.5 = 1.05 μm), yielding low load (1 wt%) adhesive blends that were tested concerning their aerosolization performance. For comparison, α-LH particles (CapsuLac®60, Meggle, Germany) were blended and tested under similar conditions. Preparation of the Adhesive Mixtures To obtain 20 g binary mixture of API and carrier, 200 mg of BDP were weighted and placed in a 50 ml glass bottle between two even layers of the excipient (19.8 g). The glass bottle was place in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 2 h at 32 rpm. The obtained blend was sieved through a 400 μm mesh and mixed again for 30 min at 32 rpm. To yield 20 g of ternary mixture of the carrier, API and 0.2 wt% magnesium stearate (MgSt) or 10 wt% ‘Preblend’ (composed of InhaLac® 120 and 0.2% MgSt), 40 mg of MgSt or 2 g of ‘Preblend’ were weighted and placed in 50 ml glass bottles between two even layers of D-mannitol (19.96 and 18.00 g of carrier, respectively). The glass bottles were placed in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 4 h at 32 rpm. Once a mixture of carrier and MgSt or ‘Preblend’ was obtained, the powders were blended with 1 wt% BDP following the same procedure as for the binary blends. Mixing Homogeneity The mixing homogeneity was determined by taking 10 samples of about 20 mg from distinct zones of the bulk powder blends. The samples were dissolved in a small amount of methanol and after that 100 ml of a mixture of methanol and water (70:30 vol%) were added and the samples were placed in an ultrasonic bath for 5 to 10 min in order to completely dissolve the API. The API content in each sample was analyzed via high performance liquid chromatography (described in the relevant section below) and the mixing homogeneity expressed as the relative standard deviation (RSD) from the mean drug content. Shot Weight Consistency Samples of binary and ternary blends (1.5 g) were manually filled into NEXThaler® devices (Chiesi, Italy) and the filled inhalers conditioned overnight in desiccators at 60% RH. The shot weight consistency was analyzed by firing the inhalers 10 times into a DUSA (Dosage Unit Sampling Apparatus) and determining the mass delivered via each actuation using the weight difference, before and after emission. Between each emission the inhalers were discharge using antistatic bars. Likewise, the mean shot weight and respective standard deviation were calculated based on the weight of 10 shots and the delivered mass consistency evaluated, accordingly. Evaluation of the Aerodynamic Performance The aerodynamic performance of binary and ternary DPI blends was assessed via next generation impactor (NGI, Copley Scientific, UK) experiments . To avoid particle bouncing, the stages of the impactor were coated with 2 vol% Tween 20 in ethanol prior to analysis. For each NGI experiment, one shot of the conditioned (at 60% RH) NEXThaler® was discharged. The flow rate was set to 60 L/min in order to reach a pressure drop of 4 kPa over the inhaler and the flow was applied for 4 s in order to ensure that 4 L of air were drawn via the mouthpiece over the inhaler. The drug content in each part of the impactor was quantified using a validated high performance liquid chromatography method (following section) and for each inhaler three NGI experiments were performed. The BDP in vitro deposition profile, fine particle fraction (FPF), fine particle dose (FPD), and the emitted dose (ED) were calculated and compared. High Performance Liquid Chromatography (HPLC) BDP was quantified via HPLC using a Waters Alliance 2695 HPLC system equipped with a 2996 photodiode array detector. A Waters Atlantis dC18 column (150 × 3.9 mm; 3 μm) was used as stationary phase and mobile phase was composed of acetonitrile/0.02 M sodium di-hydrogen phosphate monohydrate set to pH 3.0 (70:30 vol%). The system was operated in isocratic mode at a flow rate of 1 mL/min and a column temperature of 40°C. The injection volume was 50 μL and run time was 6.0 min, whereas the retention time of BDP was approximately 4.2 min. The UV-detection was conducted at a wavelength of 238 nm.
D-mannitol (Pearlitol® 300 DC) was purchased from Roquette (France) and α-LH (CapsuLac® 60 and InhaLac® 120) was obtained from Meggle (Germany). The model API, beclomethasone dipropionate (BDP) with a mean particle size of 1.05 μm was provided by Chiesi Pharmaceutici S.p.A, Italy. Magnesium Stearate (MgSt) as well as acetone were purchased from Merck KGaA, Germany.
Surface Processing Via Wet-Sieving The experimental set-up used for wet-sieving in the present study was based on the work by Robertson et al . . A standard vibratory sieve shaker (AS200, Retsch, Germany), as schematically shown in Fig. was used to wet-sieve the particles of D-mannitol. Before wet-sieving, D-mannitol and acetone (anti-solvent) were mixed in a 1:2 wt% ratio and placed in an ultrasonic bath for 5 min. The resulting mixture was transferred to a 100 μm sieve (top of the tower) and the vibration intensity was set to 0.2. The wet-sieving of the powder was then carried out by consecutively rinsing the sample with acetone (400 ml for 20 g of powder) as the tower was vibrating. When the process was finished, the washed material was transferred to a filter paper and placed under a fume hood for 24 h in order to let the material dry. α-LH (CapsuLac®60) was also engineered using the same procedure as a control/reference for comparison. Spray-Congealing The particles of D-mannitol were also engineered via spray-congealing (4 M8-TriX spray-congealer, ProCepT, Belgium). In this process, D-mannitol was first placed in an oven at 190°C and once a melt was obtained this was transferred to a heated vessel kept at 200°C. The molten fluid was pumped at 20.0 ± 1.4 g/min from the vessel to a heated bi-fluid nozzle (diameter 1.2 mm) and atomized (0.44 bar) into a glass tower chilled at −10°C, using a nitrogen flow of 0.6 m 3 /min. The solidified particles were separated from the air stream using a cyclone set at a pressure drop of 13 mbar and collected in a glass vessel at 13°C (Fig. ).
The experimental set-up used for wet-sieving in the present study was based on the work by Robertson et al . . A standard vibratory sieve shaker (AS200, Retsch, Germany), as schematically shown in Fig. was used to wet-sieve the particles of D-mannitol. Before wet-sieving, D-mannitol and acetone (anti-solvent) were mixed in a 1:2 wt% ratio and placed in an ultrasonic bath for 5 min. The resulting mixture was transferred to a 100 μm sieve (top of the tower) and the vibration intensity was set to 0.2. The wet-sieving of the powder was then carried out by consecutively rinsing the sample with acetone (400 ml for 20 g of powder) as the tower was vibrating. When the process was finished, the washed material was transferred to a filter paper and placed under a fume hood for 24 h in order to let the material dry. α-LH (CapsuLac®60) was also engineered using the same procedure as a control/reference for comparison.
The particles of D-mannitol were also engineered via spray-congealing (4 M8-TriX spray-congealer, ProCepT, Belgium). In this process, D-mannitol was first placed in an oven at 190°C and once a melt was obtained this was transferred to a heated vessel kept at 200°C. The molten fluid was pumped at 20.0 ± 1.4 g/min from the vessel to a heated bi-fluid nozzle (diameter 1.2 mm) and atomized (0.44 bar) into a glass tower chilled at −10°C, using a nitrogen flow of 0.6 m 3 /min. The solidified particles were separated from the air stream using a cyclone set at a pressure drop of 13 mbar and collected in a glass vessel at 13°C (Fig. ).
Scanning Electron Microscopy (SEM) The powder samples were observed using scanning electron microscopy (SEM). For this, the particles were sputtered with gold-palladium and then examined using a Zeiss Ultra 55 scanning microscope (Zeiss, Germany), operating at 5 kV. Particle Size Distribution The particle size distribution (PSD) was determined using laser light diffraction (HELOS/KR, Sympatec GmbH, Germany). A dry dispersing system (Rodos, Sympatec) and a vibrating chute (Vibri, Sympatec) were used for powder dispersion. The powders were analyzed using a primary dispersion pressure of 1.0 bar and using the R2 (0.45–87.50 μm) and R5 (4.5–875.0 μm) optical modes. The measurements were triggered once an optical concentration of 0.5% was achieved. The resulting volumetric particle size distributions were calculated and analyzed using Windox 5 software (Sympatec GmbH, Germany). Particle Solid-State The solid-state of the particles was characterized by differential scanning calorimetry (DSC 204F1 Phoenix®, Netzsch GmbH, Germany) and wide-angle X-ray scattering (WAXS, S3-MICRO camera, Bruker AXS GmbH, Germany). For the DSC analysis, 10–12 mg sample were weighed into an aluminum pan and crimped with a pierced lid. The samples were heated from 25 to 200°C at a rate of 10°C/min using pure nitrogen as purging gas at a flow rate of 20 mL/min. The DSC data analysis was conducted with Proteus Thermal Analysis software (Netzsch GmbH, Germany). For the WAXS analysis, the powder samples were filled into 2 mm glass capillaries and analyzed under constant rotation (9 rpm) between the angular range of 17 and 27° 2θ during 600 s at 30 counts/s (22 ± 2°C). Determination of the Specific Surface Area and Bulk Roughness Nitrogen gas adsorption (TriStar II 3020, Micromeretics, USA) was used to determine the specific surface area of the powders. Before analysis, the samples were treated under vacuum (VacPrep 061, Micromeritics, USA) overnight at room temperature (22 ± 2°C). A 5-point analysis was performed using a nitrogen relative pressure (p/p 0 ) between 0.06–0.20 and the Brunauer – Emmett – Teller (BET) adsorption theory was used to calculate the specific surface area (SSA BET ). The bulk roughness (BR) of the different D-mannitol particles was calculated as the ratio between the SSA BET and the theoretical specific surface area (SSA sv ) calculated based on the particle size volume-distribution assuming spherical particles (Eq. ) . 1 [12pt]{minimal}
$$ {}_{}=}_{} } $$ SSA SV = 6 D sv × ρ The D sv is the Sauter mean diameter determined by laser diffraction as described above in the relevant section and ρ is the true density of the particles. The true density was calculated as the ratio between the mass of particles and their respective volume. The particle volume was determined by helium pycnometry (AccuPyc II 1340, Micromeritics, USA), using 20 purges at 19.5 psi with an equilibration rate of 0.0050 psi/min. Powder Flowability The flowability of the powders was measured using a FT4 Powder Rheometer (Freeman Technology, UK). An appropriate amount of sample was placed in a 1 ml cell in order to fill it. A standard conditioning cycle was applied using a 23.5 mm blade moving down a helical path in order to generate a uniform low packing powder bed. Afterwards, the surplus of powder was removed by splitting the cell and the blade was replaced by a 24 mm shear cell. The powder was pre-consolidated at 9 kPa and then sheared at 7, 6, 5, 4, and 3 kPa. The flowability parameters of the powders were obtained from the Mohr’s stress circles. The major principal (δ 1 ) and unconfined yield (δ c ) stresses are the highest values at which the larger and smaller Mohr’s stress intercept the x axis. The cohesion (Coh) is the point of intersection of the yield locus (normal stress = 0). The flow function coefficient (ffc) is the ratio between the major principal stress and the unconfined yield stress. The angle of internal friction (AIF eff ) was determined from the effective yield locus.
The powder samples were observed using scanning electron microscopy (SEM). For this, the particles were sputtered with gold-palladium and then examined using a Zeiss Ultra 55 scanning microscope (Zeiss, Germany), operating at 5 kV.
The particle size distribution (PSD) was determined using laser light diffraction (HELOS/KR, Sympatec GmbH, Germany). A dry dispersing system (Rodos, Sympatec) and a vibrating chute (Vibri, Sympatec) were used for powder dispersion. The powders were analyzed using a primary dispersion pressure of 1.0 bar and using the R2 (0.45–87.50 μm) and R5 (4.5–875.0 μm) optical modes. The measurements were triggered once an optical concentration of 0.5% was achieved. The resulting volumetric particle size distributions were calculated and analyzed using Windox 5 software (Sympatec GmbH, Germany).
The solid-state of the particles was characterized by differential scanning calorimetry (DSC 204F1 Phoenix®, Netzsch GmbH, Germany) and wide-angle X-ray scattering (WAXS, S3-MICRO camera, Bruker AXS GmbH, Germany). For the DSC analysis, 10–12 mg sample were weighed into an aluminum pan and crimped with a pierced lid. The samples were heated from 25 to 200°C at a rate of 10°C/min using pure nitrogen as purging gas at a flow rate of 20 mL/min. The DSC data analysis was conducted with Proteus Thermal Analysis software (Netzsch GmbH, Germany). For the WAXS analysis, the powder samples were filled into 2 mm glass capillaries and analyzed under constant rotation (9 rpm) between the angular range of 17 and 27° 2θ during 600 s at 30 counts/s (22 ± 2°C).
Nitrogen gas adsorption (TriStar II 3020, Micromeretics, USA) was used to determine the specific surface area of the powders. Before analysis, the samples were treated under vacuum (VacPrep 061, Micromeritics, USA) overnight at room temperature (22 ± 2°C). A 5-point analysis was performed using a nitrogen relative pressure (p/p 0 ) between 0.06–0.20 and the Brunauer – Emmett – Teller (BET) adsorption theory was used to calculate the specific surface area (SSA BET ). The bulk roughness (BR) of the different D-mannitol particles was calculated as the ratio between the SSA BET and the theoretical specific surface area (SSA sv ) calculated based on the particle size volume-distribution assuming spherical particles (Eq. ) . 1 [12pt]{minimal}
$$ {}_{}=}_{} } $$ SSA SV = 6 D sv × ρ The D sv is the Sauter mean diameter determined by laser diffraction as described above in the relevant section and ρ is the true density of the particles. The true density was calculated as the ratio between the mass of particles and their respective volume. The particle volume was determined by helium pycnometry (AccuPyc II 1340, Micromeritics, USA), using 20 purges at 19.5 psi with an equilibration rate of 0.0050 psi/min.
The flowability of the powders was measured using a FT4 Powder Rheometer (Freeman Technology, UK). An appropriate amount of sample was placed in a 1 ml cell in order to fill it. A standard conditioning cycle was applied using a 23.5 mm blade moving down a helical path in order to generate a uniform low packing powder bed. Afterwards, the surplus of powder was removed by splitting the cell and the blade was replaced by a 24 mm shear cell. The powder was pre-consolidated at 9 kPa and then sheared at 7, 6, 5, 4, and 3 kPa. The flowability parameters of the powders were obtained from the Mohr’s stress circles. The major principal (δ 1 ) and unconfined yield (δ c ) stresses are the highest values at which the larger and smaller Mohr’s stress intercept the x axis. The cohesion (Coh) is the point of intersection of the yield locus (normal stress = 0). The flow function coefficient (ffc) is the ratio between the major principal stress and the unconfined yield stress. The angle of internal friction (AIF eff ) was determined from the effective yield locus.
To evaluate the applicability of the D-mannitol powders as carriers for inhalation, the particles were blended with BDP (Dv 0.5 = 1.05 μm), yielding low load (1 wt%) adhesive blends that were tested concerning their aerosolization performance. For comparison, α-LH particles (CapsuLac®60, Meggle, Germany) were blended and tested under similar conditions. Preparation of the Adhesive Mixtures To obtain 20 g binary mixture of API and carrier, 200 mg of BDP were weighted and placed in a 50 ml glass bottle between two even layers of the excipient (19.8 g). The glass bottle was place in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 2 h at 32 rpm. The obtained blend was sieved through a 400 μm mesh and mixed again for 30 min at 32 rpm. To yield 20 g of ternary mixture of the carrier, API and 0.2 wt% magnesium stearate (MgSt) or 10 wt% ‘Preblend’ (composed of InhaLac® 120 and 0.2% MgSt), 40 mg of MgSt or 2 g of ‘Preblend’ were weighted and placed in 50 ml glass bottles between two even layers of D-mannitol (19.96 and 18.00 g of carrier, respectively). The glass bottles were placed in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 4 h at 32 rpm. Once a mixture of carrier and MgSt or ‘Preblend’ was obtained, the powders were blended with 1 wt% BDP following the same procedure as for the binary blends. Mixing Homogeneity The mixing homogeneity was determined by taking 10 samples of about 20 mg from distinct zones of the bulk powder blends. The samples were dissolved in a small amount of methanol and after that 100 ml of a mixture of methanol and water (70:30 vol%) were added and the samples were placed in an ultrasonic bath for 5 to 10 min in order to completely dissolve the API. The API content in each sample was analyzed via high performance liquid chromatography (described in the relevant section below) and the mixing homogeneity expressed as the relative standard deviation (RSD) from the mean drug content. Shot Weight Consistency Samples of binary and ternary blends (1.5 g) were manually filled into NEXThaler® devices (Chiesi, Italy) and the filled inhalers conditioned overnight in desiccators at 60% RH. The shot weight consistency was analyzed by firing the inhalers 10 times into a DUSA (Dosage Unit Sampling Apparatus) and determining the mass delivered via each actuation using the weight difference, before and after emission. Between each emission the inhalers were discharge using antistatic bars. Likewise, the mean shot weight and respective standard deviation were calculated based on the weight of 10 shots and the delivered mass consistency evaluated, accordingly. Evaluation of the Aerodynamic Performance The aerodynamic performance of binary and ternary DPI blends was assessed via next generation impactor (NGI, Copley Scientific, UK) experiments . To avoid particle bouncing, the stages of the impactor were coated with 2 vol% Tween 20 in ethanol prior to analysis. For each NGI experiment, one shot of the conditioned (at 60% RH) NEXThaler® was discharged. The flow rate was set to 60 L/min in order to reach a pressure drop of 4 kPa over the inhaler and the flow was applied for 4 s in order to ensure that 4 L of air were drawn via the mouthpiece over the inhaler. The drug content in each part of the impactor was quantified using a validated high performance liquid chromatography method (following section) and for each inhaler three NGI experiments were performed. The BDP in vitro deposition profile, fine particle fraction (FPF), fine particle dose (FPD), and the emitted dose (ED) were calculated and compared. High Performance Liquid Chromatography (HPLC) BDP was quantified via HPLC using a Waters Alliance 2695 HPLC system equipped with a 2996 photodiode array detector. A Waters Atlantis dC18 column (150 × 3.9 mm; 3 μm) was used as stationary phase and mobile phase was composed of acetonitrile/0.02 M sodium di-hydrogen phosphate monohydrate set to pH 3.0 (70:30 vol%). The system was operated in isocratic mode at a flow rate of 1 mL/min and a column temperature of 40°C. The injection volume was 50 μL and run time was 6.0 min, whereas the retention time of BDP was approximately 4.2 min. The UV-detection was conducted at a wavelength of 238 nm.
To obtain 20 g binary mixture of API and carrier, 200 mg of BDP were weighted and placed in a 50 ml glass bottle between two even layers of the excipient (19.8 g). The glass bottle was place in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 2 h at 32 rpm. The obtained blend was sieved through a 400 μm mesh and mixed again for 30 min at 32 rpm. To yield 20 g of ternary mixture of the carrier, API and 0.2 wt% magnesium stearate (MgSt) or 10 wt% ‘Preblend’ (composed of InhaLac® 120 and 0.2% MgSt), 40 mg of MgSt or 2 g of ‘Preblend’ were weighted and placed in 50 ml glass bottles between two even layers of D-mannitol (19.96 and 18.00 g of carrier, respectively). The glass bottles were placed in a Turbula blender TC2 (Willy A. Bachofen Maschinenfabrik, Switzerland) and mixed for 4 h at 32 rpm. Once a mixture of carrier and MgSt or ‘Preblend’ was obtained, the powders were blended with 1 wt% BDP following the same procedure as for the binary blends.
The mixing homogeneity was determined by taking 10 samples of about 20 mg from distinct zones of the bulk powder blends. The samples were dissolved in a small amount of methanol and after that 100 ml of a mixture of methanol and water (70:30 vol%) were added and the samples were placed in an ultrasonic bath for 5 to 10 min in order to completely dissolve the API. The API content in each sample was analyzed via high performance liquid chromatography (described in the relevant section below) and the mixing homogeneity expressed as the relative standard deviation (RSD) from the mean drug content.
Samples of binary and ternary blends (1.5 g) were manually filled into NEXThaler® devices (Chiesi, Italy) and the filled inhalers conditioned overnight in desiccators at 60% RH. The shot weight consistency was analyzed by firing the inhalers 10 times into a DUSA (Dosage Unit Sampling Apparatus) and determining the mass delivered via each actuation using the weight difference, before and after emission. Between each emission the inhalers were discharge using antistatic bars. Likewise, the mean shot weight and respective standard deviation were calculated based on the weight of 10 shots and the delivered mass consistency evaluated, accordingly.
The aerodynamic performance of binary and ternary DPI blends was assessed via next generation impactor (NGI, Copley Scientific, UK) experiments . To avoid particle bouncing, the stages of the impactor were coated with 2 vol% Tween 20 in ethanol prior to analysis. For each NGI experiment, one shot of the conditioned (at 60% RH) NEXThaler® was discharged. The flow rate was set to 60 L/min in order to reach a pressure drop of 4 kPa over the inhaler and the flow was applied for 4 s in order to ensure that 4 L of air were drawn via the mouthpiece over the inhaler. The drug content in each part of the impactor was quantified using a validated high performance liquid chromatography method (following section) and for each inhaler three NGI experiments were performed. The BDP in vitro deposition profile, fine particle fraction (FPF), fine particle dose (FPD), and the emitted dose (ED) were calculated and compared.
BDP was quantified via HPLC using a Waters Alliance 2695 HPLC system equipped with a 2996 photodiode array detector. A Waters Atlantis dC18 column (150 × 3.9 mm; 3 μm) was used as stationary phase and mobile phase was composed of acetonitrile/0.02 M sodium di-hydrogen phosphate monohydrate set to pH 3.0 (70:30 vol%). The system was operated in isocratic mode at a flow rate of 1 mL/min and a column temperature of 40°C. The injection volume was 50 μL and run time was 6.0 min, whereas the retention time of BDP was approximately 4.2 min. The UV-detection was conducted at a wavelength of 238 nm.
Particle Engineering by Wet-Sieving Excipient particles with a mean size < 10 μm have the potential to reach the large and small respiratory airways and have shown to be beneficial for the aerosolization performance when present in carrier-based DPI formulations . Consequently, it is important to precisely control the excipient particles within this size range . As it can be observed in Fig. , Pearlitol 300 DC (Pearl300) was composed of large rough particles with a notable quantity of smaller particles filling its crevices and pores. Additionally, laser diffraction (Table ) showed that this D-mannitol grade also presented a preeminent fraction of particles < 10 μm (2.08%). Thus, to engineer particles with a narrower particle size (i.e. by lowering the percentage of fines inherited from primary manufacture) wet-sieving was employed. This allowed to control the amount of fines, by specifically adding a defined mass of them to the coarser excipient particles afterwards. CapsuLac® 60 (Cap60), containing sieved tomahawk α-LH crystal agglomerates (contrary to smoother single tomahawk particles traditionally used as carriers for DPIs) was selected as a control for comparison with D-mannitol . In a first step, an anti-solvent screening was carried out (including acetone, isopropanol, n-heptane and decafluoropentane) to identify the most promising solvent with respect to surface smoothing of the carriers (data not shown). Acetone showed to be the most promising solvent and was therefore selected for the present study. Prior to wet-sieving, Cap60 did not contain a large fraction of particles < 10 μm, notwithstanding this fraction was lowered from 0.47% to 0.17% (Table ). Wet-sieving of Cap60 also had an impact on the overall PSD of the carrier, in particular the Dv 0.9 . Although, after sieving, a large standard deviation (SD) was found for the Dv 0.9 , a trend indicating an increase of this parameter was still, possible to identify. We hypothesize that this might have been due to the fact that with washing, single particles of Cap60 with a size <100 μm might have been washed away, leaving larger agglomerates of α-LH at the top of the sieve tower. This resulted in a shift of the overall PSD to larger sizes, including the sauter mean diameter (D sv ). Visual inspection of the carrier via SEM (Fig. ), before and after washing, did not reveal any notable morphological changes. Wet-sieving of Pearl300 significantly decreased the percentage of fine particles (from 2.08% to 0.45%). The latter, translated into a slight increase of the Dv 0.1 . Although, we fractionated the larger faction of particles of D-mannitol (> 100 μm), there was a notable decrease of the Dv 0.5 and Dv 0.9 . Due to the fines, which were filling up the pronounced crevices and pores on the surface of Pearl300 particles, being washed away, it can be observed that wet-sieving of D-mannitol resulted in particles with a pumice appearance (Pearl300_WS in Fig. ). Accordingly, the rough surface of Pearl300 became apparent. Thus, we hypothesize that the pronounced irregularities at the surface of Pearl300_WS led to higher-angle scattering , posing an explanation why smaller particle sizes (Dv 0.5 and Dv 0.9 ) were observed after washing. This was also supported by an increase in the surface to volume ratio (D sv ) (more roughness larger surface). Thermal analysis of the samples (Fig. ) showed that Cap60 had two endothermic peaks; one at ≈ 141°C and another at about 213°C. These peaks were attributed to the dehydration and melting of the α-form, respectively . WAXS characterization (Fig. ) of Cap60 supported the MDSC analysis and confirmed that Cap60 was composed of α-LH, as shown by its characteristic peak patterns at 19.1°, 19.5° and 19.9° 2θ . After washing with acetone, the MDSC of Cap60_WS showed narrowing of the dehydration peak and the appearance of an exothermic event at ca. 175°C. This exothermic event was attributed to the unstable form of anhydrous α-lactose (Lα H ) converting into the anhydrous stable α-form (Lα s ) at 175°C . It is hypothesized that the changes, observed during the calorimetry measurements, were due to acetone impacting the dehydration mechanism of α-LH, leading to the formation of Lα H at higher temperatures (> 130°C) . The WAXS patterns of Cap60_WS were consistent with the ones of α-LH, evidencing that at room temperature no polymorphic changes could be detected. MDSC analysis of Pearl300 revealed a single endotherm at 166°C. Due to their very similar melting points the α- and β-forms of D-mannitol are challenging to distinguish when solely using MDSC . Thus, by supporting the analysis with WAXS, it was possible to verify the presence of a preeminent peak at 23.1° 2θ, showing that Pearl300 was composed of β-mannitol particles . Washing with acetone did not result in any detectable changes of the solid state of Pearl300 (i.e. Pearl300 and Pearl300_WS presented very similar thermograms and WAXS patterns). Cap60 presented a true density of 1.539 g/cm 3 (Table ), consistent with known value for α-LH (1.535–1.540 g/cm 3 ) and remained unchanged following wet-sieving. Pearl300 and Pearl300_WS showed a true density of about 1.49 g/cm 3 , in line with the known value for the crystals of β-mannitol . Regarding the SSA determined by gas absorption (SSA BET ), Cap60 showed a smaller mean area when compared to Pearl300, i.e., 2798 and 3932 cm 2 /g, respectively (Table ). This, was supported by the observations via SEM (Fig. ) showing that Cap60 was composed of smooth tomahawk agglomerates and Pearl300 of rough, irregular single particles with deep pores. Wet-sieving of the α-LH carrier (Cap60_WS) resulted in a slight decrease of the SSA (2121 cm 2 /g). Surprisingly, washing with acetone did not result in any change of the SSA of Pearl300. The SSA determined by gas adsorption is related to the nano- and mesoporosities presenting a mean diameter between 1.7 and 300 nm. It is apparent that for the smoother particles of Cap60, the presence of fines with size < 10 μm resulted in an increase of the porosities between 1.7–300 nm. For the very rough particles of Pearl300, the same was not observed. The theoretical specific area (SSA SV ), was calculated based on the D sv , under the assumption that the samples are composed of spherical solid particles, therefore the internal porosities and irregular shapes are not accounted for . Thus, the SSA sv values are much lower than the ones obtained by gas absorption. The BR is a parameter often used to evaluate the morphology of carrier particles intended for inhalation . It was observed that for Cap60, wet-sieving (Cap60_WS) did not result in any significant changes in the BR (Table ). However, Pearl300_WS showed a BR almost 3 times higher than the one calculated for the raw material. This was in line with SEM observations (Fig. ), where rougher, pumice single particles of D-mannitol were visualized after wet-sieving. For powder handling and formulation, rheological properties like cohesion and flowability obtained from shear cell experiments are important indicators. Comparing these values between the starting materials and the wet-sieved ones it was possible to see that, according to Jenike classification (ffc values between 2 and 4), generally, all powders were cohesive (Table ). Compared to Cap60, Cap60_WS showed slightly lower values of Coh and ffc. For the AIF eff a larger difference was observed and the wet-sieved powder presented a notable smaller value. For Pearl300, the surface treatment notably decreased the Coh, AIF eff and ffc. The AIF supplies information about the frictional forces within the powder (particle-particle) during flow. The friction within the powder is known to be influenced by particle size and shape . Considering that wet-sieving did not notably modify the overall shape of the α-LH and D-mannitol particles (Fig. ), we hypothesize that the differences in the AIF eff were mostly driven by washing out the particles <100 μm. Hence, we purpose that the fractionation of the powders led to the reduction of particle-particle contacts, decreasing friction within the powder . As a result of reduction in powder friction, slightly lower cohesion and ffc values were found indicating a potential improvement in flowability. For Pearl300, wet-sieving led to more notable changes in the particle size, and consequently a larger difference in powder flow values. Particle Engineering by Spray-Congealing Since α-LH degrades upon melting , it was only possible to engineer Pearl300 through spray-congealing. During processing no evidence of any yellowish sample, characteristic of the degradation of sugars due to oxidation, was observed , thus it was inferred that D-mannitol was stable enough to be processed via spray-congealing. SEM images in Fig. show that spray-congealing resulted in spherical particles. The spray-congealed particles were also notably smaller than their raw and wet-sieved counter-parts, presenting lower Dv 0.1 , Dv 0.5 and Dv 0.9 . Additionally, they also presented a larger SPAN when compared to the other D-mannitol samples. Indeed, in Fig. , it is possible to observe the presence of single spherical particles of diverse sizes. During spray-congealing, by the use of a twin-fluid nozzle, the viscous liquid (melt) was injected into a high velocity gas leading to the formation of droplets . Thus, when compared to other melt solidification techniques, i.e., prilling, where large narrowly monodispersed particles are obtained due to the use of nozzles that rely on hydrodynamic instabilities , twin-fluid atomization led to the formation of smaller particles. Additionally, it is speculated that because jet-breakage is more uncontrollable, droplets of various sizes were formed, leading to solid particles in a broader size span. Likewise, the Pearl300_SC sample also showed a considerable amount of fine particles below 10 μm (1.88%). MDSC analysis (Fig. ) of Pearl300_SC showed an endothermic event with a lower onset temperature (164°C) and enthalpy (288.40 J/g), when compared to the raw material. As mentioned before, from MDSC it is hard to distinguish between D-mannitol polymorphs; however, X-ray patterns of the α, β and δ forms of D-mannitol present very distinct Bragg peaks that allow their distinction. The α, β and δ forms are characterized by the peaks at 26.6°, 23.1° and 21.9°2θ, respectively . From WAXS patterns in Fig. , it is possible to distinguish a clear peak at 26.66° 2θ and a very small one at 21.9° 2θ. No peak could be found at 23.1° 2θ. Thus, it was concluded that Pearl300_SC was predominately composed of the α-form of D-mannitol with trace amounts of the δ-form. Although, Pearl300_SC presented a homogenous and smooth surface topography typical of non-crystalline surfaces, MDSC and WAXS of the same sample clearly indicate that the material was predominantly crystalline. Spray-congealing slightly decreased the true density compared to the starting and wet-sieved materials (Table ), potentially, due to the pure α-form presenting a lower true density (1.468 g/cm 3 ) . Further, given that after melting the α particles crystallized with the δ polymorph as an impurity, it is possible that the δ-mannitol acted as a crystal habit modifier affecting the true density of the compound . However, more investigations would be needed to confirm this. Compared to Pearl300 and Pearl300_WS, the spray-congealed samples show a significantly reduced surface area (SSA BET ) and roughness (BR). In contrast to all other non-spherical carriers, the SSA sv for Pearl300_SC is comparable to the SSA BET . Besides the spherical shape in line with the assumptions made for the SSA sv calculation, this also indicated that Pearl300_SC does not present notable morphological irregularities or/and porosities. Pearl300_SC showed notably smaller values of cohesion and a larger ffc (Table ), when compared to the raw and wet-sieved materials. Engineering by spray-congealing changed the D-mannitol powder from cohesive to free flowing. Interestingly, the AIF eff value of the Pearl300_SC and Pearl300_WS were very similar, thus it is more likely that the improvement in flowability is due to the packing state of the powder bed. It is assumed that due to the spherical and smooth nature of Pearl300_SC particles, the powder will present similar density in its packed and dilated conditions (Hausner ratio), facilitating the powder flow . The presence of trace amounts of δ-mannitol in Pearl300_SC raised concerns about the stability of the particles hence, the sample was conditioned for 24 h at 93% RH (set with saturated salt solution of potassium nitrate in a sealed chamber). Following the latter, it was determined that the δ-form was successfully converted into the more stable β-mannitol (Supplementary Material Fig. ), and mixing and aerosolization experiments were carried out with this sample. Impact of Particle Engineering on DPI Performance All carriers (starting material, wet-sieved and spray-congealed ones) were blended with 1 wt% BDP (binary mixtures) and additionally, with a controlled amount of fines, namely 0.2 wt% MgSt and 10 wt% of ‘Preblend’ (fine α-LH + MgSt) (ternary mixtures). It is, generally, reported that rough and irregular carrier particles have a higher loading capacity compared to smooth ones . In more rough/irregular particles, the higher number of indentations and cavities present, allow a greater number of fine particles to fill and/or coat the surface of the carrier. Likewise, with the very smooth uniform Pearl300_SC no ternary blends were prepared as the surface morphology (smooth and uniform, without any cavities and a low surface area) was not expected to have a high loading capacity . After mixing all the blends presented an RSD < 7% (Table ). According to Hassan et al ., blends with an RSD below 10% are considered homogenous , thus we found the mixtures appropriate to be further tested concerning their in vitro aerodynamic performance. Representative SEM images of the blends are presented in Figs. , and (and Supplementary Material Fig. – ). Impact of Particle Engineering on Shot Weight Consistency The shot weight consistency is a crucial factor to ensure that the release of every dose is the same and therapeutic outcomes are met . Therefore, two different inhalers of each blend were tested concerning the consistency of 10 consecutive shots and the inter- and intra-device variability were evaluated. The NEXThaler® is a breath-actuated reservoir device in which a powder is first precisely dosed by gravity into a recess and then de-agglomerated in a vortex chamber. To evaluate the dose-mass consistency, it is important to understand how the particle properties of different carriers might have affected these two steps. In Fig. , it can be observed that for the binary blends, engineering of Cap60 and Pearl300 by wet-sieving led to lower inter-device variability. We propose, this was a consequence of the more uniform sized powders (lower SPAN) produced via wet-sieving. Due to the disparity between device performances containing Pearl300 as a carrier, no clear inference concerning the effect of wet-sieving on intra-device variability could be made. For Cap60, the narrower PSD of the wet-sieved material also seemed to beneficially affect intra-device variability. A crucial observation was that spray-congealing of Pearl300 led to a higher mean mass of powder being dosed per shot (increase from about 9.9 to 13.4 mg). We hypothesize, that this was mainly related to the spherical shape of the spray-congealed material. Spherical shaped materials are known to pack more uniformly compared to irregular ones, so for the same recess volume a higher powder mass could be dispensed . Additionally, it was observed that for Pearl300_SC the two devices tested showed extremely identical performances. Here, this cannot be attributed to the SPAN of the material as Pearl300_SC actually, showed a higher value compared to Pearl300. However, Pearl300_SC demonstrated better flow when compared to the raw and wet-sieved materials. Improvement in flow has been associated with more consistency during powder filling and could potentially explain the observed results. Still, Pearl300_SC showed a larger intra-device variability (RSD ~ 6%). During vortex fluidization, particles of distinct sizes accelerate at different speeds, possibly leading to segregation; i.e., smaller lighter particles leave the device more readily and larger and heavier ones will have more tendency to move inwards . Hence, the greater intra-device variability could be associated to the larger differences in PSD of Pearl300_SC. The addition of MgSt (Fig. ) to the blends of the raw materials and BDP (Cap60 + MgSt and Pearl300 + MgSt) did not have any notable impact on the inter- and intra-device variability (Fig. ). However, for the wet-sieved materials the use of the salt led to a pronounced deterioration of inter- and intra-device variability (Cap60_WS + MgSt and Pearl300_WS + MgSt). The reason underlying this behavior needs to be clarified; however, it is known that MgSt preferentially fills large cavities of coarser particles, and its optimal effect on flow follows a non-linear correlation with the radius of the particles to be lubricated . Considering the differences induced by wet-sieving in the surface topography and micromeritic properties (i.e., BET, PSD, roughness) of α-LH and D-mannitol, it is not entirely surprising, that distinct impacts on powder flow were observed when using the same concentration of MgSt on the raw and wet-sieved materials. In future work, the effective concentration of MgSt to improve the performance of carrier particles with distinct characteristics will have to be investigated. The addition of ‘Preblend’ to Cap60 and Cap60_WS with BDP led to higher differences in intra- and inter-device variability (Fig. ). For Pearl300, the addition of ‘Preblend’ increased the mass of the emitted dose (from about 9.5 to 10.9 mg) and improved inter-device variability. Whereas, for Pearl300_WS, the addition of ‘Preblend’ did not have any notable impact on inter-device variability, but increased the intra-device RSD from ~4.5% to 9.2%. We hypothesize, that the different impact of ‘Preblend’ on α-LH and D-mannitol carriers was related to the very distinct surface topography of the two carriers. D-mannitol carriers were considerably more corrugated than the α-LH ones and, thus expected to be able to host more fine excipient particles onto/into their surface . On the contrary, the less corrugated two α-LH materials (Cap60 and Cap60_WS) could not accommodate the fines as efficiently, leading to segregation (between coarse carrier particles hosting fines and particulate agglomerates of fines, see supplementary material Fig. (c) and (f)) . Thus, powder flow was deteriorated and an increase in inter- and intra-device variability was seen. For Pearl300, it is speculated that the concentration of ‘Preblend’ plus the initial fines content of the carrier were ideal to adequately coat its rough surface, originating a denser packing, that produced an increase of the emitted mass per shot. In contrast, for the rougher surface of Pearl300_WS with reduced initial amount of fines, the concentration of ‘Preblend’ was not enough to cause potential changes in the powder bed packing; thus, no differences in the emitted mass per shot were observed. With respect to intra-device variability, it is suggested that the more efficient detachment of fine particles from Pearl300_WS than from Pearl300 (shown by its higher FPF in Fig. ) also resulted in a more efficient de-agglomeration; this, in turn leading to more particles of different sizes within the vortexes and higher dose variability (as already explained for the Pearl300_SC blends). Impact of Particle Engineering on In Vitro Inhalation Performance The ED, FPM, and FPF were used to evaluate the performance of engineered D-mannitol particles in comparison to the D-mannitol reference material as well as α-LH engineered and starting material in binary and ternary blends. No pronounced differences could be detected in the MMAD among the different formulations. All the blends presented an MMAD of 1.8 ± 0.5 μm. Impact of Particle Engineering and Addition of Ternary Agents on the Drug Dose Looking first at the binary blends, the ED values were comparable between starting and wet-sieved materials (Fig. ) and no notable differences were found between D-mannitol and α-LH particles. Further, this was in line with the shot weight results where no difference in emitted mass was observed. The FPM was slightly lower for both, wet-sieved D-mannitol and α-LH. By contrast, Pearl300_SC showed 75% higher ED and 168% higher FPM related to Pearl300. Concerning the FPF of the various D-mannitol carriers (Fig. ), a slight increase in the FPF was observed when using Pear300_SC, indicating better API de-attachment. Hence, it can be inferred that the improvement in ED and FPM was mainly due to two factors; the better API de-attachment and the increase in the mass delivered per shot (about 40% more), as explained in the previous section. Comparing the stage-wise deposition of the binary blends (Fig. ), it can bee seen that the wet-sieved and starting materials showed comparable deposition. Only the use of Pearl300_WS slightly reduced the amount of drug deposited in the mouth and throat (M + T) and pre-separator (Presep) and increased the amount of drug on stage 5. The deposition pattern of Pearl300_SC was different from the other binary blends and a very high amount of API was found in the M + T. This led to the assumption that drug detachment is quite efficient, even taking place too early and allowing for loose API to be deposited already in the mouth and throat (not being transported to the deep lung). Further, higher amounts of API were deposited on stage 3, 4 and 5. Again, the higher shot weight and resulting larger amount of BDP per NGI experiment could have, in part, contributed to this. The addition of ternary agents is reported to increase the deposition of the API at the lower stages of the NGI by varying mechanisms . Likewise, it was not surprising that in the present study, the addition of MgSt and ‘Preblend’, overall, increased the FPM for D-mannitol and α-LH carriers (binary vs ternary blends, Fig. and (a), respectively); while the ED remained comparable. Looking at the stage-wise deposition in Fig. and comparing it with the binary blends in Fig. , the addition of MgSt increased the amount of BDP on stage 4 and 5 of the impactor and limited the amount in the Presep (this was true for α-LH and D-mannitol, wet-sieved and starting material). MgSt is used as a force control agent in DPI formulations in order to reduce the adhesive interactions of the API with the carrier surface, improving de-attachment . Likewise, in the present study the use of the salt, led to more API being found in the lower stages of the impactor and higher FPFs (Fig. ). The improvement in FPM was even more pronounced when ‘Preblend’ was added to Cap60 and Pearl300_WS. Interestingly, Cap60_WS was superior compared to Cap60 in combination with MgSt (lower deposition in Presep and higher deposition in stages 3 to 7) and Pearl300_WS was superior over Pearl300 in combination with ‘Preblend’ (lower deposition in Presep and higher deposition in stages 4 to 7). Given that, excluding Pearl300_SC, all the blends presented very similar EDs, the differences in FPM can, generally, be attributed to how drug de-attachment was affected by engineering and/or the addition of ternary agents. Impact of Particle Engineering and Addition of Ternary Agents on Drug de-Attachment Figure compares the FPF of all binary and ternary blends. Here, one can clearly see how the different carriers and ternary agents affected drug de-attachment. The highest FPF of all the tested formulations was achieved using Pearl300_WS in combination with ‘Preblend’. For this system, the wet-sieved carrier showed a notably better performance compared to the starting material. This can be explained by the deep voids and clefts on the surface of Pearl300 revealed during the wet-sieving process. It is proposed that the latter were filled up with ‘Preblend’ during the blending process and allowed BDP to be more efficiently detached from the wet-sieved D-mannitol carrier surface . In contrast, the comparably smaller amount of MgSt was not enough to cause this effect. For Cap60, the addition of ‘Preblend’ resulted in the same FPFs for starting and wet-sieved materials. Here, compared to the starting material, the wet-sieved sample only showed an increase in FPF when MgSt was added. This can be explained by the morphological difference of the starting materials (α-LH vs D-mannitol). Cap60 showed no voids and clefts, where the API could be sheltered from aerosolization forces. Moreover, it is hypothesized that, here, the reduction of initial fines (0.49%) to 0.17% by wet-sieving also played a crucial role when a small amount of ternary agent (0.2% of MgSt) was added. MgSt has a high affinity to bind to lactose (no electrostatic repulsion) . Thus, it is postulated that the addition of MgSt to Cap60_WS with lower intrinsic α-LH fines, successfully covered the ‘active sites’ (high energy binding sites on the carrier surface) on the carrier surface and forced API particles to interact with passive or low energy sites, promoting its detachment . By contrast, when ‘Preblend’ was added, the difference in initial fines content (Cap60 vs Caps60_WS) becomes insignificant and the behavior of Cap60 and Cap60_WS blends is dominated by the high amount of α-LH fines (10%) compared to intrinsic α-LH fines (0.4%7 vs 0.17%). Pearl300_WS, the powder with the highest bulk roughness, showed the best performance when in combination with 10% ‘Preblend’. In turn, Pearl300, was the only carrier where the addition of ‘Preblend’ did not further increase the FPF compared to the ternary blends with MgSt. For Pearl300, the total amount of intrinsic fines plus API seemed already too high, for the addition of ‘Preblend’ to cause a positive effect (13.08% compared to 11.45% for Pearl300_WS, 11.47% for Caps60 and 11.17% for Cap60_WS formulated with ‘Preblend’). A threshold where a certain number of fines, does not further improve or even reduce the aerosolization performance has been reported before . Results vary depending on the type of device and formulation used. The difference in type and amount of fines that show a superior effect on the aerosolization performance of α-LH and/or D-mannitol is most likely connected to the effect that different mechanisms (active site, buffer, agglomeration and fluidization theories) have on API detachment. These effects might be different for the two materials and dependent on the surface topography and structure of the carrier. The FPF delivered from the spray-congealed carrier was 16 ± 2% (Fig. ) and notably higher when compared to the starting material of D-mannitol (FPF = 8%). Comparison of the FPF of Pearl300_SC to the one from the wet-sieved material, shows that the use of Pearl300_WS without ternary agents did not notably impact the FPF of D-mannitol. Likewise, without the addition of ternary agents, spray-congealing of D-mannitol has shown to be promising in terms of the relative increase of the FPF, when in relation to the starting material (around 100%). Applicability of the D-Mannitol Particles Engineered by Wet-Sieving and Spray-Congealing In order to get an idea of the performance of our novel engineered carriers (Pearl300_SC and Pearl300_WS in combination with ‘Preblend’) related to other engineered D-mannitol carriers, the FPF and relative increase in FPF (RI-FPF) for a few selected systems tested with the Novolizer® was compared. The Novolizer® also uses vortex-based fluidization and is considered most similar to the NEXThaler® used in the present study. In our study, the FPF for wet-sieved mannitol with ‘Preblend’ was 69.2%, and the FPF of Pearl300 with ‘Preblend’ 32.4% resulting in a RI-FPF of 114%. Scherließ et al . reported for Parteck® M DPI (Merck, Germany), a commercial mannitol product for DPIs, FPF values of around 40% . Compared to that the RI-FPF for Pearl300_WS + ‘Preblend’ would be 75%. In the aforementioned study, Parteck® M DPI was tested in blends with ternary agents (MgSt and mannitol fines) and the RI-FPF was 55% (for budesonide) and 65% (for salbutamol sulphate), depending on the API that was used . Littringer at al. produced spray-dried mannitol particles and the FPF of salbutamol sulphate varied from 11% to 29% dependent on the surface roughness and topography (indentations) of the carrier material. However, no comparison with the starting material was done . Our Pearl300_SC, spherical particles with a smooth surface and slightly larger size showed a FPF of 16% and RI-FPF of 100%. Overall, the FPF or relative improvement of the in-vitro aerosolization performance (RI-FPF) of Pearl300_WS + ‘Preblend’ and Pearl300_SC is superior or equal to other reported mannitol carriers. However, we note that direct comparison is not straight forward, as besides the inhalation device, performance is further affected by the carrier size, the API used, formulation and blending procedure and a combination of thereof. Therefore, we caution here that this comparison is just to showcase the relative extent of FPF gained (or not) by a certain route of carrier particle engineering and/or ternary agent addition. Finally, in the competitive market of inhalable medications, especially for patients with asthma and chronic obstructive pulmonary disease (COPD), there are a multitude of available devices each with different operating principles. Reservoir multi-dose DPI devices such as NEXThaler® and Novolizer® represent the preferred solution in terms of easiness of administration and portability for the chronic therapies, increasing adherence and minimizing errors in device handling. On the other hand, developing a DPI formulation for this kind of devices is, generally, a difficult task. Indeed, the DPI powder must behave with a high level of reproducibility during the whole life of the device. In particular, the challenge is to have good powder flow behavior to ensure the adequate and constant metering of the doses over the period of a device use. This aspect is less challenging in a unit-dose or multi-unit dose device, where a filling machine can be customized to properly meter the single dose with a larger range of viable options. Furthermore, also the de-agglomeration and aerosolization of the metered dose must be adequate in terms of performance and reproducibility, and constant through the whole life of the multi-dose device. For this reason, usually a carrier-based formulation is needed to be combined with a multi-dose reservoir device and very often the formulation platform is co-developed with the device to give a reciprocal adaptation. For this reason, the carrier-based DPI formulation described in this paper, showed noteworthy results. Indeed, these formulations were not specifically co-developed with a reservoir multi-dose device, but only adapted on an existing one, designed for other DPI carrier-based platforms. In particular, as a DPI carrier, the spray-congealed D-mannitol, Pearl300_SC , showed to be able to deliver drugs with a good reproducibility of shot weight and without the use of ternary agents such as MgSt. An optimized carrier with similar characteristics could be beneficial to reduce the number of mixing process steps and avoiding the inhalation of excess excipient fine materials. Subsequently, scale-up trials were done in order to evaluate scalability of the process and two 500 g batches were successfully produced with comparable particle characteristics and inhalation performance . By optimizing the blending protocol for spray-congealed D-mannitol and, reducing drug deposition in mouth and throat, this engineered material is expected to be a promising candidate as a novel inhalation carrier.
Excipient particles with a mean size < 10 μm have the potential to reach the large and small respiratory airways and have shown to be beneficial for the aerosolization performance when present in carrier-based DPI formulations . Consequently, it is important to precisely control the excipient particles within this size range . As it can be observed in Fig. , Pearlitol 300 DC (Pearl300) was composed of large rough particles with a notable quantity of smaller particles filling its crevices and pores. Additionally, laser diffraction (Table ) showed that this D-mannitol grade also presented a preeminent fraction of particles < 10 μm (2.08%). Thus, to engineer particles with a narrower particle size (i.e. by lowering the percentage of fines inherited from primary manufacture) wet-sieving was employed. This allowed to control the amount of fines, by specifically adding a defined mass of them to the coarser excipient particles afterwards. CapsuLac® 60 (Cap60), containing sieved tomahawk α-LH crystal agglomerates (contrary to smoother single tomahawk particles traditionally used as carriers for DPIs) was selected as a control for comparison with D-mannitol . In a first step, an anti-solvent screening was carried out (including acetone, isopropanol, n-heptane and decafluoropentane) to identify the most promising solvent with respect to surface smoothing of the carriers (data not shown). Acetone showed to be the most promising solvent and was therefore selected for the present study. Prior to wet-sieving, Cap60 did not contain a large fraction of particles < 10 μm, notwithstanding this fraction was lowered from 0.47% to 0.17% (Table ). Wet-sieving of Cap60 also had an impact on the overall PSD of the carrier, in particular the Dv 0.9 . Although, after sieving, a large standard deviation (SD) was found for the Dv 0.9 , a trend indicating an increase of this parameter was still, possible to identify. We hypothesize that this might have been due to the fact that with washing, single particles of Cap60 with a size <100 μm might have been washed away, leaving larger agglomerates of α-LH at the top of the sieve tower. This resulted in a shift of the overall PSD to larger sizes, including the sauter mean diameter (D sv ). Visual inspection of the carrier via SEM (Fig. ), before and after washing, did not reveal any notable morphological changes. Wet-sieving of Pearl300 significantly decreased the percentage of fine particles (from 2.08% to 0.45%). The latter, translated into a slight increase of the Dv 0.1 . Although, we fractionated the larger faction of particles of D-mannitol (> 100 μm), there was a notable decrease of the Dv 0.5 and Dv 0.9 . Due to the fines, which were filling up the pronounced crevices and pores on the surface of Pearl300 particles, being washed away, it can be observed that wet-sieving of D-mannitol resulted in particles with a pumice appearance (Pearl300_WS in Fig. ). Accordingly, the rough surface of Pearl300 became apparent. Thus, we hypothesize that the pronounced irregularities at the surface of Pearl300_WS led to higher-angle scattering , posing an explanation why smaller particle sizes (Dv 0.5 and Dv 0.9 ) were observed after washing. This was also supported by an increase in the surface to volume ratio (D sv ) (more roughness larger surface). Thermal analysis of the samples (Fig. ) showed that Cap60 had two endothermic peaks; one at ≈ 141°C and another at about 213°C. These peaks were attributed to the dehydration and melting of the α-form, respectively . WAXS characterization (Fig. ) of Cap60 supported the MDSC analysis and confirmed that Cap60 was composed of α-LH, as shown by its characteristic peak patterns at 19.1°, 19.5° and 19.9° 2θ . After washing with acetone, the MDSC of Cap60_WS showed narrowing of the dehydration peak and the appearance of an exothermic event at ca. 175°C. This exothermic event was attributed to the unstable form of anhydrous α-lactose (Lα H ) converting into the anhydrous stable α-form (Lα s ) at 175°C . It is hypothesized that the changes, observed during the calorimetry measurements, were due to acetone impacting the dehydration mechanism of α-LH, leading to the formation of Lα H at higher temperatures (> 130°C) . The WAXS patterns of Cap60_WS were consistent with the ones of α-LH, evidencing that at room temperature no polymorphic changes could be detected. MDSC analysis of Pearl300 revealed a single endotherm at 166°C. Due to their very similar melting points the α- and β-forms of D-mannitol are challenging to distinguish when solely using MDSC . Thus, by supporting the analysis with WAXS, it was possible to verify the presence of a preeminent peak at 23.1° 2θ, showing that Pearl300 was composed of β-mannitol particles . Washing with acetone did not result in any detectable changes of the solid state of Pearl300 (i.e. Pearl300 and Pearl300_WS presented very similar thermograms and WAXS patterns). Cap60 presented a true density of 1.539 g/cm 3 (Table ), consistent with known value for α-LH (1.535–1.540 g/cm 3 ) and remained unchanged following wet-sieving. Pearl300 and Pearl300_WS showed a true density of about 1.49 g/cm 3 , in line with the known value for the crystals of β-mannitol . Regarding the SSA determined by gas absorption (SSA BET ), Cap60 showed a smaller mean area when compared to Pearl300, i.e., 2798 and 3932 cm 2 /g, respectively (Table ). This, was supported by the observations via SEM (Fig. ) showing that Cap60 was composed of smooth tomahawk agglomerates and Pearl300 of rough, irregular single particles with deep pores. Wet-sieving of the α-LH carrier (Cap60_WS) resulted in a slight decrease of the SSA (2121 cm 2 /g). Surprisingly, washing with acetone did not result in any change of the SSA of Pearl300. The SSA determined by gas adsorption is related to the nano- and mesoporosities presenting a mean diameter between 1.7 and 300 nm. It is apparent that for the smoother particles of Cap60, the presence of fines with size < 10 μm resulted in an increase of the porosities between 1.7–300 nm. For the very rough particles of Pearl300, the same was not observed. The theoretical specific area (SSA SV ), was calculated based on the D sv , under the assumption that the samples are composed of spherical solid particles, therefore the internal porosities and irregular shapes are not accounted for . Thus, the SSA sv values are much lower than the ones obtained by gas absorption. The BR is a parameter often used to evaluate the morphology of carrier particles intended for inhalation . It was observed that for Cap60, wet-sieving (Cap60_WS) did not result in any significant changes in the BR (Table ). However, Pearl300_WS showed a BR almost 3 times higher than the one calculated for the raw material. This was in line with SEM observations (Fig. ), where rougher, pumice single particles of D-mannitol were visualized after wet-sieving. For powder handling and formulation, rheological properties like cohesion and flowability obtained from shear cell experiments are important indicators. Comparing these values between the starting materials and the wet-sieved ones it was possible to see that, according to Jenike classification (ffc values between 2 and 4), generally, all powders were cohesive (Table ). Compared to Cap60, Cap60_WS showed slightly lower values of Coh and ffc. For the AIF eff a larger difference was observed and the wet-sieved powder presented a notable smaller value. For Pearl300, the surface treatment notably decreased the Coh, AIF eff and ffc. The AIF supplies information about the frictional forces within the powder (particle-particle) during flow. The friction within the powder is known to be influenced by particle size and shape . Considering that wet-sieving did not notably modify the overall shape of the α-LH and D-mannitol particles (Fig. ), we hypothesize that the differences in the AIF eff were mostly driven by washing out the particles <100 μm. Hence, we purpose that the fractionation of the powders led to the reduction of particle-particle contacts, decreasing friction within the powder . As a result of reduction in powder friction, slightly lower cohesion and ffc values were found indicating a potential improvement in flowability. For Pearl300, wet-sieving led to more notable changes in the particle size, and consequently a larger difference in powder flow values.
Since α-LH degrades upon melting , it was only possible to engineer Pearl300 through spray-congealing. During processing no evidence of any yellowish sample, characteristic of the degradation of sugars due to oxidation, was observed , thus it was inferred that D-mannitol was stable enough to be processed via spray-congealing. SEM images in Fig. show that spray-congealing resulted in spherical particles. The spray-congealed particles were also notably smaller than their raw and wet-sieved counter-parts, presenting lower Dv 0.1 , Dv 0.5 and Dv 0.9 . Additionally, they also presented a larger SPAN when compared to the other D-mannitol samples. Indeed, in Fig. , it is possible to observe the presence of single spherical particles of diverse sizes. During spray-congealing, by the use of a twin-fluid nozzle, the viscous liquid (melt) was injected into a high velocity gas leading to the formation of droplets . Thus, when compared to other melt solidification techniques, i.e., prilling, where large narrowly monodispersed particles are obtained due to the use of nozzles that rely on hydrodynamic instabilities , twin-fluid atomization led to the formation of smaller particles. Additionally, it is speculated that because jet-breakage is more uncontrollable, droplets of various sizes were formed, leading to solid particles in a broader size span. Likewise, the Pearl300_SC sample also showed a considerable amount of fine particles below 10 μm (1.88%). MDSC analysis (Fig. ) of Pearl300_SC showed an endothermic event with a lower onset temperature (164°C) and enthalpy (288.40 J/g), when compared to the raw material. As mentioned before, from MDSC it is hard to distinguish between D-mannitol polymorphs; however, X-ray patterns of the α, β and δ forms of D-mannitol present very distinct Bragg peaks that allow their distinction. The α, β and δ forms are characterized by the peaks at 26.6°, 23.1° and 21.9°2θ, respectively . From WAXS patterns in Fig. , it is possible to distinguish a clear peak at 26.66° 2θ and a very small one at 21.9° 2θ. No peak could be found at 23.1° 2θ. Thus, it was concluded that Pearl300_SC was predominately composed of the α-form of D-mannitol with trace amounts of the δ-form. Although, Pearl300_SC presented a homogenous and smooth surface topography typical of non-crystalline surfaces, MDSC and WAXS of the same sample clearly indicate that the material was predominantly crystalline. Spray-congealing slightly decreased the true density compared to the starting and wet-sieved materials (Table ), potentially, due to the pure α-form presenting a lower true density (1.468 g/cm 3 ) . Further, given that after melting the α particles crystallized with the δ polymorph as an impurity, it is possible that the δ-mannitol acted as a crystal habit modifier affecting the true density of the compound . However, more investigations would be needed to confirm this. Compared to Pearl300 and Pearl300_WS, the spray-congealed samples show a significantly reduced surface area (SSA BET ) and roughness (BR). In contrast to all other non-spherical carriers, the SSA sv for Pearl300_SC is comparable to the SSA BET . Besides the spherical shape in line with the assumptions made for the SSA sv calculation, this also indicated that Pearl300_SC does not present notable morphological irregularities or/and porosities. Pearl300_SC showed notably smaller values of cohesion and a larger ffc (Table ), when compared to the raw and wet-sieved materials. Engineering by spray-congealing changed the D-mannitol powder from cohesive to free flowing. Interestingly, the AIF eff value of the Pearl300_SC and Pearl300_WS were very similar, thus it is more likely that the improvement in flowability is due to the packing state of the powder bed. It is assumed that due to the spherical and smooth nature of Pearl300_SC particles, the powder will present similar density in its packed and dilated conditions (Hausner ratio), facilitating the powder flow . The presence of trace amounts of δ-mannitol in Pearl300_SC raised concerns about the stability of the particles hence, the sample was conditioned for 24 h at 93% RH (set with saturated salt solution of potassium nitrate in a sealed chamber). Following the latter, it was determined that the δ-form was successfully converted into the more stable β-mannitol (Supplementary Material Fig. ), and mixing and aerosolization experiments were carried out with this sample.
All carriers (starting material, wet-sieved and spray-congealed ones) were blended with 1 wt% BDP (binary mixtures) and additionally, with a controlled amount of fines, namely 0.2 wt% MgSt and 10 wt% of ‘Preblend’ (fine α-LH + MgSt) (ternary mixtures). It is, generally, reported that rough and irregular carrier particles have a higher loading capacity compared to smooth ones . In more rough/irregular particles, the higher number of indentations and cavities present, allow a greater number of fine particles to fill and/or coat the surface of the carrier. Likewise, with the very smooth uniform Pearl300_SC no ternary blends were prepared as the surface morphology (smooth and uniform, without any cavities and a low surface area) was not expected to have a high loading capacity . After mixing all the blends presented an RSD < 7% (Table ). According to Hassan et al ., blends with an RSD below 10% are considered homogenous , thus we found the mixtures appropriate to be further tested concerning their in vitro aerodynamic performance. Representative SEM images of the blends are presented in Figs. , and (and Supplementary Material Fig. – ). Impact of Particle Engineering on Shot Weight Consistency The shot weight consistency is a crucial factor to ensure that the release of every dose is the same and therapeutic outcomes are met . Therefore, two different inhalers of each blend were tested concerning the consistency of 10 consecutive shots and the inter- and intra-device variability were evaluated. The NEXThaler® is a breath-actuated reservoir device in which a powder is first precisely dosed by gravity into a recess and then de-agglomerated in a vortex chamber. To evaluate the dose-mass consistency, it is important to understand how the particle properties of different carriers might have affected these two steps. In Fig. , it can be observed that for the binary blends, engineering of Cap60 and Pearl300 by wet-sieving led to lower inter-device variability. We propose, this was a consequence of the more uniform sized powders (lower SPAN) produced via wet-sieving. Due to the disparity between device performances containing Pearl300 as a carrier, no clear inference concerning the effect of wet-sieving on intra-device variability could be made. For Cap60, the narrower PSD of the wet-sieved material also seemed to beneficially affect intra-device variability. A crucial observation was that spray-congealing of Pearl300 led to a higher mean mass of powder being dosed per shot (increase from about 9.9 to 13.4 mg). We hypothesize, that this was mainly related to the spherical shape of the spray-congealed material. Spherical shaped materials are known to pack more uniformly compared to irregular ones, so for the same recess volume a higher powder mass could be dispensed . Additionally, it was observed that for Pearl300_SC the two devices tested showed extremely identical performances. Here, this cannot be attributed to the SPAN of the material as Pearl300_SC actually, showed a higher value compared to Pearl300. However, Pearl300_SC demonstrated better flow when compared to the raw and wet-sieved materials. Improvement in flow has been associated with more consistency during powder filling and could potentially explain the observed results. Still, Pearl300_SC showed a larger intra-device variability (RSD ~ 6%). During vortex fluidization, particles of distinct sizes accelerate at different speeds, possibly leading to segregation; i.e., smaller lighter particles leave the device more readily and larger and heavier ones will have more tendency to move inwards . Hence, the greater intra-device variability could be associated to the larger differences in PSD of Pearl300_SC. The addition of MgSt (Fig. ) to the blends of the raw materials and BDP (Cap60 + MgSt and Pearl300 + MgSt) did not have any notable impact on the inter- and intra-device variability (Fig. ). However, for the wet-sieved materials the use of the salt led to a pronounced deterioration of inter- and intra-device variability (Cap60_WS + MgSt and Pearl300_WS + MgSt). The reason underlying this behavior needs to be clarified; however, it is known that MgSt preferentially fills large cavities of coarser particles, and its optimal effect on flow follows a non-linear correlation with the radius of the particles to be lubricated . Considering the differences induced by wet-sieving in the surface topography and micromeritic properties (i.e., BET, PSD, roughness) of α-LH and D-mannitol, it is not entirely surprising, that distinct impacts on powder flow were observed when using the same concentration of MgSt on the raw and wet-sieved materials. In future work, the effective concentration of MgSt to improve the performance of carrier particles with distinct characteristics will have to be investigated. The addition of ‘Preblend’ to Cap60 and Cap60_WS with BDP led to higher differences in intra- and inter-device variability (Fig. ). For Pearl300, the addition of ‘Preblend’ increased the mass of the emitted dose (from about 9.5 to 10.9 mg) and improved inter-device variability. Whereas, for Pearl300_WS, the addition of ‘Preblend’ did not have any notable impact on inter-device variability, but increased the intra-device RSD from ~4.5% to 9.2%. We hypothesize, that the different impact of ‘Preblend’ on α-LH and D-mannitol carriers was related to the very distinct surface topography of the two carriers. D-mannitol carriers were considerably more corrugated than the α-LH ones and, thus expected to be able to host more fine excipient particles onto/into their surface . On the contrary, the less corrugated two α-LH materials (Cap60 and Cap60_WS) could not accommodate the fines as efficiently, leading to segregation (between coarse carrier particles hosting fines and particulate agglomerates of fines, see supplementary material Fig. (c) and (f)) . Thus, powder flow was deteriorated and an increase in inter- and intra-device variability was seen. For Pearl300, it is speculated that the concentration of ‘Preblend’ plus the initial fines content of the carrier were ideal to adequately coat its rough surface, originating a denser packing, that produced an increase of the emitted mass per shot. In contrast, for the rougher surface of Pearl300_WS with reduced initial amount of fines, the concentration of ‘Preblend’ was not enough to cause potential changes in the powder bed packing; thus, no differences in the emitted mass per shot were observed. With respect to intra-device variability, it is suggested that the more efficient detachment of fine particles from Pearl300_WS than from Pearl300 (shown by its higher FPF in Fig. ) also resulted in a more efficient de-agglomeration; this, in turn leading to more particles of different sizes within the vortexes and higher dose variability (as already explained for the Pearl300_SC blends).
The shot weight consistency is a crucial factor to ensure that the release of every dose is the same and therapeutic outcomes are met . Therefore, two different inhalers of each blend were tested concerning the consistency of 10 consecutive shots and the inter- and intra-device variability were evaluated. The NEXThaler® is a breath-actuated reservoir device in which a powder is first precisely dosed by gravity into a recess and then de-agglomerated in a vortex chamber. To evaluate the dose-mass consistency, it is important to understand how the particle properties of different carriers might have affected these two steps. In Fig. , it can be observed that for the binary blends, engineering of Cap60 and Pearl300 by wet-sieving led to lower inter-device variability. We propose, this was a consequence of the more uniform sized powders (lower SPAN) produced via wet-sieving. Due to the disparity between device performances containing Pearl300 as a carrier, no clear inference concerning the effect of wet-sieving on intra-device variability could be made. For Cap60, the narrower PSD of the wet-sieved material also seemed to beneficially affect intra-device variability. A crucial observation was that spray-congealing of Pearl300 led to a higher mean mass of powder being dosed per shot (increase from about 9.9 to 13.4 mg). We hypothesize, that this was mainly related to the spherical shape of the spray-congealed material. Spherical shaped materials are known to pack more uniformly compared to irregular ones, so for the same recess volume a higher powder mass could be dispensed . Additionally, it was observed that for Pearl300_SC the two devices tested showed extremely identical performances. Here, this cannot be attributed to the SPAN of the material as Pearl300_SC actually, showed a higher value compared to Pearl300. However, Pearl300_SC demonstrated better flow when compared to the raw and wet-sieved materials. Improvement in flow has been associated with more consistency during powder filling and could potentially explain the observed results. Still, Pearl300_SC showed a larger intra-device variability (RSD ~ 6%). During vortex fluidization, particles of distinct sizes accelerate at different speeds, possibly leading to segregation; i.e., smaller lighter particles leave the device more readily and larger and heavier ones will have more tendency to move inwards . Hence, the greater intra-device variability could be associated to the larger differences in PSD of Pearl300_SC. The addition of MgSt (Fig. ) to the blends of the raw materials and BDP (Cap60 + MgSt and Pearl300 + MgSt) did not have any notable impact on the inter- and intra-device variability (Fig. ). However, for the wet-sieved materials the use of the salt led to a pronounced deterioration of inter- and intra-device variability (Cap60_WS + MgSt and Pearl300_WS + MgSt). The reason underlying this behavior needs to be clarified; however, it is known that MgSt preferentially fills large cavities of coarser particles, and its optimal effect on flow follows a non-linear correlation with the radius of the particles to be lubricated . Considering the differences induced by wet-sieving in the surface topography and micromeritic properties (i.e., BET, PSD, roughness) of α-LH and D-mannitol, it is not entirely surprising, that distinct impacts on powder flow were observed when using the same concentration of MgSt on the raw and wet-sieved materials. In future work, the effective concentration of MgSt to improve the performance of carrier particles with distinct characteristics will have to be investigated. The addition of ‘Preblend’ to Cap60 and Cap60_WS with BDP led to higher differences in intra- and inter-device variability (Fig. ). For Pearl300, the addition of ‘Preblend’ increased the mass of the emitted dose (from about 9.5 to 10.9 mg) and improved inter-device variability. Whereas, for Pearl300_WS, the addition of ‘Preblend’ did not have any notable impact on inter-device variability, but increased the intra-device RSD from ~4.5% to 9.2%. We hypothesize, that the different impact of ‘Preblend’ on α-LH and D-mannitol carriers was related to the very distinct surface topography of the two carriers. D-mannitol carriers were considerably more corrugated than the α-LH ones and, thus expected to be able to host more fine excipient particles onto/into their surface . On the contrary, the less corrugated two α-LH materials (Cap60 and Cap60_WS) could not accommodate the fines as efficiently, leading to segregation (between coarse carrier particles hosting fines and particulate agglomerates of fines, see supplementary material Fig. (c) and (f)) . Thus, powder flow was deteriorated and an increase in inter- and intra-device variability was seen. For Pearl300, it is speculated that the concentration of ‘Preblend’ plus the initial fines content of the carrier were ideal to adequately coat its rough surface, originating a denser packing, that produced an increase of the emitted mass per shot. In contrast, for the rougher surface of Pearl300_WS with reduced initial amount of fines, the concentration of ‘Preblend’ was not enough to cause potential changes in the powder bed packing; thus, no differences in the emitted mass per shot were observed. With respect to intra-device variability, it is suggested that the more efficient detachment of fine particles from Pearl300_WS than from Pearl300 (shown by its higher FPF in Fig. ) also resulted in a more efficient de-agglomeration; this, in turn leading to more particles of different sizes within the vortexes and higher dose variability (as already explained for the Pearl300_SC blends).
In Vitro Inhalation Performance The ED, FPM, and FPF were used to evaluate the performance of engineered D-mannitol particles in comparison to the D-mannitol reference material as well as α-LH engineered and starting material in binary and ternary blends. No pronounced differences could be detected in the MMAD among the different formulations. All the blends presented an MMAD of 1.8 ± 0.5 μm. Impact of Particle Engineering and Addition of Ternary Agents on the Drug Dose Looking first at the binary blends, the ED values were comparable between starting and wet-sieved materials (Fig. ) and no notable differences were found between D-mannitol and α-LH particles. Further, this was in line with the shot weight results where no difference in emitted mass was observed. The FPM was slightly lower for both, wet-sieved D-mannitol and α-LH. By contrast, Pearl300_SC showed 75% higher ED and 168% higher FPM related to Pearl300. Concerning the FPF of the various D-mannitol carriers (Fig. ), a slight increase in the FPF was observed when using Pear300_SC, indicating better API de-attachment. Hence, it can be inferred that the improvement in ED and FPM was mainly due to two factors; the better API de-attachment and the increase in the mass delivered per shot (about 40% more), as explained in the previous section. Comparing the stage-wise deposition of the binary blends (Fig. ), it can bee seen that the wet-sieved and starting materials showed comparable deposition. Only the use of Pearl300_WS slightly reduced the amount of drug deposited in the mouth and throat (M + T) and pre-separator (Presep) and increased the amount of drug on stage 5. The deposition pattern of Pearl300_SC was different from the other binary blends and a very high amount of API was found in the M + T. This led to the assumption that drug detachment is quite efficient, even taking place too early and allowing for loose API to be deposited already in the mouth and throat (not being transported to the deep lung). Further, higher amounts of API were deposited on stage 3, 4 and 5. Again, the higher shot weight and resulting larger amount of BDP per NGI experiment could have, in part, contributed to this. The addition of ternary agents is reported to increase the deposition of the API at the lower stages of the NGI by varying mechanisms . Likewise, it was not surprising that in the present study, the addition of MgSt and ‘Preblend’, overall, increased the FPM for D-mannitol and α-LH carriers (binary vs ternary blends, Fig. and (a), respectively); while the ED remained comparable. Looking at the stage-wise deposition in Fig. and comparing it with the binary blends in Fig. , the addition of MgSt increased the amount of BDP on stage 4 and 5 of the impactor and limited the amount in the Presep (this was true for α-LH and D-mannitol, wet-sieved and starting material). MgSt is used as a force control agent in DPI formulations in order to reduce the adhesive interactions of the API with the carrier surface, improving de-attachment . Likewise, in the present study the use of the salt, led to more API being found in the lower stages of the impactor and higher FPFs (Fig. ). The improvement in FPM was even more pronounced when ‘Preblend’ was added to Cap60 and Pearl300_WS. Interestingly, Cap60_WS was superior compared to Cap60 in combination with MgSt (lower deposition in Presep and higher deposition in stages 3 to 7) and Pearl300_WS was superior over Pearl300 in combination with ‘Preblend’ (lower deposition in Presep and higher deposition in stages 4 to 7). Given that, excluding Pearl300_SC, all the blends presented very similar EDs, the differences in FPM can, generally, be attributed to how drug de-attachment was affected by engineering and/or the addition of ternary agents. Impact of Particle Engineering and Addition of Ternary Agents on Drug de-Attachment Figure compares the FPF of all binary and ternary blends. Here, one can clearly see how the different carriers and ternary agents affected drug de-attachment. The highest FPF of all the tested formulations was achieved using Pearl300_WS in combination with ‘Preblend’. For this system, the wet-sieved carrier showed a notably better performance compared to the starting material. This can be explained by the deep voids and clefts on the surface of Pearl300 revealed during the wet-sieving process. It is proposed that the latter were filled up with ‘Preblend’ during the blending process and allowed BDP to be more efficiently detached from the wet-sieved D-mannitol carrier surface . In contrast, the comparably smaller amount of MgSt was not enough to cause this effect. For Cap60, the addition of ‘Preblend’ resulted in the same FPFs for starting and wet-sieved materials. Here, compared to the starting material, the wet-sieved sample only showed an increase in FPF when MgSt was added. This can be explained by the morphological difference of the starting materials (α-LH vs D-mannitol). Cap60 showed no voids and clefts, where the API could be sheltered from aerosolization forces. Moreover, it is hypothesized that, here, the reduction of initial fines (0.49%) to 0.17% by wet-sieving also played a crucial role when a small amount of ternary agent (0.2% of MgSt) was added. MgSt has a high affinity to bind to lactose (no electrostatic repulsion) . Thus, it is postulated that the addition of MgSt to Cap60_WS with lower intrinsic α-LH fines, successfully covered the ‘active sites’ (high energy binding sites on the carrier surface) on the carrier surface and forced API particles to interact with passive or low energy sites, promoting its detachment . By contrast, when ‘Preblend’ was added, the difference in initial fines content (Cap60 vs Caps60_WS) becomes insignificant and the behavior of Cap60 and Cap60_WS blends is dominated by the high amount of α-LH fines (10%) compared to intrinsic α-LH fines (0.4%7 vs 0.17%). Pearl300_WS, the powder with the highest bulk roughness, showed the best performance when in combination with 10% ‘Preblend’. In turn, Pearl300, was the only carrier where the addition of ‘Preblend’ did not further increase the FPF compared to the ternary blends with MgSt. For Pearl300, the total amount of intrinsic fines plus API seemed already too high, for the addition of ‘Preblend’ to cause a positive effect (13.08% compared to 11.45% for Pearl300_WS, 11.47% for Caps60 and 11.17% for Cap60_WS formulated with ‘Preblend’). A threshold where a certain number of fines, does not further improve or even reduce the aerosolization performance has been reported before . Results vary depending on the type of device and formulation used. The difference in type and amount of fines that show a superior effect on the aerosolization performance of α-LH and/or D-mannitol is most likely connected to the effect that different mechanisms (active site, buffer, agglomeration and fluidization theories) have on API detachment. These effects might be different for the two materials and dependent on the surface topography and structure of the carrier. The FPF delivered from the spray-congealed carrier was 16 ± 2% (Fig. ) and notably higher when compared to the starting material of D-mannitol (FPF = 8%). Comparison of the FPF of Pearl300_SC to the one from the wet-sieved material, shows that the use of Pearl300_WS without ternary agents did not notably impact the FPF of D-mannitol. Likewise, without the addition of ternary agents, spray-congealing of D-mannitol has shown to be promising in terms of the relative increase of the FPF, when in relation to the starting material (around 100%).
Looking first at the binary blends, the ED values were comparable between starting and wet-sieved materials (Fig. ) and no notable differences were found between D-mannitol and α-LH particles. Further, this was in line with the shot weight results where no difference in emitted mass was observed. The FPM was slightly lower for both, wet-sieved D-mannitol and α-LH. By contrast, Pearl300_SC showed 75% higher ED and 168% higher FPM related to Pearl300. Concerning the FPF of the various D-mannitol carriers (Fig. ), a slight increase in the FPF was observed when using Pear300_SC, indicating better API de-attachment. Hence, it can be inferred that the improvement in ED and FPM was mainly due to two factors; the better API de-attachment and the increase in the mass delivered per shot (about 40% more), as explained in the previous section. Comparing the stage-wise deposition of the binary blends (Fig. ), it can bee seen that the wet-sieved and starting materials showed comparable deposition. Only the use of Pearl300_WS slightly reduced the amount of drug deposited in the mouth and throat (M + T) and pre-separator (Presep) and increased the amount of drug on stage 5. The deposition pattern of Pearl300_SC was different from the other binary blends and a very high amount of API was found in the M + T. This led to the assumption that drug detachment is quite efficient, even taking place too early and allowing for loose API to be deposited already in the mouth and throat (not being transported to the deep lung). Further, higher amounts of API were deposited on stage 3, 4 and 5. Again, the higher shot weight and resulting larger amount of BDP per NGI experiment could have, in part, contributed to this. The addition of ternary agents is reported to increase the deposition of the API at the lower stages of the NGI by varying mechanisms . Likewise, it was not surprising that in the present study, the addition of MgSt and ‘Preblend’, overall, increased the FPM for D-mannitol and α-LH carriers (binary vs ternary blends, Fig. and (a), respectively); while the ED remained comparable. Looking at the stage-wise deposition in Fig. and comparing it with the binary blends in Fig. , the addition of MgSt increased the amount of BDP on stage 4 and 5 of the impactor and limited the amount in the Presep (this was true for α-LH and D-mannitol, wet-sieved and starting material). MgSt is used as a force control agent in DPI formulations in order to reduce the adhesive interactions of the API with the carrier surface, improving de-attachment . Likewise, in the present study the use of the salt, led to more API being found in the lower stages of the impactor and higher FPFs (Fig. ). The improvement in FPM was even more pronounced when ‘Preblend’ was added to Cap60 and Pearl300_WS. Interestingly, Cap60_WS was superior compared to Cap60 in combination with MgSt (lower deposition in Presep and higher deposition in stages 3 to 7) and Pearl300_WS was superior over Pearl300 in combination with ‘Preblend’ (lower deposition in Presep and higher deposition in stages 4 to 7). Given that, excluding Pearl300_SC, all the blends presented very similar EDs, the differences in FPM can, generally, be attributed to how drug de-attachment was affected by engineering and/or the addition of ternary agents.
Figure compares the FPF of all binary and ternary blends. Here, one can clearly see how the different carriers and ternary agents affected drug de-attachment. The highest FPF of all the tested formulations was achieved using Pearl300_WS in combination with ‘Preblend’. For this system, the wet-sieved carrier showed a notably better performance compared to the starting material. This can be explained by the deep voids and clefts on the surface of Pearl300 revealed during the wet-sieving process. It is proposed that the latter were filled up with ‘Preblend’ during the blending process and allowed BDP to be more efficiently detached from the wet-sieved D-mannitol carrier surface . In contrast, the comparably smaller amount of MgSt was not enough to cause this effect. For Cap60, the addition of ‘Preblend’ resulted in the same FPFs for starting and wet-sieved materials. Here, compared to the starting material, the wet-sieved sample only showed an increase in FPF when MgSt was added. This can be explained by the morphological difference of the starting materials (α-LH vs D-mannitol). Cap60 showed no voids and clefts, where the API could be sheltered from aerosolization forces. Moreover, it is hypothesized that, here, the reduction of initial fines (0.49%) to 0.17% by wet-sieving also played a crucial role when a small amount of ternary agent (0.2% of MgSt) was added. MgSt has a high affinity to bind to lactose (no electrostatic repulsion) . Thus, it is postulated that the addition of MgSt to Cap60_WS with lower intrinsic α-LH fines, successfully covered the ‘active sites’ (high energy binding sites on the carrier surface) on the carrier surface and forced API particles to interact with passive or low energy sites, promoting its detachment . By contrast, when ‘Preblend’ was added, the difference in initial fines content (Cap60 vs Caps60_WS) becomes insignificant and the behavior of Cap60 and Cap60_WS blends is dominated by the high amount of α-LH fines (10%) compared to intrinsic α-LH fines (0.4%7 vs 0.17%). Pearl300_WS, the powder with the highest bulk roughness, showed the best performance when in combination with 10% ‘Preblend’. In turn, Pearl300, was the only carrier where the addition of ‘Preblend’ did not further increase the FPF compared to the ternary blends with MgSt. For Pearl300, the total amount of intrinsic fines plus API seemed already too high, for the addition of ‘Preblend’ to cause a positive effect (13.08% compared to 11.45% for Pearl300_WS, 11.47% for Caps60 and 11.17% for Cap60_WS formulated with ‘Preblend’). A threshold where a certain number of fines, does not further improve or even reduce the aerosolization performance has been reported before . Results vary depending on the type of device and formulation used. The difference in type and amount of fines that show a superior effect on the aerosolization performance of α-LH and/or D-mannitol is most likely connected to the effect that different mechanisms (active site, buffer, agglomeration and fluidization theories) have on API detachment. These effects might be different for the two materials and dependent on the surface topography and structure of the carrier. The FPF delivered from the spray-congealed carrier was 16 ± 2% (Fig. ) and notably higher when compared to the starting material of D-mannitol (FPF = 8%). Comparison of the FPF of Pearl300_SC to the one from the wet-sieved material, shows that the use of Pearl300_WS without ternary agents did not notably impact the FPF of D-mannitol. Likewise, without the addition of ternary agents, spray-congealing of D-mannitol has shown to be promising in terms of the relative increase of the FPF, when in relation to the starting material (around 100%).
In order to get an idea of the performance of our novel engineered carriers (Pearl300_SC and Pearl300_WS in combination with ‘Preblend’) related to other engineered D-mannitol carriers, the FPF and relative increase in FPF (RI-FPF) for a few selected systems tested with the Novolizer® was compared. The Novolizer® also uses vortex-based fluidization and is considered most similar to the NEXThaler® used in the present study. In our study, the FPF for wet-sieved mannitol with ‘Preblend’ was 69.2%, and the FPF of Pearl300 with ‘Preblend’ 32.4% resulting in a RI-FPF of 114%. Scherließ et al . reported for Parteck® M DPI (Merck, Germany), a commercial mannitol product for DPIs, FPF values of around 40% . Compared to that the RI-FPF for Pearl300_WS + ‘Preblend’ would be 75%. In the aforementioned study, Parteck® M DPI was tested in blends with ternary agents (MgSt and mannitol fines) and the RI-FPF was 55% (for budesonide) and 65% (for salbutamol sulphate), depending on the API that was used . Littringer at al. produced spray-dried mannitol particles and the FPF of salbutamol sulphate varied from 11% to 29% dependent on the surface roughness and topography (indentations) of the carrier material. However, no comparison with the starting material was done . Our Pearl300_SC, spherical particles with a smooth surface and slightly larger size showed a FPF of 16% and RI-FPF of 100%. Overall, the FPF or relative improvement of the in-vitro aerosolization performance (RI-FPF) of Pearl300_WS + ‘Preblend’ and Pearl300_SC is superior or equal to other reported mannitol carriers. However, we note that direct comparison is not straight forward, as besides the inhalation device, performance is further affected by the carrier size, the API used, formulation and blending procedure and a combination of thereof. Therefore, we caution here that this comparison is just to showcase the relative extent of FPF gained (or not) by a certain route of carrier particle engineering and/or ternary agent addition. Finally, in the competitive market of inhalable medications, especially for patients with asthma and chronic obstructive pulmonary disease (COPD), there are a multitude of available devices each with different operating principles. Reservoir multi-dose DPI devices such as NEXThaler® and Novolizer® represent the preferred solution in terms of easiness of administration and portability for the chronic therapies, increasing adherence and minimizing errors in device handling. On the other hand, developing a DPI formulation for this kind of devices is, generally, a difficult task. Indeed, the DPI powder must behave with a high level of reproducibility during the whole life of the device. In particular, the challenge is to have good powder flow behavior to ensure the adequate and constant metering of the doses over the period of a device use. This aspect is less challenging in a unit-dose or multi-unit dose device, where a filling machine can be customized to properly meter the single dose with a larger range of viable options. Furthermore, also the de-agglomeration and aerosolization of the metered dose must be adequate in terms of performance and reproducibility, and constant through the whole life of the multi-dose device. For this reason, usually a carrier-based formulation is needed to be combined with a multi-dose reservoir device and very often the formulation platform is co-developed with the device to give a reciprocal adaptation. For this reason, the carrier-based DPI formulation described in this paper, showed noteworthy results. Indeed, these formulations were not specifically co-developed with a reservoir multi-dose device, but only adapted on an existing one, designed for other DPI carrier-based platforms. In particular, as a DPI carrier, the spray-congealed D-mannitol, Pearl300_SC , showed to be able to deliver drugs with a good reproducibility of shot weight and without the use of ternary agents such as MgSt. An optimized carrier with similar characteristics could be beneficial to reduce the number of mixing process steps and avoiding the inhalation of excess excipient fine materials. Subsequently, scale-up trials were done in order to evaluate scalability of the process and two 500 g batches were successfully produced with comparable particle characteristics and inhalation performance . By optimizing the blending protocol for spray-congealed D-mannitol and, reducing drug deposition in mouth and throat, this engineered material is expected to be a promising candidate as a novel inhalation carrier.
In our study, we showed the results of spray-congealing and wet-sieving of D-mannitol as innovative particle engineering processes to develop superior inhalation carrier particles. Wet-sieving, being an appropriate technique to generate smooth carriers with a narrow particle size distribution enabled better control of the number of fines needed in the formulation. Results have shown that the wet-sieving process and the related aerosolization performance are strongly dependent on the topography and structure of the starting material. Further, this study, again showed the interdependency of carrier particle surface and formulation parameters and their effect on inhalation performance; α-LH and D-mannitol do not show identical performance when engineered via wet-sieving and the same ternary agents are added. The more uniform pumice particles with deep voids and clefts of Pearl300_WS led to a beneficial effect in combination with 10% ‘Preblend’. By contrast, for the agglomerated Cap60_WS with smooth surfaces and pronounced edges, the addition of 0.2% MgSt was advantageous for the inhalation performance. Spray-congealing, a single step process, has shown its potential in generating smooth spherical particles of δ-D-mannitol that easily (conditioning overnight) can be converted into the stable β-form. The initial benefit of using spray-congealed D-mannitol to enhance the in vitro aerosolization performance of binary blends of the carrier with a low dose of BDP was shown (RI-FPF of 100%). ACKNOWLEDGMENTS AND DISCLOSURES This work was funded through the Austrian COMET Program by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT), the Austrian Federal Ministry of Economy, Family and Youth (BMWFJ) and by the State of Styria (Styrian Funding Agency SFG). The authors would also like to thank Sabrina Mertschnigg at FELMI-ZFE − Austrian Centre for Electron Microscopy for her assistance in the scanning electron microscopy measurements, Meggle for kindly providing lactose samples, Roquette for providing D-mannitol samples and Bruker AXS GmbH (Germany) for allowing the use of their equipment. TG and FS are employees of Chiesi Farmaceutici; HS is an employee of Austrian Centre for Electron Microscopy and Nanoanalysis; JTP, SZ and AP are employees of the Research Center Pharmaceutical Engineering GmbH, which received funding for their work from Chiesi Farmaceutici.
This work was funded through the Austrian COMET Program by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT), the Austrian Federal Ministry of Economy, Family and Youth (BMWFJ) and by the State of Styria (Styrian Funding Agency SFG). The authors would also like to thank Sabrina Mertschnigg at FELMI-ZFE − Austrian Centre for Electron Microscopy for her assistance in the scanning electron microscopy measurements, Meggle for kindly providing lactose samples, Roquette for providing D-mannitol samples and Bruker AXS GmbH (Germany) for allowing the use of their equipment. TG and FS are employees of Chiesi Farmaceutici; HS is an employee of Austrian Centre for Electron Microscopy and Nanoanalysis; JTP, SZ and AP are employees of the Research Center Pharmaceutical Engineering GmbH, which received funding for their work from Chiesi Farmaceutici.
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Combining Thyroglobulin Levels in Lymph Node Wash-out Fluid with TI-RADS to Predict Lymph Node Metastasis in Papillary Thyroid Carcinoma | ab902530-b6d6-46d9-b87d-8acdf2ae5d35 | 11862841 | Biopsy[mh] | The identification rate of thyroid nodules has significantly increased in recent years due to advances in high-frequency ultrasound equipment and improved awareness among health professionals . Approximately 7%-15% of these thyroid nodules are malignant , with papillary thyroid carcinoma (PTC) accounting for about 84% . Generally, PTC has a good prognosis, but about 35% of the patients still develop cervical lymph node metastasis . Fine-needle aspiration cytology (FNAC) is widely accepted by thyroid surgeons for cytopathological diagnosis of thyroid nodules to assess benign and malignant nature. Studies have shown that the diagnostic concordance rate of FNAC for thyroid nodules can reach 90% , but the concordance rate for lymph node metastasis is quite low. Clinical ultrasound is the most convenient and commonly used imaging technique to evaluate lymph node metastases , although its sensitivity and specificity are low, at about 30% and 86.8%, respectively . Lymph node FNAC has high accuracy but low sensitivity, so improving the diagnostic rate of lymph node metastasis in PTC is of great clinical importance. In previous studies, researchers have focused more on the predictive value of BRAF V600E gene mutations for lymph node metastasis, the size, location, extra thyroid extension (ETE), and capsular invasion of the nodule for predicting cervical lymph node metastasis , . However this study aimed at finding out the value of combining Thyroglobulin levels in lymph node wash out fluid with ultrasound features of thyroid and lymph node nodules using ACR TI-RADS to predict lymph node metastasis in patients with confirmed papillary thyroid carcinoma.
Patient Selection This study retrospectively collected and analyzed 1479 patients who underwent FNAC for thyroid nodules from January 2019 to December 2021 at The First Affiliated Hospital of Xi'an Jiaotong University. All these patients had at least one or more thyroid nodules that were rated category 4 or 5 by the criteria of ACR TI-RADS and were advised to undergo FNAC. This study eventually enrolled 251 patients who underwent surgery and were pathologically diagnosed with PTC. Those without surgical pathology or malignant tumors other than PTC were excluded. All the enrolled patients underwent thyroid nodules and lymph nodes. FNAC, BRAF V600E gene detection and thyroglobulin (Tg) detection in lymph node aspiration wash-out fluid. All patients' thyroid nodule ultrasound examinations were scored and categorized according to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). The Ethics Committee of Xi'an Jiaotong University's First Affiliated Hospital (XJTU-ZD10) granted ethical permission for this study. TI-RADS in Thyroid Nodule Processing This study utilized ACR TI-RADS reporting system in thyroid ultrasound assessment of the patients suspected to have papillary thyroid carcinoma. ACR TI-RADS uses ultrasonography features such as composition, echogenicity, shape, margin and echogenic foci features of thyroid nodules and assign values from 1 to 3 in each feature then add them up to the thyroid nodules to get scores, and the obtained scores are weighted to obtain the category of the nodules. Based on the size and categories of the nodules, nodules smaller than 10 mm in category 5 or 15 mm in category 4 are advised to do follow up visit, and nodules bigger than 10 mm in category 5 or 15 mm in category 4 are advised to do fine needle aspiration biopsy (FNAB) according to the ACR TI-RADS. All thyroid nodules and cervical lymph nodes were scanned using Canon Aplio i900 ultrasound diagnosing system equipped with i18LX5 high-frequency linear probe. The ultrasound examination method for cervical lymph nodes was the same as that for thyroid nodules. When one of the following sonographic features were detected: 1) liquefaction area in the lymph node; 2) calcification or punctate foci appearance in the lymph node; 3) round shape of the lymph node (longitudinal to transverse ratio < 1.5); 4) abnormally rich color doppler blood flow in the lymph node, metastasis was suspected and required FNAB. Ultrasound-Guided Thyroid Nodule and Lymph Node Fine-Needle Aspiration Biopsy All patients in category 4 and 5 with nodule size greater than or equal to 10 mm for category 5 and equal to or greater than 15 mm for category 4 were recommended for FNAB. Sample collection followed the standard procedure practiced at The First Affiliated Hospital of Xian Jiaotong University where a 23 G (0.6 mm) fine needle is inserted into the thyroid nodule under ultrasound guidance, repeatedly punctured until a small amount of tissue fluid appears in the junction of the biopsy needle, then the biopsy needle is removed. A 5 mL syringe filled with air is connected to the biopsy needle and the aspired tissue fluid is quickly expelled onto a glass slide, spread evenly with another glass slide, and then fixed in 95% ethanol. The residual tissue fluid inside the needle is washed repeatedly with buffer solution and placed in a centrifuge tube. The same method is used for lymph node fine-needle aspiration biopsy, and after placing the puncture tissue fluid on the glass slide, 5 µL of puncture tissue fluid is taken and placed in 50 µL of buffer solution for thyroglobulin determination, and the remaining tissue fluid on the glass slide is used for pathological smearing. Lymph Node Aspiration Fluid Tg Detection The lymph node aspiration fluid Tg detection was performed using a radioimmunoassay method. 200 µL of lymph node aspiration fluid and buffer solution in an Eppendorf (EP) tube were mixed evenly on a mixer, 100 µL of the mixed solution was added to the Tg-coated tube, then 400 µL of the label was added, mixed, and placed in an incubator for 16-20 hours. After washing with the wash solution twice, the coated tube was allowed to dry, and the counting measurement was performed using a gamma counter. Cytopathological Analysis and BRAF V600E Gene Detection After fixation with 95% ethanol, the puncture smears were stained with HE, and the sediment in the centrifuge tube was placed on a slide for Papanicolaou staining. A small amount of tissue fluid from the bottom of the centrifuge tube was used for polymerase chain reaction (PCR), and BRAF V600E gene mutation detection was performed with a genetic test kit. Statistical Analysis Statistical analysis was performed using SPSS version 20.0. The comparison of diagnostic results of different methods for lymph nodes was conducted using the chi-square test or Mann-Whitney U test. Quantitative data were displayed as mean ± standard deviation (SD). The postoperative pathological results of all patients were used as the gold standard for diagnosis. The diagnostic efficacy between lymph node FNA thyroglobulin (Tg-FNA) and BRAF V600E gene detection results was compared, calculating the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of both methods. Finally, the receiver operating characteristic (ROC) curve was drawn for both methods to determine the threshold for predicting lymph node metastasis by lymph node FNA thyroglobulin. A P-value of <0.05 was considered statistically significant. Using lymph node wash-out thyroglobulin, BRAF V600E mutation status, and thyroid nodule TI-RADS score as independent variables, and lymph node metastasis as the dependent variable, a binary logistic regression model was established to analyze the predictive impact of globulin levels, gene mutation status, and nodule TI-RADS score for lymph node metastasis.
This study retrospectively collected and analyzed 1479 patients who underwent FNAC for thyroid nodules from January 2019 to December 2021 at The First Affiliated Hospital of Xi'an Jiaotong University. All these patients had at least one or more thyroid nodules that were rated category 4 or 5 by the criteria of ACR TI-RADS and were advised to undergo FNAC. This study eventually enrolled 251 patients who underwent surgery and were pathologically diagnosed with PTC. Those without surgical pathology or malignant tumors other than PTC were excluded. All the enrolled patients underwent thyroid nodules and lymph nodes. FNAC, BRAF V600E gene detection and thyroglobulin (Tg) detection in lymph node aspiration wash-out fluid. All patients' thyroid nodule ultrasound examinations were scored and categorized according to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). The Ethics Committee of Xi'an Jiaotong University's First Affiliated Hospital (XJTU-ZD10) granted ethical permission for this study.
This study utilized ACR TI-RADS reporting system in thyroid ultrasound assessment of the patients suspected to have papillary thyroid carcinoma. ACR TI-RADS uses ultrasonography features such as composition, echogenicity, shape, margin and echogenic foci features of thyroid nodules and assign values from 1 to 3 in each feature then add them up to the thyroid nodules to get scores, and the obtained scores are weighted to obtain the category of the nodules. Based on the size and categories of the nodules, nodules smaller than 10 mm in category 5 or 15 mm in category 4 are advised to do follow up visit, and nodules bigger than 10 mm in category 5 or 15 mm in category 4 are advised to do fine needle aspiration biopsy (FNAB) according to the ACR TI-RADS. All thyroid nodules and cervical lymph nodes were scanned using Canon Aplio i900 ultrasound diagnosing system equipped with i18LX5 high-frequency linear probe. The ultrasound examination method for cervical lymph nodes was the same as that for thyroid nodules. When one of the following sonographic features were detected: 1) liquefaction area in the lymph node; 2) calcification or punctate foci appearance in the lymph node; 3) round shape of the lymph node (longitudinal to transverse ratio < 1.5); 4) abnormally rich color doppler blood flow in the lymph node, metastasis was suspected and required FNAB.
All patients in category 4 and 5 with nodule size greater than or equal to 10 mm for category 5 and equal to or greater than 15 mm for category 4 were recommended for FNAB. Sample collection followed the standard procedure practiced at The First Affiliated Hospital of Xian Jiaotong University where a 23 G (0.6 mm) fine needle is inserted into the thyroid nodule under ultrasound guidance, repeatedly punctured until a small amount of tissue fluid appears in the junction of the biopsy needle, then the biopsy needle is removed. A 5 mL syringe filled with air is connected to the biopsy needle and the aspired tissue fluid is quickly expelled onto a glass slide, spread evenly with another glass slide, and then fixed in 95% ethanol. The residual tissue fluid inside the needle is washed repeatedly with buffer solution and placed in a centrifuge tube. The same method is used for lymph node fine-needle aspiration biopsy, and after placing the puncture tissue fluid on the glass slide, 5 µL of puncture tissue fluid is taken and placed in 50 µL of buffer solution for thyroglobulin determination, and the remaining tissue fluid on the glass slide is used for pathological smearing.
The lymph node aspiration fluid Tg detection was performed using a radioimmunoassay method. 200 µL of lymph node aspiration fluid and buffer solution in an Eppendorf (EP) tube were mixed evenly on a mixer, 100 µL of the mixed solution was added to the Tg-coated tube, then 400 µL of the label was added, mixed, and placed in an incubator for 16-20 hours. After washing with the wash solution twice, the coated tube was allowed to dry, and the counting measurement was performed using a gamma counter.
After fixation with 95% ethanol, the puncture smears were stained with HE, and the sediment in the centrifuge tube was placed on a slide for Papanicolaou staining. A small amount of tissue fluid from the bottom of the centrifuge tube was used for polymerase chain reaction (PCR), and BRAF V600E gene mutation detection was performed with a genetic test kit.
Statistical analysis was performed using SPSS version 20.0. The comparison of diagnostic results of different methods for lymph nodes was conducted using the chi-square test or Mann-Whitney U test. Quantitative data were displayed as mean ± standard deviation (SD). The postoperative pathological results of all patients were used as the gold standard for diagnosis. The diagnostic efficacy between lymph node FNA thyroglobulin (Tg-FNA) and BRAF V600E gene detection results was compared, calculating the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of both methods. Finally, the receiver operating characteristic (ROC) curve was drawn for both methods to determine the threshold for predicting lymph node metastasis by lymph node FNA thyroglobulin. A P-value of <0.05 was considered statistically significant. Using lymph node wash-out thyroglobulin, BRAF V600E mutation status, and thyroid nodule TI-RADS score as independent variables, and lymph node metastasis as the dependent variable, a binary logistic regression model was established to analyze the predictive impact of globulin levels, gene mutation status, and nodule TI-RADS score for lymph node metastasis.
All 251 enrolled patients underwent FNA of thyroid nodules and cervical lymph nodes and BRAF V600E gene detection, and thyroglobulin were measured in the aspirated lymph nodes wash-out fluid. Serum thyroglobulin levels were also measured in all patients before biopsy procedure. Out of the 251 enrolled patients, 198 were postoperatively pathologically diagnosed with unilateral PTC and 53 with bilateral PTC. In the BRAF V600E gene detection, 219/251 (87.25%) patients (58 males, 161 females) were detected with BRAF V600E mutations, and 32 patients (5 males, 27 females) were not detected with mutations. Similarly, 132/251 (52.59%) patients (41 males, 91 females) were postoperatively pathologically confirmed to have cervical lymph node metastasis. Furthermore, 115/219 (52.51%) patients (38 males, 77 females) had lymph node metastasis and among those without detected mutations, 17/32, (53.13%) patients (3 males, 14 females) had lymph node metastasis. The Tg level in the lymph node aspiration fluid of patients with metastasis was 324.94 ± 192.52 ng/mL (range 0-500 ng/mL), and the serum Tg level was 27.08 ± 71.60 ng/mL. The Tg level in the lymph node aspiration fluid of patients without metastasis was 67.93 ± 136.62 ng/mL (range 0-500 ng/mL), and the serum Tg level was 20.73 ± 55.21 ng/mL (range 0-500 ng/mL). There was a significant statistical difference in lymph node aspiration fluid Tg levels between the two groups, P = 0.000. The area under the ROC curve for lymph node aspiration fluid Tg was 0.858, with a sensitivity of 0.829 and a specificity of 0.804 when the cut-off value was set at 62.99 ng/mL. According to the ACR TI-RADS, the thyroid nodule score for patients with metastasis was 10.29 ± 1.90, and for those without lymph node metastasis, it was 10.18 ± 2.03. The Mann-Whitney U test showed no difference between the two groups (P = 0.674). The size of the thyroid nodules in the group pathologically diagnosed with PTC and lymph node metastasis was approximately 11.48 ± 7.69 mm, and in the group without metastasis was about 9.61 ± 6.65 mm (p = 0.037). The Mann-Whitney U test showed a statistically significant difference between the two groups (P = 0.001). The sensitivity of FNA for the diagnosis of PTC lymph node metastasis was 63.86%, specificity 100%, positive predictive value 100%, negative predictive value 69.65%, and diagnostic efficiency 80.13%. The sensitivity of aspiration wash-out fluid Tg for the diagnosis of PTC lymph node metastasis was 86.59%, specificity 69.93%, positive predictive value 76.76%, negative predictive value 81.97%, and diagnostic efficiency 78.83%. The regression results showed that Wash-out thyroglobulin level has a significant positive predictive effect on cervical lymph node metastasis, with a regression coefficient of 0.003 and P = 0.000 < 0.001. BRAF V600E mutation and thyroid nodule TI-RADS score did not have a significant effect on lymph node metastasis, with P-values > 0.05.
The predictive significance of lymph node aspiration washout fluid thyroglobulin level, BRAF V600E gene mutation, ACR TI-RADS score of thyroid nodule ultrasonography features for cervical lymph node metastasis were examined in this retrospective cross-sectional study. A prospective study conducted in China which included 145 patients with papillary thyroid carcinoma found that BRAF gene mutation has good predictive value for lymph node metastasis , but the sample size of the study was relatively small. In a retrospective review analysis, the BRAF V600E gene mutation rate was about 74.6%, which is relatively high , and there was a significant difference between the overall metastasis rate. A study conducted on PTC, up to 35% of patients had metastasis , and in these patients, the ultrasound metastatic features of the lymph nodes were not obvious. How to specifically and sensitively identify these cervical metastatic lymph nodes before surgery has always been a problem for endocrine and surgical doctors. In recent years, fine-needle aspiration biopsy (FNAB)has become a method for diagnosing the benign and malignant nature of thyroid nodules , and combined with the Bethesda system, it can stratify the pathological diagnosis of thyroid nodules , with good diagnostic rate and repeatability. However, this method has some shortcomings in the diagnosis of lymph node metastasis. In this study, we found that lymph node thyroglobulin has better sensitivity and specificity than FNAC, but the diagnostic efficiency between the two is comparable. Similarly, the Tg level in metastatic lymph nodes was higher than in nonmetastatic lymph nodes, and there was a significant statistical difference between the two, indicating that this method has good diagnostic value and potential in diagnosing metastatic lymph nodes, consistent with the results of published studies , , but limited by the small sample size of these studies. Despite the good value obtained from the previous results, in this study, we found that the solitary ACR TI-RADS score of thyroid nodules did not show a significant difference in estimating lymph node metastasis. ACR TI-RADS is a commonly used method for radiologists to assess the stratified risk of thyroid nodules in recent years. This method quantifies the ultrasound characteristics of thyroid nodules, including echogenicity, composition, shape, margin, and echogenic foci, and then adds the scores to obtain five risk levels . The higher the nodule score, the greater the risk of malignancy of the nodule. This study attempted to use this method to predict lymph node metastasis with the score of thyroid nodules, but no statistical difference was obtained. One of the main reasons could be that the malignant risk range of TI-RADS category 5 nodules is broad and cannot classify the risk into more detailed levels. Although there was no difference in the TI-RADS scoring system of thyroid nodules between metastatic and non-metastatic lymph nodes, this study still showed that the size of thyroid nodules in metastatic cervical lymph nodes was larger than that of thyroid nodules without cervical lymph node metastasis. There is still controversy over the overtreatment of low-risk PTC, especially papillary thyroid microcarcinoma. Some researchers believe that active surveillance (AS) is currently the main approach , for example, an observational study conducted in Japan found that the progression is very slow . Assessing the lymph node metastasis of PTC in various ways may have a significant impact on whether AS is chosen.
This study still has many shortcomings. First, selection bias is inevitable. In addition, our hospital is a referral hospital and the probability of PTC patients having metastasis may be higher than in other hospitals. Similarly, the number of patients in this study is relatively small, and more samples need to be added in the future.
Lymph node FNA for Thyroglobulin level evaluation has good sensitivity and specificity for predicting lymph node metastasis in patients with PTC, combined with ACR TI-RADS classification in patients with larger thyroid nodules.
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Phylogenetic Signal in Primate Tooth Enamel Proteins and its Relevance for Paleoproteomics | d4e9baa8-32a8-43f9-8816-9ddc76760845 | 11878541 | Biochemistry[mh] | The survival of endogenous amino acids in fossils was demonstrated in the mid-20th century . More recently, access to protein sequence data from long deceased organisms has been achieved with the aid of mass spectrometry methods . Since then, the field has grown to propose a set of standards , and has proven to reliably determine sequence information from samples from as much as 14.8 million years ago (Ma) . The persistence of peptides for millions of years, even from temperate to warm environments, contrasts with the maximum biomolecule age of 2 million years from ancient DNA (aDNA) under permafrost conditions, which are considered ideal for DNA preservation . Despite post mortem degradation and often low protein abundance in the tissue , scientists have started studying ancient proteomes from a phylogenetic perspective . Given the abundance of tooth remains in the archaeological record, a considerable amount of paleoproteomic research has focused on tooth enamel . Several protein fragments are persistent in mature enamel . These protein fragments have been successfully used to infer the phylogenetic position of extinct taxa, such as the Pleistocene rhinoceros Stephanorhinus , and the extinct hominids Gigantopithecus blacki and Homo antecessor . However, these studies have also highlighted some of the current challenges of addressing phylogenetic analysis through ancient proteins. The most evident drawback is the limited amount of information due to the short length of the recovered peptides. In particular, the enamel proteome is rather small, comprising <15 proteins, which are further enzymatically degraded in vivo during enamel formation , and even more post mortem. To date, the combined length of recovered peptides from ancient enamelomes can range between 456 amino acids and 1,014 amino acids . In addition, the peptides from the enamel proteome are not evenly recovered along the protein sequence , further limiting subsequent analyses. Whole-genome sequencing can provide many more informative sites than a whole proteome ever could. This advance has led to a continuous refinement of molecular phylogenies and thus provides a robust reference against which to compare protein sequence-based phylogenies. Moreover, protein sequences can be bioinformatically predicted from nucleotide sequences. This enables us to infer protein sequences without the need to sequence the proteins directly. To our knowledge, a comprehensive assessment of the phylogenetic signal present in the enamel proteome has not been made thus far. Here, we evaluate the accuracy of phylogenetic reconstructions that can be achieved with fragmentary peptide data, compared to a robust, dated whole-genome phylogeny . We performed several phylogenetic analyses on protein sequences predicted from DNA data that span 16 families of the order Primates . The analysis is based on 14 proteins that have been associated with the enamel proteome . The proteins (or protein subunits) analyzed are alpha 2-HS glycoprotein (AHSG), albumin (ALB), ameloblastin (AMBN), amelotin (AMTN), amelogenin X-linked protein (AMELX), enamelin (ENAM), matrix metallopeptidase 20 (MMP20), odontogenic, ameloblast-associated protein (ODAM), serpin family C member 1 protein (SERPINC1), tuftelin 1 (TUFT1), collagen type I alpha 1 chain (COL1A1), collagen type I alpha 2 chain (COL1A2), collagen type XVII alpha 1 chain (COL17A1), and collagen type II alpha 1 chain (COL2A1). All predicted protein sequences were aligned. We assessed the degree of sequence conservation at each site of these alignments. Phylogenetic analysis was performed on the full-length translated sequences of the 14 enamel-associated proteins. A further analysis was carried out only with peptides corresponding to the protein regions typically captured in paleoproteomic studies, with the aim of simulating the limited amount of data in paleoproteomic studies. We further searched for segments in the protein sequences that appear most phylogenetically informative. The results of these analyses will inform future paleoproteomic studies by indicating which peptides should have priority in experimental recovery, but also by setting realistic expectations for the discriminatory power of these sequences in subsequent phylogenetic studies. Lastly, we discuss the implications of these findings and related factors, such as possible dependencies between the studied loci, when using ancient enamel peptides for evolutionary studies.
Assessment of Protein Sequence Conservation The degree of sequence conservation and evolutionary rates were examined for a set of 14 proteins from 232 primate species and 1 nonprimate outgroup ( Tupaia ). The analysis was performed on a concatenation of multiple sequence alignments (MSAs) of each protein into one large multiprotein MSA. Each species was represented by the individual that had the most complete sequence data (i.e. fewest gaps or masked positions). Both Shannon entropy and Rate4Site (R4S) can be applied to measure the degree of protein sequence conservation. While Rate4Site accounts for the different likelihoods of substitution during sequence evolution, Shannon entropy values are agnostic to any evolutionary or physico-chemical constraints. Shannon entropy values and Rate4Site scores both demonstrate that sequence diversity and evolutionary rates vary across the length of each protein sequence . In particular, collagens (except some sites in COL17A1) evolve at a slower rate than noncollagen proteins . Rate4Site scores roughly correlate with Shannon entropy values ( , Pearson correlation ρ = 0.54, P -value < 2.2e-16). About 4% of all sites are residues with particularly high evolutionary rates (R4S score > 2) that also fall into the regions that could be experimentally recovered in ancient samples . This is particularly the case in ALB, AMELX, AMBN, and ENAM. In most other proteins, such as AHSG, AMTN, COL17A, MMP20, ODAM, or TUFT1, the regions of particularly high evolutionary rates correspond to peptides that have not yet been experimentally recovered. At the other extreme, some regions of high sequence conservation levels stand out. In ENAM, there is a stretch of 49 highly conserved amino acids (corresponding to the positions 191 to 239 in UniProt ID Q9NRM1) that carries 2 phosphorylation sites. The region falls into the 32 kilodalton (kDa) cleavage product of ENAM , which belongs to peptides that can be experimentally recovered in deep time . MMP20 also displays larger regions of highly conserved amino acids that fall into the experimentally recovered sequences. One of those regions (corresponding to UniProt ID O60882, positions 174 to 254) lies around the active center (position 227) and its surrounding inorganic ion binding regions; another one lies around positions 330 to 483, a region whose ends are connected via a disulfide-bridge. Other longer experimentally recovered regions of relatively highly conserved sequences belong to AMBN, COL1A1, COL1A2, COL17A1, and SERPINC1. To examine if the above described patterns also hold beyond primates, Rate4Site scores were calculated on a set of 22 species from different taxonomic groups across mammals ( online, for list of species see online). The general pattern of slower evolutionary rates in collagens is consistent across mammals, particularly for COL1A1, COL1A2, and COL2A1. The area of the 32 kDa fragment in ENAM is not as strongly conserved as within primates; whereas, the region around the active center in MMP20 shows a persistently low evolutionary rate. Across mammals as a whole, the N-terminus of AMELX displays a higher degree of conservation, as is the case for primates specifically. In contrast, the C-terminus of AMTN, and the N-terminus of COL1A1 appear to evolve at a higher rate in the mammal-wide data compared to the primates-only data. Phylogenies Based on Full-Length Sequences The phylogenetic signal in each protein sequence dataset was assessed by measuring the Robinson–Foulds distance (RF-distance, topology only) between the tree resulting from that dataset and the reference tree, as well as manual inspection of differences in the topologies. There was no major difference in the phylogenetic trees created by maximum likelihood (ML) or Bayesian analysis ( online). The Bayesian analysis performed slightly better by creating more accurate trees (smaller RF-distances to reference tree) from the 5 (ML = 170, Bayesian = 153) and 10 (ML = 122, Bayesian = 117) protein concatenations; however, the ML approach produced a slightly more accurate tree for the 14 (ML = 108, Bayesian = 110) protein concatenation. Since the differences between the methods appeared to be minor, all following analyses were performed using the ML approach because it shows a higher computational efficiency ( online). In all trees, all taxa were placed correctly at least at the family level, with 2 exceptions: First, in the tree based on the 5 protein concatenation, Galagonidae and Lorisidae remain unresolved, meaning that species of these 2 families do not form 2 distinct clades. Second, while the general tendency is that the more proteins that are included in the concatenation, the more similar the tree is to the reference tree, there is 1 caveat for the 14 protein concatenation: the deepest relationship within Primates, namely the branching pattern between lorises and lemurs (Strepsirrhini), tarsiers (Tarsiiformes), and monkeys and apes (Simiiformes), is incorrectly resolved. Specifically, in the trees of the 14 protein concatenation (ML and Bayesian), Tarsiiformes form a clade with Strepsirrhini to the exclusion of Simiiformes with a bootstrap value of 90 and a posterior probability of 1; however, current molecular and morphological evidence collectively provides compelling support for Tarsiiformes + Simiiformes to the exclusion of Strepsirhini. In contrast, in the phylogenies from the 5 and 10 protein concatenations, Tarsiiformes and Simiiformes form a clade, in agreement with the reference tree ( online). In our case, the addition of 4 collagen genes to the dataset, resulting in the 14 protein concatenation, drove the misplacement of Tarsiiformes. We tested different combinations of collagens and noncollagen proteins of our dataset to see which gene products in particular are driving this misplacement ( online). If any of these individual collagens is combined with all 10 noncollagen proteins into an 11 protein concatenation, the noncollagen proteins drive the placement of tarsiers to the correct position, according to the species tree. However, if the 10 noncollagen proteins are combined with COL1A2 and COL1A1 or COL17A1, this is sufficient to override the signal in the noncollagen proteins and place Tarsiiformes with Strepsirrhini. Phylogenies by Fragmentation Stage To date, there is only a limited amount of information on how enamel proteins degrade post mortem over large time scales. We created a simple model of peptide fragment degradation by inspecting publicly available experimental enamel proteomes, combined with newly sequenced enamel proteomes from this study. These experimentally recovered enamel proteome sequences were aligned to the MSAs of our predicted protein sequences (“BLOCK3” in online). Different stages of post mortem protein sequence fragmentation were then modeled by removing specific sites (i.e. columns) in the MSA of each protein. The older the modeled fragmentation stage, the more sites were removed. For the model, we assumed heterogeneous post mortem survival times across all sites of each protein for 2 reasons: first, because the enamelome is already enzymatically cleaved in vivo , and second because different peptides may have different physico-chemical properties that influence their chemical breakdown. To understand the approximate patterns of this heterogeneity, we assessed how often each site in a protein could be experimentally recovered from published data together with new data using the MSAs. To date, the amount of available ancient protein sequences is not sufficient to use statistical methods to model the process of fragmentation across millions of years. Instead, we followed the rationale of reducing the amount of sequence information similar to what we observed in sequences of a certain age range. These ages give rise to the eponymous fragmentation stages. The more coverage a single site has, the longer is its anticipated survival. Based on the modeled fragmentation stages, we created 4 concatenated MSAs with increasingly reduced sequence data and examined phylogenetic trees that were calculated from those MSAs in order to understand the standalone phylogenetic information of fragmented protein sequences. The protein concatenation corresponding to the fragmentation stage of “100 ka” had a total length of 3,884 amino acids (∼41% of the original MSA's length, see online). The phylogeny based on this data showed a RF-distance of 156 to the species tree , in contrast with the phylogeny based on the full-length 14 proteins (alignment length 9,557 amino acids), which showed a RF-distance to the species tree of 108. All placements at family level and mostly genus level are in accordance with the reference tree, except for Tarsiiformes being grouped with Strepsirrhini (for more details see online). This is in line with the previous observation that the inclusion of COL1A2 and COL1A1 or COL17A1 can produce this result, even if just fragments of these protein sequences are included. Most differences that explain the RF-distance of 156 stem from different placements of species within their genus. The phylogeny based on the fragmentation stage “1 to 2 Ma” (MSA length 1,139 aa, ∼12% of the original MSA's length) has a very similar distance to the species tree (158). Most nodes at family level are placed in accordance with all confidently resolved nodes of the reference tree, with some exceptions ( online). For instance, in Hominidae, contrasting the reference tree, Pan and Gorilla are sister taxa, with Homo as an outgroup. Tarsiiformes are placed as an outgroup to both Strepsirhini and Simiiformes (bootstrap 100), a placement that is rejected by current molecular and morphological evidence . The tree based on data of the fragmentation stage “5 Ma” (alignment length 593 amino acids, ∼6% of the original MSA's length) has an RF-distance to the species tree of 240. In catarrhines, all family level relationships still agree with the reference tree, but there are some inconsistencies within families compared to the reference tree ( online). In platyrrhines, correct resolution of nodes at family level is widely lost. The placement of nodes at family level in Lemuridae is in accordance with the species tree, except for the placement of Varecia and Daubentonia madagascariensis ( online). Tarsiiformes form a clade with Strepsirhini (bootstrap 93). At the fragmentation stage “10 Ma” (alignment length 98 amino acids, ∼1% of the original MSA's length), the phylogeny is largely unresolved, with an RF-distance to the reference tree of 420 and most bootstrap values far below 50. Only lorisiforms are correctly separated as their own taxon. The 4 tarsiiform species are monophyletic and placed with low confidence within Simiiformes. Case Studies of Simulated Ancient Samples Often, paleoproteomic studies will only aim to place a few closely related specimens at a time into a framework of mostly complete reference protein sequences. To simulate such a scenario, we created 4 cases in which protein sequence data from a group with fairly well-known taxonomic placement were fragmented and aligned to reference sequences that are at full-length. In the first case, sequence data of 2 Neanderthals (individuals Vindija 33.19 and Altai) and 1 Denisovan (Denisova3 individual) that were fragmented to the degradation stage “100 ka” were aligned to a reference MSA of 14 enamel-related proteins from Hominoidea. The phylogenetic placement is in accordance with the reference tree at genus level, but not at species level . The Neanderthal and Denisovan individuals place within the Homo sapiens clade with low branch support, instead of forming a sister clade as shown by large-scale genomic data . In the same tree, individuals of the 2 species with the youngest split, namely Pongo abelii and Pongo pygmaeus , do not form 2 distinct clades, nor do the individuals of Gorilla gorilla and Gorilla beringei , despite being based on full-length protein data. These results align with previous observations on the limitations of paleoproteomic data to resolve phylogenies in Hominidae at species-level resolution . In particular, if several individuals per clade are examined using such limited sequence data; the interspecific differences can fall within the range of intraspecific variation . Reasons for this low phylogenetic resolution between species of the same genus can be incomplete lineage sorting or the overall slow evolutionary rate of the proteins found in dental enamel. The example of simulated ancient chimpanzee data of a fragmentation stage of “5 Ma” produces a different result . While the phylogenetic relationships of the species within Pongo and Gorilla cannot be resolved, the 3 Pan troglodytes individuals are placed confidently in a clade that is a sister taxon to Pan paniscus (bootstrap 100). Divergence times have been estimated using MCMCtree for each node of a simplified version (1 individual per species) of the “Chimpanzee case” tree ( and and online). The confidence intervals for the estimates of the case study and the reference tree overlap at nearly all nodes. On average, divergence time estimates derived from the protein-based data of the “Chimpanzee case” are 21% younger than those of the genome-based reference. While this is only one case example, it shows that divergence time estimates with similar results to those derived from high quality genome data are possible. In the “Colobine case” , simulated ancient samples (fragmentation stage “5 Ma”) of Rhinopithecus roxellana , and Colobus guereza are placed correctly at species level. However, the simulated ancient sample of Trachypithecus geei is placed within its sister genus Semnopithecus . Slight modifications of the methodology can fix this misplacement. T. geei was placed within its correct genus, when mixture models were allowed ( online). It was also placed correctly when the topology of the reference data was constrained based on information from the DNA-based reference tree ( online). In the “Lemur case” , the simulated ancient samples (fragmentation stage “100 ka”) of Eulemur sanfordi and Cheirogaleus major were placed correctly at species level and Lepilemur ankaranensis at genus level. Phylogenies by Amino Acid Conservation To quantify the contribution of the variable sites in each MSA to the correct resolution of the according tree, we divided all concatenated MSAs into 2 MSAs, 1 consisting of variable sites, the other of conserved sites. To divide between variable and conserved, the MSA of each protein was normalized to a mean of 1 in their Shannon entropy values or Rate4Site scores. They were then divided into sites above this value, i.e. the “variable” sites, and below, i.e. the “conserved” sites ( online). These sites from all proteins were concatenated and used for phylogenetic analysis with ML. Phylogenies based only on variable sites identified by Rate4Site ( online, “R4S variable”) are just as similar to the species tree as in the case of phylogenies based on the full-length protein sequences ( online, both have a RF-distance of 108 to the reference tree). Similarly, when using Shannon entropy to define conserved and variable sites, phylogenies based on the variable sites ( online, “Shannon variable”) are more similar to the reference tree than those based on the more conserved sites (“Shannon conserved”). In general, all phylogenies based on variable sites that were identified using Rate4Site (“R4S variable”) are more similar to the reference tree than those based on variable sites that were identified using Shannon entropy (“Shannon variable”). Thus, the more variable sites contain most of the phylogenetic signal. In this case, to define the most variable sites, Rate4Site has been a better predictor of phylogenetically informative sites. Evolutionary Rate Covariation Scores The enamel proteome is functionally linked, in particular because all proteins are expressed only during amelogenesis (formation of enamel) during a very short phase of an individual's development . As a possible consequence of this, the evolution of their genes may occur in a nonindependent manner. We estimated the degree of evolutionary covariation of the set of 14 genes using Evolutionary Rate Covariation (ERC) analysis . ERC returns pairwise correlation coefficients of the branch-specific evolutionary rates of a set of genes . All ERC scores are based on comparisons between phylogenetic trees that were derived from a representative dataset of coding sequence alignments produced from whole-genome alignments of 120 mammalian species . Permutation testing indicated that all pairwise values between amelogenesis proteins are significantly elevated ( P -value < 0.0001). There is particularly elevated covariation (Fisher-transformed value > 3) in the evolutionary rates of all pairs between COL1A1 , COL1A2 , and COL2A1 , whose protein sequences are 64% to 72% identical. COL17A , the most divergent of all of the collagens and the only one known to have a function in enamel formation, displays lower covariation with the other collagens. AMBN , AMTN , ENAM , and ODAM are located on a syntenic block (e.g. Homo sapiens , chr 4; P. troglodytes , chr 4; Microcebus murinus , chr 26, Mus musculus , chr 5) in the SCPP (secretory calcium-binding phosphoprotein) gene cluster . Together with AMELX , they all evolved through duplications from the ancestral vertebrate SPARC gene and resemble each other in gene structure and chemical protein properties . The elevated and significant ERC values between them may reflect the evolutionary, functional, and spatial connection of these genes. One of the genes with the highest pairwise correlation values is MMP20 , a gene that encodes for an enzyme that cleaves the proteins AMBN, AMELX, AMELY, and ENAM during amelogenesis . All genes encoding those cleavage targets display elevated values of covariation of evolutionary rates. AMTN is another gene that displays a higher correlation in evolutionary rates with the aforementioned group, but little is known about its interactions and function. The most striking degree of covariation (Fisher-transformed value = 19.2) can be observed between AMELX (chromosome X) and AMELY (chromosome Y). For being encoded on the sex chromosomes they can be considered paralogs. It is known that both are expressed, if a Y chromosome is present, and AMELX and AMELY seem to fulfill the same function . In summary, many enamelome genes display significant degrees of covariation in their evolutionary rate, which suggests evolutionary nonindependence. Thus, the inference of a species tree from these nonindependent loci may result in a tree that reflects the shared evolutionary history of the loci rather than the actual evolution of the species .
The degree of sequence conservation and evolutionary rates were examined for a set of 14 proteins from 232 primate species and 1 nonprimate outgroup ( Tupaia ). The analysis was performed on a concatenation of multiple sequence alignments (MSAs) of each protein into one large multiprotein MSA. Each species was represented by the individual that had the most complete sequence data (i.e. fewest gaps or masked positions). Both Shannon entropy and Rate4Site (R4S) can be applied to measure the degree of protein sequence conservation. While Rate4Site accounts for the different likelihoods of substitution during sequence evolution, Shannon entropy values are agnostic to any evolutionary or physico-chemical constraints. Shannon entropy values and Rate4Site scores both demonstrate that sequence diversity and evolutionary rates vary across the length of each protein sequence . In particular, collagens (except some sites in COL17A1) evolve at a slower rate than noncollagen proteins . Rate4Site scores roughly correlate with Shannon entropy values ( , Pearson correlation ρ = 0.54, P -value < 2.2e-16). About 4% of all sites are residues with particularly high evolutionary rates (R4S score > 2) that also fall into the regions that could be experimentally recovered in ancient samples . This is particularly the case in ALB, AMELX, AMBN, and ENAM. In most other proteins, such as AHSG, AMTN, COL17A, MMP20, ODAM, or TUFT1, the regions of particularly high evolutionary rates correspond to peptides that have not yet been experimentally recovered. At the other extreme, some regions of high sequence conservation levels stand out. In ENAM, there is a stretch of 49 highly conserved amino acids (corresponding to the positions 191 to 239 in UniProt ID Q9NRM1) that carries 2 phosphorylation sites. The region falls into the 32 kilodalton (kDa) cleavage product of ENAM , which belongs to peptides that can be experimentally recovered in deep time . MMP20 also displays larger regions of highly conserved amino acids that fall into the experimentally recovered sequences. One of those regions (corresponding to UniProt ID O60882, positions 174 to 254) lies around the active center (position 227) and its surrounding inorganic ion binding regions; another one lies around positions 330 to 483, a region whose ends are connected via a disulfide-bridge. Other longer experimentally recovered regions of relatively highly conserved sequences belong to AMBN, COL1A1, COL1A2, COL17A1, and SERPINC1. To examine if the above described patterns also hold beyond primates, Rate4Site scores were calculated on a set of 22 species from different taxonomic groups across mammals ( online, for list of species see online). The general pattern of slower evolutionary rates in collagens is consistent across mammals, particularly for COL1A1, COL1A2, and COL2A1. The area of the 32 kDa fragment in ENAM is not as strongly conserved as within primates; whereas, the region around the active center in MMP20 shows a persistently low evolutionary rate. Across mammals as a whole, the N-terminus of AMELX displays a higher degree of conservation, as is the case for primates specifically. In contrast, the C-terminus of AMTN, and the N-terminus of COL1A1 appear to evolve at a higher rate in the mammal-wide data compared to the primates-only data.
The phylogenetic signal in each protein sequence dataset was assessed by measuring the Robinson–Foulds distance (RF-distance, topology only) between the tree resulting from that dataset and the reference tree, as well as manual inspection of differences in the topologies. There was no major difference in the phylogenetic trees created by maximum likelihood (ML) or Bayesian analysis ( online). The Bayesian analysis performed slightly better by creating more accurate trees (smaller RF-distances to reference tree) from the 5 (ML = 170, Bayesian = 153) and 10 (ML = 122, Bayesian = 117) protein concatenations; however, the ML approach produced a slightly more accurate tree for the 14 (ML = 108, Bayesian = 110) protein concatenation. Since the differences between the methods appeared to be minor, all following analyses were performed using the ML approach because it shows a higher computational efficiency ( online). In all trees, all taxa were placed correctly at least at the family level, with 2 exceptions: First, in the tree based on the 5 protein concatenation, Galagonidae and Lorisidae remain unresolved, meaning that species of these 2 families do not form 2 distinct clades. Second, while the general tendency is that the more proteins that are included in the concatenation, the more similar the tree is to the reference tree, there is 1 caveat for the 14 protein concatenation: the deepest relationship within Primates, namely the branching pattern between lorises and lemurs (Strepsirrhini), tarsiers (Tarsiiformes), and monkeys and apes (Simiiformes), is incorrectly resolved. Specifically, in the trees of the 14 protein concatenation (ML and Bayesian), Tarsiiformes form a clade with Strepsirrhini to the exclusion of Simiiformes with a bootstrap value of 90 and a posterior probability of 1; however, current molecular and morphological evidence collectively provides compelling support for Tarsiiformes + Simiiformes to the exclusion of Strepsirhini. In contrast, in the phylogenies from the 5 and 10 protein concatenations, Tarsiiformes and Simiiformes form a clade, in agreement with the reference tree ( online). In our case, the addition of 4 collagen genes to the dataset, resulting in the 14 protein concatenation, drove the misplacement of Tarsiiformes. We tested different combinations of collagens and noncollagen proteins of our dataset to see which gene products in particular are driving this misplacement ( online). If any of these individual collagens is combined with all 10 noncollagen proteins into an 11 protein concatenation, the noncollagen proteins drive the placement of tarsiers to the correct position, according to the species tree. However, if the 10 noncollagen proteins are combined with COL1A2 and COL1A1 or COL17A1, this is sufficient to override the signal in the noncollagen proteins and place Tarsiiformes with Strepsirrhini.
To date, there is only a limited amount of information on how enamel proteins degrade post mortem over large time scales. We created a simple model of peptide fragment degradation by inspecting publicly available experimental enamel proteomes, combined with newly sequenced enamel proteomes from this study. These experimentally recovered enamel proteome sequences were aligned to the MSAs of our predicted protein sequences (“BLOCK3” in online). Different stages of post mortem protein sequence fragmentation were then modeled by removing specific sites (i.e. columns) in the MSA of each protein. The older the modeled fragmentation stage, the more sites were removed. For the model, we assumed heterogeneous post mortem survival times across all sites of each protein for 2 reasons: first, because the enamelome is already enzymatically cleaved in vivo , and second because different peptides may have different physico-chemical properties that influence their chemical breakdown. To understand the approximate patterns of this heterogeneity, we assessed how often each site in a protein could be experimentally recovered from published data together with new data using the MSAs. To date, the amount of available ancient protein sequences is not sufficient to use statistical methods to model the process of fragmentation across millions of years. Instead, we followed the rationale of reducing the amount of sequence information similar to what we observed in sequences of a certain age range. These ages give rise to the eponymous fragmentation stages. The more coverage a single site has, the longer is its anticipated survival. Based on the modeled fragmentation stages, we created 4 concatenated MSAs with increasingly reduced sequence data and examined phylogenetic trees that were calculated from those MSAs in order to understand the standalone phylogenetic information of fragmented protein sequences. The protein concatenation corresponding to the fragmentation stage of “100 ka” had a total length of 3,884 amino acids (∼41% of the original MSA's length, see online). The phylogeny based on this data showed a RF-distance of 156 to the species tree , in contrast with the phylogeny based on the full-length 14 proteins (alignment length 9,557 amino acids), which showed a RF-distance to the species tree of 108. All placements at family level and mostly genus level are in accordance with the reference tree, except for Tarsiiformes being grouped with Strepsirrhini (for more details see online). This is in line with the previous observation that the inclusion of COL1A2 and COL1A1 or COL17A1 can produce this result, even if just fragments of these protein sequences are included. Most differences that explain the RF-distance of 156 stem from different placements of species within their genus. The phylogeny based on the fragmentation stage “1 to 2 Ma” (MSA length 1,139 aa, ∼12% of the original MSA's length) has a very similar distance to the species tree (158). Most nodes at family level are placed in accordance with all confidently resolved nodes of the reference tree, with some exceptions ( online). For instance, in Hominidae, contrasting the reference tree, Pan and Gorilla are sister taxa, with Homo as an outgroup. Tarsiiformes are placed as an outgroup to both Strepsirhini and Simiiformes (bootstrap 100), a placement that is rejected by current molecular and morphological evidence . The tree based on data of the fragmentation stage “5 Ma” (alignment length 593 amino acids, ∼6% of the original MSA's length) has an RF-distance to the species tree of 240. In catarrhines, all family level relationships still agree with the reference tree, but there are some inconsistencies within families compared to the reference tree ( online). In platyrrhines, correct resolution of nodes at family level is widely lost. The placement of nodes at family level in Lemuridae is in accordance with the species tree, except for the placement of Varecia and Daubentonia madagascariensis ( online). Tarsiiformes form a clade with Strepsirhini (bootstrap 93). At the fragmentation stage “10 Ma” (alignment length 98 amino acids, ∼1% of the original MSA's length), the phylogeny is largely unresolved, with an RF-distance to the reference tree of 420 and most bootstrap values far below 50. Only lorisiforms are correctly separated as their own taxon. The 4 tarsiiform species are monophyletic and placed with low confidence within Simiiformes.
Often, paleoproteomic studies will only aim to place a few closely related specimens at a time into a framework of mostly complete reference protein sequences. To simulate such a scenario, we created 4 cases in which protein sequence data from a group with fairly well-known taxonomic placement were fragmented and aligned to reference sequences that are at full-length. In the first case, sequence data of 2 Neanderthals (individuals Vindija 33.19 and Altai) and 1 Denisovan (Denisova3 individual) that were fragmented to the degradation stage “100 ka” were aligned to a reference MSA of 14 enamel-related proteins from Hominoidea. The phylogenetic placement is in accordance with the reference tree at genus level, but not at species level . The Neanderthal and Denisovan individuals place within the Homo sapiens clade with low branch support, instead of forming a sister clade as shown by large-scale genomic data . In the same tree, individuals of the 2 species with the youngest split, namely Pongo abelii and Pongo pygmaeus , do not form 2 distinct clades, nor do the individuals of Gorilla gorilla and Gorilla beringei , despite being based on full-length protein data. These results align with previous observations on the limitations of paleoproteomic data to resolve phylogenies in Hominidae at species-level resolution . In particular, if several individuals per clade are examined using such limited sequence data; the interspecific differences can fall within the range of intraspecific variation . Reasons for this low phylogenetic resolution between species of the same genus can be incomplete lineage sorting or the overall slow evolutionary rate of the proteins found in dental enamel. The example of simulated ancient chimpanzee data of a fragmentation stage of “5 Ma” produces a different result . While the phylogenetic relationships of the species within Pongo and Gorilla cannot be resolved, the 3 Pan troglodytes individuals are placed confidently in a clade that is a sister taxon to Pan paniscus (bootstrap 100). Divergence times have been estimated using MCMCtree for each node of a simplified version (1 individual per species) of the “Chimpanzee case” tree ( and and online). The confidence intervals for the estimates of the case study and the reference tree overlap at nearly all nodes. On average, divergence time estimates derived from the protein-based data of the “Chimpanzee case” are 21% younger than those of the genome-based reference. While this is only one case example, it shows that divergence time estimates with similar results to those derived from high quality genome data are possible. In the “Colobine case” , simulated ancient samples (fragmentation stage “5 Ma”) of Rhinopithecus roxellana , and Colobus guereza are placed correctly at species level. However, the simulated ancient sample of Trachypithecus geei is placed within its sister genus Semnopithecus . Slight modifications of the methodology can fix this misplacement. T. geei was placed within its correct genus, when mixture models were allowed ( online). It was also placed correctly when the topology of the reference data was constrained based on information from the DNA-based reference tree ( online). In the “Lemur case” , the simulated ancient samples (fragmentation stage “100 ka”) of Eulemur sanfordi and Cheirogaleus major were placed correctly at species level and Lepilemur ankaranensis at genus level.
To quantify the contribution of the variable sites in each MSA to the correct resolution of the according tree, we divided all concatenated MSAs into 2 MSAs, 1 consisting of variable sites, the other of conserved sites. To divide between variable and conserved, the MSA of each protein was normalized to a mean of 1 in their Shannon entropy values or Rate4Site scores. They were then divided into sites above this value, i.e. the “variable” sites, and below, i.e. the “conserved” sites ( online). These sites from all proteins were concatenated and used for phylogenetic analysis with ML. Phylogenies based only on variable sites identified by Rate4Site ( online, “R4S variable”) are just as similar to the species tree as in the case of phylogenies based on the full-length protein sequences ( online, both have a RF-distance of 108 to the reference tree). Similarly, when using Shannon entropy to define conserved and variable sites, phylogenies based on the variable sites ( online, “Shannon variable”) are more similar to the reference tree than those based on the more conserved sites (“Shannon conserved”). In general, all phylogenies based on variable sites that were identified using Rate4Site (“R4S variable”) are more similar to the reference tree than those based on variable sites that were identified using Shannon entropy (“Shannon variable”). Thus, the more variable sites contain most of the phylogenetic signal. In this case, to define the most variable sites, Rate4Site has been a better predictor of phylogenetically informative sites.
The enamel proteome is functionally linked, in particular because all proteins are expressed only during amelogenesis (formation of enamel) during a very short phase of an individual's development . As a possible consequence of this, the evolution of their genes may occur in a nonindependent manner. We estimated the degree of evolutionary covariation of the set of 14 genes using Evolutionary Rate Covariation (ERC) analysis . ERC returns pairwise correlation coefficients of the branch-specific evolutionary rates of a set of genes . All ERC scores are based on comparisons between phylogenetic trees that were derived from a representative dataset of coding sequence alignments produced from whole-genome alignments of 120 mammalian species . Permutation testing indicated that all pairwise values between amelogenesis proteins are significantly elevated ( P -value < 0.0001). There is particularly elevated covariation (Fisher-transformed value > 3) in the evolutionary rates of all pairs between COL1A1 , COL1A2 , and COL2A1 , whose protein sequences are 64% to 72% identical. COL17A , the most divergent of all of the collagens and the only one known to have a function in enamel formation, displays lower covariation with the other collagens. AMBN , AMTN , ENAM , and ODAM are located on a syntenic block (e.g. Homo sapiens , chr 4; P. troglodytes , chr 4; Microcebus murinus , chr 26, Mus musculus , chr 5) in the SCPP (secretory calcium-binding phosphoprotein) gene cluster . Together with AMELX , they all evolved through duplications from the ancestral vertebrate SPARC gene and resemble each other in gene structure and chemical protein properties . The elevated and significant ERC values between them may reflect the evolutionary, functional, and spatial connection of these genes. One of the genes with the highest pairwise correlation values is MMP20 , a gene that encodes for an enzyme that cleaves the proteins AMBN, AMELX, AMELY, and ENAM during amelogenesis . All genes encoding those cleavage targets display elevated values of covariation of evolutionary rates. AMTN is another gene that displays a higher correlation in evolutionary rates with the aforementioned group, but little is known about its interactions and function. The most striking degree of covariation (Fisher-transformed value = 19.2) can be observed between AMELX (chromosome X) and AMELY (chromosome Y). For being encoded on the sex chromosomes they can be considered paralogs. It is known that both are expressed, if a Y chromosome is present, and AMELX and AMELY seem to fulfill the same function . In summary, many enamelome genes display significant degrees of covariation in their evolutionary rate, which suggests evolutionary nonindependence. Thus, the inference of a species tree from these nonindependent loci may result in a tree that reflects the shared evolutionary history of the loci rather than the actual evolution of the species .
In this study, we estimated the degree of sequence conservation, evolutionary rate, and phylogenetic signal of protein sequences that are associated with the primate enamel proteome. Our analyses emphasized evaluating these metrics from a perspective of experimental feasibility, since ancient peptide data are highly fragmentary and diagenetically altered (e.g. by deamidation, ). The process of degradation was simulated for different stages of fragmentation, which were anticipated from experimental data. Given the limited amount of experimental data and the over-representation of samples younger than 2 Ma, it has not yet been possible to statistically assess the patterns of post mortem sequence degradation, but hopefully it will be in the future as more ancient enamel peptide sequences are published. However, patterns are already visible, e.g. the deep time sequence survival of N-terminal peptides of ENAM , and that of the N-terminal region of AMELX and its C-terminal proline rich region . When simulating fragmented data and subsequently performing phylogenetic inference, most families were in accordance with the reference tree up to a fragmentation stage similar to published samples of an age of 1 to 2 Ma from temperate-to-tropical regions. This does not exclude that sequences with a higher degree of fragmentation (stage “5 Ma”) could be placed correctly in a phylogeny that is based on unfragmented reference sequences, as the P. troglodytes sequences in our case study were rather highly fragmented (stage “5 Ma”) and still correctly placed. The same was true for equally fragmented sequences of colobine species. The effects of missing data on phylogenetic analysis have been explored before , but it would also be interesting to further study how to best address missing data in the particular case of ancient enamelomes. Comparing the case studies with only a few fragmented sequences to the phylogenies based on exclusively fragmented data, we could observe that, in phylogenetic analysis, more fragmentation can be tolerated if it affects only some sequences of the MSA. Thus, the conclusions drawn from the phylogenies based on exclusively fragmented data can be considered a conservative consideration, which draws a baseline for expectations. Understanding the use of many fragmentary sequences at a time can also be relevant for future studies, when more paleoproteomic data are available and compared to each other. Rate4Site identified well the sites that are most phylogenetically informative ( online). This falls within the expectation, since Rate4Site accounts for amino acid replacement models and phylogenetic relationships between the input sequences. However, informative sites do not always fall within those regions that could be experimentally recovered, e.g. in AHSG, AMTN, COL17A, MMP20, ODAM, or TUFT1 . It may be possible to adapt protocols for peptide isolation from tooth enamel in order to maximize the yield of phylogenetically informative sequences. Some progress has been achieved recently by fractionating the sample in order to recover more fragments of different hydrophobicity . Identifying variable sites in collagens may also be of interest for optimizing protocols for the application of ZooMS . The general pattern of conservation of individual sites can also be observed across mammals ( online). Some cases distinguish primates from the general trend in mammals, e.g. the 32 kDa fragment of ENAM appears particularly conserved in primates. In fact, in this region, signals of positive selection have been reported in primates . This indicates that the degree of sequence conservation might differ across clades. Evolution of a set of proteins from a specialized tissue may be tightly linked due to the constraints of morphology and function of this tissue. Our example of tarsiers underlines why working with such a small tissue-specific set of biological sequences should be accompanied by morphometric and histological expertise. For example, compared to Simiiformes, Tarsiiformes and Strepsirrhini share the traits of thinner tooth enamel , and similar enamel microstructure . Both may be reflected in a similar genetic basis, e.g. as a conserved ancestral trait or as a result of convergent evolution. Beyond the morpho-functional constraints, the relationships between such a small set of genes can be further entangled, as this is the case for AMBN , AMTN , ENAM , and ODAM , which are located in close proximity to each other on the same chromosome in most mammals (e.g. Homo sapiens , chr 4). This has also been reflected in significantly higher ERC values in our analysis and partly observed in another study that was able to associate evolutionary rates of ENAM and ODAM to enamel thickness . A third aspect of covariation and possible codependence of this set of typically studied genes is high sequence similarity between some of them. For instance, all collagens in this study share 38% to 72% sequence identity among each other in humans (aligning UniProt entries P02452, P08123, P02458, and Q9UMD9). We did not have sufficient genomic data to include the Y-chromosomal AMELX paralog, AMELY , into our analyses based on predicted protein sequences. It is known to share around 88.5% sequence similarity with AMELX in humans (aligning UniProt entries Q99217-3 and Q99218-2) and it showed by far the highest degree of covariation in the ERC analysis. In other mammals, signs of gene conversion between AMELX and AMELY have been reported, indicating that these 2 genes and their protein sequences are not acting as independent loci . The dependencies that exist within this small proteome challenge the practice of concatenating them into a single, long MSA to address phylogenetic questions, because an overrepresented set of dependent loci might skew the outcome toward their shared evolutionary history. Gene trees can differ from species trees for various reasons : Especially in cases of deep coalescence, i.e. when the common ancestry of a set of gene copies from different species extends further back than the speciation events, the lineage sorting of the genes does not necessarily agree with the splits between species. Also gene duplication and loss events can lead to discordance between species tree and gene tree because (sometimes unknowingly) the genes considered are in reality paralogs. Thus, the sampling of a reasonably high number of unlinked loci can help to mitigate the impact of discordant gene trees by reducing their stochastic impact . Differences between gene trees and the species tree may be a possible explanation for the case of tarsiers, which were placed in profoundly different locations within the phylogenetic tree depending on whether or not collagens were included in the dataset ( ; online). However, we cannot rule out other causes, such as model misspecification ( online), i.e. the collagen sequences may have evolved in a way that cannot be appropriately modeled by the phylogenetic model used in our analysis . This case example highlights a potential pitfall of paleoproteomics when used for phylogenetic analysis. The specimen of interest might be placed with a reasonably high confidence in a phylogeny based on concatenated protein sequences, as for example tarsiers were placed with Strepsirrhini at the “100 ka” fragmentation stage. Still, as this example demonstrates, such a placement could be in conflict with genomic evidence, and yet there may be no genomic data for the ancient sample that can be used to test the accuracy of the proteomic data. The difference between single-gene trees and species trees in the context of the enamel proteome has been demonstrated and discussed in previous publications , in which phylogenetic inference based on concatenated MSAs delivered results that were more consistent with the recognized species tree for the verifiable extant reference taxa. A common approach for deriving a species tree from a set of gene trees is the multispecies coalescent . A multispecies coalescent approach was compared to several Bayesian and maximum likelihood tools in the study of ancient proteins from Paranthropus robustus , where the results did not differ significantly from the other approaches . Even with optimal phylogenetic tools, it still condenses to making an adequate choice of proteins to be considered (e.g. for studying ancient tarsiers it may be advisable to omit COL1A1). Yet, omission of sequences is costly and needs to be well-justified, when sequence information is scarce. Altogether, our results provide several lessons for future paleoproteomic studies, in particular on dental enamel: Generally, the genetic distinction of species of the same genus is not possible with the sequences of the enamelome, even with complete sequence data. Consequently, ancient enamelome sequence studies are most likely inadequate to resolve research questions of the phylogenetic relationship between species of the same genus. An exception to this rule of thumb may be justified, if the divergence between the species is relatively deep, such as this was the case in our study of the relationship between chimpanzees and bonobos. We observed that a small set of loci can have the potential to affect the position of deep splits in the phylogeny and produce wrong results that nevertheless have high statistical confidence (e.g. high bootstrap values in the wrong placement of tarsiers with strepsirrhines). For any specimen that is of interest for paleoproteomic study, we advise to gather protein sequences of the closest related extant species, prior to sampling it. A phylogenetic analysis of these species may reveal the expected phylogenetic resolution of the enamelome in this particular clade and if the protein sequences of some loci can cause unexpected results. Lastly, we could observe that there is a degree of sequence fragmentation beyond which meaningful phylogenetic inference is impossible (between 1% and 6% of the whole enamelome, between fragmentation stages “5 Ma” and “10 Ma”). It is difficult to anticipate the expected yield of a sample solely based on its estimated age. In particular, temperature is a main driver for protein degradation, with lower temperatures being much more favorable for slowing down this process . An approach to estimate the expected protein preservation in a specimen of interest is to conduct pilot studies on more abundant specimens from other mammalian species that were ideally found in a comparable paleontological context at the same locality . Our results and conclusions help evaluate whether a specimen is an adequate candidate for a paleoproteomics-based phylogenetic study, providing guidance on the expected outcome. More publicly available experimental paleoproteomic data will hopefully contribute to refining this picture of the potential of paleoproteomics for phylogenetic applications.
Genes of Interest The proteins analyzed are the products the genes AHSG, ALB, AMBN, AMTN, AMELX, ENAM, MMP20, ODAM, SERPINC1, TUFT1, COL1A1, COL1A2, COL17A1, and COL2A1 . The selection of these proteins was mainly driven by the availability of experimental proteomic and genomic data. Other proteins associated with tooth enamel, such as KLK4, may play a key role in enamel formation , but barely leave behind any peptides that can be experimentally recovered in paleoproteomic studies . Similarly, AMELY is considered enamel-specific, but since it is encoded on the difficult-to-sequence Y chromosome, there is little genomic reference data available. Although their gene products are not canonically considered to be part of tooth enamel, COL1A1 , COL1A2 , and COL2A1 have been included in this study, because they are occasionally co-extracted from dentin fragments still attached to ancient enamel samples processed for paleoproteomic analysis , or because they are recovered in experiments targeting bone or dentin on younger fossils . Lastly, these collagens are of great importance for the peptide mass fingerprinting method conventionally called “zooarchaeology by mass spectrometry” or “ZooMS” for short . Dataset The primate DNA sequences stem from 718 Variant Calling Format files (VCFs) from whole-genome sequence data, which were analyzed along with publicly available DNA sequences of the outgroup taxon Tupaia belangeri chinensis . In total, this represented 719 individuals: 135 great apes mapped to the human assembly hg19; 561 individuals spanning 16 primate families (including more great apes) mapped against 31 primate genomes as listed in the online ; 19 modern humans from the Simons Genome Diversity Project and 3 extinct hominins , all which were mapped to hg19, and publicly available protein sequences of Tupaia as the outgroup . Sequences of Nomascus leucogenys and Pongo tapanuliensis were subsequently excluded due to low quality. Sequences of Neanderthal and Denisovan were only included in one case study (“Neanderthal case”). Amino Acid Sequence Translation and MSA For all 14 genes under study, we restricted our analyses to the canonical isoforms from the human hg38 annotation (Ensembl) ( online) to ensure comparable sequences across species. The VCFs were used to integrate genomic variants in the coding sequence (CDS) of interest using samtools and bcftools ( online). For each individual, the resulting CDS were translated to proteins through in-house python scripts based on the standard genetic code. Low-quality regions at the DNA level were represented as “N,” and affected codons masked as an “X” in the amino acid sequence. The resulting translations were grouped by protein and aligned with MAFFT v7.520 . Alignments were trimmed using trimal 1.2rev59 (for parameters see online). The resulting alignment files were manually explored and any spurious variation (in most cases due to frameshifts caused by indels) was removed or masked (for details see online). In addition to their original annotation, the hg38 annotation was projected onto the 31 reference genomes of the 561 primates from . Using the liftOver tool with default parameters ( online), we obtained GTF-files of the projected CDS coordinates for each of the 31 reference genomes . About half of the original annotations were previously published and have been achieved in various ways (see accessions in ). The other half stems from , and has been annotated with a combination of de-novo and homology-based strategies. In some cases, the predicted protein sequence from the original annotation resulted in a higher quality protein model than LiftOver-based annotations (less premature truncation and less spurious variation), but in other cases the opposite was true. The protein model that yielded the fewest number of gaps was kept for further analysis. Different sets of MSAs were concatenated, comprising groups of 5, 10, and 14 proteins. The 5 protein concatenation consists of AMBN, AMELX, AMTN, ENAM, and MMP20, which are proteins that are an integral part of the enamel structure and have been consistently identified from fossil teeth in previous studies . The 10 protein concatenation represents a larger, noncollagenous enamel proteome by adding AHSG, ALB, ODAM, SERPINC1, and TUFT1. The 14 protein concatenation also included 4 collagens: COL17A1, COL1A1, COL1A2, and COL2A1. For subsequent phylogenetic analyses, the signal peptide sequence was removed from every protein sequence, given that it is usually not recovered in paleoproteomic experiments . If not otherwise stated, in the following, “MSA” always refers to a concatenation of different sets of proteins of interest. Variable and parsimony-informative sites were assessed using MEGA11 (Molecular Evolutionary Genetics Analysis v. 11) . Assessment of Protein Sequence Conservation Shannon entropy is a measure that can be applied to MSAs to quantify the degree of variability at each given homologous site. It is agnostic to physico-chemical similarities and substitution rates between amino acids. It was calculated with a moving average of 20 ( https://gist.github.com/jrjhealey/130d4efc6260dd76821edc8a41d45b6a ) on the concatenated MSA of 14 proteins with 1 individual per species. Rate4Site is a tool used to calculate conservation scores in homologous amino acid sites. For the same MSA, Rate4Site scores were calculated using default options and setting the concatenated Tupaia belangeri chinensis proteins (outgroup) as reference sequence. Gaps in Tupaia proteins were filled with the consensus sequence, since the Rate4Site tool will omit sites with an incomplete reference. A moving average of 20 was used to calculate all Rate4Site scores. Alternatively, for the estimation of evolutionary rates in these proteins across mammals, Rate4Site scores were calculated on a concatenated MSA of 22 species (for list of species and sequence IDs see online). The protein sequence data were downloaded from UniParc using the ProteoParc v1.0 tool ( https://github.com/guillecarrillo/proteoparc ). We selected a set of species that had a mostly complete sequence for each gene and that represented most clades across the group of mammals. Rate4Site scores were calculated using default parameters, setting the reference sequence to Homo sapiens . Phylogenetic Analysis For any further downstream analysis, the MSA of all 719 individuals was downsampled to 1 individual per species (with the most complete sequence), yielding a total of 233 terminal taxa. All phylogenetic analyses were performed using ML with IQ-TREE v.1.6.12 including the Shimodaira Hasegawa approximate likelihood-ratio test (SH-alrt), for 5,000 iterations with ultrafast bootstrap approximation. The evolutionary model of each of the individual proteins was obtained through ModelFinder . For a detailed description of the code and parameters see online. In addition, for the complete protein sequence (except the signal peptide) of all 3 concatenations (5, 10, and 14 proteins), phylogenetic trees were also calculated using Bayesian analysis performed using MrBayes v.3.2.7a . Each Bayesian analysis was run for 3 million generations, with a burn-in of 25%. For all trees, the distance to the reference species tree was assessed via RF-distance using the R package “phangorn” . Next, we calculated phylogenetic trees using the above-mentioned parameters for different subsets of amino acid positions. The rationale for building these subsets is described in the following sections. Ancient Sequence Reconstruction of Enamel Peptides From Fossil Specimens Ancient peptide sequences were isolated from the tooth enamel of fossil equids and deinotheriid proboscideans of different ages. The former include specimens of Equus cf. ferus (IPS87498, 136 mg enamel powder, and IPS87522, 820 mg) from the Late Pleistocene of La Carihuela (probably <100 ka), Equus cf. altidens (IPS137786, 169 mg) from the Early Pleistocene of Vallparadís layer EVT7 (0.9 to 0.8 Ma) , and Hippotherium cf. primigenium (IPS98842, 50 mg) from the Late Miocene of Can Llobateres 1 (9.8 Ma) . Considering that a detailed study of these fossil samples is needed, at the present time, we use the open nomenclature for these specimens. The deinotheriid specimens correspond to Deinotherium giganteum (IPS28029, 80 mg) from Can Llobateres (see above) and Deinotherium levius (IPS121827, 130 mg) from the Middle/Late Miocene of Abocador de Can Mata locality ACM/C8-A3 (11.6 Ma) . All the fossil specimens are housed in the Institut Català de Paleontologia Miquel Crusafont, Sabadell, Spain. Enamel samples were precisely extracted using a rotary tool with a diamond disc and a slow-speed drill (Dremel®). Traces of dentin adhering to the enamel were removed with a scalpel and fiberglass pencil. Ancient peptide sequences were isolated from the enamel pieces in a dedicated clean room following published protocols , using trifluoroacetic acid as the demineralizing agent. The solubilized peptides were immobilized on a C18 membrane STAGE tip and washed with 5% v/v formic acid. Elution followed with a 5% v/v formic acid 50% v/v acetonitrile solution. The eluted peptides were subjected to reverse phase nanoliquid chromatography coupled with tandem mass spectrometry. Samples were analyzed using an Orbitrap Eclipse mass spectrometer (Thermo Fisher Scientific, San Jose, USA) coupled to an EASY-nLC 1200 (Thermo Fisher Scientific, San Jose, USA). More details on the run on this instrument are described in online. As negative controls, extraction blanks were processed together with the ancient samples during peptide extraction. In addition, injection blanks were injected into the mass spectrometer, between the single injections of the samples and extraction blanks. The ancient peptides were identified in iterative reference database searches using MaxQuant and MaxNovo. The databases were built from public repositories using the ProteoParc v1.0 tool. A list of the proteins in the databases and database search parameters can be found in online ( online). The resulting ancient reconstructed sequences were used to inform the creation of subsets of the MSA. Reducing Alignments to Simulate Ancient Peptide Sequences Ancient sequence reconstructions , from tooth enamel of various mammals were downloaded from publicly available data and sequenced at the Institute for Evolutionary Biology and the Centre for Genomic Regulation in Barcelona (see section above). The ancient sequences were aligned using MAFFT v7.520 to the corresponding human reference protein from UniProt . The alignments were manually curated because the highly fragmentary nature of the sequenced ancient peptides can cause misalignment at nonhomologous positions. These curated alignments were then added to the predicted protein sequences of this study, using MAFFT v7.520 with the –add and –keeplength option. Inspecting the ancient sequences of different ages, we defined a set of sites which needed to be removed in order to simulate data loss due to degradation. Reducing the MSA to those positions was done using an in-house python script. The older the modeled fragmentation stage, the more sites were removed. A list of all positional information, in relation to the single gene MSAs before concatenation, can be found in the dataset published alongside this article . Note that the sample ages that describe the different fragmentation stages (“100 ka,” “1 to 2 Ma,” “5 Ma,” and “10 Ma”) are based on the actual age of each sample and that most of them stem from sites with annual average temperatures higher than 10 °C. The fragmentation stage in samples of similar age might be different depending on its environment. For the stage “100 ka,” a rather large coverage of collagens is anticipated because, at this fragmentation stage, additional sampling of dentin or bone may be possible. For the stage “5 Ma,” experimental data are not available, so that this stage is an intermediate between “1 to 2 Ma” and “10 Ma.” We could not find any public peptides that stem from TUFT1, nor could we confidently sequence them. Phylogenetic analysis with ML was performed on the 4 subset MSAs, and the resulting topologies were compared against the reference tree with RF-distance. Case Studies of Simulated Ancient Samples With the aim of simulating typical phylogenetic inference with paleoproteomic data, several phylogenetic analyses were performed as case studies (“Neanderthal case,” “Chimpanzee case,” “Colobine case,” and “Lemur case”). In these 4 scenarios, the “100 ka” fragmentation pattern was used for the “Neanderthal case” and the “Lemur case,” and the “5 Ma” pattern for the “Chimpanzee case” and the “Colobine case,” aiming to mimic the fragmentary pattern that could be recovered from actual fossils after their split from their most recent extant sister group. The objective of these 2 analyses was to observe if the fragmented data still allowed the individuals to be positioned correctly in the phylogenetic tree. The reference data for the “Neanderthal case” consisted of a concatenation of the set of 14 proteins (full-length) of 5 individuals from each of the hominid species, including 5 Homo sapiens individuals, and 1 Hylobates lar individual as an outgroup. The 3 Neanderthal/Denisovan sequences with the “100 ka” fragmentation pattern were added to this scaffold. The “Chimpanzee case” also comprised 14 concatenated proteins of 5 individuals per hominid species, including 5 Homo sapiens , but excluding P. troglodytes , and using Hylobates lar as an outgroup. Three simulated P. troglodytes sequences with the fragmentation pattern of “5 Ma” were then added to this scaffold. The reference data for the “Colobine case” consisted of 1 individual of all available species of the subfamily Colobinae. Fragmented sequence data (stage “5 Ma”) of 3 individuals from different colobine species was added to this reference. The reference data for the “Lemur case” consisted of 1 individual for all available species in Lemuroidea. Fragmented sequence data (stage “100 ka”) of 3 individuals from different lemur species was added to this reference. ML phylogenetic analysis was performed on all of these case studies. For the “Colobine case”, we also tested approaches with mixture models and fixed topologies. For more details, see the online. Phylogenies by Amino Acid Conservation For subsequent analysis, the MSAs were separated into sections of higher or lower conservation. We used 2 methods (Rate4Site and Shannon entropy) to measure variability of each site in the MSA. The Rate4Site score and Shannon entropy values were calculated for each protein and normalized to a mean of 1. The MSAs of each protein were then subset by values equal or higher than 1 and lower than 1 and concatenated into a long MSA. For the 2 metrics, this resulted in 4 different types of concatenated MSAs “Shannon variable,” “Shannon conserved,” “Rate4Site variable,” and “Rate4Site conserved.” This, applied to all 3 concatenations (5, 10, and 14 proteins), resulted in a total of 12 MSAs. Phylogenetic analysis with ML was performed on each of them. The resulting tree topologies were compared to the trees resulting from the full-length proteins and to the reference tree using RF-distance. Evolutionary Rate Covariation Scores The degree of evolutionary covariation of the set of 14 genes was estimated using Evolutionary Rate Covariation (ERC) analysis . The ERC for 19,137 orthologous genes from 120 mammalian species was calculated using the R code available at https://github.com/nclark-lab/erc . The covariation in relative evolutionary rates for each gene pair was calculated using only the branches that are shared between the 2 genes. The raw correlations were then Fisher-transformed, normalizing for the number of branches that contributed to the correlation. In R v.4.3.1, significance was estimated via permutation analysis using the mean as test statistic and 10,000 permutations. The results were plotted in R using the package “ggplot2” .
The proteins analyzed are the products the genes AHSG, ALB, AMBN, AMTN, AMELX, ENAM, MMP20, ODAM, SERPINC1, TUFT1, COL1A1, COL1A2, COL17A1, and COL2A1 . The selection of these proteins was mainly driven by the availability of experimental proteomic and genomic data. Other proteins associated with tooth enamel, such as KLK4, may play a key role in enamel formation , but barely leave behind any peptides that can be experimentally recovered in paleoproteomic studies . Similarly, AMELY is considered enamel-specific, but since it is encoded on the difficult-to-sequence Y chromosome, there is little genomic reference data available. Although their gene products are not canonically considered to be part of tooth enamel, COL1A1 , COL1A2 , and COL2A1 have been included in this study, because they are occasionally co-extracted from dentin fragments still attached to ancient enamel samples processed for paleoproteomic analysis , or because they are recovered in experiments targeting bone or dentin on younger fossils . Lastly, these collagens are of great importance for the peptide mass fingerprinting method conventionally called “zooarchaeology by mass spectrometry” or “ZooMS” for short .
The primate DNA sequences stem from 718 Variant Calling Format files (VCFs) from whole-genome sequence data, which were analyzed along with publicly available DNA sequences of the outgroup taxon Tupaia belangeri chinensis . In total, this represented 719 individuals: 135 great apes mapped to the human assembly hg19; 561 individuals spanning 16 primate families (including more great apes) mapped against 31 primate genomes as listed in the online ; 19 modern humans from the Simons Genome Diversity Project and 3 extinct hominins , all which were mapped to hg19, and publicly available protein sequences of Tupaia as the outgroup . Sequences of Nomascus leucogenys and Pongo tapanuliensis were subsequently excluded due to low quality. Sequences of Neanderthal and Denisovan were only included in one case study (“Neanderthal case”).
For all 14 genes under study, we restricted our analyses to the canonical isoforms from the human hg38 annotation (Ensembl) ( online) to ensure comparable sequences across species. The VCFs were used to integrate genomic variants in the coding sequence (CDS) of interest using samtools and bcftools ( online). For each individual, the resulting CDS were translated to proteins through in-house python scripts based on the standard genetic code. Low-quality regions at the DNA level were represented as “N,” and affected codons masked as an “X” in the amino acid sequence. The resulting translations were grouped by protein and aligned with MAFFT v7.520 . Alignments were trimmed using trimal 1.2rev59 (for parameters see online). The resulting alignment files were manually explored and any spurious variation (in most cases due to frameshifts caused by indels) was removed or masked (for details see online). In addition to their original annotation, the hg38 annotation was projected onto the 31 reference genomes of the 561 primates from . Using the liftOver tool with default parameters ( online), we obtained GTF-files of the projected CDS coordinates for each of the 31 reference genomes . About half of the original annotations were previously published and have been achieved in various ways (see accessions in ). The other half stems from , and has been annotated with a combination of de-novo and homology-based strategies. In some cases, the predicted protein sequence from the original annotation resulted in a higher quality protein model than LiftOver-based annotations (less premature truncation and less spurious variation), but in other cases the opposite was true. The protein model that yielded the fewest number of gaps was kept for further analysis. Different sets of MSAs were concatenated, comprising groups of 5, 10, and 14 proteins. The 5 protein concatenation consists of AMBN, AMELX, AMTN, ENAM, and MMP20, which are proteins that are an integral part of the enamel structure and have been consistently identified from fossil teeth in previous studies . The 10 protein concatenation represents a larger, noncollagenous enamel proteome by adding AHSG, ALB, ODAM, SERPINC1, and TUFT1. The 14 protein concatenation also included 4 collagens: COL17A1, COL1A1, COL1A2, and COL2A1. For subsequent phylogenetic analyses, the signal peptide sequence was removed from every protein sequence, given that it is usually not recovered in paleoproteomic experiments . If not otherwise stated, in the following, “MSA” always refers to a concatenation of different sets of proteins of interest. Variable and parsimony-informative sites were assessed using MEGA11 (Molecular Evolutionary Genetics Analysis v. 11) .
Shannon entropy is a measure that can be applied to MSAs to quantify the degree of variability at each given homologous site. It is agnostic to physico-chemical similarities and substitution rates between amino acids. It was calculated with a moving average of 20 ( https://gist.github.com/jrjhealey/130d4efc6260dd76821edc8a41d45b6a ) on the concatenated MSA of 14 proteins with 1 individual per species. Rate4Site is a tool used to calculate conservation scores in homologous amino acid sites. For the same MSA, Rate4Site scores were calculated using default options and setting the concatenated Tupaia belangeri chinensis proteins (outgroup) as reference sequence. Gaps in Tupaia proteins were filled with the consensus sequence, since the Rate4Site tool will omit sites with an incomplete reference. A moving average of 20 was used to calculate all Rate4Site scores. Alternatively, for the estimation of evolutionary rates in these proteins across mammals, Rate4Site scores were calculated on a concatenated MSA of 22 species (for list of species and sequence IDs see online). The protein sequence data were downloaded from UniParc using the ProteoParc v1.0 tool ( https://github.com/guillecarrillo/proteoparc ). We selected a set of species that had a mostly complete sequence for each gene and that represented most clades across the group of mammals. Rate4Site scores were calculated using default parameters, setting the reference sequence to Homo sapiens .
For any further downstream analysis, the MSA of all 719 individuals was downsampled to 1 individual per species (with the most complete sequence), yielding a total of 233 terminal taxa. All phylogenetic analyses were performed using ML with IQ-TREE v.1.6.12 including the Shimodaira Hasegawa approximate likelihood-ratio test (SH-alrt), for 5,000 iterations with ultrafast bootstrap approximation. The evolutionary model of each of the individual proteins was obtained through ModelFinder . For a detailed description of the code and parameters see online. In addition, for the complete protein sequence (except the signal peptide) of all 3 concatenations (5, 10, and 14 proteins), phylogenetic trees were also calculated using Bayesian analysis performed using MrBayes v.3.2.7a . Each Bayesian analysis was run for 3 million generations, with a burn-in of 25%. For all trees, the distance to the reference species tree was assessed via RF-distance using the R package “phangorn” . Next, we calculated phylogenetic trees using the above-mentioned parameters for different subsets of amino acid positions. The rationale for building these subsets is described in the following sections.
Ancient peptide sequences were isolated from the tooth enamel of fossil equids and deinotheriid proboscideans of different ages. The former include specimens of Equus cf. ferus (IPS87498, 136 mg enamel powder, and IPS87522, 820 mg) from the Late Pleistocene of La Carihuela (probably <100 ka), Equus cf. altidens (IPS137786, 169 mg) from the Early Pleistocene of Vallparadís layer EVT7 (0.9 to 0.8 Ma) , and Hippotherium cf. primigenium (IPS98842, 50 mg) from the Late Miocene of Can Llobateres 1 (9.8 Ma) . Considering that a detailed study of these fossil samples is needed, at the present time, we use the open nomenclature for these specimens. The deinotheriid specimens correspond to Deinotherium giganteum (IPS28029, 80 mg) from Can Llobateres (see above) and Deinotherium levius (IPS121827, 130 mg) from the Middle/Late Miocene of Abocador de Can Mata locality ACM/C8-A3 (11.6 Ma) . All the fossil specimens are housed in the Institut Català de Paleontologia Miquel Crusafont, Sabadell, Spain. Enamel samples were precisely extracted using a rotary tool with a diamond disc and a slow-speed drill (Dremel®). Traces of dentin adhering to the enamel were removed with a scalpel and fiberglass pencil. Ancient peptide sequences were isolated from the enamel pieces in a dedicated clean room following published protocols , using trifluoroacetic acid as the demineralizing agent. The solubilized peptides were immobilized on a C18 membrane STAGE tip and washed with 5% v/v formic acid. Elution followed with a 5% v/v formic acid 50% v/v acetonitrile solution. The eluted peptides were subjected to reverse phase nanoliquid chromatography coupled with tandem mass spectrometry. Samples were analyzed using an Orbitrap Eclipse mass spectrometer (Thermo Fisher Scientific, San Jose, USA) coupled to an EASY-nLC 1200 (Thermo Fisher Scientific, San Jose, USA). More details on the run on this instrument are described in online. As negative controls, extraction blanks were processed together with the ancient samples during peptide extraction. In addition, injection blanks were injected into the mass spectrometer, between the single injections of the samples and extraction blanks. The ancient peptides were identified in iterative reference database searches using MaxQuant and MaxNovo. The databases were built from public repositories using the ProteoParc v1.0 tool. A list of the proteins in the databases and database search parameters can be found in online ( online). The resulting ancient reconstructed sequences were used to inform the creation of subsets of the MSA.
Ancient sequence reconstructions , from tooth enamel of various mammals were downloaded from publicly available data and sequenced at the Institute for Evolutionary Biology and the Centre for Genomic Regulation in Barcelona (see section above). The ancient sequences were aligned using MAFFT v7.520 to the corresponding human reference protein from UniProt . The alignments were manually curated because the highly fragmentary nature of the sequenced ancient peptides can cause misalignment at nonhomologous positions. These curated alignments were then added to the predicted protein sequences of this study, using MAFFT v7.520 with the –add and –keeplength option. Inspecting the ancient sequences of different ages, we defined a set of sites which needed to be removed in order to simulate data loss due to degradation. Reducing the MSA to those positions was done using an in-house python script. The older the modeled fragmentation stage, the more sites were removed. A list of all positional information, in relation to the single gene MSAs before concatenation, can be found in the dataset published alongside this article . Note that the sample ages that describe the different fragmentation stages (“100 ka,” “1 to 2 Ma,” “5 Ma,” and “10 Ma”) are based on the actual age of each sample and that most of them stem from sites with annual average temperatures higher than 10 °C. The fragmentation stage in samples of similar age might be different depending on its environment. For the stage “100 ka,” a rather large coverage of collagens is anticipated because, at this fragmentation stage, additional sampling of dentin or bone may be possible. For the stage “5 Ma,” experimental data are not available, so that this stage is an intermediate between “1 to 2 Ma” and “10 Ma.” We could not find any public peptides that stem from TUFT1, nor could we confidently sequence them. Phylogenetic analysis with ML was performed on the 4 subset MSAs, and the resulting topologies were compared against the reference tree with RF-distance.
With the aim of simulating typical phylogenetic inference with paleoproteomic data, several phylogenetic analyses were performed as case studies (“Neanderthal case,” “Chimpanzee case,” “Colobine case,” and “Lemur case”). In these 4 scenarios, the “100 ka” fragmentation pattern was used for the “Neanderthal case” and the “Lemur case,” and the “5 Ma” pattern for the “Chimpanzee case” and the “Colobine case,” aiming to mimic the fragmentary pattern that could be recovered from actual fossils after their split from their most recent extant sister group. The objective of these 2 analyses was to observe if the fragmented data still allowed the individuals to be positioned correctly in the phylogenetic tree. The reference data for the “Neanderthal case” consisted of a concatenation of the set of 14 proteins (full-length) of 5 individuals from each of the hominid species, including 5 Homo sapiens individuals, and 1 Hylobates lar individual as an outgroup. The 3 Neanderthal/Denisovan sequences with the “100 ka” fragmentation pattern were added to this scaffold. The “Chimpanzee case” also comprised 14 concatenated proteins of 5 individuals per hominid species, including 5 Homo sapiens , but excluding P. troglodytes , and using Hylobates lar as an outgroup. Three simulated P. troglodytes sequences with the fragmentation pattern of “5 Ma” were then added to this scaffold. The reference data for the “Colobine case” consisted of 1 individual of all available species of the subfamily Colobinae. Fragmented sequence data (stage “5 Ma”) of 3 individuals from different colobine species was added to this reference. The reference data for the “Lemur case” consisted of 1 individual for all available species in Lemuroidea. Fragmented sequence data (stage “100 ka”) of 3 individuals from different lemur species was added to this reference. ML phylogenetic analysis was performed on all of these case studies. For the “Colobine case”, we also tested approaches with mixture models and fixed topologies. For more details, see the online.
For subsequent analysis, the MSAs were separated into sections of higher or lower conservation. We used 2 methods (Rate4Site and Shannon entropy) to measure variability of each site in the MSA. The Rate4Site score and Shannon entropy values were calculated for each protein and normalized to a mean of 1. The MSAs of each protein were then subset by values equal or higher than 1 and lower than 1 and concatenated into a long MSA. For the 2 metrics, this resulted in 4 different types of concatenated MSAs “Shannon variable,” “Shannon conserved,” “Rate4Site variable,” and “Rate4Site conserved.” This, applied to all 3 concatenations (5, 10, and 14 proteins), resulted in a total of 12 MSAs. Phylogenetic analysis with ML was performed on each of them. The resulting tree topologies were compared to the trees resulting from the full-length proteins and to the reference tree using RF-distance.
The degree of evolutionary covariation of the set of 14 genes was estimated using Evolutionary Rate Covariation (ERC) analysis . The ERC for 19,137 orthologous genes from 120 mammalian species was calculated using the R code available at https://github.com/nclark-lab/erc . The covariation in relative evolutionary rates for each gene pair was calculated using only the branches that are shared between the 2 genes. The raw correlations were then Fisher-transformed, normalizing for the number of branches that contributed to the correlation. In R v.4.3.1, significance was estimated via permutation analysis using the mean as test statistic and 10,000 permutations. The results were plotted in R using the package “ggplot2” .
evaf007_Supplementary_Data
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ASH Research Collaborative: a real-world data infrastructure to support real-world evidence development and learning healthcare systems in hematology | 10f3eae5-9b1d-42ed-883b-7002676bbf84 | 9153041 | Internal Medicine[mh] | The cost and time to generate evidence in hematology represent barriers to progress in research and transformation of clinical practice. However, digitalization of health care data and the availability of clinical, administrative, laboratory, and patient-reported information derived from routine clinical care represent opportunities to accelerate evidence generation. These opportunities are supported by recent legislation, including the 21st Century Cures Act and the reauthorization of the Prescription Drug User Fee Act (PDUFA VI), that have encouraged trial modernization and the evaluation of data from sources outside of traditional clinical trials to support regulatory decision making. This report describes the ASH Research Collaborative and its primary components, the Data Hub and the Sickle Cell Disease Clinical Trials Network (SCD CTN). The development and implementation of the initiative’s methods for data collection and tools for users of the data are reviewed, and initial use cases for the generation of real-world evidence (RWE) and the improvement of clinical care are discussed. The report concludes with directions for the future evolution of the ASH Research Collaborative.
The ASH Research Collaborative was founded as a nonprofit organization by the American Society of Hematology in 2018, to improve the lives of people affected by blood diseases by enhancing research and clinical practice. The Data Hub aggregates curated data from multiple sites for a variety of uses by researchers, providers, and other stakeholders, while the SCD CTN engages institutions to introduce efficiencies in multicenter clinical research. The ASH Research Collaborative is governed by an executive committee comprised of appointed members, with subcommittees, working groups, and task forces that support specific areas of focus. The Data Hub oversight group and the SCD CTN oversight committee provide programmatic guidance. Though the initial focus for the Data Hub and SCD CTN is initially in multiple myeloma (MM) and sickle cell disease , early work in these areas will develop templates that will be used for future program expansion.
The Data Hub is building a shared information resource for the global hematology community. Clinical care sites, such as health care systems, hospitals, and outpatient practices, can participate in the Data Hub and establish EHR data integration that facilitates data submission. Data submission formats for structured EHR data include Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) and Fast Healthcare Interoperability Resource (FHIR) standards. OMOP and FHIR, terms that may be unfamiliar to many hematologists, refer to 2 contemporary and increasingly used clinical informatics models to extract and/or transmit data from the electronic health record. Based on the Data Hub experience to date, most participating institutions have information technology and informatics expertise, and in some cases, have approached these methods to organize and transmit data for other data aggregation efforts outside of hematology. As new transmission methods for data submission become available, such as application programming interfaces (APIs) between third-party applications and the EHR, these opportunities will be accepted by the Data Hub as well. Besides EHR data, other data sources will be incorporated into the Data Hub such as patient-reported outcomes (PROs) from patient-facing portals and apps, patient-generated health data (PGHD) from connected digital sensors, case report form-based electronic data capture for clinical information maintained outside structured EHR fields, genomic and molecular data, and population data from a variety of sources. In some instances, data specifications, including accepted formats, vocabularies, and standards including details related to data acquisition, curation, and linking to external sources, are still evolving. For example, genomic data could include either “ground truth” data files or interpreted data summaries, but details related to data acquisition, curation, and linking to external sources remain to be determined. The Data Hub plans to facilitate the collection of PROs and PGHD through patient-facing portals; because patients are linked to records at the site level, data can be simultaneously collected directly from patients while being shared back to sites for clinical care and site-level population analyses. Exploration of data integration from industry, government datasets, registries, and other U.S. or international sources is also planned, with assessments of feasibility, appropriateness, and fitness for purpose in different contexts.
The ASH Research Collaborative adopted a multistakeholder collaborative philosophy that includes patients and community members, clinical care sites, research sponsors, clinicians, researchers, and federal entities, including the U.S. Food and Drug Administration (FDA), National Institutes of Health (NIH), U.S. Department of Health and Human Services (HHS), and others. The ASH Research Collaborative Data Hub works closely with patients to understand priorities, incentives, and barriers to research participation. The patient community is recognized as a key driver to the Data Hub’s ability to enable the broadest possible use of real-world data (RWD) to accelerate evidence development, advance research, and improve care. An electronic consent platform has been developed with patient input, modeled after best practices that have been demonstrated in the National Institutes of Health's All of Us research program. Patients have also been integrally involved in key ASH Research Collaborative projects, including the SCD Learning Community (LC), which aims to iteratively inform Data Hub design alongside the particular clinical improvement priorities identified. Patients will become increasingly involved as PRO and PGHD capabilities are identified and integrated. At this point, direct patient querying of aggregate Data Hub data is not anticipated but could be considered in the future. Nonetheless, patients will continue to have an important voice in Data Hub development and execution so that their priorities are identified and implemented. Providing sites with data tools that help them directly assess their clinical care and patient outcomes and engaging a network of care providers who exchange best practices and lessons learned are key elements that support care enhancements and program sustainability. Tools provided to participating sites include real-time dashboards that provide unique site care and outcome metric results and comparisons to aggregate data from all sites. Sites also have access to their own data using online queries and cohort analyzer tools and data exports for local research. As the Data Hub grows, researchers can submit research proposals to access deidentified data across all participating sites. To preserve confidentiality for participating sites, clinicians, and patients, research data sets exclude site and clinician identifiers and include a limited data set or deidentified data set for analysis. The level of identification is determined on a case-by-case basis and complies with institutional review board (IRB) oversight and the Data Hub’s governance policy. For research sponsors, the Data Hub can provide access and analysis of RWD for use in contemporaneous control arms, postapproval surveillance, and identification of cohorts for pre and postmarket research. The ASH Research Collaborative is working to align its interests with those of federal agencies in promoting the development and access to safe, efficacious, and patient-centered therapies by generating new clinical and translational research discoveries and promoting equity in access to evidence-based care and novel therapies throughout the field of hematology. The following paragraphs describe in more detail the rationale for the inclusion of the initial 2 hematologic conditions (SCD and MM) and will use these 2 areas to illustrate overall Data Hub operations and strategy. SCD ASH has a long-standing commitment to addressing disparities associated with SCD and facilitating the development of therapeutic strategies. The SCD drug development pipeline is active, and FDA-regulated research includes small molecules, monoclonal antibodies, gene therapies, and other approaches to ameliorate disease-related symptoms and to achieve a cure. As improvements in SCD have extended survival for affected children and young adults, new questions are being developed about the course of the disease in older individuals and/or those with end-organ dysfunction. The ASH Research Collaborative’s patient-centered approach and community engagement are important program elements to answer these questions and to accelerate clinical trials and accumulation of RWD with longitudinal follow-up. MM MM was selected as the initial disease area of focus within malignant hematology as data sharing opportunities utilizing RWD in this disease are particularly timely. Improvements in current prognostic models (eg, an improved version of the Revised International Staging System) and the development of new prognostic biomarkers (eg, the role of minimal residual disease to guide evaluation and selection of therapies) require large datasets for development and validation. The refinement of genomic markers for risk stratification and treatment selection continues to evolve. In the setting of recently approved treatments for MM, sequencing of therapies and the optimal role of autologous hematopoietic cell transplantation and CAR-T cell therapies remain unclear and will benefit from the accumulation of RWD over long periods of time. Further, racial and ethnic barriers to clinical trial enrollment and access to effective therapies outside of trials mandate creative problem-solving approaches.
ASH has a long-standing commitment to addressing disparities associated with SCD and facilitating the development of therapeutic strategies. The SCD drug development pipeline is active, and FDA-regulated research includes small molecules, monoclonal antibodies, gene therapies, and other approaches to ameliorate disease-related symptoms and to achieve a cure. As improvements in SCD have extended survival for affected children and young adults, new questions are being developed about the course of the disease in older individuals and/or those with end-organ dysfunction. The ASH Research Collaborative’s patient-centered approach and community engagement are important program elements to answer these questions and to accelerate clinical trials and accumulation of RWD with longitudinal follow-up.
MM was selected as the initial disease area of focus within malignant hematology as data sharing opportunities utilizing RWD in this disease are particularly timely. Improvements in current prognostic models (eg, an improved version of the Revised International Staging System) and the development of new prognostic biomarkers (eg, the role of minimal residual disease to guide evaluation and selection of therapies) require large datasets for development and validation. The refinement of genomic markers for risk stratification and treatment selection continues to evolve. In the setting of recently approved treatments for MM, sequencing of therapies and the optimal role of autologous hematopoietic cell transplantation and CAR-T cell therapies remain unclear and will benefit from the accumulation of RWD over long periods of time. Further, racial and ethnic barriers to clinical trial enrollment and access to effective therapies outside of trials mandate creative problem-solving approaches.
Though full EHR data are captured within the Data Hub for each included participant, each disease-specific program within the Data Hub has a harmonized data model that includes evidence-based data elements with accompanying validation rules. Here, data harmonization is referring to the way in which data with different formatting, naming, and organization frameworks can be brought together and transformed into a cohesive data set to facilitate “apples to apples” comparisons for visualizations and analysis. The harmonized data models do not limit the scope of full EHR data ingestion but support the Data Hub’s ability to optimize the use of the data. Core data elements are iteratively updated over time in parallel with new advances in clinical care and research and are derived from a common construction methodology and commonly shared data language(s). Closely tied to the core data elements are metrics that use specific algorithms to align with outcomes of interest. The Data Hub core data elements and metrics are established by an iterative process and are intended to be informed by a wide variety of drug development stakeholders. A modified Delphi process that engages patients, clinicians, regulators, payers, health technology assessment (HTA) groups, drug developers, and other key stakeholders as used for other initiatives (eg, coreSCD) is being tailored and optimized within the ASH Research Collaborative Data Hub to identify priority metrics and outcomes across decision contexts for regulatory purposes, coverage and reimbursement, and patient care. Similar approaches that consider multiple stakeholders and sources of data are being used to identify core data elements in SCD and MM and are planned for other malignant and nonmalignant hematologic diseases. The core data elements, metrics, and overall data model development process is coordinated across ASH Research Collaborative multistakeholder subcommittees.
The development of a RWD platform for both SCD and MM presents a set of challenges common to other RWD initiatives and unique to rare diseases. There are limitations with EHR data consistency, accuracy, and completeness that require multidisciplinary approaches for analysis, verification, and augmentation via linkage to secondary data sources. Rare diseases like SCD are subject to chronic miscoding due to the highly specialized knowledge required for accurate diagnosis and treatment. As with other clinical data points, SCD and MM RWD are most valuable when analyzed using complex computable phenotypes that incorporate data across domains, including but not limited to laboratory results, diagnoses, procedures, visits, and imaging studies. The concept of a computable phenotype includes the composite of data elements, and representative codes obtained longitudinally at multiple clinical encounters can be brought together through a value set (a set of codes where “any one counts”) for identification and uses rules-based algorithms (“if/then”), queries, and/or machine learning (ML)/artificial intelligence (AI) (agnostic to what underlying relationships might exist) to represent a single health concept. The relationship between the computable phenotype and the known underlying health concept (gold standard) is measurable with traditional test characteristics. The availability and reliability of these data vary across and within health systems, necessitating supplemental data collection and validation approaches to enhance the quality of RWD to ensure fitness for purpose. The SCD and MM Data Hub programs are being developed by hematology experts who examined disease-specific endpoints, clinical guidelines, and other evidence documents to inform the creation of clinical core data elements and metrics of interest. Working with clinical informaticists, hematologists are assessing the reliability and validity of structured EHR data to determine additional manual verification or data entry needs. Baseline computable phenotypes (e-phenotypes) for clinical concepts are constructed using value sets comprised of clinical terms derived from EHR documentation codes such as ICD-10, SNOMED-CT, LOINC, and RxNorm. Where possible, published value sets from the Value Set Authority Center (VSAC) are used. The VSAC is a central repository of clinical concepts and their associated terminology definitions, hosted by the National Library of Medicine. Value sets in the VSAC are developed by a variety of health care entities, and value sets authored by national organizations and frequently updated have been prioritized. Future Data Hub projects will include the development of a comprehensive phenotype knowledge base with further collaboration to develop and share e-phenotypes for broad use. The Data Hub envisions the development and maturity of e-phenotypes across stages. In the first stage, an inclusive list of codes is generated to achieve acceptable sensitivity for capturing the health concept of interest. In the second stage, rules-based logic is used to develop algorithms of codes to further improve sensitivity, specificity, and positive predictive value of the underlying health concept (eg, one of several diagnosis codes, repeated in at least 2 outpatient visits, accompanied by 1 or more from a set of laboratory and imaging results, and exclusive of other specific codes from the EHR). In the third stage, ML and AI can be applied to agnostically determine other contributors to e-phenotypes where prespecified rules may not exist. Not every stage may be required for every e-phenotype; the amount of development and validation required depends on consensus standards across the stakeholder community as well as the needs of specific use cases. As this area is not yet well defined, the Data Hub will contribute to efforts involving the FDA and others to help define when an e-phenotype is “fit for purpose” for inclusion within a disease program. The Data Hub is constructing an e-phenotype “innovation lab” where Data Hub participants can review results of proposed e-phenotypes using their own data and provide feedback to guide refinement prior to publication as proposed national standards. An example of a first stage ASH Research Collaborative e-phenotype using an inclusive list of EHR codes for vaso-occlusive episodes is shown in supplemental Table 1. The concept at this stage is to find all potentially applicable codes that might be used to identify an individual with SCD in order to improve the sensitivity (true positive) of the technique for picking up all potential patients. Additional work will be conducted as needed, with new data elements and/or repeated measures such as laboratory values and other diagnoses to further refine this e-phenotype using second-stage and third-stage processes to improve specificity and positive predictive value of the resulting patient identification algorithm.
In addition to data directly derived from the EHR, we identified high-value data elements that cannot be reliably extracted from EHRs due to variable documentation across sites. For example, these could include concepts such as genotype in SCD, or disease progression (or “time to treatment failure” [TTF]), or the Revised International Staging System in MM. Though the data elements undergirding these concepts could be present in the EHR (in myeloma, the serum protein electrophoresis, free light chain values, lactate dehydrogenase, β 2 microglobulin, albumin, etc), they may not adequately or reliably be captured for a given patient at the primary institution contributing data. Or, short of application of natural language processing, FISH/cytogenetic data may not be immediately accessible through the EHR data because of the format for original capture of the data. When needed, supplemental data such as the examples provided here have formed the basis for electronic Case Report Forms (eCRFs) for each disease. The Data Hub’s eCRFs were designed to meet several program goals: (1) to reliably capture data elements not well-structured or present within EHRs; (2) to allow sites who are unable to connect their EHRs to submit data to the Data Hub to access Data Hub data for benchmarking and research; and (3) to provide a mechanism for amending EHR data that was miscoded, missing, or otherwise inaccurate in their EHR. Supplemental eCRF data will be critical in the calculation of metrics such as TTF for MM, where the clinical data necessary to determine treatment initiation and criteria for treatment failure were not consistently coded or readily available from most EHRs. While the Data Hub will address current gaps in clinically relevant EHR data capture through eCRFs, the Data Hub will also work to facilitate the development and implementation of EHR clinical documentation standards in order to reduce redundancies and inefficiencies associated with duplicate data entry. In addition to data captured via EHR and eCRF, the Data Hub can also receive data extracted from sites’ local research programs and submitted via a simple flat-file format. Sites that submit local research data will harmonize data element definitions and map fields to the Data Hub’s standardized data dictionary to facilitate reliable meta-analyses. is a representative schematic for pathways to Data Hub data submission and validation. Data quality can be challenging for EHR RWD because data are documented by a variety of providers across care settings and systems. An important goal for the ASH Research Collaborative is to provide sites with a data quality report with each data submission. Site data quality reports focus on areas of high variability in EHR data to help sites identify potential concerns surrounding data completeness and accuracy. If data quality issues are identified, it may not be possible to reconcile EHR data with Data Hubstandards. In this case, sites can use prepopulated eCRFs to amend a patient’s record in the Data Hub. Subsequent EHR transmissions will not overwrite data that has been amended through the site’s eCRF (eg, the eCRF is treated as the primary source of truth when data are in conflict). Future data quality assessments will include crossreferencing longitudinal chart data to identify inconsistencies, duplication, and potential miscoding that impact the accuracy of metrics and research analyses.
The Data Hub’s site dashboards provide real-time access to metric results for the site submitting data with deidentified aggregate comparison results across all submitting sites. Because measurement needs vary across expert groups with regard to SCD and MM care, the Data Hub has developed different data visualization and analysis approaches for the SCD and MM dashboards. For example, the majority of the SCD dashboard data are best understood in the context of trends over time for specific and repeatable metrics largely derived from structured EHR data, with a need to identify potential outliers for further investigation. See for a list of metrics included in the SCD site dashboard. The SCD site dashboard uses p-charts to illustrate each site’s trend for a metric, with an associated mean value across the analysis period and 1, 2, and 3 standard deviations to show potential outliers in need of further analysis. In contrast, the MM site dashboard ( ) uses a blend of descriptive statistics such as frequencies and means, as well as Kaplan-Meier survival curves to analyze metrics of interest, initially overall survival (OS) and TTF. The MM site dashboard also includes multiple filters to create subgroups based on complex logical relationships between data elements such as treatments, disease type and subtype, disease history, and the presence or absence of specific genetic aberrations. Site data can be visualized alongside aggregate data from all other sites participating in the Data Hub, in entirety or by filtered subgroups. For both site dashboards, when a cohort of interest has been specified for a set of metrics, sites can drill down to participant-level detailed data to facilitate advanced statistical analysis and quality improvement activities. Site dashboards do not include the complete set of metrics that are tracked by the Data Hub. For example, the development of new or secondary malignancies is not included in the current dashboard versions but is an important long-term clinical outcome that the Data Hub will track.
The Data Hub database is primarily populated with patient EHR data submitted by sites. Centers using any type of EHR (Epic, Cerner, or others) are able to participate. In the future, EHR-agnostic API-based data transmission solutions from third-party apps may also be considered. The ASH Research Collaborative has partnered with Prometheus Research (PR), an IQVIA company, to aggregate and curate data from multiple sources such as EHRs, and, in the future, patient-reported outcomes, PGHD, genomics, and other data sources. The Data Hub data curation method ingests the totality of EHR data from sites using the OMOP CDM or FHIR data exchange format. This approach to data acquisition is intended to reduce the burden for participating Data Hubsites and may better support long-term sustainability by reducing the resources required for redundant data capture. As previously noted, a web-based data entry tool is available to facilitate additional or alternative data entry as needed. This tool also allows sites to validate e-phenotypes and override inaccurate data. Generally, initial data submission involves support from the institutional information technology team, though this support is not expected to be significant over the long run. Some sites can expedite data submission when IT personnel have participated in similar projects, and others have benefited from modest ASH Research Collaborative grant support to help prioritize data integration work needed to submit data. Subsequent manual data curation at the site level is facilitated by clinical teams who are incentivized to participate based on the particular disease and project for which data are being submitted. Regardless of the data ingestion method, data captured are longitudinal and comprehensive with detailed information on patient demographics, comorbidities, medications, treatments, utilization, processes, and outcomes, as covered through the United States Core Data for Interoperability (USCDI). See for a list of USCDI v2 data categories and data descriptions. As new versions of the USCDI are created and released, the Data Hubwill correspondingly update its data capture methods to improve the comprehensiveness of the data ingested. The Data Hub will also ingest clinical notes, pathology and imaging reports, and other types of documentation that may contain “unstructured” data. Future approaches to handling unstructured data will include natural language processing (NLP) software to “read” and glean information from the unstructured notes, as well as efforts to bring additional structure into these data sources through advocacy and consensus-building efforts. Regardless of the source, in totality, the data inform research analyses and clinical dashboards and can be queried and exported. Data Hub sites submit data at least quarterly (most select monthly), and data are curated and collated within the corresponding disease-specific data model. When sites submit data, existing records are refreshed. Refreshes do not overwrite information in the eCRFs. Because all potential future data needs and analyses are not known, the entirety of the EHR data for each patient continues to be stored within the Data Hub. The Data Hub has developed a data quality maturity model to ensure data are adaptable, reusable, and scalable for performance improvement initiatives. Once a site submits data, a data quality report is generated.
Through harmonizing approaches to achieve comparable data at the site level, the Data Hub is positioning its data to be used for ML and AI. Advances in digital medicine have not translated easily into implementation mostly due to the lack of standardized data across health systems. The ASH Research Collaborative is working to create widely adopted e-phenotypes that translate EHR codes, such as RxNorm, SNOMED, LOINC, and ICD-10, into clinically relevant data variables, attempting to reduce manual data curation where possible. As data are submitted to the Data Hub, data quality is addressed through data standardization methods, data quality reports, and local data validation procedures. Truly interoperable data can be used for other purposes, including the development of predictive models to inform clinical decision support at point of care for participating sites. The ASH Research Collaborative will align where possible with other efforts such as mCODE (minimal Common Oncology Data Elements) that have overlapping goals.
Longitudinal follow-up of patients is a priority, and traditional registries have used follow-up procedures that require direct patient interaction and manual data entry. New approaches to longitudinal follow-up using EHR and claims data will benefit the Data Hub. Linked medical claims data have been used as outcomes data in some studies. Currently, 17 states have all-payer claims databases (including New York and California), and national legislation is pending to create a national all-payer claims database. The prospect of a national all claims database may enhance the ASH Research Collaborative Data Hub and the creation of a hematology coordinated registry network similar to those developed by other specialty societies. Expansion of the Data Hub to accommodate a broader network of sites, community participation, and patient-generated data will also help to address the longitudinal loss to follow-up issue.
To facilitate patient-centered research and care, the information provided directly by or obtained from patients is important and difficult to standardize in routine practice. Mobile apps, sensors, and the addition of data collected in usual care can be linked to rosters of patients followed in RWD/RWE studies. An electronic informed patient consent module is available to allow the collection of these types of data and allow patients to be recontacted to inform longitudinal outcome evaluations. Further, RWD/RWE platforms will be leveraged to facilitate more efficient prospective randomized study designs through so-called “hybrid” studies. Prospective hybrid studies can address several important challenges, such as difficulty accounting for known and unknown prognostic factors and differences in endpoint definitions between trial and RWD data. In hybrid trials, patients can be randomized to balance prognostic factors, and endpoint definitions (eg, rwPFS) will be the same for both arms. These trials are especially suited for approved drugs and postmarketing research investigating comparative effectiveness, sequencing of agents, comparative tolerability, and other important objectives. These trials can also be used as part of pragmatic trials and other studies of health care delivery interventions within learning networks. With these approaches, careful analytics and data quality assessment are needed to ensure fitness for purpose.
The ASH Research Collaborative is expanding its stakeholder community to facilitate RWE generation, with an initial focus on SCD genomic therapy research that will require longitudinal evidence generation. The ASH Research Collaborative and the Innovative Genomics Institute (IGI), in collaboration with the FDA, have engaged people living with SCD, clinicians, researchers, industry, and regulators to explore methods to support SCD RWE generation using the Data Hub program. The initiative’s stakeholder participants are working to recommend data to collect and methods to coordinate clinically relevant and reliable RWD. Stakeholders have convened through roundtable meetings and working groups. The first stakeholder roundtable was held in March 2021 to discuss the role of RWE for FDA regulated studies, examples of how coordinated registry networks (CRN) have facilitated the use of RWD for improved safety, efficacy, and label expansion, and the urgency of harmonizing data collection in new genomic therapies. A CRN working group is exploring how the Data Hub could serve as a CRN to provide RWD for a variety of regulatory purposes and linkage to other data sources (claims, EHR, and data collected via apps or remote monitoring) that potentially increase utility, reduce costs, and better reflect patients’ experiences compared with traditional methods. The Genomic Therapies Work Group is seeking consensus on data points that should be collected and procedures and assays to be used to generate actionable, regulatory-grade RWE for genomic therapies for these blood disorders. A final report will address recommendations for the collection, curation, storage, and sharing of data collected in clinical settings (therapeutic and research) that can also provide reliable, fit-for-purpose RWE to regulators, health care providers and payers, investigators, and patients about the safety and effectiveness of genome editing and other novel therapies for SCD and other hematologic conditions.
The Data Hub facilitates the exchange of information through real-time dashboards, queries, and research. Data are also used to highlight gaps in clinical care and patient outcomes to facilitate quality improvement. HHS and the Office of Minority Health (OMH) awarded ASH, the ASH Research Collaborative, and the Learning Networks Program at the James M. Anderson Center for Health Systems Excellence at Cincinnati Children’s (Anderson Center) a grant to build an SCD clinical data platform and an SCD LC. Anderson Center has extensive experience developing learning networks using a learning network model, which aligns with the National Academy of Medicine framework of a learning healthcare system. The SCD clinical data platform will leverage the Data Hub’s longitudinal patient data to track practice patterns, and the LC will focus on actionable and measurable areas to improve, implementation of evidence-based strategies to support selected areas for improvement, and measurement of change using Data Hub data. LC stakeholders include clinical teams, patient and family members, implementation scientists, quality improvement experts, and psychologists. Stakeholders are designing a pilot implementation that will include 15 to 20 sites participating in the Data Hub’s SCD program. The global aim and priority themes are listed in . Sites will engage with each other to share lessons learned and strategies for success. The pilot LC will inform the launch of a nationwide SCD LC to improve outcomes at a national level. The nationwide LC will be available to all sites enrolled in the SCD Data Hub program. The ASH Research Collaborative is also exploring ways in which lessons from the SCD LC can be applied to develop LC activities in other disease programs supported by the Data Hub.
The ASH Research Collaborative SCD CTN was launched to improve outcomes for individuals with SCD by expediting the development of treatments and facilitating innovation in clinical trial research. Since the Data Hub provides a valuable and essential resource for the operation of the SCD CTN, all sites in the network will contribute data to the Data Hub. The Data Hub will be used to identify cohorts for trials and provide RWE control arms, among other uses relevant to the SCD CTN. The SCD CTN provides 3 resources that will be of benefit to investigators, sponsors, and ultimately patients. First, it provides a collection of advisory boards that will help overcome barriers to clinical trial participation, prioritize research areas of interest to the SCD community, improve enrollment, design, and execution of clinical trials, and local community advisory boards at each of the sites to supplement the opinions that are provided by national patient advocates. Second, it is connected to the Data Hub, which provides a centralized data repository, will identify cohorts for research (ie, well-characterized patients for inclusion and exclusion criteria), natural history studies, and a contemporaneous control group. Third, the SCD CTN provides well-vetted and engaged clinical trial sites with a culture of collaboration and research, an efficient, coordinated approach to clinical trials research, and centralized IRB & contracting. The SCD CTN and its partners share a commitment to: (1) forge new relationships with the SCD community to increase their understanding of clinical trials and trust in SCD researchers; (2) eliminate inefficiencies through the use of a centralized data repository (the ASH Research Collaborative Data Hub), a single institutional review board approval, and centralized contracting; and (3) focus on the research opportunities that hold the most promise for individuals living with SCD. While there are currently only 4 FDA-approved drugs to treat SCD, there is now a robust SCD drug development pipeline poised to drive demand for SCD clinical trials, providing a prime opportunity to advance treatment and care of those affected by SCD. The SCD CTN has been designed to address the many issues limiting evidence generation and, importantly, to incorporate the voice of patients. It is important to note that the SCD CTN functions primarily as a clinical trials accelerator. The SCD CTN is not a contract research organization (CRO) and thus does not actually conduct the trials itself; instead, it brings sites, investigators, and patients together through shared purpose with a common infrastructure. When fully enrolled, the SCD CTN and Data Hub will encompass approximately half of all patients with SCD in the United States, thereby representing an unparalleled opportunity to benefit this population through accelerated research and improved clinical practice. The SCD CTN is designed to substantially shorten time-to-trial launch and completion, in part by engaging sites quickly and reaching patients expeditiously, providing value to industry, researchers, clinicians, patients, and other stakeholders. At the same time, the SCD CTN serves as a steward of a culture that is patient-informed, patient-centered, and determined to address and ameliorate disparities in access to potential life-extending therapies.
The ASH Research Collaborative was well-positioned to accommodate unanticipated and urgent data needs relevant to hematology, including the global COVID-19 pandemic. Early in the pandemic, clinicians were concerned that patients with underlying hematologic conditions could be at risk for adverse outcomes from COVID-19. As the pandemic evolved, there was also increasing recognition that hematologic complications of COVID-19 infection, such as thrombosis, were also prevalent. The ASH Research Collaborative launched the COVID-19 registry for hematology in April of 2020 as a global public reference tool. The registry captures RWD on individuals who test positive for COVID-19 and have a hematologic condition (past or present) and/or have experienced a post-COVID-19 hematologic complication. Initial results from the registry have been recently presented and published. As data are received and analyzed, real-time observational summaries are made available via a publicly displayed dashboard intended to support clinical decision-making. The registry has been designed as a provider-entered, case report form-based, voluntary submission program. There are efforts underway in which the ASH Research Collaborative is participating to increase COVID-19 testing and promote laboratory standardization, and the ASH Research Collaborative anticipates collecting COVID-19 data from EHR-integrated data capture in the future as part of the SCD and MM programs to gain a better understanding of any potential long-term sequelae or interactions with diseases or treatments.
The examples provided above demonstrate many ways the Data Hub will be used to accelerate research and improve practice and patient outcomes in hematology. Ultimately, the value of the resource depends on the degree to which it is used by providers who input data as well as trained users who use the data for research, analysis, and improvement of clinical practice. Many of the data tools being developed by the ASH Research Collaborative will be available to all participating sites, including site dashboards that incorporate metrics from resources such as ASH evidence-based clinical guidelines, the ability to analyze site-level data and visualize comparisons with aggregate data, and in the future, point of care clinical decision support. Individual researchers also access Data Hub data to facilitate specific analyses, grant submissions, and other objectives. The Data Hub oversight group has developed data access and use procedures which will be made widely available to the hematology community, along with training and ongoing support to ensure high-quality analyses when the Data Hub has accrued sufficient data and is ready to be made available for scientific analyses. In the future, insights and developments in the field based on Data Hub activities will also be communicated broadly with the hematology community through newsletters and other means. The Data Hub will also work to be as useful as possible to the patient community. Future features of a patient-facing portal, in addition to direct data entry from patients, could include the ability for patients to access treatment guidelines, opportunities to participate in clinical studies, and the ability to access information related to centers specializing in the care of individuals like them. Ongoing input from patients and external stakeholders will be actively sought to ensure that the Data Hub provides maximum value to all those who might wish to interact with it.
Over the next several years, the Data Hub will capture longitudinal data on many individuals in the United States living with SCD or MM. Efforts will soon expand to encompass additional hematologic conditions. The ASH Research Collaborative SCD CTN will continue to expand and engage clinicians and patients across the country as new sites are onboarded. The Data Hub will be used for hypothesis-generating research and RWD analytics to inform drug development. Data quality is a prominent priority, and it is anticipated that Data Hub data will be used to create new point-of-care clinical decision support tools. Throughout these activities, the ASH Research Collaborative will continue its process of multistakeholder engagement to ensure that the resulting trials and data are fit for purpose for various entities throughout the regulatory, clinical, research, and health care policy ecosystem.
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Current opinions and recommendations of paediatric healthcare professionals – The importance of tablets: Emerging orally disintegrating versus traditional tablets | bbc042ee-dc15-49e9-aa89-e72ca6a4f794 | 5830997 | Pediatrics[mh] | The European Medicines Agency (EMA) recognised that there was limited data concerning paediatric population acceptance of oral dosage forms in relation to age and developmental status, along with the inadequate availability of licensed medicines appropriate for administration to children . In addition, there is anecdotal evidence that there are increasing concerns amongst healthcare professionals about paediatric patients failing to take their prescribed medication . Many medicines are formulated to enable usage in adults, which may not be suitable for use by children. There may be difficulties in swallowing solid dosage forms (e.g. tablets) and there may be issues concerning the availability of the dose strength, based on current dosage forms available. Many children will require doses smaller than adults, prompting the use of liquids or splitting the dose of solid tablets by cutting them into halves and quarters. If suitable dosage forms are not available then patient compliance with prescribed medication may be reduced with potential adverse clinical consequences . Reasons that may affect a child’s success in swallowing solid dosage forms include developmental stage, depending on their age (0 to 18 years), anxiety, fear, intolerance to unpleasant flavours and not being able to appreciate the risks associated with noncompliance . Treatment failure may result, leading to poor clinical control and unnecessary expense as a result of unused medication waste. In primary care around £300 million worth of medicines are wasted every year of which £150 million is preventable . Formulation work so far in pharmaceutical industries has revealed that liquids seem to be more customary with the paediatric population (infant age between 1 month to 2 years and pre-school age between 2 to 5 years), whereas oral disintegrating tablets (ODT) may be preferred by those who are older (5 to 11 years), and in the adolescent age (12 to 16/18 years), tablets and capsules may be more appropriate and convenient . An ODT is an easy to use dosage form which disintegrates in the mouth upon contact with saliva. ODTs can be taken without the need to swallow the tablet whole and does not require water. Advancements in the area of ODT formulation were aimed equally at escalating the performance of the dosage form by lessening the disintegration time, and by increasing the compliance of patients via masking the unpleasant taste of the API. These successes require stable improvement of formulation variables, together with technologies concerned in the manufacture of dosage forms. The inclusion of super-disintegrants to produce efficient ODTs is not new. Conversely, with the development design of innovative techniques, it has become promising to formulate ODTs with less content of super disintegrants and with improved mouth feel . There is evidence to suggest that ODTs are a potential ideal formulation for children since they avoid concerns children may have regarding swallowing tablets. . A previous study by the authors was conducted in three countries Jordan, Saudi Arabia and the UK found that approximately 58.0% of the participants (children age 6–18 years) preferred taking ODTs compared to conventional tablets, liquids and capsules . Few studies have been carried out aimed at identifying healthcare professional perceptions or opinions regarding the use of different dosage forms for paediatric use. However, previous research conducted in similar fields has explored healthcare professional’s perceptions on HIV treatment adherence in children with an investigation in to unlicensed/off label medicines use and those exploring paediatric nurses knowledge and practice of mixing medicines with foodstuffs . Most research in this field is targeted at reducing prescribing and dispensing errors for children. However, to ensure medication adherence in children is supported, when making a decision on medication formulation choice for a child, clinicians should take into consideration the acceptability of the dosage form to paediatric patients. To the best of our knowledge there are limited published studies regarding the opinions of healthcare providers concerning ODTs preparations. As ODTs are an emerging dosage form which is increasing in popularity, it is important to gather opinions of paediatric healthcare professionals as to their prescribing habits and also preference for ODTs. Their opinion on the desired characteristics is important as this may reflect their prescribing/administration of the dosage form. Furthermore, limited data is available concerning the effect of ODTs properties (i.e. organoleptic, taste (sweet, sour, bitter, salty or umami), texture, flavour, colour, shape, size and disintegration time) on child acceptance. Poor acceptance could lead to a child resisting or rejecting a medication. The palatability of paediatric oral medicines is one of the most important factor with potential to impact adherence to therapeutic regimens. Drug design and manufacture goes beyond the basic principles of producing drugs with the best therapeutic profile. It also involves the manufacture of drugs whose taste is acceptable to the target age group, in this case the paediatric population. Drugs, which are not palatable, have lower acceptability. For this reason, the taste may be masked or the drug flavoured to ‘conceal’ the bad taste. Flavouring involves adding substances that give the drug a characteristic taste and smell, different from that of the actual drug. Taste addiction is a situation in which the patient develops a liking for the taste of the drug and feels an urge to take the drug often. Although taste addiction may resolve the issue of non-adherence, it may result in grave consequences such as abuse of the drug. Care should be taken to avert this. The flavouring is important because it tailors the taste and smell of the drug to the convenience of the target age group. Previous results obtained from research studies on the popular flavours aid in developing drugs with specific flavours and which suit the needs of the target age group [ , , ]. To complement and supplement the findings of formulation preference in children , and to gather the opinion of healthcare professionals responsible for the care of a child in terms of prescribing, supplying and administering their medication, it was therefore necessary to conduct a study exploring the opinions of healthcare professionals regarding paediatric dosage forms, and in particular ODTs. The primary aim of the present work is to evaluate healthcare professional’s perceptions of the paediatric dosage forms to support patient choice and ultimately patient adherence to prescribed medication regimens. The main objective of the focus group and semi-structured interviews (phase 1 and 2 respectively) was to design a validated online survey (phase 3) delivered to pharmacists, nurses and medical practitioners to evaluate their views and perceptions with regards to paediatric dosage forms. This study will provide the opinion of healthcare professionals in what dosage forms they believe are preferred by children and to also identify healthcare professional’s personal opinions concerning the safety and cost effectiveness of formulation types. The secondary aim of this study was to compare the findings of this present study concerning healthcare professionals with the findings from the previous study concerning children in respect to dosage forms .
Overall methodological design of the study The study consisted of dual site, cross-sectional, mixed methods study of hospital based paediatric doctors, pharmacists and nurses, using an anonymised electronic survey (Bristol Online Survey software–BOS); informed by a literature search, focus groups and semi-structured interviews. This study was carried out at two UK city based paediatric hospitals in the West Midlands and North West of England, in this article named as Hospital 1 and Hospital 2. Informed by a literature search, this study included a three-phase consensus-building process comprising of Phase (1) focus groups with pharmacists and nurses (separately); Phase (2) semi-structure face-to-face interviews with each of the three main groups of professionals, consent forms were given to focus group phase (1) and semi-structure interviews phase (2) and Phase (3) electronic survey of paediatric hospital healthcare professionals. Qualitative verbatim transcripts from phases 1 and 2 were subjected to framework analysis . Themes from phase 1 underpinned the basis for phase 2 interviewees. Themes from phases 1 and 2 generated issues for inclusion within phase 3. The final electronic questionnaire (phase 3) was assembled and managed using bespoke software (Bristol Online Survey ™). Results were transferred to SPSS version 22 and NVivo version 10 software for analysis to facilitate descriptive statistical analysis and framework analysis respectively. presents a flow diagram of the three phases that were carried out. The questionnaire was comprised of both closed and open questions to identify participants’ perceptions and opinions about dosage forms for children. Recruitment and consent Phase 1 –Focus group Two focus groups were undertaken within this study. One focus group consisted of 4 nurses and one of 7 pharmacists. These focus groups were designed to support the development of the healthcare professionals’ questionnaire. All focus groups were conducted at the primary study site (Hospital 1). Email invitations to attend the focus groups were arranged via the research leads of the two professions at Hospital 1. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form. Private rooms were pre-booked within Hospital 1 in locations accessible for staff, to create a suitable and convenient environment for discussion. The focus groups were facilitated by HA (Hamad Alyami) and assisted by CH (Chi Huynh) (research pharmacist/lecturer in clinical pharmacy). The groups were digitally audio-recorded. A question guide was developed including questions to be discussed by the facilitator to ensure coverage of pre-determined themes identified by the project support team. Phase 2 –Semi-structured interviews Participants from the three professional groups were recruited to undertake semi-structured interviews. They were recruited by recommendation from the professional research leads or via their involvement in the Academic Practice Unit at Hospital 1. A minimum of three participants from each of the three professional groups were recruited to the study. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form. Analysis of the focus groups and semi-structured interviews data The data collected from Phase 1 and Phase 2 were analysed using framework analysis by with the following stages, 1) Data entry and processing; 2) Familiarisation of the focus group and interview data collection and identifying an initial framework based on the question guide 5); 3) Coding–all focus groups and interviews were coded and indexed using NVIVO 10; 4) Generation of themes (charting) results were charted according to the themes; 5) Finalised framework (mapping and interpretation). HA transcribed each focus group and semi-structured interview as soon as was possible after facilitating the group and interview. Verbatim transcripts were produced in Microsoft Office Word 2013 from the digital audio-recordings. Participants were anonymously assigned a coded identifier within the text (e.g. speaker 1, speaker 2 etc.) to ensure the extent to which views were shared could not be identified. The verbatim text was copied in to a qualitative data analysis and coding software (QSR NVivo 10) and framework content analysis was developed to analyse the verbatim files. Qualitative research software (NVivo 10) was used to arrange information and combine analysis with linking . A framework analysis approach was used to qualitatively analyse the data . The data was coded using coding framework based on the question guide for the focus group, interviews and objectives of this study (see ). The initial 10 minutes (20%) of the transcript recording, was coded independently by two investigators, HA and CH, using the initial framework with NVivo Version 10 to assist with indexing the codes. The similarity and differences between the two coders was discussed. The differences between the two coders were resolved via discussion of differences until a consensus was reached. A resulting final framework developed. The coding framework was used to code the rest of the transcript. The interpretation of the results from the coding of the focus group and semi-structured interviews were conducted by HA and was based on the objectives of the focus group and interviews. Phase 3 –Electronic survey An electronic survey tool was chosen as the instrument for this study. Healthcare professionals working at the time of the study for Hospital 1 and Hospital 2 were invited to complete an online survey. Managing of this survey by the use of purpose designed electronic survey software was therefore considered to be both deliverable and efficient due to suitability of having automated data collection, which saves researcher time, effort and offers cost savings advantages . The questionnaire development was supported by the HCPs focus groups and the semi-structured interviews. The themes and concerns identified in the phase 1 and 2 were considered for inclusion in the survey, including for example factors influencing choice of formulations for paediatric patients. A draft survey was created on 11th August 2016 using Bristol Online Survey software (BOS). Email addresses of HCPs were obtained from the site leads at Hospital 1 and Hospital 2 (CH and chief pharmacist) respectively and they managed this process by reference to staffing lists and responses. The invitation to participate was sent from Bristol online survey to the NHS Trust email addresses of the study cohort with a link to the survey. The purpose of the survey was explained in the beginning of the survey and informed consent was presumed when the participant decided to complete the survey. First emails were sent out on with reminder emails sent to all respondents 3 and 6 weeks after the initial email was sent. Each site was required to return completed surveys from a minimum of five professionals in each group. Participants were advised that all data were held confidentiality and anonymity was assured. Responses were exported from Bristol survey into MS Excel 2013 and IBM SPSS version 22 for analysis and production of descriptive statistics. Inclusion and exclusion criteria Inclusion criteria: Healthcare professionals (HCPs) (doctor, nurse, and pharmacist) at Hospital 1. Healthcare professionals (doctor, nurse, and pharmacist) at Hospital 2. Exclusion criteria: General public Ethical considerations The study design was approved by both the Aston University School of Life and Health Sciences and the Research & Development Departments at both Hospital 1 and 2. All participants in the study gave informed consent. Data was only accessible by the study team. All responses were fully anonymised prior to analysis and all reports accommodated confidentiality requirements. Audio files from the focus groups/semi-structured interviews were held on-site at Hospital 1, within the secure area of the Academic Practice Unit. Once transcripts were approved, original recordings were destroyed. Additionally, paper records (from the semi-structured interviews) were also kept within the secure area of the Academic Practice Unit at Hospital 1, and were destroyed upon transcription of the interviews.
The study consisted of dual site, cross-sectional, mixed methods study of hospital based paediatric doctors, pharmacists and nurses, using an anonymised electronic survey (Bristol Online Survey software–BOS); informed by a literature search, focus groups and semi-structured interviews. This study was carried out at two UK city based paediatric hospitals in the West Midlands and North West of England, in this article named as Hospital 1 and Hospital 2. Informed by a literature search, this study included a three-phase consensus-building process comprising of Phase (1) focus groups with pharmacists and nurses (separately); Phase (2) semi-structure face-to-face interviews with each of the three main groups of professionals, consent forms were given to focus group phase (1) and semi-structure interviews phase (2) and Phase (3) electronic survey of paediatric hospital healthcare professionals. Qualitative verbatim transcripts from phases 1 and 2 were subjected to framework analysis . Themes from phase 1 underpinned the basis for phase 2 interviewees. Themes from phases 1 and 2 generated issues for inclusion within phase 3. The final electronic questionnaire (phase 3) was assembled and managed using bespoke software (Bristol Online Survey ™). Results were transferred to SPSS version 22 and NVivo version 10 software for analysis to facilitate descriptive statistical analysis and framework analysis respectively. presents a flow diagram of the three phases that were carried out. The questionnaire was comprised of both closed and open questions to identify participants’ perceptions and opinions about dosage forms for children.
Phase 1 –Focus group Two focus groups were undertaken within this study. One focus group consisted of 4 nurses and one of 7 pharmacists. These focus groups were designed to support the development of the healthcare professionals’ questionnaire. All focus groups were conducted at the primary study site (Hospital 1). Email invitations to attend the focus groups were arranged via the research leads of the two professions at Hospital 1. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form. Private rooms were pre-booked within Hospital 1 in locations accessible for staff, to create a suitable and convenient environment for discussion. The focus groups were facilitated by HA (Hamad Alyami) and assisted by CH (Chi Huynh) (research pharmacist/lecturer in clinical pharmacy). The groups were digitally audio-recorded. A question guide was developed including questions to be discussed by the facilitator to ensure coverage of pre-determined themes identified by the project support team. Phase 2 –Semi-structured interviews Participants from the three professional groups were recruited to undertake semi-structured interviews. They were recruited by recommendation from the professional research leads or via their involvement in the Academic Practice Unit at Hospital 1. A minimum of three participants from each of the three professional groups were recruited to the study. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form. Analysis of the focus groups and semi-structured interviews data The data collected from Phase 1 and Phase 2 were analysed using framework analysis by with the following stages, 1) Data entry and processing; 2) Familiarisation of the focus group and interview data collection and identifying an initial framework based on the question guide 5); 3) Coding–all focus groups and interviews were coded and indexed using NVIVO 10; 4) Generation of themes (charting) results were charted according to the themes; 5) Finalised framework (mapping and interpretation). HA transcribed each focus group and semi-structured interview as soon as was possible after facilitating the group and interview. Verbatim transcripts were produced in Microsoft Office Word 2013 from the digital audio-recordings. Participants were anonymously assigned a coded identifier within the text (e.g. speaker 1, speaker 2 etc.) to ensure the extent to which views were shared could not be identified. The verbatim text was copied in to a qualitative data analysis and coding software (QSR NVivo 10) and framework content analysis was developed to analyse the verbatim files. Qualitative research software (NVivo 10) was used to arrange information and combine analysis with linking . A framework analysis approach was used to qualitatively analyse the data . The data was coded using coding framework based on the question guide for the focus group, interviews and objectives of this study (see ). The initial 10 minutes (20%) of the transcript recording, was coded independently by two investigators, HA and CH, using the initial framework with NVivo Version 10 to assist with indexing the codes. The similarity and differences between the two coders was discussed. The differences between the two coders were resolved via discussion of differences until a consensus was reached. A resulting final framework developed. The coding framework was used to code the rest of the transcript. The interpretation of the results from the coding of the focus group and semi-structured interviews were conducted by HA and was based on the objectives of the focus group and interviews. Phase 3 –Electronic survey An electronic survey tool was chosen as the instrument for this study. Healthcare professionals working at the time of the study for Hospital 1 and Hospital 2 were invited to complete an online survey. Managing of this survey by the use of purpose designed electronic survey software was therefore considered to be both deliverable and efficient due to suitability of having automated data collection, which saves researcher time, effort and offers cost savings advantages . The questionnaire development was supported by the HCPs focus groups and the semi-structured interviews. The themes and concerns identified in the phase 1 and 2 were considered for inclusion in the survey, including for example factors influencing choice of formulations for paediatric patients. A draft survey was created on 11th August 2016 using Bristol Online Survey software (BOS). Email addresses of HCPs were obtained from the site leads at Hospital 1 and Hospital 2 (CH and chief pharmacist) respectively and they managed this process by reference to staffing lists and responses. The invitation to participate was sent from Bristol online survey to the NHS Trust email addresses of the study cohort with a link to the survey. The purpose of the survey was explained in the beginning of the survey and informed consent was presumed when the participant decided to complete the survey. First emails were sent out on with reminder emails sent to all respondents 3 and 6 weeks after the initial email was sent. Each site was required to return completed surveys from a minimum of five professionals in each group. Participants were advised that all data were held confidentiality and anonymity was assured. Responses were exported from Bristol survey into MS Excel 2013 and IBM SPSS version 22 for analysis and production of descriptive statistics.
Two focus groups were undertaken within this study. One focus group consisted of 4 nurses and one of 7 pharmacists. These focus groups were designed to support the development of the healthcare professionals’ questionnaire. All focus groups were conducted at the primary study site (Hospital 1). Email invitations to attend the focus groups were arranged via the research leads of the two professions at Hospital 1. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form. Private rooms were pre-booked within Hospital 1 in locations accessible for staff, to create a suitable and convenient environment for discussion. The focus groups were facilitated by HA (Hamad Alyami) and assisted by CH (Chi Huynh) (research pharmacist/lecturer in clinical pharmacy). The groups were digitally audio-recorded. A question guide was developed including questions to be discussed by the facilitator to ensure coverage of pre-determined themes identified by the project support team.
Participants from the three professional groups were recruited to undertake semi-structured interviews. They were recruited by recommendation from the professional research leads or via their involvement in the Academic Practice Unit at Hospital 1. A minimum of three participants from each of the three professional groups were recruited to the study. All potential participants received a Participant Information Sheet and those recruited to the study completed and signed the relevant consent form.
The data collected from Phase 1 and Phase 2 were analysed using framework analysis by with the following stages, 1) Data entry and processing; 2) Familiarisation of the focus group and interview data collection and identifying an initial framework based on the question guide 5); 3) Coding–all focus groups and interviews were coded and indexed using NVIVO 10; 4) Generation of themes (charting) results were charted according to the themes; 5) Finalised framework (mapping and interpretation). HA transcribed each focus group and semi-structured interview as soon as was possible after facilitating the group and interview. Verbatim transcripts were produced in Microsoft Office Word 2013 from the digital audio-recordings. Participants were anonymously assigned a coded identifier within the text (e.g. speaker 1, speaker 2 etc.) to ensure the extent to which views were shared could not be identified. The verbatim text was copied in to a qualitative data analysis and coding software (QSR NVivo 10) and framework content analysis was developed to analyse the verbatim files. Qualitative research software (NVivo 10) was used to arrange information and combine analysis with linking . A framework analysis approach was used to qualitatively analyse the data . The data was coded using coding framework based on the question guide for the focus group, interviews and objectives of this study (see ). The initial 10 minutes (20%) of the transcript recording, was coded independently by two investigators, HA and CH, using the initial framework with NVivo Version 10 to assist with indexing the codes. The similarity and differences between the two coders was discussed. The differences between the two coders were resolved via discussion of differences until a consensus was reached. A resulting final framework developed. The coding framework was used to code the rest of the transcript. The interpretation of the results from the coding of the focus group and semi-structured interviews were conducted by HA and was based on the objectives of the focus group and interviews.
An electronic survey tool was chosen as the instrument for this study. Healthcare professionals working at the time of the study for Hospital 1 and Hospital 2 were invited to complete an online survey. Managing of this survey by the use of purpose designed electronic survey software was therefore considered to be both deliverable and efficient due to suitability of having automated data collection, which saves researcher time, effort and offers cost savings advantages . The questionnaire development was supported by the HCPs focus groups and the semi-structured interviews. The themes and concerns identified in the phase 1 and 2 were considered for inclusion in the survey, including for example factors influencing choice of formulations for paediatric patients. A draft survey was created on 11th August 2016 using Bristol Online Survey software (BOS). Email addresses of HCPs were obtained from the site leads at Hospital 1 and Hospital 2 (CH and chief pharmacist) respectively and they managed this process by reference to staffing lists and responses. The invitation to participate was sent from Bristol online survey to the NHS Trust email addresses of the study cohort with a link to the survey. The purpose of the survey was explained in the beginning of the survey and informed consent was presumed when the participant decided to complete the survey. First emails were sent out on with reminder emails sent to all respondents 3 and 6 weeks after the initial email was sent. Each site was required to return completed surveys from a minimum of five professionals in each group. Participants were advised that all data were held confidentiality and anonymity was assured. Responses were exported from Bristol survey into MS Excel 2013 and IBM SPSS version 22 for analysis and production of descriptive statistics.
Inclusion criteria: Healthcare professionals (HCPs) (doctor, nurse, and pharmacist) at Hospital 1. Healthcare professionals (doctor, nurse, and pharmacist) at Hospital 2. Exclusion criteria: General public
The study design was approved by both the Aston University School of Life and Health Sciences and the Research & Development Departments at both Hospital 1 and 2. All participants in the study gave informed consent. Data was only accessible by the study team. All responses were fully anonymised prior to analysis and all reports accommodated confidentiality requirements. Audio files from the focus groups/semi-structured interviews were held on-site at Hospital 1, within the secure area of the Academic Practice Unit. Once transcripts were approved, original recordings were destroyed. Additionally, paper records (from the semi-structured interviews) were also kept within the secure area of the Academic Practice Unit at Hospital 1, and were destroyed upon transcription of the interviews.
The presentation of the findings is divided into three phases. The first phase reports the focus groups of healthcare professionals; the second phase addresses the semi-structured interviews and the third phase (main phase) presents the online survey for healthcare professionals concerning paediatric dosage forms. The healthcare professionals that were selected to participate in this study were medical practitioners, pharmacists and nurses. The rational for selection of HCPs was to show the relationship leading from the prescribing (doctor) through to dispensing medicine (pharmacist) and lastly administration (nurse). Phase 1- Focus group The focus groups were used to scope the research and inform design of the online survey with healthcare professionals (phase 3) and aimed at seeking opinions of participants with a different range of backgrounds. One limitation of this method was that participants had to obligate their time to take part. Although it was planned to conduct a focus group for doctors, it was not feasible due to the clinical demands of the service. However, the information gathered from the Hospital 1 focus groups provided an understanding in to the opinions of pharmacists and nurses concerning paediatric dosage forms, whilst the sample size for doctors was proposed to be increased within the semi-structured interviews (phase 2). shows the number of participants, dates conducted and location of the focus groups. The pharmacist and nurse groups were conducted at lunchtime, it was intended that each session would last between 30 and 50 minutes. The exact timings of digital audio-recordings are shown in ( ) below and discussion flowed well between the group members. It was mentioned by a pharmacist that the most preferred dosage forms for paediatric population age (6–18 years) depends upon the patients and what they would prefer, for example if they were unable to swallow tablets, liquids are the obvious default, but if the liquid was unavailable an alternative would be suitable for example an ODT or crushable. In addition it was reported that texture and taste of ODTs was important for children so the ideal taste would be sweet with either citrus or strawberry flavours. Across the focus groups, the large sizes of tablets were related to swallowing difficulties in paediatric patients especially those less than 6 years of age. Several studies exploring children suffering from HIV support these findings and stated the negative attitudes of children regarding the size of antiretroviral tablets [ , , ]. Phase 2- Semi-structured interviews A total of 12 healthcare professionals were interviewed at Hospital 1 during the study period, the HCPs recruited for this phase of the study were predominantly medical staff (2 consultants and 4 junior doctors) ( ). All participants answered the questions regarding the paediatric dosage forms followed by properties of ODTs. Phase 2 findings suggested that the main issues with the properties of ODT formulations are those associated with taste, size and disintegration time. However, colour and shape of ODTs were highlighted the least important by 85% of respondents. Additional informal recommendations from healthcare professionals within phase 2 on how to improve ODTs formulations were reported in ( ). Overall, in phase 1 and 2, the majority of respondents (90%) recommended that taste and disintegration time were the most important properties respectively in order to develop and design ODTs formulations. Similarly, various studies stated that taste was an important factor in influencing medication adherence and acceptability in paediatric population . Phase 3- Online survey A total of 41 online surveys (study cohort n = 110, response rate 37.3%) were completed. The final online survey consisted of four sections. These were: demographic data including details of different healthcare professionals and participant years’ experience of working with paediatric patient; healthcare professionals views and their preferences for various oral dosage forms (liquids, tablets, capsules and ODTs); HCPs recommendations concerning colour, shape, size, thickness, taste, flavour and disintegration time of tablets; participant feedback about the survey and further recommendations. Section one: Demographic results of 41 healthcare professionals The first section of results displayed the number of respondents from each Hospital. Participants were from multidisciplinary professions. It gives the breakdown of their professions and years’ experience working in paediatrics. Pharmacist were the highest percentage of participants in this phase (46%) followed by nurse (29%) and medical practitioners (24%) respectively. More than half (54%) of the respondents reported their experience ranged from 1 to 5 years. The results showed a significant difference among the different healthcare professionals years of experience (p<0.05) ( ). Section two: Healthcare professionals views regarding paediatric dosage forms This section involves the analysis of the responses of the participants according to types of dosage forms that have been prescribed, supplied or given to paediatric patients. illustrated that liquids dosage forms were thought to be more popular (58%) compared to tablets (33%), ODTs (8%), capsules (1%) and other dosage forms. There was a significant difference among distribution of different dosage forms to children (p<0.05). In this study liquids were the most prescribed dosage forms among dual sites, possibly due to availability as well as shortages for other dosage forms. This was supported by evidence from who indicated that when healthcare professionals were asked to rank the factors that impact their selection of paediatric medicines, availability was the most important factor when prescribing oral medications to children. In the previous study, respondents were asked to rank their opinion on the most preferred oral dosage forms, results showed that liquids were the most popular oral dosage form (52%) followed by ODTs (30%), tablets (18%) with no preference for capsules (0%) ( ). The rational for healthcare professionals on preference of liquids in the pediatric population was possibly due to a number of factors ( ), including child age and weight, parents, cost effectivness and medicine manipulation. Furthermore, there is a regularly thought bias amongst healthcare professionals that liquids are preferred by younger children . Section three: ODTs formulations Healthcare experience regarding ODTs It is essential to mention that ODTs have become a popular area of research for scientists in the last decade as a new ‘drug delivery system’, with benefits including ODTs being a more acceptable dosage form specifically for paediatric patients due to ease of use and administration . Orally disintegrating dosage forms have great promise for paediatric patients as they are easy to administer and don’t require water, with a reduction in choking risk due to the rapid disintegration . Furthermore, previous studies and surveys stated that ODTs are well received by paediatric patients and healthcare professionals . The results in this study ( ) showed that a total of 32 (78%) healthcare professionals prescribed/dispensed or administered ODT formulations to children whereas 22% of participants did not prescribe ODTs. Additionally, respondents were asked regarding the number of ODT dosage forms that had been given to patients; approximately half of the respondents (53.7%) followed by only (2.4%) indicated that between 1 to 5 and more than 10 formulations were given over the last 12 months respectively. Interestingly, when healthcare professionals were asked concerning what extent they agree or disagree that liquid formulations could be substituted with ODTs in paediatric patients, approximately (63%) of respondents agreed that a suitable alternative to liquids was the ODT dosage form as shown in ( ). Similarly, identified that approximately 80% of prescribed liquid formulations could be substituted with a solid dosage forms in children. Considering ODTs could be an alterative to liquid formulations, healthcare professionals were asked to give their opinions regarding multiple factors such as safety, efficacy, cost effectiveness and compliance. Pharmacists indicated more benefits regarding safety and suggested that “liquid medications may be more likely to have unsuitable excipients for children particularly if they have been formulated for the adult population”. Furthermore, regarding dosing error, liquid formulations require calculation and measurement of the dose volume whereas ODT's are used because they are available in the appropriate dose and don't need further manipulation. They also mentioned that possible risk of accidental overdose for the patient was higher with liquids, for instance, if a young sibling accessed a liquid medicine they may be more likely to consume more than if they accessed ODTs. On the contrary, one pharmacist stated that a lot of solid forms come in very poor dosing variances so the tendency is to dissolve in liquid and give a proportion, but an accurate dose cannot be guaranteed. Lastly, there was a number of issues with children who have feeding tubes and the dispersed tablets blocking them. When asked regarding efficacy, the majority of participants indicated that they had no idea as there were too few ODT formulations available compared to liquids. The vast majority of respondents mentioned that in general, oral solid forms are much less costly than liquid formulations, since they are easier to develop, manufacture, transport, store and distribute. These findings were in line with previous results by who stated that solid dosage forms were more convenient and less costly compared with liquid medications for paediatric patients. With regard to compliance and adherence, respondents recommended that ODT formulations may increase compliance but it depended on the taste. Similarly, a study concluded that tablets for children may be considered as a viable alternative to improve adherence and therefore overall acceptability . Furthermore, research by confirmed that adherence to tablet formulations was significantly superior than liquid formulations. Characteristics of ODTs Acceptability and adherence of medication in paediatric patients is potentially affected by characteristics (i.e. taste, flavour, size, shape and colour) of dosage forms . Consequently, the next set of investigations were focused on assessing the healthcare professionals views and their preferences on different attributes of ODTs such as colour, taste, shape, flavour and disintegration time. Healthcare professionals were asked how medicines for children should taste. Their responses–overall and stratified by healthcare profession types are shown in ( ). The majority of participants (65%) preferred sweet tasting medicines for children followed by neutral/no taste and bitter taste (33% and 2% respectively). There was a statistically significant difference (p<0.05) between acceptable taste by healthcare care professionals. This is in line with findings from Adams who stated that the majority of participants preferred sweet tasting medicines for paediatric populations. The addition of flavours into formulations not only masks the taste of active ingredients but also improves medication adherence, for instance flavouring medicine increases patient adherence to over 90%, from an average of 50% . In the present study nearly the half of the participants (48.6%) preferred strawberry followed by orange and banana (18.9% and 17.6% respectively) while no preference (0%) was recorded for mint and lemon ( ). Overall strawberry was the most preferred flavour, significant differences were found among respondent preferences (p<0.05). Similarly, the previous study which was carried out with the paediatric population, confirmed that the participants preferred sweet taste (76.9%) along with strawberry flavour (30.8%) . Due to consideration of size and shape of dosage forms, they may affect the transit of the product through the pharynx and oesophagus and may directly affect a patient’s capability to swallow a particular drug product . The current study reported that vast majority (90.2%) of respondents’ preferred small size (5 to 7 mm) compared to the medium 9.8% (8 to 12 mm) or big with 0% preference (≥13mm), as shown in ( ). The study for opinions in paediatric patients was also in agreement with the opinion of healthcare professionals, as 64.4% of patients preferred small tablets, with large tablets being the least favour (1.9%) . The size of ODTs was potentially highlighted across all groups of healthcare professionals with small size highly recommended. Several studies support the findings and have stated the negative attitudes of children concerning big sizes of tablets [ , , ]. The chart below ( ) shows the respondents preferences based on the shape of the ODT formulations. The majority of the participants preferred ODTs that are round in shape. This accounted for 82.9% of the responses while the oval shape was second with a preference of 9.8%, approximately 4.9% reported that they had no preference for shape with the least preferred shapes being triangle and square at 2.4% and 0% respectively. Patient preference, as highlighted in the previous study, also identified round shape as the most preferred (35.6%), however patients also indicated the preference to a more profound shape such as a heart (22.1%), with square shaped tablets being negatively perceived (4.7%) . With respect to colour preferences ( ) demonstrated that white was the most preferred colour for ODTs by more than 70.0% of the respondents followed by pink (17%), yellow (5%) and finally blue (2%). A significant difference was identified by Chi-square test for colour preferences p<0.05. This was in contrast to the study conducted with paediatric patients, where pink was the preferred colour by 30.8% of patients, which was followed by white (26%) . It was worth mentioning that the selection of an appropriate colouring agent may positively impact child acceptance and also enhance medication adherence . The results in ( ) showed that the healthcare professionals opinions regarding length of time for ODT formulations to be disintegrated in the mouth, with the vast majority of the participants (95.1%) preferring very rapidly (<30sec) disintegrating ODTs followed by rapidly disintegrating ODTs (between 30 to 90 sec) at 4.9%. The opinions of the healthcare professionals in this study reflected the paediatric population from the previous study . Respondents were also asked what the most important characteristics of ODTs were and the results showed that taste was the most important property (29.5%), followed by disintegration time, flavour and size (28.7%, 21.7% and 18.6% respectively) whereas, colour and shape were the least important characteristics ( ). A significant difference was found between those characters (p<0.05). The results indicated that the most important factor was taste with the findings aligning with the published literature [ , , ]. These results reflected the previous study, which identified disintegration time and taste as the two most important factors according to patient opinion, with flavour and size also being important Section four: Further recommendations, feedback and limitations In the last section of the study, the healthcare professionals were asked to give their opinions, recommendations and feedback on how the study was conducted. The vast majority of respondents designated that regardless of the fact that it was a good idea, there were areas that could be improved. For instance, they pointed out that most questions should be asked to paediatric patients, however this had been covered in the previous study . In addition, pharmacists also indicated that there were very few ODT formulations available for example, Calpol Fast Melts, Maxalt-MLT (Rizatriptan), Nurofen Meltlets and Reglan ODT (Metoclopramide) to enable them to make an informed answer to most of the survey questions . With regard to drug manufacture and design, a few participants recommended that film formulations may be another form of oral dispersible formulations that could offer further advantages. Participants also suggested that taste was the most important property reported for ODT administration, hence the manufacturers should ensure that the taste is neutral to sweet, but not bitter. The recruitment process in focus groups (phase 1) was carried out through pharmacists and nurses but not the medical practitioner group. This may have led to under representation of doctors’ perspectives and input. Certainly some healthcare professionals participating in focus group from the same institution were known to each other, this might have been seen as a potential limitation as respondents may have been more disposed to speak in a ‘socially accepted’ style (i.e. less fairly) . The study was conducted at two sites in the UK, thus it cannot be generalised and viewed as a nationwide perspective, and further exploration in another countries is required.
The focus groups were used to scope the research and inform design of the online survey with healthcare professionals (phase 3) and aimed at seeking opinions of participants with a different range of backgrounds. One limitation of this method was that participants had to obligate their time to take part. Although it was planned to conduct a focus group for doctors, it was not feasible due to the clinical demands of the service. However, the information gathered from the Hospital 1 focus groups provided an understanding in to the opinions of pharmacists and nurses concerning paediatric dosage forms, whilst the sample size for doctors was proposed to be increased within the semi-structured interviews (phase 2). shows the number of participants, dates conducted and location of the focus groups. The pharmacist and nurse groups were conducted at lunchtime, it was intended that each session would last between 30 and 50 minutes. The exact timings of digital audio-recordings are shown in ( ) below and discussion flowed well between the group members. It was mentioned by a pharmacist that the most preferred dosage forms for paediatric population age (6–18 years) depends upon the patients and what they would prefer, for example if they were unable to swallow tablets, liquids are the obvious default, but if the liquid was unavailable an alternative would be suitable for example an ODT or crushable. In addition it was reported that texture and taste of ODTs was important for children so the ideal taste would be sweet with either citrus or strawberry flavours. Across the focus groups, the large sizes of tablets were related to swallowing difficulties in paediatric patients especially those less than 6 years of age. Several studies exploring children suffering from HIV support these findings and stated the negative attitudes of children regarding the size of antiretroviral tablets [ , , ].
A total of 12 healthcare professionals were interviewed at Hospital 1 during the study period, the HCPs recruited for this phase of the study were predominantly medical staff (2 consultants and 4 junior doctors) ( ). All participants answered the questions regarding the paediatric dosage forms followed by properties of ODTs. Phase 2 findings suggested that the main issues with the properties of ODT formulations are those associated with taste, size and disintegration time. However, colour and shape of ODTs were highlighted the least important by 85% of respondents. Additional informal recommendations from healthcare professionals within phase 2 on how to improve ODTs formulations were reported in ( ). Overall, in phase 1 and 2, the majority of respondents (90%) recommended that taste and disintegration time were the most important properties respectively in order to develop and design ODTs formulations. Similarly, various studies stated that taste was an important factor in influencing medication adherence and acceptability in paediatric population .
A total of 41 online surveys (study cohort n = 110, response rate 37.3%) were completed. The final online survey consisted of four sections. These were: demographic data including details of different healthcare professionals and participant years’ experience of working with paediatric patient; healthcare professionals views and their preferences for various oral dosage forms (liquids, tablets, capsules and ODTs); HCPs recommendations concerning colour, shape, size, thickness, taste, flavour and disintegration time of tablets; participant feedback about the survey and further recommendations.
The first section of results displayed the number of respondents from each Hospital. Participants were from multidisciplinary professions. It gives the breakdown of their professions and years’ experience working in paediatrics. Pharmacist were the highest percentage of participants in this phase (46%) followed by nurse (29%) and medical practitioners (24%) respectively. More than half (54%) of the respondents reported their experience ranged from 1 to 5 years. The results showed a significant difference among the different healthcare professionals years of experience (p<0.05) ( ).
This section involves the analysis of the responses of the participants according to types of dosage forms that have been prescribed, supplied or given to paediatric patients. illustrated that liquids dosage forms were thought to be more popular (58%) compared to tablets (33%), ODTs (8%), capsules (1%) and other dosage forms. There was a significant difference among distribution of different dosage forms to children (p<0.05). In this study liquids were the most prescribed dosage forms among dual sites, possibly due to availability as well as shortages for other dosage forms. This was supported by evidence from who indicated that when healthcare professionals were asked to rank the factors that impact their selection of paediatric medicines, availability was the most important factor when prescribing oral medications to children. In the previous study, respondents were asked to rank their opinion on the most preferred oral dosage forms, results showed that liquids were the most popular oral dosage form (52%) followed by ODTs (30%), tablets (18%) with no preference for capsules (0%) ( ). The rational for healthcare professionals on preference of liquids in the pediatric population was possibly due to a number of factors ( ), including child age and weight, parents, cost effectivness and medicine manipulation. Furthermore, there is a regularly thought bias amongst healthcare professionals that liquids are preferred by younger children .
Healthcare experience regarding ODTs It is essential to mention that ODTs have become a popular area of research for scientists in the last decade as a new ‘drug delivery system’, with benefits including ODTs being a more acceptable dosage form specifically for paediatric patients due to ease of use and administration . Orally disintegrating dosage forms have great promise for paediatric patients as they are easy to administer and don’t require water, with a reduction in choking risk due to the rapid disintegration . Furthermore, previous studies and surveys stated that ODTs are well received by paediatric patients and healthcare professionals . The results in this study ( ) showed that a total of 32 (78%) healthcare professionals prescribed/dispensed or administered ODT formulations to children whereas 22% of participants did not prescribe ODTs. Additionally, respondents were asked regarding the number of ODT dosage forms that had been given to patients; approximately half of the respondents (53.7%) followed by only (2.4%) indicated that between 1 to 5 and more than 10 formulations were given over the last 12 months respectively. Interestingly, when healthcare professionals were asked concerning what extent they agree or disagree that liquid formulations could be substituted with ODTs in paediatric patients, approximately (63%) of respondents agreed that a suitable alternative to liquids was the ODT dosage form as shown in ( ). Similarly, identified that approximately 80% of prescribed liquid formulations could be substituted with a solid dosage forms in children. Considering ODTs could be an alterative to liquid formulations, healthcare professionals were asked to give their opinions regarding multiple factors such as safety, efficacy, cost effectiveness and compliance. Pharmacists indicated more benefits regarding safety and suggested that “liquid medications may be more likely to have unsuitable excipients for children particularly if they have been formulated for the adult population”. Furthermore, regarding dosing error, liquid formulations require calculation and measurement of the dose volume whereas ODT's are used because they are available in the appropriate dose and don't need further manipulation. They also mentioned that possible risk of accidental overdose for the patient was higher with liquids, for instance, if a young sibling accessed a liquid medicine they may be more likely to consume more than if they accessed ODTs. On the contrary, one pharmacist stated that a lot of solid forms come in very poor dosing variances so the tendency is to dissolve in liquid and give a proportion, but an accurate dose cannot be guaranteed. Lastly, there was a number of issues with children who have feeding tubes and the dispersed tablets blocking them. When asked regarding efficacy, the majority of participants indicated that they had no idea as there were too few ODT formulations available compared to liquids. The vast majority of respondents mentioned that in general, oral solid forms are much less costly than liquid formulations, since they are easier to develop, manufacture, transport, store and distribute. These findings were in line with previous results by who stated that solid dosage forms were more convenient and less costly compared with liquid medications for paediatric patients. With regard to compliance and adherence, respondents recommended that ODT formulations may increase compliance but it depended on the taste. Similarly, a study concluded that tablets for children may be considered as a viable alternative to improve adherence and therefore overall acceptability . Furthermore, research by confirmed that adherence to tablet formulations was significantly superior than liquid formulations. Characteristics of ODTs Acceptability and adherence of medication in paediatric patients is potentially affected by characteristics (i.e. taste, flavour, size, shape and colour) of dosage forms . Consequently, the next set of investigations were focused on assessing the healthcare professionals views and their preferences on different attributes of ODTs such as colour, taste, shape, flavour and disintegration time. Healthcare professionals were asked how medicines for children should taste. Their responses–overall and stratified by healthcare profession types are shown in ( ). The majority of participants (65%) preferred sweet tasting medicines for children followed by neutral/no taste and bitter taste (33% and 2% respectively). There was a statistically significant difference (p<0.05) between acceptable taste by healthcare care professionals. This is in line with findings from Adams who stated that the majority of participants preferred sweet tasting medicines for paediatric populations. The addition of flavours into formulations not only masks the taste of active ingredients but also improves medication adherence, for instance flavouring medicine increases patient adherence to over 90%, from an average of 50% . In the present study nearly the half of the participants (48.6%) preferred strawberry followed by orange and banana (18.9% and 17.6% respectively) while no preference (0%) was recorded for mint and lemon ( ). Overall strawberry was the most preferred flavour, significant differences were found among respondent preferences (p<0.05). Similarly, the previous study which was carried out with the paediatric population, confirmed that the participants preferred sweet taste (76.9%) along with strawberry flavour (30.8%) . Due to consideration of size and shape of dosage forms, they may affect the transit of the product through the pharynx and oesophagus and may directly affect a patient’s capability to swallow a particular drug product . The current study reported that vast majority (90.2%) of respondents’ preferred small size (5 to 7 mm) compared to the medium 9.8% (8 to 12 mm) or big with 0% preference (≥13mm), as shown in ( ). The study for opinions in paediatric patients was also in agreement with the opinion of healthcare professionals, as 64.4% of patients preferred small tablets, with large tablets being the least favour (1.9%) . The size of ODTs was potentially highlighted across all groups of healthcare professionals with small size highly recommended. Several studies support the findings and have stated the negative attitudes of children concerning big sizes of tablets [ , , ]. The chart below ( ) shows the respondents preferences based on the shape of the ODT formulations. The majority of the participants preferred ODTs that are round in shape. This accounted for 82.9% of the responses while the oval shape was second with a preference of 9.8%, approximately 4.9% reported that they had no preference for shape with the least preferred shapes being triangle and square at 2.4% and 0% respectively. Patient preference, as highlighted in the previous study, also identified round shape as the most preferred (35.6%), however patients also indicated the preference to a more profound shape such as a heart (22.1%), with square shaped tablets being negatively perceived (4.7%) . With respect to colour preferences ( ) demonstrated that white was the most preferred colour for ODTs by more than 70.0% of the respondents followed by pink (17%), yellow (5%) and finally blue (2%). A significant difference was identified by Chi-square test for colour preferences p<0.05. This was in contrast to the study conducted with paediatric patients, where pink was the preferred colour by 30.8% of patients, which was followed by white (26%) . It was worth mentioning that the selection of an appropriate colouring agent may positively impact child acceptance and also enhance medication adherence . The results in ( ) showed that the healthcare professionals opinions regarding length of time for ODT formulations to be disintegrated in the mouth, with the vast majority of the participants (95.1%) preferring very rapidly (<30sec) disintegrating ODTs followed by rapidly disintegrating ODTs (between 30 to 90 sec) at 4.9%. The opinions of the healthcare professionals in this study reflected the paediatric population from the previous study . Respondents were also asked what the most important characteristics of ODTs were and the results showed that taste was the most important property (29.5%), followed by disintegration time, flavour and size (28.7%, 21.7% and 18.6% respectively) whereas, colour and shape were the least important characteristics ( ). A significant difference was found between those characters (p<0.05). The results indicated that the most important factor was taste with the findings aligning with the published literature [ , , ]. These results reflected the previous study, which identified disintegration time and taste as the two most important factors according to patient opinion, with flavour and size also being important
It is essential to mention that ODTs have become a popular area of research for scientists in the last decade as a new ‘drug delivery system’, with benefits including ODTs being a more acceptable dosage form specifically for paediatric patients due to ease of use and administration . Orally disintegrating dosage forms have great promise for paediatric patients as they are easy to administer and don’t require water, with a reduction in choking risk due to the rapid disintegration . Furthermore, previous studies and surveys stated that ODTs are well received by paediatric patients and healthcare professionals . The results in this study ( ) showed that a total of 32 (78%) healthcare professionals prescribed/dispensed or administered ODT formulations to children whereas 22% of participants did not prescribe ODTs. Additionally, respondents were asked regarding the number of ODT dosage forms that had been given to patients; approximately half of the respondents (53.7%) followed by only (2.4%) indicated that between 1 to 5 and more than 10 formulations were given over the last 12 months respectively. Interestingly, when healthcare professionals were asked concerning what extent they agree or disagree that liquid formulations could be substituted with ODTs in paediatric patients, approximately (63%) of respondents agreed that a suitable alternative to liquids was the ODT dosage form as shown in ( ). Similarly, identified that approximately 80% of prescribed liquid formulations could be substituted with a solid dosage forms in children. Considering ODTs could be an alterative to liquid formulations, healthcare professionals were asked to give their opinions regarding multiple factors such as safety, efficacy, cost effectiveness and compliance. Pharmacists indicated more benefits regarding safety and suggested that “liquid medications may be more likely to have unsuitable excipients for children particularly if they have been formulated for the adult population”. Furthermore, regarding dosing error, liquid formulations require calculation and measurement of the dose volume whereas ODT's are used because they are available in the appropriate dose and don't need further manipulation. They also mentioned that possible risk of accidental overdose for the patient was higher with liquids, for instance, if a young sibling accessed a liquid medicine they may be more likely to consume more than if they accessed ODTs. On the contrary, one pharmacist stated that a lot of solid forms come in very poor dosing variances so the tendency is to dissolve in liquid and give a proportion, but an accurate dose cannot be guaranteed. Lastly, there was a number of issues with children who have feeding tubes and the dispersed tablets blocking them. When asked regarding efficacy, the majority of participants indicated that they had no idea as there were too few ODT formulations available compared to liquids. The vast majority of respondents mentioned that in general, oral solid forms are much less costly than liquid formulations, since they are easier to develop, manufacture, transport, store and distribute. These findings were in line with previous results by who stated that solid dosage forms were more convenient and less costly compared with liquid medications for paediatric patients. With regard to compliance and adherence, respondents recommended that ODT formulations may increase compliance but it depended on the taste. Similarly, a study concluded that tablets for children may be considered as a viable alternative to improve adherence and therefore overall acceptability . Furthermore, research by confirmed that adherence to tablet formulations was significantly superior than liquid formulations.
Acceptability and adherence of medication in paediatric patients is potentially affected by characteristics (i.e. taste, flavour, size, shape and colour) of dosage forms . Consequently, the next set of investigations were focused on assessing the healthcare professionals views and their preferences on different attributes of ODTs such as colour, taste, shape, flavour and disintegration time. Healthcare professionals were asked how medicines for children should taste. Their responses–overall and stratified by healthcare profession types are shown in ( ). The majority of participants (65%) preferred sweet tasting medicines for children followed by neutral/no taste and bitter taste (33% and 2% respectively). There was a statistically significant difference (p<0.05) between acceptable taste by healthcare care professionals. This is in line with findings from Adams who stated that the majority of participants preferred sweet tasting medicines for paediatric populations. The addition of flavours into formulations not only masks the taste of active ingredients but also improves medication adherence, for instance flavouring medicine increases patient adherence to over 90%, from an average of 50% . In the present study nearly the half of the participants (48.6%) preferred strawberry followed by orange and banana (18.9% and 17.6% respectively) while no preference (0%) was recorded for mint and lemon ( ). Overall strawberry was the most preferred flavour, significant differences were found among respondent preferences (p<0.05). Similarly, the previous study which was carried out with the paediatric population, confirmed that the participants preferred sweet taste (76.9%) along with strawberry flavour (30.8%) . Due to consideration of size and shape of dosage forms, they may affect the transit of the product through the pharynx and oesophagus and may directly affect a patient’s capability to swallow a particular drug product . The current study reported that vast majority (90.2%) of respondents’ preferred small size (5 to 7 mm) compared to the medium 9.8% (8 to 12 mm) or big with 0% preference (≥13mm), as shown in ( ). The study for opinions in paediatric patients was also in agreement with the opinion of healthcare professionals, as 64.4% of patients preferred small tablets, with large tablets being the least favour (1.9%) . The size of ODTs was potentially highlighted across all groups of healthcare professionals with small size highly recommended. Several studies support the findings and have stated the negative attitudes of children concerning big sizes of tablets [ , , ]. The chart below ( ) shows the respondents preferences based on the shape of the ODT formulations. The majority of the participants preferred ODTs that are round in shape. This accounted for 82.9% of the responses while the oval shape was second with a preference of 9.8%, approximately 4.9% reported that they had no preference for shape with the least preferred shapes being triangle and square at 2.4% and 0% respectively. Patient preference, as highlighted in the previous study, also identified round shape as the most preferred (35.6%), however patients also indicated the preference to a more profound shape such as a heart (22.1%), with square shaped tablets being negatively perceived (4.7%) . With respect to colour preferences ( ) demonstrated that white was the most preferred colour for ODTs by more than 70.0% of the respondents followed by pink (17%), yellow (5%) and finally blue (2%). A significant difference was identified by Chi-square test for colour preferences p<0.05. This was in contrast to the study conducted with paediatric patients, where pink was the preferred colour by 30.8% of patients, which was followed by white (26%) . It was worth mentioning that the selection of an appropriate colouring agent may positively impact child acceptance and also enhance medication adherence . The results in ( ) showed that the healthcare professionals opinions regarding length of time for ODT formulations to be disintegrated in the mouth, with the vast majority of the participants (95.1%) preferring very rapidly (<30sec) disintegrating ODTs followed by rapidly disintegrating ODTs (between 30 to 90 sec) at 4.9%. The opinions of the healthcare professionals in this study reflected the paediatric population from the previous study . Respondents were also asked what the most important characteristics of ODTs were and the results showed that taste was the most important property (29.5%), followed by disintegration time, flavour and size (28.7%, 21.7% and 18.6% respectively) whereas, colour and shape were the least important characteristics ( ). A significant difference was found between those characters (p<0.05). The results indicated that the most important factor was taste with the findings aligning with the published literature [ , , ]. These results reflected the previous study, which identified disintegration time and taste as the two most important factors according to patient opinion, with flavour and size also being important
In the last section of the study, the healthcare professionals were asked to give their opinions, recommendations and feedback on how the study was conducted. The vast majority of respondents designated that regardless of the fact that it was a good idea, there were areas that could be improved. For instance, they pointed out that most questions should be asked to paediatric patients, however this had been covered in the previous study . In addition, pharmacists also indicated that there were very few ODT formulations available for example, Calpol Fast Melts, Maxalt-MLT (Rizatriptan), Nurofen Meltlets and Reglan ODT (Metoclopramide) to enable them to make an informed answer to most of the survey questions . With regard to drug manufacture and design, a few participants recommended that film formulations may be another form of oral dispersible formulations that could offer further advantages. Participants also suggested that taste was the most important property reported for ODT administration, hence the manufacturers should ensure that the taste is neutral to sweet, but not bitter. The recruitment process in focus groups (phase 1) was carried out through pharmacists and nurses but not the medical practitioner group. This may have led to under representation of doctors’ perspectives and input. Certainly some healthcare professionals participating in focus group from the same institution were known to each other, this might have been seen as a potential limitation as respondents may have been more disposed to speak in a ‘socially accepted’ style (i.e. less fairly) . The study was conducted at two sites in the UK, thus it cannot be generalised and viewed as a nationwide perspective, and further exploration in another countries is required.
In summary, this study identified a plethora of recommendations and opinions for paediatric dosage forms, particularly how ODTs are perceived by healthcare professionals. Secondly, the study identified that HCP perceived suitable organoleptic properties of ODTs (e.g. disintegration time) which influenced acceptability in paediatric patients. As a result this pragmatic study explored healthcare professional’s views and recommendations of the acceptability and characteristic properties of ODT using a mixed methods approach (focus group, semi-structured- interviews and online survey). The overall results from dual sites demonstrated that 58.0% of respondents preferred to prescribe/administer liquid dosage forms form followed by ODTs. Factors found to significantly influence choice of formulations for paediatric patients were age, weight, parent/care giver and cost effectiveness of dosage forms. Although, 63.0% of respondents agreed that liquid formulations could be substituted with ODTs in paediatric patients, the number of available ODTs were insufficient to be prescribed or administered. From the characteristics results in this study, it was concluded that taste, disintegration time and flavour were the most important properties related to ODT administration as highlighted by 29.5%, 28.7% and 21.7% of respondents. Additionally, the other important characteristics of solid dosage forms were white colour, small size, round shape, strawberry flavour and rapid disintegration time. Further studies exploring the opinions of parents concerning paediatric dosage forms would complement this research. This study also suggests that there is a need for further research to develop a wider range of ODTs for use in the paediatric population.
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A computer decision aid for medical prevention: a pilot qualitative study of the Personalized Estimate of Risks ( | acef89f0-5cd0-433c-a4ce-3077cff7208e | 317339 | Preventive Medicine[mh] | In France, a considerable number of deaths are due to preventable diseases. Ischemic heart diseases and cerebrovascular diseases still account for more than 80,000 premature deaths and breast cancer, more than 10,000 deaths. The control of the main cardiovascular risk factors, such as hypertension, remains poor, both because of lack of awareness and insufficient blood pressure control . The objectives of breast cancer screening (mammography every 2 years in women aged between 50 and 69 years recommended in French guidelines) are not completely attained either . In France, the promotion of prevention strategies in the ambulatory setting remains a national challenge. Several initiatives have been undertaken by Public Health authorities and by Health Insurance National Office, to prompt general practitioners to modify their prevention practices and improve their adherence to national guidelines. The development of the EsPeR system ( Personalised Estimate of Risks ) is one of these actions. It relies on three hypotheses: 1. for a given individual, an accurate estimation of his (her) health risks allows a more pertinent choice of prevention interventions 2. presentation of a patient-customized clinical guideline, will promote its implementation. 3. the combination of risk estimations and patient-specific guidelines embedded in a computerised decision aid can promote physician application of guideline recommendations during consultations and stimulate the communication with the patient. The objective of this paper is to describe EsPeR , a computerised decision support system designed to help prevention practices by use of risk estimates and guidelines and to present a pilot qualitative evaluation of its ergonomics, understanding and acceptance by general practitioners.
Design of EsPeR The EsPeR system is designed for health professionals and it is freely accessible on the Internet, after a simple identification process. An interactive decision support system allows an estimation of risks and a presentation of clinical guidelines. A non-interactive part describes the scientific rationale and background of the system (the documentation part) and provides its sources of medical and epidemiological knowledge (the library part). The following functional description focuses on the decision support system. Functional description The decision support system on the EsPeR website includes four primary functions: 1. Presentation of the 10 highest risks of avoidable causes of death according to demographic characteristics (age, sex and region of residence). 2. Estimation of specific risks, using published risk prediction models. 3. Individualized presentation of French guidelines on cardiovascular risk management and cancer screening 4. Printable summary of prevention messages for physicians and patients. Highest risks of death For a specific patient, the user is asked to enter the system via a screen that presents the 10 highest risks of avoidable causes of death according to demographic characteristics (age, sex and region of residence) (see figure ). The total 10-year mortality risk is displayed along with the absolute risk and the relative part of risk for each cause. These probabilities have been computed from 1) the French national statistics on the causes of deaths (along with available explicative variables (age, sex and region of residence) and 2) the French population data given by 1990 national census and intermediate estimates by INSEE (the French national Institute of Statistics and Economics). The probability of death from one cause, at a given age is estimated thanks to the method used by INSEE, based on a the use of fictitious cohort, which allows to estimate prospective probabilities from the transformation of transversal observational data . The aim of this part is to suggest a hierarchy of preventable risks that should be adjusted according to the patient specific risk factors ( e.g. consumption of tobacco and alcohol, blood pressure level, etc.). Specific risks and individualized guidelines After this first screen the physician can choose the specific risks he(she) wants to further estimate and consider for prevention in his(her) patient (cardiovascular risk, alcohol abuse screening, breast cancer, colorectal cancer, uterine cervix and prostate cancer screening, depression and suicide risk). A data input form is dynamically created with relevant clinical and biological items, once the physician has selected the risks (Figure ). For breast cancer and cardiovascular disease, the form is integrated with a module which allows to create a family tree, enter disease history for each person in the pedigree and estimate familial risk of the patient (Figure ). The validation of the form provides a risk estimate for each selected risk, and a presentation of guidelines. The method of implementation of guidelines has been previously described . It relies on a generic guideline representation model derived from the GLIF 2 (Guideline Interchange Format) model , and the use of XML as a language of representation for any specific guideline, according to a specific DTD (document type definition) of this model. An inference engine implements the guideline model and executes any specific guideline represented in XML. All original guidelines have been analysed to specify a decision algorithm, represented in XML language, and a list of elementary messages ( e.i. extracts of guideline for a given patient profile). Two physicians experienced in medical informatics performed these analysis and specifications. For a given patient, the presentation of guideline consists in 1) the list of variables ( i.e. the patient's characteristics) used in the decision algorithm, and 2) the successive elementary recommendations related to his(her) characteristics. Knowledge base All knowledge used in the system has been selected on the basis of extensive validation (according to evidence-based medicine methodology). Cardiovascular risks and breast cancer risk are computed thanks to published risk prediction models . We considered the Framingham models as sufficiently validated for cardiovascular risk stratification in various cohorts, including French ones . Since the Gail model for breast cancer has never been tested on any French data, we chose to only present an estimate of relative risk. Provided guidelines have been selected from those published by the French National Agency for Health Evaluation (ANAES) for: • Diagnosis and management of hypertension, hyperlipidemia, and type 2 diabetes • Screening for breast cancer, colorectal cancer, cervical cancer, and prostate cancer • Diagnosis of depression and suicide risk • Diagnosis and management of alcohol abuse. Printable summary Finally, a printable summary of all risk estimates and guidelines is made accessible for both physician and patient, with words and format adapted to each. Technical architecture The EsPeR system is based on a 3-tier client-server architecture. The concepts used by the decision support modules (patient data, risks estimates) are implemented in JAVA classes; these classes encapsulate relational databases with SQL queries and generate with the results HTML pages by using Active Server Pages technology. Qualitative evaluation Following published recommendations , we designed a pilot qualitative study to evaluate the ergonomics, understanding and acceptance of the interactive decision support system of EsPeR by general practitioners. The main objective of this preliminary evaluation in laboratory was to appreciate how general practitioners could use and react to EsPeR and to go in depth with them into their reactions and beliefs. A secondary objective of this study was to prepare a larger qualitative study to be organised in ambulatory practice, with use of EsPeR during consultation. Study design The study was performed in two sessions, each consisting in two focus groups. The first session was organised in January 2002 with the version 1 of the system and the second one in October 2002, with the version 2, improved according to several results of the first session. The differences between the first version and the second one concern the number of provided guidelines and the global ergonomics and navigation within the site. All focus groups were animated by three investigators (GC, IC and TD for the first and second ones, GC, IC and LL for the third and fourth ones) Each focus group was divided into four phases: 1) a structured discussion to evaluate skills and culture on prevention (at the beginning of the session) 2) a presentation of the project and short training to EsPeR ( 1 hour ), 3) an individual work on 6 to 12 structured clinical scenarios with or without EsPeR ( 2 to 4 hours ) and 4) a structured discussion to draw a consensus synthesis on the evaluation of EsPeR (at the end of the session) ( 1 to 2 hours ). The same investigator (GC) conducted discussion during phases 1 and 4 in all groups, according to outlines presented in Table , while the others (IC and TD for the 1 st session in January and IC and LL for the 2 nd session in October) took notes of the discussion. The later were asked to transcribe original comments of physicians as faithfully as possible, rather than their own interpretations. Both topics of discussion (prevention and synthesis of evaluation) were also addressed thanks to a structured individual questionnaire filled out by physicians before the corresponding discussion. During the second phase, the three investigators observed the physicians' behaviour in using the system. They collected physicians' remarks, difficulties and suggestions, along with their personal comments or opinion on these reactions. Structured clinical scenarios were formulated according to a priori hypotheses on physician's practices or beliefs, which could be in contradiction with the scientific content of EsPeR . For example, as current French guideline recommend systematic mammography screening of breast cancers in women aged 50 to 70 years, we depicted a scenario of a 43 aged women with average personal risk of breast cancer according to the Gail model (particularly, with one history of breast cancer in her mother, diagnosed at the age of 70). Physicians were asked to answer to each scenario on a structured form, about what would be their estimates of health risks and prevention strategies, whether concordant or not with EsPeR , used as decision aid. Recruitment of general practitioners Physicians were recruited differently for both sessions. For the January session, we requested volunteers in two different professional groups by the intermediate of the executive manager of each group (the National French Federation of Mutuality, which manages non for profit health centres with full-time of part time salaried GPs, and the National College of Teaching GPs). For the October session, we recruited volunteers by a mail shot to physicians who practice in two administrative departments of France (n = 437 in Indre et Loire, n = 135 in Seine et Marne) and who already participated in a prevention program organized by the CANAM (Health Insurance National Office for non salaried workers). Volunteers were asked to have minimal computer and Internet skills. In each focus group, the participants were not supposed to know each other and had no working contacts with the investigators before the sessions. All GPs were paid for their participation in the study. Data collection and analysis Demographic and professional characteristics of participants were collected by a questionnaire mailed to each participant before the session. Evaluation data were collected: 1. During the discussion phases: from discussion notes collected by two investigators 2. During individual work on clinical scenarios: from standardized structured answer form filled out by each physician for all scenarios, with open commentaries and observation notes from the three investigators 3. Using two structured questionnaires evaluating the degree of knowledge (beginning of the session) and the satisfaction of physicians with EsPeR (end of the session). Observations and discussion notes collected by the different investigators were all pooled together, with indication of the origin of each item (original comments by physicians or interpretation by investigators). They were summarized by one investigator (IC) and validated by two others (by GC and TD in January then by GC and LL in October). This qualitative verbatim of the focus group was further classified into: • Ergonomics of the system (navigation, speed, intuitiveness) • Understanding of contents • Acceptance of advices (barriers and facilitators to put guidelines into practice). We also checked the consistency of this verbatim with answers to questionnaires and we tried to infer from this verbatim some pragmatic interpretation potentially leading to concrete improvement of the EsPeR system. Finally, we analysed the answers to each individual clinical scenario as concordant or discordant with the answers recommended in EsPeR . We expressed this concordance in terms of "acceptance" ("not acceptable": no concordance with the recommendation of EsPeR and negative comments from physicians; "intermediate": no concordance but no negative comments or concordance but negative comments; "acceptable": concordance with the recommendation of EsPeR and positive comments). We tried to explain this acceptance in the light of the verbatim of the focus group.
EsPeR The EsPeR system is designed for health professionals and it is freely accessible on the Internet, after a simple identification process. An interactive decision support system allows an estimation of risks and a presentation of clinical guidelines. A non-interactive part describes the scientific rationale and background of the system (the documentation part) and provides its sources of medical and epidemiological knowledge (the library part). The following functional description focuses on the decision support system.
The decision support system on the EsPeR website includes four primary functions: 1. Presentation of the 10 highest risks of avoidable causes of death according to demographic characteristics (age, sex and region of residence). 2. Estimation of specific risks, using published risk prediction models. 3. Individualized presentation of French guidelines on cardiovascular risk management and cancer screening 4. Printable summary of prevention messages for physicians and patients. Highest risks of death For a specific patient, the user is asked to enter the system via a screen that presents the 10 highest risks of avoidable causes of death according to demographic characteristics (age, sex and region of residence) (see figure ). The total 10-year mortality risk is displayed along with the absolute risk and the relative part of risk for each cause. These probabilities have been computed from 1) the French national statistics on the causes of deaths (along with available explicative variables (age, sex and region of residence) and 2) the French population data given by 1990 national census and intermediate estimates by INSEE (the French national Institute of Statistics and Economics). The probability of death from one cause, at a given age is estimated thanks to the method used by INSEE, based on a the use of fictitious cohort, which allows to estimate prospective probabilities from the transformation of transversal observational data . The aim of this part is to suggest a hierarchy of preventable risks that should be adjusted according to the patient specific risk factors ( e.g. consumption of tobacco and alcohol, blood pressure level, etc.). Specific risks and individualized guidelines After this first screen the physician can choose the specific risks he(she) wants to further estimate and consider for prevention in his(her) patient (cardiovascular risk, alcohol abuse screening, breast cancer, colorectal cancer, uterine cervix and prostate cancer screening, depression and suicide risk). A data input form is dynamically created with relevant clinical and biological items, once the physician has selected the risks (Figure ). For breast cancer and cardiovascular disease, the form is integrated with a module which allows to create a family tree, enter disease history for each person in the pedigree and estimate familial risk of the patient (Figure ). The validation of the form provides a risk estimate for each selected risk, and a presentation of guidelines. The method of implementation of guidelines has been previously described . It relies on a generic guideline representation model derived from the GLIF 2 (Guideline Interchange Format) model , and the use of XML as a language of representation for any specific guideline, according to a specific DTD (document type definition) of this model. An inference engine implements the guideline model and executes any specific guideline represented in XML. All original guidelines have been analysed to specify a decision algorithm, represented in XML language, and a list of elementary messages ( e.i. extracts of guideline for a given patient profile). Two physicians experienced in medical informatics performed these analysis and specifications. For a given patient, the presentation of guideline consists in 1) the list of variables ( i.e. the patient's characteristics) used in the decision algorithm, and 2) the successive elementary recommendations related to his(her) characteristics. Knowledge base All knowledge used in the system has been selected on the basis of extensive validation (according to evidence-based medicine methodology). Cardiovascular risks and breast cancer risk are computed thanks to published risk prediction models . We considered the Framingham models as sufficiently validated for cardiovascular risk stratification in various cohorts, including French ones . Since the Gail model for breast cancer has never been tested on any French data, we chose to only present an estimate of relative risk. Provided guidelines have been selected from those published by the French National Agency for Health Evaluation (ANAES) for: • Diagnosis and management of hypertension, hyperlipidemia, and type 2 diabetes • Screening for breast cancer, colorectal cancer, cervical cancer, and prostate cancer • Diagnosis of depression and suicide risk • Diagnosis and management of alcohol abuse. Printable summary Finally, a printable summary of all risk estimates and guidelines is made accessible for both physician and patient, with words and format adapted to each.
For a specific patient, the user is asked to enter the system via a screen that presents the 10 highest risks of avoidable causes of death according to demographic characteristics (age, sex and region of residence) (see figure ). The total 10-year mortality risk is displayed along with the absolute risk and the relative part of risk for each cause. These probabilities have been computed from 1) the French national statistics on the causes of deaths (along with available explicative variables (age, sex and region of residence) and 2) the French population data given by 1990 national census and intermediate estimates by INSEE (the French national Institute of Statistics and Economics). The probability of death from one cause, at a given age is estimated thanks to the method used by INSEE, based on a the use of fictitious cohort, which allows to estimate prospective probabilities from the transformation of transversal observational data . The aim of this part is to suggest a hierarchy of preventable risks that should be adjusted according to the patient specific risk factors ( e.g. consumption of tobacco and alcohol, blood pressure level, etc.).
After this first screen the physician can choose the specific risks he(she) wants to further estimate and consider for prevention in his(her) patient (cardiovascular risk, alcohol abuse screening, breast cancer, colorectal cancer, uterine cervix and prostate cancer screening, depression and suicide risk). A data input form is dynamically created with relevant clinical and biological items, once the physician has selected the risks (Figure ). For breast cancer and cardiovascular disease, the form is integrated with a module which allows to create a family tree, enter disease history for each person in the pedigree and estimate familial risk of the patient (Figure ). The validation of the form provides a risk estimate for each selected risk, and a presentation of guidelines. The method of implementation of guidelines has been previously described . It relies on a generic guideline representation model derived from the GLIF 2 (Guideline Interchange Format) model , and the use of XML as a language of representation for any specific guideline, according to a specific DTD (document type definition) of this model. An inference engine implements the guideline model and executes any specific guideline represented in XML. All original guidelines have been analysed to specify a decision algorithm, represented in XML language, and a list of elementary messages ( e.i. extracts of guideline for a given patient profile). Two physicians experienced in medical informatics performed these analysis and specifications. For a given patient, the presentation of guideline consists in 1) the list of variables ( i.e. the patient's characteristics) used in the decision algorithm, and 2) the successive elementary recommendations related to his(her) characteristics.
All knowledge used in the system has been selected on the basis of extensive validation (according to evidence-based medicine methodology). Cardiovascular risks and breast cancer risk are computed thanks to published risk prediction models . We considered the Framingham models as sufficiently validated for cardiovascular risk stratification in various cohorts, including French ones . Since the Gail model for breast cancer has never been tested on any French data, we chose to only present an estimate of relative risk. Provided guidelines have been selected from those published by the French National Agency for Health Evaluation (ANAES) for: • Diagnosis and management of hypertension, hyperlipidemia, and type 2 diabetes • Screening for breast cancer, colorectal cancer, cervical cancer, and prostate cancer • Diagnosis of depression and suicide risk • Diagnosis and management of alcohol abuse.
Finally, a printable summary of all risk estimates and guidelines is made accessible for both physician and patient, with words and format adapted to each.
The EsPeR system is based on a 3-tier client-server architecture. The concepts used by the decision support modules (patient data, risks estimates) are implemented in JAVA classes; these classes encapsulate relational databases with SQL queries and generate with the results HTML pages by using Active Server Pages technology.
Following published recommendations , we designed a pilot qualitative study to evaluate the ergonomics, understanding and acceptance of the interactive decision support system of EsPeR by general practitioners. The main objective of this preliminary evaluation in laboratory was to appreciate how general practitioners could use and react to EsPeR and to go in depth with them into their reactions and beliefs. A secondary objective of this study was to prepare a larger qualitative study to be organised in ambulatory practice, with use of EsPeR during consultation.
The study was performed in two sessions, each consisting in two focus groups. The first session was organised in January 2002 with the version 1 of the system and the second one in October 2002, with the version 2, improved according to several results of the first session. The differences between the first version and the second one concern the number of provided guidelines and the global ergonomics and navigation within the site. All focus groups were animated by three investigators (GC, IC and TD for the first and second ones, GC, IC and LL for the third and fourth ones) Each focus group was divided into four phases: 1) a structured discussion to evaluate skills and culture on prevention (at the beginning of the session) 2) a presentation of the project and short training to EsPeR ( 1 hour ), 3) an individual work on 6 to 12 structured clinical scenarios with or without EsPeR ( 2 to 4 hours ) and 4) a structured discussion to draw a consensus synthesis on the evaluation of EsPeR (at the end of the session) ( 1 to 2 hours ). The same investigator (GC) conducted discussion during phases 1 and 4 in all groups, according to outlines presented in Table , while the others (IC and TD for the 1 st session in January and IC and LL for the 2 nd session in October) took notes of the discussion. The later were asked to transcribe original comments of physicians as faithfully as possible, rather than their own interpretations. Both topics of discussion (prevention and synthesis of evaluation) were also addressed thanks to a structured individual questionnaire filled out by physicians before the corresponding discussion. During the second phase, the three investigators observed the physicians' behaviour in using the system. They collected physicians' remarks, difficulties and suggestions, along with their personal comments or opinion on these reactions. Structured clinical scenarios were formulated according to a priori hypotheses on physician's practices or beliefs, which could be in contradiction with the scientific content of EsPeR . For example, as current French guideline recommend systematic mammography screening of breast cancers in women aged 50 to 70 years, we depicted a scenario of a 43 aged women with average personal risk of breast cancer according to the Gail model (particularly, with one history of breast cancer in her mother, diagnosed at the age of 70). Physicians were asked to answer to each scenario on a structured form, about what would be their estimates of health risks and prevention strategies, whether concordant or not with EsPeR , used as decision aid.
Physicians were recruited differently for both sessions. For the January session, we requested volunteers in two different professional groups by the intermediate of the executive manager of each group (the National French Federation of Mutuality, which manages non for profit health centres with full-time of part time salaried GPs, and the National College of Teaching GPs). For the October session, we recruited volunteers by a mail shot to physicians who practice in two administrative departments of France (n = 437 in Indre et Loire, n = 135 in Seine et Marne) and who already participated in a prevention program organized by the CANAM (Health Insurance National Office for non salaried workers). Volunteers were asked to have minimal computer and Internet skills. In each focus group, the participants were not supposed to know each other and had no working contacts with the investigators before the sessions. All GPs were paid for their participation in the study.
Demographic and professional characteristics of participants were collected by a questionnaire mailed to each participant before the session. Evaluation data were collected: 1. During the discussion phases: from discussion notes collected by two investigators 2. During individual work on clinical scenarios: from standardized structured answer form filled out by each physician for all scenarios, with open commentaries and observation notes from the three investigators 3. Using two structured questionnaires evaluating the degree of knowledge (beginning of the session) and the satisfaction of physicians with EsPeR (end of the session). Observations and discussion notes collected by the different investigators were all pooled together, with indication of the origin of each item (original comments by physicians or interpretation by investigators). They were summarized by one investigator (IC) and validated by two others (by GC and TD in January then by GC and LL in October). This qualitative verbatim of the focus group was further classified into: • Ergonomics of the system (navigation, speed, intuitiveness) • Understanding of contents • Acceptance of advices (barriers and facilitators to put guidelines into practice). We also checked the consistency of this verbatim with answers to questionnaires and we tried to infer from this verbatim some pragmatic interpretation potentially leading to concrete improvement of the EsPeR system. Finally, we analysed the answers to each individual clinical scenario as concordant or discordant with the answers recommended in EsPeR . We expressed this concordance in terms of "acceptance" ("not acceptable": no concordance with the recommendation of EsPeR and negative comments from physicians; "intermediate": no concordance but no negative comments or concordance but negative comments; "acceptable": concordance with the recommendation of EsPeR and positive comments). We tried to explain this acceptance in the light of the verbatim of the focus group.
Participants characteristics The four focus groups were performed respectively with a total of 36 participants (11 and 11 in January session, 8 and 6 in October session). Mean age was 48 years, 89% were male and 80% used electronic medical record software. The four groups were different in terms of professional setting and use of informatics (Table ). Problems of ergonomics Several problems of ergonomics were clearly identified with the two first groups in January (both through observation by investigators and reports by physicians). These problems concerned: • Navigation in the family tree module • Navigation between data forms and results (risk and guidelines) • Absence of archive of medical record and absence of an export function to avoid duplicate data entry (in EsPeR and in personal EMR software) Some solutions to these problems were developed for the version 2 and GPs of the October sessions found the ergonomics and navigation correct, easy to use and fast enough (see Table ). Physicians needed 15 to 20 minutes to work on one clinical scenario with EsPeR . Problems of understanding The physicians' understanding of risks was highly variable. Several of them were not familiar with a quantitative estimate of risk. They did not know how to apply the absolute risk provided in EsPeR and asked for explanations. Few participants asserted being more confident in their own risk estimate. Few GPs did not know clinical practice guidelines. Most had heard about them but did not refer to them, and few both read and used them routinely (Table ). Acceptance of EsPeR content The acceptance of the guideline messages was evaluated from GPs answers to clinical scenarios (adherence or no adherence to the messages), from their reactions observed during individual work and from the comments reported in discussion notes during open group discussion (Table ). The cardiovascular guidelines were in general better accepted than guidelines on cancer screening. Several recommendations given by EsPeR concerning cancers screening were perceived as inappropriate because of patients' demands and social or organizational pressures. Overall, physicians perceived the system as useful. Few participants would have liked to be guided more directly to select the risks that should be considered in priority for prevention for a given patient. Table presents examples of the acceptance of some recommendations of EsPeR , for different clinical situations addressed in scenarios, along with plausible explanations and solutions inferred from discussion notes and from physicians' comments.
The four focus groups were performed respectively with a total of 36 participants (11 and 11 in January session, 8 and 6 in October session). Mean age was 48 years, 89% were male and 80% used electronic medical record software. The four groups were different in terms of professional setting and use of informatics (Table ).
Several problems of ergonomics were clearly identified with the two first groups in January (both through observation by investigators and reports by physicians). These problems concerned: • Navigation in the family tree module • Navigation between data forms and results (risk and guidelines) • Absence of archive of medical record and absence of an export function to avoid duplicate data entry (in EsPeR and in personal EMR software) Some solutions to these problems were developed for the version 2 and GPs of the October sessions found the ergonomics and navigation correct, easy to use and fast enough (see Table ). Physicians needed 15 to 20 minutes to work on one clinical scenario with EsPeR .
The physicians' understanding of risks was highly variable. Several of them were not familiar with a quantitative estimate of risk. They did not know how to apply the absolute risk provided in EsPeR and asked for explanations. Few participants asserted being more confident in their own risk estimate. Few GPs did not know clinical practice guidelines. Most had heard about them but did not refer to them, and few both read and used them routinely (Table ).
EsPeR content The acceptance of the guideline messages was evaluated from GPs answers to clinical scenarios (adherence or no adherence to the messages), from their reactions observed during individual work and from the comments reported in discussion notes during open group discussion (Table ). The cardiovascular guidelines were in general better accepted than guidelines on cancer screening. Several recommendations given by EsPeR concerning cancers screening were perceived as inappropriate because of patients' demands and social or organizational pressures. Overall, physicians perceived the system as useful. Few participants would have liked to be guided more directly to select the risks that should be considered in priority for prevention for a given patient. Table presents examples of the acceptance of some recommendations of EsPeR , for different clinical situations addressed in scenarios, along with plausible explanations and solutions inferred from discussion notes and from physicians' comments.
The present paper describes a computerised system devoted to the prevention of avoidable morbidity, based on risk assessment and valid recommendations. The main objective of EsPeR is to put in perspective the different health risks for one individual and to present guideline messages appropriate for this individual. The hierarchy of risks currently relies on the presentation of French mortality data and is therefore poorly "individualized", taking into account age, sex and region of residence. A more accurate estimate of several risks is possible thanks to specific models such as the Framingham model. However, these models have been demonstrated as being adequately discriminent but poorly calibrated in French population . Other models have been recently published thanks to the SCORE project and are recommended by the Third Joint Task Force of European Societies on Cardiovascular prevention . We intend to integrate them in EsPeR . We also experienced difficulties in implementing the French guidelines on cardiovascular prevention because of the heterogeneity of recommended tools for risk stratification. We ran a pilot qualitative study in laboratory, in order to observe physicians' reaction and behaviour while using EsPeR and to find with them some explanations. We interpreted the collected verbatim and observations as potential barriers and facilitators for the diffusion of this tool. No focus group session was recorded or videotaped and no social scientist was involved in the study: the groups were animated by three different investigators among whom one was not involved directly in the design of EsPeR and supposed to be "neutral". Recruitment was different for both sessions (in January and October) and led to very different groups which interestingly suggested that different kinds of reactions may pertain to different backgrounds (socio-professional environment, use of informatics, etc.). Despite these limitations, ergonomics problems were easily identified thanks to the first two focus groups. Corrective measures were taken in the version 2 and led to solve these problems, as verified with the second session of focus groups. The main problems pertained to the content of EsPeR and presentation of knowledge. Analysis of these results led to several actions. The first one consisted in giving a feedback to the ANAES (the French national agency in charge of the development of guidelines) on difficulties encountered while computerizing guidelines. This resulted in a partnership between our laboratory and the ANAES to set up a guideline development framework designed for the guideline authors, in order for them to write directly and unequivocally "computerizable" guidelines. Our results also suggest that improving the quality of preventive strategies in the primary care setting requires considering the multiple competing demands faced by patients and physicians during each consultation. The promotion of the EsPeR system, designed for assisting physicians in setting rational priorities in prevention strategies, should therefore include both an educational intervention ( i.e. teaching evidence and the concept of risk for increasing physician's confidence in recommendations) and an organisational intervention ( i.e. increase of the consultation duration to allow the complete use of the computerised decision support system, or promote the delegation of certain tasks to nurse practitioners). The key assumption made by people developing decision aids is that providing decision support (recommendations, alerts, reminders, calculations) as well as useful clinical information at the point of care can reduce unwarranted variations in care and improve patients' health. It is generally acknowledged that computerised reminders and alerts improve the practice of simple preventive measures (screening, vaccinations...) . However, more complex decision support systems such as computerised guidelines , or calculation of cardiovascular risk did not improved quality of care in several recent well designed randomised trials. These findings can have several explanations: either the system does not work, or it is not used because it does not fit the physicians' needs or else it is in conflict with physicians beliefs and constraints. In keeping with this idea, some authors encourage evaluating computerised decision support systems not only with randomised trials . In some examples, a qualitative study helps to explain the negative of poor results of a randomised controlled trial . We therefore plan a qualitative on-field evaluation of the system to assess its usability and its acceptance by general practitioners on larger scale, in two different regions of France, before considering evaluating its impact in a randomised trial.
We presented an original computerized decision support system for medical prevention based on concepts like risks and complex knowledge found in clinical practice guidelines. The pilot qualitative evaluation of this system reinforces the need of training on its content, prior to its on-field evaluation. The main perspective of this work is the design of a larger qualitative study to evaluate the utilization and barriers to acceptance of the EsPeR system in the day to day practice. Potential important implication of this project could be the use of EsPeR as a structuring tool for prevention strategies in ambulatory medicine.
None declared.
The pre-publication history for this paper can be accessed here:
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Surgical and postoperative management of congenital heart disease: a systematic review of observational studies | 93a8eeef-ee5a-48d0-8ebd-9c0fe950919e | 11958500 | Thoracic Surgery[mh] | Congenital heart disease (CHD) is the most common congenital anomaly, affecting approximately 1% of live births worldwide . Over recent decades, advancements in diagnostic techniques and treatment have significantly increased survival rates among children born with CHD, resulting in a growing population of adolescents and adults living with the condition . Despite these advances, optimizing surgical techniques, managing anesthesia, and providing effective postoperative care remain significant challenges . Management of CHD requires a multidisciplinary approach, involving cardiac surgeons, anesthesiologists, and critical care specialists. The complexity of congenital heart defects often necessitates individualized surgical solutions . Recent innovations, such as minimally invasive procedures and hybrid approaches, have the potential to reduce perioperative complications and shorten recovery times . However, these techniques come with challenges, including technical complexity and the need for specialized training . Anesthesia management for CHD surgery has evolved, particularly in minimizing the risk of neurodevelopmental impairments. Neonates and infants undergoing heart surgery are particularly vulnerable to neurological damage during the perioperative period . To mitigate these risks, recent strategies have focused on optimizing cardiopulmonary bypass (CPB) techniques and incorporating neuroprotective measures during surgery . Beyond perioperative management, long-term outcomes, including neurodevelopmental trajectories and quality of life, are increasingly recognized as crucial factors in assessing CHD surgical success. Emerging evidence suggests that prolonged exposure to anesthesia, intraoperative cerebral perfusion strategies, and postoperative complications may contribute to cognitive and motor delays in children undergoing CHD surgery. Studies have highlighted the need for improved perioperative neuroprotection and early developmental interventions to mitigate these risks. Furthermore, most research on CHD surgical outcomes originates from high-income countries, limiting its applicability to resource-limited settings where advanced surgical techniques and specialized postoperative care may not be readily available. Addressing disparities in CHD management requires an evaluation of outcomes in diverse healthcare settings, identification of region-specific challenges, and the development of scalable solutions tailored to low-resource environments. Incorporating data from underrepresented regions will enhance the generalizability of findings and contribute to the development of equitable global standards for CHD care. This systematic review aims to examine the latest innovations and persistent challenges in CHD surgery, with a particular focus on surgical outcomes, anesthesia techniques, and postoperative management. By synthesizing the current evidence, this review seeks to identify areas for improvement and highlight potential directions for future research. Objectives This systematic review aims to synthesize the available evidence on the perioperative management of congenital heart disease, focusing on identifying risk factors, evaluating outcomes, and assessing innovations in surgical and anesthetic techniques. Specifically, it addresses the following objectives: What are the key risk factors influencing postoperative outcomes in congenital heart surgeries? What are the most effective perioperative management strategies to optimize patient recovery? How do innovations in anesthetic and surgical techniques impact patient safety and long-term outcomes? What role do biomarkers and monitoring tools play in predicting neurological and systemic complications? What systemic and economic challenges affect the implementation of evidence-based practices in congenital heart surgery?
This systematic review aims to synthesize the available evidence on the perioperative management of congenital heart disease, focusing on identifying risk factors, evaluating outcomes, and assessing innovations in surgical and anesthetic techniques. Specifically, it addresses the following objectives: What are the key risk factors influencing postoperative outcomes in congenital heart surgeries? What are the most effective perioperative management strategies to optimize patient recovery? How do innovations in anesthetic and surgical techniques impact patient safety and long-term outcomes? What role do biomarkers and monitoring tools play in predicting neurological and systemic complications? What systemic and economic challenges affect the implementation of evidence-based practices in congenital heart surgery?
Study design This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and methodological rigor. The review specifically focuses on observational studies evaluating surgical outcomes, anesthesia techniques, and postoperative management in congenital heart disease (CHD) surgeries. The population included pediatric and adult patients undergoing CHD surgery, with outcomes reviewed encompassing mortality, postoperative morbidity, neurodevelopmental outcomes, advancements in surgical techniques, and perioperative care strategies. Additionally, this review incorporates studies examining long-term neurodevelopmental outcomes in CHD patients, assessing cognitive, motor, and sensory impairments following surgical interventions. Given the increasing emphasis on global disparities in CHD management, studies from low- and middle-income countries (LMICs) were also included to explore the impact of resource availability, access to surgical care, and postoperative follow-up on patient outcomes. While randomized controlled trials (RCTs) are typically considered high-quality evidence, they were excluded from this review to maintain a focus on real-world data derived from observational study designs that reflect routine clinical practice. Search strategy A systematic search was conducted in PubMed, MEDLINE, Google Scholar, ProQuest, and Scopus databases to identify studies published between 1999 and 2024. The search terms used included combinations of keywords and Medical Subject Headings (MeSH) terms tailored to capture relevant studies. The search terms used included combinations of keywords and Medical Subject Headings (MeSH) terms tailored to capture relevant studies. The search terms were: "("congenital heart disease" OR "CHD" OR "pediatric heart surgery" OR "adult congenital heart surgery") AND ("surgical outcomes" OR "perioperative management" OR "postoperative complications" OR "mortality" OR "morbidity" OR "neurodevelopmental outcomes" OR "anesthesia techniques" OR "long-term cognitive outcomes" OR "geographical disparities in CHD management" OR "low-resource settings")." Boolean operators (AND, OR) were used to refine the search, and filters for language (English) and study type (observational studies) were applied. The reference lists of selected studies were manually screened to identify additional relevant publications. Inclusion criteria Studies were included if they met the following criteria: they were observational in design (cohort, case–control, or cross-sectional studies); focused on pediatric or adult patients undergoing congenital heart disease surgery; and reported at least one relevant outcome, including mortality, morbidity (e.g., arrhythmia, heart failure), neurodevelopmental outcomes, hospital length of stay, or advancements in surgical or anesthesia techniques. Only peer-reviewed articles published in English between 1999 and 2024 were considered eligible. Studies assessing neurodevelopmental outcomes, including cognitive, motor, and sensory impairments following CHD surgery, were included. Additionally, observational studies from low- and middle-income countries (LMICs) that evaluated geographical disparities in CHD surgical care, resource availability, and patient outcomes were considered to ensure broader generalizability. Exclusion criteria Studies were excluded if they did not report on surgical outcomes, such as mortality or morbidity, or if they focused solely on non-surgical interventions like pharmacotherapy or catheter-based procedures. Articles were also excluded if they primarily investigated diagnostic or imaging outcomes unrelated to surgical care, were review articles, RCTs, and non-peer-reviewed conference abstracts, or if they lacked sufficient sample size or control groups, where applicable. Non-human studies and non-English publications were also excluded. Data extraction Data extraction was performed independently by two reviewers using a standardized extraction form designed to collect key information such as study characteristics (e.g., author, publication year, study design), patient demographics (e.g., age, sex, underlying CHD conditions, study region), intervention details (e.g., surgical or perioperative procedures), and reported outcomes, including mortality, postoperative complications, neurodevelopmental assessments (e.g., Bayley-III, Vineland-II), and geographical disparities in patient care. Quality assessment The methodological quality of the included studies was assessed using appropriate tools tailored to their study designs. For observational studies, the Newcastle–Ottawa Scale (NOS) was employed, evaluating three domains: the selection of study participants, the comparability of study groups, and the adequacy of outcome assessment. Each observational study was scored on a scale of 0 to 9, with scores categorized as low quality (0–4 points), moderate quality (5–7 points), or high quality (8–9 points). For case reports, the Joanna Briggs Institute (JBI) checklist was used to evaluate methodological quality. The checklist assessed key aspects such as clarity in patient description, intervention details, outcome documentation, and applicability to clinical practice. Studies were rated based on an 8-point scale, with higher scores indicating greater methodological rigor. The quality assessments were conducted independently by two reviewers to ensure objectivity and reliability. Any discrepancies between the reviewers were resolved through discussion until consensus was achieved (Table ). Data synthesis A narrative synthesis was undertaken to summarize the findings from the included studies, given the heterogeneity in study designs, populations, and outcome measures. Key trends were described for mortality rates, postoperative complications, neurodevelopmental outcomes, and advancements in surgical and anesthesia techniques. To account for geographical disparities, subgroup analyses were performed to compare surgical outcomes, postoperative complications, and access to care across high-income and low- and middle-income countries (LMICs). Additionally, a comparative synthesis of neurodevelopmental impairments, stratified by surgical techniques and perioperative management, was conducted. The findings from LMIC studies were assessed to identify barriers to care, resource limitations, and differences in surgical infrastructure influencing CHD outcomes globally. Subgroup analyses were conducted to highlight differences in outcomes between pediatric and adult populations, as well as across different surgical approaches. Due to the variability in reported outcomes and study methodologies, a meta-analysis was not feasible. Ethical considerations Ethical approval was not required as the review exclusively used previously published data. The review adhered to high ethical standards, including transparency, rigorous methodology, and minimization of potential biases during data synthesis.
This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and methodological rigor. The review specifically focuses on observational studies evaluating surgical outcomes, anesthesia techniques, and postoperative management in congenital heart disease (CHD) surgeries. The population included pediatric and adult patients undergoing CHD surgery, with outcomes reviewed encompassing mortality, postoperative morbidity, neurodevelopmental outcomes, advancements in surgical techniques, and perioperative care strategies. Additionally, this review incorporates studies examining long-term neurodevelopmental outcomes in CHD patients, assessing cognitive, motor, and sensory impairments following surgical interventions. Given the increasing emphasis on global disparities in CHD management, studies from low- and middle-income countries (LMICs) were also included to explore the impact of resource availability, access to surgical care, and postoperative follow-up on patient outcomes. While randomized controlled trials (RCTs) are typically considered high-quality evidence, they were excluded from this review to maintain a focus on real-world data derived from observational study designs that reflect routine clinical practice.
A systematic search was conducted in PubMed, MEDLINE, Google Scholar, ProQuest, and Scopus databases to identify studies published between 1999 and 2024. The search terms used included combinations of keywords and Medical Subject Headings (MeSH) terms tailored to capture relevant studies. The search terms used included combinations of keywords and Medical Subject Headings (MeSH) terms tailored to capture relevant studies. The search terms were: "("congenital heart disease" OR "CHD" OR "pediatric heart surgery" OR "adult congenital heart surgery") AND ("surgical outcomes" OR "perioperative management" OR "postoperative complications" OR "mortality" OR "morbidity" OR "neurodevelopmental outcomes" OR "anesthesia techniques" OR "long-term cognitive outcomes" OR "geographical disparities in CHD management" OR "low-resource settings")." Boolean operators (AND, OR) were used to refine the search, and filters for language (English) and study type (observational studies) were applied. The reference lists of selected studies were manually screened to identify additional relevant publications.
Studies were included if they met the following criteria: they were observational in design (cohort, case–control, or cross-sectional studies); focused on pediatric or adult patients undergoing congenital heart disease surgery; and reported at least one relevant outcome, including mortality, morbidity (e.g., arrhythmia, heart failure), neurodevelopmental outcomes, hospital length of stay, or advancements in surgical or anesthesia techniques. Only peer-reviewed articles published in English between 1999 and 2024 were considered eligible. Studies assessing neurodevelopmental outcomes, including cognitive, motor, and sensory impairments following CHD surgery, were included. Additionally, observational studies from low- and middle-income countries (LMICs) that evaluated geographical disparities in CHD surgical care, resource availability, and patient outcomes were considered to ensure broader generalizability.
Studies were excluded if they did not report on surgical outcomes, such as mortality or morbidity, or if they focused solely on non-surgical interventions like pharmacotherapy or catheter-based procedures. Articles were also excluded if they primarily investigated diagnostic or imaging outcomes unrelated to surgical care, were review articles, RCTs, and non-peer-reviewed conference abstracts, or if they lacked sufficient sample size or control groups, where applicable. Non-human studies and non-English publications were also excluded.
Data extraction was performed independently by two reviewers using a standardized extraction form designed to collect key information such as study characteristics (e.g., author, publication year, study design), patient demographics (e.g., age, sex, underlying CHD conditions, study region), intervention details (e.g., surgical or perioperative procedures), and reported outcomes, including mortality, postoperative complications, neurodevelopmental assessments (e.g., Bayley-III, Vineland-II), and geographical disparities in patient care.
The methodological quality of the included studies was assessed using appropriate tools tailored to their study designs. For observational studies, the Newcastle–Ottawa Scale (NOS) was employed, evaluating three domains: the selection of study participants, the comparability of study groups, and the adequacy of outcome assessment. Each observational study was scored on a scale of 0 to 9, with scores categorized as low quality (0–4 points), moderate quality (5–7 points), or high quality (8–9 points). For case reports, the Joanna Briggs Institute (JBI) checklist was used to evaluate methodological quality. The checklist assessed key aspects such as clarity in patient description, intervention details, outcome documentation, and applicability to clinical practice. Studies were rated based on an 8-point scale, with higher scores indicating greater methodological rigor. The quality assessments were conducted independently by two reviewers to ensure objectivity and reliability. Any discrepancies between the reviewers were resolved through discussion until consensus was achieved (Table ).
A narrative synthesis was undertaken to summarize the findings from the included studies, given the heterogeneity in study designs, populations, and outcome measures. Key trends were described for mortality rates, postoperative complications, neurodevelopmental outcomes, and advancements in surgical and anesthesia techniques. To account for geographical disparities, subgroup analyses were performed to compare surgical outcomes, postoperative complications, and access to care across high-income and low- and middle-income countries (LMICs). Additionally, a comparative synthesis of neurodevelopmental impairments, stratified by surgical techniques and perioperative management, was conducted. The findings from LMIC studies were assessed to identify barriers to care, resource limitations, and differences in surgical infrastructure influencing CHD outcomes globally. Subgroup analyses were conducted to highlight differences in outcomes between pediatric and adult populations, as well as across different surgical approaches. Due to the variability in reported outcomes and study methodologies, a meta-analysis was not feasible.
Ethical approval was not required as the review exclusively used previously published data. The review adhered to high ethical standards, including transparency, rigorous methodology, and minimization of potential biases during data synthesis.
Screening and selection We identified a total of 778 titles through systematic database searches, including Google Scholar, PubMed, ProQuest, Scopus, and MEDLINE, complemented by reference list hand searches. Screening by title and abstract yielded 338 potentially eligible articles. After rigorous evaluation against the inclusion and exclusion criteria, 311 studies were excluded, leaving 27 studies for the systematic review. The study selection process is detailed in Fig. . Study characteristics The included studies comprised diverse designs and methodologies, including retrospective observational studies (10), prospective cohort studies (3), and case reports (8). Among the included studies, 6 investigated patient outcomes in low-income and resource-limited settings, providing a broader global perspective on congenital heart disease (CHD) management. Additionally, 5 studies specifically examined neurodevelopmental outcomes following CHD surgery, expanding the scope of long-term patient assessment. Geographically, the studies were conducted across multiple regions, with 5 studies from North America (United States and Canada), 4 from Europe (Germany and the Netherlands), 3 from Asia (China, Japan, and Pakistan), and 4 from low- and middle-income countries (Ethiopia, Rwanda, Kenya, and South Africa). The study populations varied significantly, including neonates, infants, children, and adults undergoing congenital heart surgeries for conditions such as Tetralogy of Fallot (TOF), Ventricular Septal Defect (VSD), Atrial Septal Defect (ASD), Patent Ductus Arteriosus (PDA) closure, coarctation of the aorta, and hypoplastic left heart syndrome (HLHS). Sample sizes ranged from 1 (case reports) to 919 (observational studies), with a median sample size of 110 patients per study. In terms of study focus, 8 studies primarily examined perioperative and surgical outcomes, including mortality, morbidity, ICU length of stay, and complications such as anastomotic leakage and respiratory distress. Six studies investigated neurological outcomes, including neurodevelopmental impairments, hearing loss, and cognitive function following surgery. Another 5 studies explored the impact of healthcare disparities and resource limitations on CHD surgical outcomes, emphasizing the challenges faced in low-income settings. The inclusion of these studies broadens the applicability of the findings and provides a more comprehensive evaluation of CHD management strategies. A detailed summary of each study, including design, setting, sample size, patient characteristics, and primary outcomes, is provided in Table . Predictive factors for postoperative outcomes Hemoglobin and oxygen saturation in tetralogy of fallot (TOF) Children undergoing surgery for TOF were found to have adverse outcomes significantly associated with reduced hemoglobin and oxygen saturation (HbSpO2) levels. Patients with HbSpO2 below the critical threshold (OR = 2.4, 95% CI: 1.8–3.1) experienced prolonged mechanical ventilation, extended ICU stays, and increased in-hospital costs. This underscores the need for rigorous preoperative optimization to enhance oxygen delivery . Predictors of anastomotic leakage In surgeries addressing esophageal atresia, anesthesia duration was a pivotal factor influencing postoperative anastomotic leakage. Procedures lasting over 360 min showed a fourfold increase in risk (OR = 4.2, 95% CI: 2.5–7.0), suggesting a critical need for time-efficient surgical interventions to reduce complications . Delayed extubation and ICU transfer Among pediatric scoliosis patients undergoing posterior spinal fusion, a high Cobb angle (> 70°), significant intraoperative bleeding (> 200 mL/kg), and prolonged surgery (> 8 h) were identified as key predictors for delayed extubation and ICU transfers. These findings emphasize the importance of preoperative pulmonary function evaluation and intraoperative strategies to mitigate risk . Risk factors in cyanotic CHD surgeries Gai et al. identified that low preoperative platelet counts (< 150,000/μL) and elevated lactate levels (> 3 mmol/L) were associated with poor outcomes in cyanotic CHD surgeries. These parameters were predictors of prolonged ICU stays (OR = 3.5, 95% CI: 1.8–6.7) and higher rates of postoperative complications, emphasizing the need for robust preoperative monitoring and intervention strategies . Innovations in perioperative management Fast-track protocols The fast-track (FT) extubation protocol demonstrated shorter ICU stays (mean reduction of 2.3 days) and reduced postoperative complications (incidence reduced by 25%) without increasing reintubation rates. However, despite its clinical benefits, inadequate reimbursement incentives in healthcare systems like the German DRG system present a significant barrier to its widespread adoption. Similar challenges are observed in other healthcare systems, such as the US DRG system, where reimbursement rates do not reflect the full benefits of early extubation protocols . Anesthetic advances in neonates Catheter-based PDA closure in neonates weighing under 3 kg showcased high success rates, with only minimal perioperative complications such as hypothermia (5% incidence) and transfusions (2% incidence). The findings highlight the importance of standardized, multidisciplinary approaches for high-risk neonates . Tailored anesthetic techniques In patients with complex cardiovascular conditions, tailored anesthesia proved critical. For example, epidural anesthesia for cesarean sections in women with Fontan circulation ensured stable hemodynamics, while laparoscopic gastrectomy in patients with coarctation of the aorta emphasized pain control and blood pressure management . Blood conservation techniques Jehovah’s Witness patients undergoing hybrid procedures for hypoplastic left heart syndrome benefited from innovative blood conservation strategies. Techniques such as acute normovolemic hemodilution and customized cardiopulmonary bypass adjustments minimized the need for allogeneic blood products, addressing both ethical and medical concerns . Neurological implications Biomarkers of brain injury Amplitude-integrated EEG (aEEG) emerged as a powerful early marker for identifying neonates at risk of brain injury during cardiac surgeries. Abnormal patterns such as burst suppression and ictal discharges were strongly associated with postoperative brain injuries (OR = 3.8, 95% CI: 2.5–5.8), providing clinicians with actionable insights for early intervention . Cerebral oxygenation Lower intraoperative cerebral oxygen saturation (< 55%) was significantly correlated with elevated glial fibrillary acid protein levels (> 3 ng/mL), a biomarker for hypoxic-ischemic brain injury (OR = 4.5, 95% CI: 2.2–9.0). This highlights the critical need for neuroprotective strategies during surgeries like the Norwood procedure . Neurodevelopmental delays after CHD surgery Neurodevelopmental impairments remain a major concern in CHD patients, particularly those undergoing complex neonatal surgeries. A retrospective cohort study found that cumulative ketamine exposure was associated with lower motor scores at 18 months (mean reduction: 0.34 points per mg/kg, P = 0.024). However, exposure to volatile anesthetic agents was not correlated with cognitive impairments, suggesting a selective effect of anesthetic type on developmental trajectories . Long-term cognitive and language outcomes A 4-year follow-up study found that 21.6% of CHD survivors exhibited hearing loss, which was significantly associated with worse language and cognitive scores ( P < 0.01). Risk factors included younger gestational age, prolonged ICU stay, and presence of genetic anomalies. These findings emphasize the need for early audiological screening in CHD patients and highlight hearing loss as a modifiable risk factor for long-term neurodevelopment . Intraoperative EEG suppression and cognitive outcomes Neonates who developed prolonged intraoperative EEG suppression had significantly lower communication scores at age 5 ( P < 0.01). In particular, EEG isoelectric states lasting > 90 min correlated with reduced Vineland-II scores, reinforcing the importance of real-time brain monitoring during CHD surgery . Case-specific clinical challenges Complex surgical scenarios Unique cases provided valuable insights into perioperative challenges. A middle-aged patient with unrepaired TOF undergoing laparoscopic cholecystectomy demonstrated the importance of comprehensive preoperative planning and pharmacological adjustments . Similarly, prone positioning effectively reduced respiratory distress in a patient with TOF and absent pulmonary valve syndrome, showcasing a simple yet impactful postoperative strategy . Thoracic surgery complications The Nuss procedure, despite its minimally invasive nature, was associated with rare but severe complications like pneumothorax (3% incidence) and subcutaneous emphysema (5% incidence). Effective management of these events emphasized the role of vigilant postoperative monitoring and timely interventions . PFO and postoperative outcomes in non-cardiac surgeries explored the role of patent foramen ovale (PFO) in patients undergoing elective hip and knee arthroplasties. Despite concerns about paradoxical embolism, their study revealed a low incidence of postoperative delirium (0.5%) and no major adverse cardiovascular events in patients with PFO. This underscores the limited clinical relevance of routine PFO screening in non-cardiac surgeries, while highlighting the potential for advanced imaging techniques, like transthoracic echocardiography with bubble studies, to refine perioperative risk assessment. Systemic and economic considerations Healthcare policy barriers Key findings from this review underscore the importance of careful perioperative management in congenital heart disease, focusing on predictors of postoperative outcomes, advancements in anesthetic techniques, and the growing role of multidisciplinary care in reducing complications. Furthermore, challenges in health economics and reimbursement, particularly in the German DRG system, remain critical barriers to the widespread adoption of FT protocols, underscoring the need for policy reforms to align reimbursement models with clinical benefits . Optimizing resource utilization Efficient utilization of resources, including personnel and ICU capacities, was emphasized in studies adopting FT protocols. Despite reduced staffing, these units maintained excellent postoperative outcomes, suggesting that workflow optimizations can significantly benefit healthcare systems . Synthesis of findings This review highlights significant advancements in surgical techniques, perioperative management, and neurological monitoring for patients with congenital heart disease. The integration of personalized strategies—such as tailored anesthesia, fast-track protocols, and neuroprotective interventions—demonstrates a shift toward optimizing outcomes while minimizing risks. However, systemic barriers, such as inadequate reimbursement models, remain a critical challenge, underscoring the need for policy reforms to incentivize high-quality care. Geographical disparities in CHD surgery Significant disparities exist in CHD surgical outcomes between high-income and low-income settings. A study conducted in Ethiopia found that 39.5% of pediatric CHD patients developed postoperative complications, with prolonged ICU stays and increased mortality rates compared to high-income countries . Similarly, malnutrition and late referrals in South Africa were associated with poorer growth recovery and delayed cognitive development after surgery . In a 10-year review of CHD surgery in Cambodia and Mozambique, postoperative mortality was significantly higher in Mozambique (6.1%) compared to Cambodia (3.1%), largely due to limited access to specialized pediatric ICUs and post-surgical follow-up challenges . Additionally, a study from Rwanda’s first pediatric cardiac surgery program demonstrated favorable 30-day mortality outcomes (1.9%), reinforcing the feasibility of developing sustainable CHD programs in LMICs . These findings highlight the need for global collaborations, investment in surgical training, and expansion of pediatric cardiac ICUs to bridge the disparity gap in CHD management.
We identified a total of 778 titles through systematic database searches, including Google Scholar, PubMed, ProQuest, Scopus, and MEDLINE, complemented by reference list hand searches. Screening by title and abstract yielded 338 potentially eligible articles. After rigorous evaluation against the inclusion and exclusion criteria, 311 studies were excluded, leaving 27 studies for the systematic review. The study selection process is detailed in Fig. .
The included studies comprised diverse designs and methodologies, including retrospective observational studies (10), prospective cohort studies (3), and case reports (8). Among the included studies, 6 investigated patient outcomes in low-income and resource-limited settings, providing a broader global perspective on congenital heart disease (CHD) management. Additionally, 5 studies specifically examined neurodevelopmental outcomes following CHD surgery, expanding the scope of long-term patient assessment. Geographically, the studies were conducted across multiple regions, with 5 studies from North America (United States and Canada), 4 from Europe (Germany and the Netherlands), 3 from Asia (China, Japan, and Pakistan), and 4 from low- and middle-income countries (Ethiopia, Rwanda, Kenya, and South Africa). The study populations varied significantly, including neonates, infants, children, and adults undergoing congenital heart surgeries for conditions such as Tetralogy of Fallot (TOF), Ventricular Septal Defect (VSD), Atrial Septal Defect (ASD), Patent Ductus Arteriosus (PDA) closure, coarctation of the aorta, and hypoplastic left heart syndrome (HLHS). Sample sizes ranged from 1 (case reports) to 919 (observational studies), with a median sample size of 110 patients per study. In terms of study focus, 8 studies primarily examined perioperative and surgical outcomes, including mortality, morbidity, ICU length of stay, and complications such as anastomotic leakage and respiratory distress. Six studies investigated neurological outcomes, including neurodevelopmental impairments, hearing loss, and cognitive function following surgery. Another 5 studies explored the impact of healthcare disparities and resource limitations on CHD surgical outcomes, emphasizing the challenges faced in low-income settings. The inclusion of these studies broadens the applicability of the findings and provides a more comprehensive evaluation of CHD management strategies. A detailed summary of each study, including design, setting, sample size, patient characteristics, and primary outcomes, is provided in Table .
Hemoglobin and oxygen saturation in tetralogy of fallot (TOF) Children undergoing surgery for TOF were found to have adverse outcomes significantly associated with reduced hemoglobin and oxygen saturation (HbSpO2) levels. Patients with HbSpO2 below the critical threshold (OR = 2.4, 95% CI: 1.8–3.1) experienced prolonged mechanical ventilation, extended ICU stays, and increased in-hospital costs. This underscores the need for rigorous preoperative optimization to enhance oxygen delivery . Predictors of anastomotic leakage In surgeries addressing esophageal atresia, anesthesia duration was a pivotal factor influencing postoperative anastomotic leakage. Procedures lasting over 360 min showed a fourfold increase in risk (OR = 4.2, 95% CI: 2.5–7.0), suggesting a critical need for time-efficient surgical interventions to reduce complications . Delayed extubation and ICU transfer Among pediatric scoliosis patients undergoing posterior spinal fusion, a high Cobb angle (> 70°), significant intraoperative bleeding (> 200 mL/kg), and prolonged surgery (> 8 h) were identified as key predictors for delayed extubation and ICU transfers. These findings emphasize the importance of preoperative pulmonary function evaluation and intraoperative strategies to mitigate risk . Risk factors in cyanotic CHD surgeries Gai et al. identified that low preoperative platelet counts (< 150,000/μL) and elevated lactate levels (> 3 mmol/L) were associated with poor outcomes in cyanotic CHD surgeries. These parameters were predictors of prolonged ICU stays (OR = 3.5, 95% CI: 1.8–6.7) and higher rates of postoperative complications, emphasizing the need for robust preoperative monitoring and intervention strategies .
Children undergoing surgery for TOF were found to have adverse outcomes significantly associated with reduced hemoglobin and oxygen saturation (HbSpO2) levels. Patients with HbSpO2 below the critical threshold (OR = 2.4, 95% CI: 1.8–3.1) experienced prolonged mechanical ventilation, extended ICU stays, and increased in-hospital costs. This underscores the need for rigorous preoperative optimization to enhance oxygen delivery .
In surgeries addressing esophageal atresia, anesthesia duration was a pivotal factor influencing postoperative anastomotic leakage. Procedures lasting over 360 min showed a fourfold increase in risk (OR = 4.2, 95% CI: 2.5–7.0), suggesting a critical need for time-efficient surgical interventions to reduce complications .
Among pediatric scoliosis patients undergoing posterior spinal fusion, a high Cobb angle (> 70°), significant intraoperative bleeding (> 200 mL/kg), and prolonged surgery (> 8 h) were identified as key predictors for delayed extubation and ICU transfers. These findings emphasize the importance of preoperative pulmonary function evaluation and intraoperative strategies to mitigate risk .
Gai et al. identified that low preoperative platelet counts (< 150,000/μL) and elevated lactate levels (> 3 mmol/L) were associated with poor outcomes in cyanotic CHD surgeries. These parameters were predictors of prolonged ICU stays (OR = 3.5, 95% CI: 1.8–6.7) and higher rates of postoperative complications, emphasizing the need for robust preoperative monitoring and intervention strategies .
Fast-track protocols The fast-track (FT) extubation protocol demonstrated shorter ICU stays (mean reduction of 2.3 days) and reduced postoperative complications (incidence reduced by 25%) without increasing reintubation rates. However, despite its clinical benefits, inadequate reimbursement incentives in healthcare systems like the German DRG system present a significant barrier to its widespread adoption. Similar challenges are observed in other healthcare systems, such as the US DRG system, where reimbursement rates do not reflect the full benefits of early extubation protocols . Anesthetic advances in neonates Catheter-based PDA closure in neonates weighing under 3 kg showcased high success rates, with only minimal perioperative complications such as hypothermia (5% incidence) and transfusions (2% incidence). The findings highlight the importance of standardized, multidisciplinary approaches for high-risk neonates . Tailored anesthetic techniques In patients with complex cardiovascular conditions, tailored anesthesia proved critical. For example, epidural anesthesia for cesarean sections in women with Fontan circulation ensured stable hemodynamics, while laparoscopic gastrectomy in patients with coarctation of the aorta emphasized pain control and blood pressure management . Blood conservation techniques Jehovah’s Witness patients undergoing hybrid procedures for hypoplastic left heart syndrome benefited from innovative blood conservation strategies. Techniques such as acute normovolemic hemodilution and customized cardiopulmonary bypass adjustments minimized the need for allogeneic blood products, addressing both ethical and medical concerns .
The fast-track (FT) extubation protocol demonstrated shorter ICU stays (mean reduction of 2.3 days) and reduced postoperative complications (incidence reduced by 25%) without increasing reintubation rates. However, despite its clinical benefits, inadequate reimbursement incentives in healthcare systems like the German DRG system present a significant barrier to its widespread adoption. Similar challenges are observed in other healthcare systems, such as the US DRG system, where reimbursement rates do not reflect the full benefits of early extubation protocols .
Catheter-based PDA closure in neonates weighing under 3 kg showcased high success rates, with only minimal perioperative complications such as hypothermia (5% incidence) and transfusions (2% incidence). The findings highlight the importance of standardized, multidisciplinary approaches for high-risk neonates .
In patients with complex cardiovascular conditions, tailored anesthesia proved critical. For example, epidural anesthesia for cesarean sections in women with Fontan circulation ensured stable hemodynamics, while laparoscopic gastrectomy in patients with coarctation of the aorta emphasized pain control and blood pressure management .
Jehovah’s Witness patients undergoing hybrid procedures for hypoplastic left heart syndrome benefited from innovative blood conservation strategies. Techniques such as acute normovolemic hemodilution and customized cardiopulmonary bypass adjustments minimized the need for allogeneic blood products, addressing both ethical and medical concerns .
Biomarkers of brain injury Amplitude-integrated EEG (aEEG) emerged as a powerful early marker for identifying neonates at risk of brain injury during cardiac surgeries. Abnormal patterns such as burst suppression and ictal discharges were strongly associated with postoperative brain injuries (OR = 3.8, 95% CI: 2.5–5.8), providing clinicians with actionable insights for early intervention . Cerebral oxygenation Lower intraoperative cerebral oxygen saturation (< 55%) was significantly correlated with elevated glial fibrillary acid protein levels (> 3 ng/mL), a biomarker for hypoxic-ischemic brain injury (OR = 4.5, 95% CI: 2.2–9.0). This highlights the critical need for neuroprotective strategies during surgeries like the Norwood procedure . Neurodevelopmental delays after CHD surgery Neurodevelopmental impairments remain a major concern in CHD patients, particularly those undergoing complex neonatal surgeries. A retrospective cohort study found that cumulative ketamine exposure was associated with lower motor scores at 18 months (mean reduction: 0.34 points per mg/kg, P = 0.024). However, exposure to volatile anesthetic agents was not correlated with cognitive impairments, suggesting a selective effect of anesthetic type on developmental trajectories . Long-term cognitive and language outcomes A 4-year follow-up study found that 21.6% of CHD survivors exhibited hearing loss, which was significantly associated with worse language and cognitive scores ( P < 0.01). Risk factors included younger gestational age, prolonged ICU stay, and presence of genetic anomalies. These findings emphasize the need for early audiological screening in CHD patients and highlight hearing loss as a modifiable risk factor for long-term neurodevelopment . Intraoperative EEG suppression and cognitive outcomes Neonates who developed prolonged intraoperative EEG suppression had significantly lower communication scores at age 5 ( P < 0.01). In particular, EEG isoelectric states lasting > 90 min correlated with reduced Vineland-II scores, reinforcing the importance of real-time brain monitoring during CHD surgery .
Amplitude-integrated EEG (aEEG) emerged as a powerful early marker for identifying neonates at risk of brain injury during cardiac surgeries. Abnormal patterns such as burst suppression and ictal discharges were strongly associated with postoperative brain injuries (OR = 3.8, 95% CI: 2.5–5.8), providing clinicians with actionable insights for early intervention .
Lower intraoperative cerebral oxygen saturation (< 55%) was significantly correlated with elevated glial fibrillary acid protein levels (> 3 ng/mL), a biomarker for hypoxic-ischemic brain injury (OR = 4.5, 95% CI: 2.2–9.0). This highlights the critical need for neuroprotective strategies during surgeries like the Norwood procedure .
Neurodevelopmental impairments remain a major concern in CHD patients, particularly those undergoing complex neonatal surgeries. A retrospective cohort study found that cumulative ketamine exposure was associated with lower motor scores at 18 months (mean reduction: 0.34 points per mg/kg, P = 0.024). However, exposure to volatile anesthetic agents was not correlated with cognitive impairments, suggesting a selective effect of anesthetic type on developmental trajectories .
A 4-year follow-up study found that 21.6% of CHD survivors exhibited hearing loss, which was significantly associated with worse language and cognitive scores ( P < 0.01). Risk factors included younger gestational age, prolonged ICU stay, and presence of genetic anomalies. These findings emphasize the need for early audiological screening in CHD patients and highlight hearing loss as a modifiable risk factor for long-term neurodevelopment .
Neonates who developed prolonged intraoperative EEG suppression had significantly lower communication scores at age 5 ( P < 0.01). In particular, EEG isoelectric states lasting > 90 min correlated with reduced Vineland-II scores, reinforcing the importance of real-time brain monitoring during CHD surgery .
Complex surgical scenarios Unique cases provided valuable insights into perioperative challenges. A middle-aged patient with unrepaired TOF undergoing laparoscopic cholecystectomy demonstrated the importance of comprehensive preoperative planning and pharmacological adjustments . Similarly, prone positioning effectively reduced respiratory distress in a patient with TOF and absent pulmonary valve syndrome, showcasing a simple yet impactful postoperative strategy . Thoracic surgery complications The Nuss procedure, despite its minimally invasive nature, was associated with rare but severe complications like pneumothorax (3% incidence) and subcutaneous emphysema (5% incidence). Effective management of these events emphasized the role of vigilant postoperative monitoring and timely interventions . PFO and postoperative outcomes in non-cardiac surgeries explored the role of patent foramen ovale (PFO) in patients undergoing elective hip and knee arthroplasties. Despite concerns about paradoxical embolism, their study revealed a low incidence of postoperative delirium (0.5%) and no major adverse cardiovascular events in patients with PFO. This underscores the limited clinical relevance of routine PFO screening in non-cardiac surgeries, while highlighting the potential for advanced imaging techniques, like transthoracic echocardiography with bubble studies, to refine perioperative risk assessment.
Unique cases provided valuable insights into perioperative challenges. A middle-aged patient with unrepaired TOF undergoing laparoscopic cholecystectomy demonstrated the importance of comprehensive preoperative planning and pharmacological adjustments . Similarly, prone positioning effectively reduced respiratory distress in a patient with TOF and absent pulmonary valve syndrome, showcasing a simple yet impactful postoperative strategy .
The Nuss procedure, despite its minimally invasive nature, was associated with rare but severe complications like pneumothorax (3% incidence) and subcutaneous emphysema (5% incidence). Effective management of these events emphasized the role of vigilant postoperative monitoring and timely interventions .
explored the role of patent foramen ovale (PFO) in patients undergoing elective hip and knee arthroplasties. Despite concerns about paradoxical embolism, their study revealed a low incidence of postoperative delirium (0.5%) and no major adverse cardiovascular events in patients with PFO. This underscores the limited clinical relevance of routine PFO screening in non-cardiac surgeries, while highlighting the potential for advanced imaging techniques, like transthoracic echocardiography with bubble studies, to refine perioperative risk assessment.
Healthcare policy barriers Key findings from this review underscore the importance of careful perioperative management in congenital heart disease, focusing on predictors of postoperative outcomes, advancements in anesthetic techniques, and the growing role of multidisciplinary care in reducing complications. Furthermore, challenges in health economics and reimbursement, particularly in the German DRG system, remain critical barriers to the widespread adoption of FT protocols, underscoring the need for policy reforms to align reimbursement models with clinical benefits . Optimizing resource utilization Efficient utilization of resources, including personnel and ICU capacities, was emphasized in studies adopting FT protocols. Despite reduced staffing, these units maintained excellent postoperative outcomes, suggesting that workflow optimizations can significantly benefit healthcare systems .
Key findings from this review underscore the importance of careful perioperative management in congenital heart disease, focusing on predictors of postoperative outcomes, advancements in anesthetic techniques, and the growing role of multidisciplinary care in reducing complications. Furthermore, challenges in health economics and reimbursement, particularly in the German DRG system, remain critical barriers to the widespread adoption of FT protocols, underscoring the need for policy reforms to align reimbursement models with clinical benefits .
Efficient utilization of resources, including personnel and ICU capacities, was emphasized in studies adopting FT protocols. Despite reduced staffing, these units maintained excellent postoperative outcomes, suggesting that workflow optimizations can significantly benefit healthcare systems .
This review highlights significant advancements in surgical techniques, perioperative management, and neurological monitoring for patients with congenital heart disease. The integration of personalized strategies—such as tailored anesthesia, fast-track protocols, and neuroprotective interventions—demonstrates a shift toward optimizing outcomes while minimizing risks. However, systemic barriers, such as inadequate reimbursement models, remain a critical challenge, underscoring the need for policy reforms to incentivize high-quality care.
Significant disparities exist in CHD surgical outcomes between high-income and low-income settings. A study conducted in Ethiopia found that 39.5% of pediatric CHD patients developed postoperative complications, with prolonged ICU stays and increased mortality rates compared to high-income countries . Similarly, malnutrition and late referrals in South Africa were associated with poorer growth recovery and delayed cognitive development after surgery . In a 10-year review of CHD surgery in Cambodia and Mozambique, postoperative mortality was significantly higher in Mozambique (6.1%) compared to Cambodia (3.1%), largely due to limited access to specialized pediatric ICUs and post-surgical follow-up challenges . Additionally, a study from Rwanda’s first pediatric cardiac surgery program demonstrated favorable 30-day mortality outcomes (1.9%), reinforcing the feasibility of developing sustainable CHD programs in LMICs . These findings highlight the need for global collaborations, investment in surgical training, and expansion of pediatric cardiac ICUs to bridge the disparity gap in CHD management.
Overview of findings This systematic review synthesizes data from 27 observational studies, which collectively highlight advancements in congenital heart surgery, perioperative management, and the identification of postoperative risk factors. The reviewed studies demonstrate the importance of individualized perioperative care, predictive models for postoperative outcomes, and emerging technologies like biomarkers and point-of-care imaging. Despite these advancements, challenges such as economic inefficiencies, systemic barriers, and the need for neurological monitoring remain pressing. While surgical techniques have progressed significantly, addressing healthcare system inefficiencies and resource allocation issues will be pivotal in ensuring equitable access to high-quality care (Tables , ). A comprehensive policy approach must be devised to support these best practices, which should include addressing the gap between clinical outcomes and financial incentives (Table ). Moreover, this review expands on previously underexplored areas, including long-term neurodevelopmental outcomes after CHD surgery and disparities in surgical outcomes between high-income and low-income countries. By incorporating these additional perspectives, this review provides a more comprehensive understanding of CHD management challenges and opportunities worldwide. Postoperative risk prediction and management The identification of predictive factors for postoperative outcomes has been a major focus of this review, particularly in relation to preoperative optimization and the integration of predictive models into clinical practice. For example, demonstrated that hemoglobin and oxygen saturation (HbSpO2) levels were strong predictors of adverse outcomes in children with TOF. These findings support the early identification of at-risk patients and the optimization of preoperative care. Similarly, Ishimaru et al. emphasized that long anesthesia duration in esophageal atresia surgeries was a critical factor in increased complications, advocating for streamlined surgical processes. The ability to identify these risks early and integrate them into clinical decision-making could significantly improve outcomes while optimizing resource allocation. highlights the need for streamlined surgical processes to minimize complications. These findings collectively support integrating predictive models into preoperative planning to guide clinical decision-making. The findings regarding delayed extubation and ICU transfers in pediatric scoliosis patients undergoing posterior fusion further broaden our understanding of perioperative risk factors, such as high Cobb angle and pulmonary dysfunction. The delayed extubation and ICU transfer risks in pediatric scoliosis patients further emphasize the importance of individualizing perioperative management strategies. High-risk factors, such as high Cobb angle and pulmonary dysfunction, can be mitigated with early recognition and targeted interventions. Integrating predictive models into preoperative planning will help clinicians tailor interventions, reduce hospital stays, and improve recovery times. These insights enable healthcare providers to tailor perioperative management strategies, improving patient outcomes and resource utilization. Additionally, findings from low-income settings reveal distinct risk factors that impact postoperative outcomes, including malnutrition, delayed surgical intervention, and limited access to intensive postoperative care. Studies from Ethiopia, Rwanda, and Kenya indicate that preoperative malnutrition significantly contributes to increased mortality and prolonged ICU stays in CHD patients. These insights underscore the urgent need for targeted interventions, including early nutritional support and improved perioperative monitoring, to enhance surgical outcomes in resource-limited settings [ , , ]. Advances in perioperative management Fast-track protocols Fast-track extubation protocols have consistently demonstrated reduced ICU stays and postoperative morbidity, as seen in the study by . However, the economic barriers to implementing these protocols remain significant. In healthcare systems like the German DRG model, the lack of reimbursement for resource-efficient practices such as FT protocols discourages their adoption, despite the clinical evidence supporting their effectiveness. Policy solutions could focus on aligning reimbursement policies with clinical outcomes, ensuring that hospitals are financially incentivized to adopt evidence-based best practices. One potential solution is to implement outcome-based reimbursement models, where hospitals are reimbursed based on the quality of care provided, rather than the quantity of services rendered. This would foster the adoption of cost-effective, outcome-driven approaches, such as FT protocols, across healthcare systems. Tailored anesthetic techniques The review also highlights the success of tailored anesthetic techniques in complex surgeries, such as those performed on Fontan circulation patients undergoing cesarean sections and those undergoing gastrectomy for coarctation of the aorta , demonstrate how individualized care can improve outcomes in high-risk scenarios. These cases underscore the importance of individualized care in improving outcomes for high-risk patients. The integration of minimally invasive techniques, like catheter-based PDA closure is another area where advancements have demonstrated significant benefits in reducing complications and improving recovery times. Tailored care should be considered a standard of practice for complex surgeries, and training programs for anesthesiologists and surgeons should be expanded to emphasize these individualized approaches. Blood conservation strategies In patients with religious or medical contraindications to transfusion, such as Jehovah’s Witness patients, blood conservation strategies have been critical in reducing reliance on allogeneic blood products. Techniques like normovolemic hemodilution and adjustments to cardiopulmonary bypass protocols can be effective alternatives. Expanding the use of blood conservation techniques should be promoted through policy incentives for centers that adopt such practices. Financial incentives or reimbursement adjustments for hospitals implementing innovative, blood-saving protocols would encourage more centers to adopt these practices, improving patient safety and reducing complications related to blood transfusion. Neuroprotective strategies in perioperative care Neurodevelopmental impairments are a significant concern for infants undergoing CHD surgery. Emerging evidence suggests that prolonged exposure to anesthesia and intraoperative brain activity suppression may contribute to long-term cognitive deficits. Studies have identified key biomarkers, such as glial fibrillary acidic protein (GFAP), as predictors of brain injury in neonates undergoing cardiac surgery. Additionally, intraoperative EEG monitoring has been shown to detect prolonged cortical isoelectric states, which correlate with adverse neurodevelopmental outcomes. By integrating real-time neurophysiological monitoring and modifying anesthesia protocols, clinicians can potentially reduce the risk of neurological complications and optimize long-term outcomes for CHD patients . Neurological outcomes and monitoring Biomarkers and monitoring The introduction of biomarkers like glial fibrillary acid protein (GFAP) and amplitude-integrated EEG (aEEG) offers significant advantages in monitoring neurological outcomes in neonates undergoing cardiac surgeries . These tools provide early indicators of brain injury, which allows for timely interventions that can improve long-term neurodevelopmental outcomes. Integrating these technologies into routine clinical practice should be a priority, as it could dramatically improve the quality of care for high-risk neonates. Reimbursement for these diagnostic tools should be expanded to support widespread use, with policymakers adjusting coding systems to account for the value of advanced neurological monitoring. (Table ). Implications for neonatal care The association of neurological complications with burst suppression and ictal discharges reinforces the need for neuroprotective strategies during high-risk surgeries like the Norwood and arterial switch procedures. The implementation of neurological monitoring in these surgeries can allow for the detection of issues intraoperatively, reducing the risk of long-term brain injury. Neuroprotective strategies could be incorporated into standardized care protocols, and funding for research into advanced monitoring techniques should be prioritized to further improve care. Beyond immediate surgical outcomes, recent studies highlight the long-term neurodevelopmental consequences of congenital heart surgery. Prolonged ICU stays and mechanical ventilation have been linked to developmental delays, underscoring the importance of minimizing unnecessary sedation and optimizing early postoperative rehabilitation. Furthermore, findings suggest that hearing loss is an underrecognized yet prevalent issue among CHD survivors, with significant implications for cognitive and language development. Systematic post-surgical auditory screening and early intervention strategies are necessary to mitigate these risks and improve long-term quality of life in CHD patients. Diagnostic advances in neurological monitoring The study by The study by Gai et al. demonstrates the utility of point-of-care imaging, such as transthoracic echocardiography (TTE) with bubble studies, in refining perioperative risk assessment. While the study found minimal impact on outcomes such as postoperative delirium in patients with patent foramen ovale (PFO), the integration of imaging technologies offers valuable insights in more complex or borderline cases. Incorporating advanced imaging into routine clinical practice would improve patient-specific monitoring and potentially reduce uncertainties in decision-making. Policies supporting reimbursement for these imaging technologies could enhance the precision of preoperative risk stratification. Insights from unique clinical scenarios Case reports as learning opportunities Individual case reports provide invaluable insights into managing rare or challenging conditions. For example, the prone positioning strategy for a patient with TOF and absent pulmonary valve syndrome highlights the importance of innovative, non-invasive interventions for postoperative respiratory distress. Similarly, the management of complications like pneumothorax following Nuss procedures underscores the necessity of vigilant intraoperative and postoperative monitoring. Adapting to complex physiologies Patients with complex cardiac physiologies, such as those with unrepaired TOF or coarctation of the aorta, present unique perioperative challenges. Successful outcomes in such cases, as reported by and , underscore the critical role of interdisciplinary teamwork and meticulous anesthetic planning. These cases highlight the importance of leveraging clinical expertise and adapting strategies to individual patient needs. In low-resource settings, innovative approaches to CHD surgery have emerged as viable solutions to overcome infrastructural and financial limitations. Studies from Rwanda and Ethiopia highlight the role of capacity-building programs, where local surgical teams trained by international specialists have successfully performed complex CHD surgeries with outcomes comparable to those in high-income countries. Additionally, simplified postoperative care strategies, such as mobile-based follow-up programs, have shown promise in addressing gaps in long-term patient monitoring. These findings suggest that sustainable solutions tailored to specific regional challenges can significantly enhance CHD surgical outcomes in developing regions . Imaging in risk assessment provided insights into the utility of advanced imaging techniques for identifying subtle yet potentially significant cardiac abnormalities like PFO during elective surgeries. Although their findings demonstrated minimal postoperative complications in patients with PFO, they advocate for the use of imaging as a tool for refining clinical decision-making in complex or borderline cases (Table ). Healthcare system challenges Economic barriers to implementation The mismatch between clinical outcomes and reimbursement structures remains a significant challenge. In systems like Germany’s DRG, despite the proven effectiveness of practices like fast-track extubation, reimbursement rates are insufficient to cover the costs of these resource-saving measures. Policy reform is necessary to address this gap. One possible solution is to implement outcome-based reimbursement that aligns financial incentives with clinical results. For instance, hospitals that achieve lower complication rates and shorter ICU stays could be eligible for higher reimbursement rates. This would encourage the adoption of evidence-based best practices, leading to overall improved patient outcomes (Table ). Beyond financial inefficiencies in high-income countries, CHD surgical programs in low-resource settings face major economic constraints that severely limit access to life-saving interventions. Studies from Kenya, South Africa, and Cambodia highlight the significant burden of out-of-pocket expenses on families seeking surgical treatment. Limited healthcare funding, lack of insurance coverage, and high costs of imported surgical materials further exacerbate these challenges. Addressing these issues requires a multipronged approach, including expanding government-subsidized surgical programs, increasing international funding support, and fostering regional collaborations for cost-effective procurement of medical supplies. Additionally, the implementation of task-shifting strategies—such as training local healthcare providers to perform specific CHD-related procedures—may offer a sustainable solution to enhance surgical capacity and accessibility in underserved regions [ , , , ]. Resource optimization Efforts to optimize resource utilization, particularly in high-demand areas like the ICU, have shown promising results. Even with staffing reductions, units that employed fast-track protocols maintained excellent outcomes, proving that operational efficiency can coexist with high-quality care . Expanding these practices would alleviate systemic pressures and reduce healthcare costs without compromising the quality of care. Policymakers should consider developing best practice guidelines that optimize resource allocation, streamline care pathways, and reduce inefficiencies. Practical implications for clinicians, researchers, and policymakers For clinicians, the findings of this review provide important insights into risk prediction and perioperative management, encouraging the integration of predictive models and innovative care protocols like fast-track extubation. Clinicians should prioritize the use of personalized care plans, ensuring that patient-specific factors are taken into account in both surgical planning and postoperative care. For researchers, the findings emphasize the need for further studies into the economic impact of adopting advanced technologies and innovative care protocols. Research on cost-effectiveness and outcome-based reimbursement models could provide crucial evidence for policymakers looking to reform healthcare systems. For policymakers, the findings highlight the need for reform in healthcare reimbursement models, aligning financial incentives with clinical outcomes. They must consider value-based reimbursement systems that reward hospitals for delivering high-quality care while reducing inefficiencies. Furthermore, public funding for innovative technologies, such as neurological monitoring and minimally invasive procedures, should be prioritized to foster widespread adoption of these practices. Future research should prioritize large-scale, multicenter studies to investigate long-term neurodevelopmental outcomes following CHD surgery, particularly in low-income settings where such data remains scarce. Additionally, international collaborations are needed to bridge the gap in CHD surgical care between high- and low-income regions. By fostering knowledge exchange, resource-sharing initiatives, and global training programs, significant strides can be made toward ensuring equitable access to high-quality CHD treatment worldwide Table .
This systematic review synthesizes data from 27 observational studies, which collectively highlight advancements in congenital heart surgery, perioperative management, and the identification of postoperative risk factors. The reviewed studies demonstrate the importance of individualized perioperative care, predictive models for postoperative outcomes, and emerging technologies like biomarkers and point-of-care imaging. Despite these advancements, challenges such as economic inefficiencies, systemic barriers, and the need for neurological monitoring remain pressing. While surgical techniques have progressed significantly, addressing healthcare system inefficiencies and resource allocation issues will be pivotal in ensuring equitable access to high-quality care (Tables , ). A comprehensive policy approach must be devised to support these best practices, which should include addressing the gap between clinical outcomes and financial incentives (Table ). Moreover, this review expands on previously underexplored areas, including long-term neurodevelopmental outcomes after CHD surgery and disparities in surgical outcomes between high-income and low-income countries. By incorporating these additional perspectives, this review provides a more comprehensive understanding of CHD management challenges and opportunities worldwide.
The identification of predictive factors for postoperative outcomes has been a major focus of this review, particularly in relation to preoperative optimization and the integration of predictive models into clinical practice. For example, demonstrated that hemoglobin and oxygen saturation (HbSpO2) levels were strong predictors of adverse outcomes in children with TOF. These findings support the early identification of at-risk patients and the optimization of preoperative care. Similarly, Ishimaru et al. emphasized that long anesthesia duration in esophageal atresia surgeries was a critical factor in increased complications, advocating for streamlined surgical processes. The ability to identify these risks early and integrate them into clinical decision-making could significantly improve outcomes while optimizing resource allocation. highlights the need for streamlined surgical processes to minimize complications. These findings collectively support integrating predictive models into preoperative planning to guide clinical decision-making. The findings regarding delayed extubation and ICU transfers in pediatric scoliosis patients undergoing posterior fusion further broaden our understanding of perioperative risk factors, such as high Cobb angle and pulmonary dysfunction. The delayed extubation and ICU transfer risks in pediatric scoliosis patients further emphasize the importance of individualizing perioperative management strategies. High-risk factors, such as high Cobb angle and pulmonary dysfunction, can be mitigated with early recognition and targeted interventions. Integrating predictive models into preoperative planning will help clinicians tailor interventions, reduce hospital stays, and improve recovery times. These insights enable healthcare providers to tailor perioperative management strategies, improving patient outcomes and resource utilization. Additionally, findings from low-income settings reveal distinct risk factors that impact postoperative outcomes, including malnutrition, delayed surgical intervention, and limited access to intensive postoperative care. Studies from Ethiopia, Rwanda, and Kenya indicate that preoperative malnutrition significantly contributes to increased mortality and prolonged ICU stays in CHD patients. These insights underscore the urgent need for targeted interventions, including early nutritional support and improved perioperative monitoring, to enhance surgical outcomes in resource-limited settings [ , , ].
Fast-track protocols Fast-track extubation protocols have consistently demonstrated reduced ICU stays and postoperative morbidity, as seen in the study by . However, the economic barriers to implementing these protocols remain significant. In healthcare systems like the German DRG model, the lack of reimbursement for resource-efficient practices such as FT protocols discourages their adoption, despite the clinical evidence supporting their effectiveness. Policy solutions could focus on aligning reimbursement policies with clinical outcomes, ensuring that hospitals are financially incentivized to adopt evidence-based best practices. One potential solution is to implement outcome-based reimbursement models, where hospitals are reimbursed based on the quality of care provided, rather than the quantity of services rendered. This would foster the adoption of cost-effective, outcome-driven approaches, such as FT protocols, across healthcare systems. Tailored anesthetic techniques The review also highlights the success of tailored anesthetic techniques in complex surgeries, such as those performed on Fontan circulation patients undergoing cesarean sections and those undergoing gastrectomy for coarctation of the aorta , demonstrate how individualized care can improve outcomes in high-risk scenarios. These cases underscore the importance of individualized care in improving outcomes for high-risk patients. The integration of minimally invasive techniques, like catheter-based PDA closure is another area where advancements have demonstrated significant benefits in reducing complications and improving recovery times. Tailored care should be considered a standard of practice for complex surgeries, and training programs for anesthesiologists and surgeons should be expanded to emphasize these individualized approaches. Blood conservation strategies In patients with religious or medical contraindications to transfusion, such as Jehovah’s Witness patients, blood conservation strategies have been critical in reducing reliance on allogeneic blood products. Techniques like normovolemic hemodilution and adjustments to cardiopulmonary bypass protocols can be effective alternatives. Expanding the use of blood conservation techniques should be promoted through policy incentives for centers that adopt such practices. Financial incentives or reimbursement adjustments for hospitals implementing innovative, blood-saving protocols would encourage more centers to adopt these practices, improving patient safety and reducing complications related to blood transfusion. Neuroprotective strategies in perioperative care Neurodevelopmental impairments are a significant concern for infants undergoing CHD surgery. Emerging evidence suggests that prolonged exposure to anesthesia and intraoperative brain activity suppression may contribute to long-term cognitive deficits. Studies have identified key biomarkers, such as glial fibrillary acidic protein (GFAP), as predictors of brain injury in neonates undergoing cardiac surgery. Additionally, intraoperative EEG monitoring has been shown to detect prolonged cortical isoelectric states, which correlate with adverse neurodevelopmental outcomes. By integrating real-time neurophysiological monitoring and modifying anesthesia protocols, clinicians can potentially reduce the risk of neurological complications and optimize long-term outcomes for CHD patients .
Fast-track extubation protocols have consistently demonstrated reduced ICU stays and postoperative morbidity, as seen in the study by . However, the economic barriers to implementing these protocols remain significant. In healthcare systems like the German DRG model, the lack of reimbursement for resource-efficient practices such as FT protocols discourages their adoption, despite the clinical evidence supporting their effectiveness. Policy solutions could focus on aligning reimbursement policies with clinical outcomes, ensuring that hospitals are financially incentivized to adopt evidence-based best practices. One potential solution is to implement outcome-based reimbursement models, where hospitals are reimbursed based on the quality of care provided, rather than the quantity of services rendered. This would foster the adoption of cost-effective, outcome-driven approaches, such as FT protocols, across healthcare systems.
The review also highlights the success of tailored anesthetic techniques in complex surgeries, such as those performed on Fontan circulation patients undergoing cesarean sections and those undergoing gastrectomy for coarctation of the aorta , demonstrate how individualized care can improve outcomes in high-risk scenarios. These cases underscore the importance of individualized care in improving outcomes for high-risk patients. The integration of minimally invasive techniques, like catheter-based PDA closure is another area where advancements have demonstrated significant benefits in reducing complications and improving recovery times. Tailored care should be considered a standard of practice for complex surgeries, and training programs for anesthesiologists and surgeons should be expanded to emphasize these individualized approaches.
In patients with religious or medical contraindications to transfusion, such as Jehovah’s Witness patients, blood conservation strategies have been critical in reducing reliance on allogeneic blood products. Techniques like normovolemic hemodilution and adjustments to cardiopulmonary bypass protocols can be effective alternatives. Expanding the use of blood conservation techniques should be promoted through policy incentives for centers that adopt such practices. Financial incentives or reimbursement adjustments for hospitals implementing innovative, blood-saving protocols would encourage more centers to adopt these practices, improving patient safety and reducing complications related to blood transfusion.
Neurodevelopmental impairments are a significant concern for infants undergoing CHD surgery. Emerging evidence suggests that prolonged exposure to anesthesia and intraoperative brain activity suppression may contribute to long-term cognitive deficits. Studies have identified key biomarkers, such as glial fibrillary acidic protein (GFAP), as predictors of brain injury in neonates undergoing cardiac surgery. Additionally, intraoperative EEG monitoring has been shown to detect prolonged cortical isoelectric states, which correlate with adverse neurodevelopmental outcomes. By integrating real-time neurophysiological monitoring and modifying anesthesia protocols, clinicians can potentially reduce the risk of neurological complications and optimize long-term outcomes for CHD patients .
Biomarkers and monitoring The introduction of biomarkers like glial fibrillary acid protein (GFAP) and amplitude-integrated EEG (aEEG) offers significant advantages in monitoring neurological outcomes in neonates undergoing cardiac surgeries . These tools provide early indicators of brain injury, which allows for timely interventions that can improve long-term neurodevelopmental outcomes. Integrating these technologies into routine clinical practice should be a priority, as it could dramatically improve the quality of care for high-risk neonates. Reimbursement for these diagnostic tools should be expanded to support widespread use, with policymakers adjusting coding systems to account for the value of advanced neurological monitoring. (Table ). Implications for neonatal care The association of neurological complications with burst suppression and ictal discharges reinforces the need for neuroprotective strategies during high-risk surgeries like the Norwood and arterial switch procedures. The implementation of neurological monitoring in these surgeries can allow for the detection of issues intraoperatively, reducing the risk of long-term brain injury. Neuroprotective strategies could be incorporated into standardized care protocols, and funding for research into advanced monitoring techniques should be prioritized to further improve care. Beyond immediate surgical outcomes, recent studies highlight the long-term neurodevelopmental consequences of congenital heart surgery. Prolonged ICU stays and mechanical ventilation have been linked to developmental delays, underscoring the importance of minimizing unnecessary sedation and optimizing early postoperative rehabilitation. Furthermore, findings suggest that hearing loss is an underrecognized yet prevalent issue among CHD survivors, with significant implications for cognitive and language development. Systematic post-surgical auditory screening and early intervention strategies are necessary to mitigate these risks and improve long-term quality of life in CHD patients. Diagnostic advances in neurological monitoring The study by The study by Gai et al. demonstrates the utility of point-of-care imaging, such as transthoracic echocardiography (TTE) with bubble studies, in refining perioperative risk assessment. While the study found minimal impact on outcomes such as postoperative delirium in patients with patent foramen ovale (PFO), the integration of imaging technologies offers valuable insights in more complex or borderline cases. Incorporating advanced imaging into routine clinical practice would improve patient-specific monitoring and potentially reduce uncertainties in decision-making. Policies supporting reimbursement for these imaging technologies could enhance the precision of preoperative risk stratification.
The introduction of biomarkers like glial fibrillary acid protein (GFAP) and amplitude-integrated EEG (aEEG) offers significant advantages in monitoring neurological outcomes in neonates undergoing cardiac surgeries . These tools provide early indicators of brain injury, which allows for timely interventions that can improve long-term neurodevelopmental outcomes. Integrating these technologies into routine clinical practice should be a priority, as it could dramatically improve the quality of care for high-risk neonates. Reimbursement for these diagnostic tools should be expanded to support widespread use, with policymakers adjusting coding systems to account for the value of advanced neurological monitoring. (Table ).
The association of neurological complications with burst suppression and ictal discharges reinforces the need for neuroprotective strategies during high-risk surgeries like the Norwood and arterial switch procedures. The implementation of neurological monitoring in these surgeries can allow for the detection of issues intraoperatively, reducing the risk of long-term brain injury. Neuroprotective strategies could be incorporated into standardized care protocols, and funding for research into advanced monitoring techniques should be prioritized to further improve care. Beyond immediate surgical outcomes, recent studies highlight the long-term neurodevelopmental consequences of congenital heart surgery. Prolonged ICU stays and mechanical ventilation have been linked to developmental delays, underscoring the importance of minimizing unnecessary sedation and optimizing early postoperative rehabilitation. Furthermore, findings suggest that hearing loss is an underrecognized yet prevalent issue among CHD survivors, with significant implications for cognitive and language development. Systematic post-surgical auditory screening and early intervention strategies are necessary to mitigate these risks and improve long-term quality of life in CHD patients.
The study by The study by Gai et al. demonstrates the utility of point-of-care imaging, such as transthoracic echocardiography (TTE) with bubble studies, in refining perioperative risk assessment. While the study found minimal impact on outcomes such as postoperative delirium in patients with patent foramen ovale (PFO), the integration of imaging technologies offers valuable insights in more complex or borderline cases. Incorporating advanced imaging into routine clinical practice would improve patient-specific monitoring and potentially reduce uncertainties in decision-making. Policies supporting reimbursement for these imaging technologies could enhance the precision of preoperative risk stratification.
Case reports as learning opportunities Individual case reports provide invaluable insights into managing rare or challenging conditions. For example, the prone positioning strategy for a patient with TOF and absent pulmonary valve syndrome highlights the importance of innovative, non-invasive interventions for postoperative respiratory distress. Similarly, the management of complications like pneumothorax following Nuss procedures underscores the necessity of vigilant intraoperative and postoperative monitoring. Adapting to complex physiologies Patients with complex cardiac physiologies, such as those with unrepaired TOF or coarctation of the aorta, present unique perioperative challenges. Successful outcomes in such cases, as reported by and , underscore the critical role of interdisciplinary teamwork and meticulous anesthetic planning. These cases highlight the importance of leveraging clinical expertise and adapting strategies to individual patient needs. In low-resource settings, innovative approaches to CHD surgery have emerged as viable solutions to overcome infrastructural and financial limitations. Studies from Rwanda and Ethiopia highlight the role of capacity-building programs, where local surgical teams trained by international specialists have successfully performed complex CHD surgeries with outcomes comparable to those in high-income countries. Additionally, simplified postoperative care strategies, such as mobile-based follow-up programs, have shown promise in addressing gaps in long-term patient monitoring. These findings suggest that sustainable solutions tailored to specific regional challenges can significantly enhance CHD surgical outcomes in developing regions . Imaging in risk assessment provided insights into the utility of advanced imaging techniques for identifying subtle yet potentially significant cardiac abnormalities like PFO during elective surgeries. Although their findings demonstrated minimal postoperative complications in patients with PFO, they advocate for the use of imaging as a tool for refining clinical decision-making in complex or borderline cases (Table ).
Individual case reports provide invaluable insights into managing rare or challenging conditions. For example, the prone positioning strategy for a patient with TOF and absent pulmonary valve syndrome highlights the importance of innovative, non-invasive interventions for postoperative respiratory distress. Similarly, the management of complications like pneumothorax following Nuss procedures underscores the necessity of vigilant intraoperative and postoperative monitoring.
Patients with complex cardiac physiologies, such as those with unrepaired TOF or coarctation of the aorta, present unique perioperative challenges. Successful outcomes in such cases, as reported by and , underscore the critical role of interdisciplinary teamwork and meticulous anesthetic planning. These cases highlight the importance of leveraging clinical expertise and adapting strategies to individual patient needs. In low-resource settings, innovative approaches to CHD surgery have emerged as viable solutions to overcome infrastructural and financial limitations. Studies from Rwanda and Ethiopia highlight the role of capacity-building programs, where local surgical teams trained by international specialists have successfully performed complex CHD surgeries with outcomes comparable to those in high-income countries. Additionally, simplified postoperative care strategies, such as mobile-based follow-up programs, have shown promise in addressing gaps in long-term patient monitoring. These findings suggest that sustainable solutions tailored to specific regional challenges can significantly enhance CHD surgical outcomes in developing regions .
provided insights into the utility of advanced imaging techniques for identifying subtle yet potentially significant cardiac abnormalities like PFO during elective surgeries. Although their findings demonstrated minimal postoperative complications in patients with PFO, they advocate for the use of imaging as a tool for refining clinical decision-making in complex or borderline cases (Table ).
Economic barriers to implementation The mismatch between clinical outcomes and reimbursement structures remains a significant challenge. In systems like Germany’s DRG, despite the proven effectiveness of practices like fast-track extubation, reimbursement rates are insufficient to cover the costs of these resource-saving measures. Policy reform is necessary to address this gap. One possible solution is to implement outcome-based reimbursement that aligns financial incentives with clinical results. For instance, hospitals that achieve lower complication rates and shorter ICU stays could be eligible for higher reimbursement rates. This would encourage the adoption of evidence-based best practices, leading to overall improved patient outcomes (Table ). Beyond financial inefficiencies in high-income countries, CHD surgical programs in low-resource settings face major economic constraints that severely limit access to life-saving interventions. Studies from Kenya, South Africa, and Cambodia highlight the significant burden of out-of-pocket expenses on families seeking surgical treatment. Limited healthcare funding, lack of insurance coverage, and high costs of imported surgical materials further exacerbate these challenges. Addressing these issues requires a multipronged approach, including expanding government-subsidized surgical programs, increasing international funding support, and fostering regional collaborations for cost-effective procurement of medical supplies. Additionally, the implementation of task-shifting strategies—such as training local healthcare providers to perform specific CHD-related procedures—may offer a sustainable solution to enhance surgical capacity and accessibility in underserved regions [ , , , ]. Resource optimization Efforts to optimize resource utilization, particularly in high-demand areas like the ICU, have shown promising results. Even with staffing reductions, units that employed fast-track protocols maintained excellent outcomes, proving that operational efficiency can coexist with high-quality care . Expanding these practices would alleviate systemic pressures and reduce healthcare costs without compromising the quality of care. Policymakers should consider developing best practice guidelines that optimize resource allocation, streamline care pathways, and reduce inefficiencies.
The mismatch between clinical outcomes and reimbursement structures remains a significant challenge. In systems like Germany’s DRG, despite the proven effectiveness of practices like fast-track extubation, reimbursement rates are insufficient to cover the costs of these resource-saving measures. Policy reform is necessary to address this gap. One possible solution is to implement outcome-based reimbursement that aligns financial incentives with clinical results. For instance, hospitals that achieve lower complication rates and shorter ICU stays could be eligible for higher reimbursement rates. This would encourage the adoption of evidence-based best practices, leading to overall improved patient outcomes (Table ). Beyond financial inefficiencies in high-income countries, CHD surgical programs in low-resource settings face major economic constraints that severely limit access to life-saving interventions. Studies from Kenya, South Africa, and Cambodia highlight the significant burden of out-of-pocket expenses on families seeking surgical treatment. Limited healthcare funding, lack of insurance coverage, and high costs of imported surgical materials further exacerbate these challenges. Addressing these issues requires a multipronged approach, including expanding government-subsidized surgical programs, increasing international funding support, and fostering regional collaborations for cost-effective procurement of medical supplies. Additionally, the implementation of task-shifting strategies—such as training local healthcare providers to perform specific CHD-related procedures—may offer a sustainable solution to enhance surgical capacity and accessibility in underserved regions [ , , , ].
Efforts to optimize resource utilization, particularly in high-demand areas like the ICU, have shown promising results. Even with staffing reductions, units that employed fast-track protocols maintained excellent outcomes, proving that operational efficiency can coexist with high-quality care . Expanding these practices would alleviate systemic pressures and reduce healthcare costs without compromising the quality of care. Policymakers should consider developing best practice guidelines that optimize resource allocation, streamline care pathways, and reduce inefficiencies.
For clinicians, the findings of this review provide important insights into risk prediction and perioperative management, encouraging the integration of predictive models and innovative care protocols like fast-track extubation. Clinicians should prioritize the use of personalized care plans, ensuring that patient-specific factors are taken into account in both surgical planning and postoperative care. For researchers, the findings emphasize the need for further studies into the economic impact of adopting advanced technologies and innovative care protocols. Research on cost-effectiveness and outcome-based reimbursement models could provide crucial evidence for policymakers looking to reform healthcare systems. For policymakers, the findings highlight the need for reform in healthcare reimbursement models, aligning financial incentives with clinical outcomes. They must consider value-based reimbursement systems that reward hospitals for delivering high-quality care while reducing inefficiencies. Furthermore, public funding for innovative technologies, such as neurological monitoring and minimally invasive procedures, should be prioritized to foster widespread adoption of these practices. Future research should prioritize large-scale, multicenter studies to investigate long-term neurodevelopmental outcomes following CHD surgery, particularly in low-income settings where such data remains scarce. Additionally, international collaborations are needed to bridge the gap in CHD surgical care between high- and low-income regions. By fostering knowledge exchange, resource-sharing initiatives, and global training programs, significant strides can be made toward ensuring equitable access to high-quality CHD treatment worldwide Table .
Bridging research gaps While significant progress has been made, areas such as long-term neurodevelopmental outcomes, the efficacy of new biomarkers, and systemic barriers to implementing evidence-based practices warrant further investigation. Additionally, the potential of novel technologies like AI and predictive analytics in perioperative care remains underexplored. Further investigation is required to assess the long-term neurodevelopmental consequences of CHD surgery, particularly regarding the prevalence of hearing loss, cognitive delays, and behavioral outcomes. Additionally, there is a significant gap in research on CHD perioperative care in low-income countries, where access to advanced monitoring tools and specialized surgical interventions remains limited. Addressing these disparities through large-scale, multicenter studies will be crucial in ensuring equitable outcomes worldwide. Furthermore, the integration of artificial intelligence (AI) and machine learning models into perioperative decision-making could enhance risk stratification, predict adverse events, and optimize patient-specific treatment strategies. Policy and practice integration Healthcare systems must prioritize aligning reimbursement models with evidence-based clinical practices. Policymakers should incentivize resource-efficient interventions, such as FT protocols, to ensure that high-quality care is accessible and sustainable. Healthcare policies should also focus on improving CHD care accessibility in low-resource settings. Strengthening regional surgical programs, establishing task-shifting models, and fostering international collaborations could facilitate capacity-building and improve patient outcomes in underserved regions. Additionally, targeted funding for research on cost-effective interventions and outcome-based reimbursement models could accelerate the adoption of evidence-based perioperative strategies. Focus on personalized care The findings highlight the growing importance of patient-specific approaches, from tailored anesthesia to advanced monitoring tools. Integrating multidisciplinary collaboration and precision medicine into standard care pathways will be essential for addressing the complexities of congenital heart disease.
While significant progress has been made, areas such as long-term neurodevelopmental outcomes, the efficacy of new biomarkers, and systemic barriers to implementing evidence-based practices warrant further investigation. Additionally, the potential of novel technologies like AI and predictive analytics in perioperative care remains underexplored. Further investigation is required to assess the long-term neurodevelopmental consequences of CHD surgery, particularly regarding the prevalence of hearing loss, cognitive delays, and behavioral outcomes. Additionally, there is a significant gap in research on CHD perioperative care in low-income countries, where access to advanced monitoring tools and specialized surgical interventions remains limited. Addressing these disparities through large-scale, multicenter studies will be crucial in ensuring equitable outcomes worldwide. Furthermore, the integration of artificial intelligence (AI) and machine learning models into perioperative decision-making could enhance risk stratification, predict adverse events, and optimize patient-specific treatment strategies.
Healthcare systems must prioritize aligning reimbursement models with evidence-based clinical practices. Policymakers should incentivize resource-efficient interventions, such as FT protocols, to ensure that high-quality care is accessible and sustainable. Healthcare policies should also focus on improving CHD care accessibility in low-resource settings. Strengthening regional surgical programs, establishing task-shifting models, and fostering international collaborations could facilitate capacity-building and improve patient outcomes in underserved regions. Additionally, targeted funding for research on cost-effective interventions and outcome-based reimbursement models could accelerate the adoption of evidence-based perioperative strategies.
The findings highlight the growing importance of patient-specific approaches, from tailored anesthesia to advanced monitoring tools. Integrating multidisciplinary collaboration and precision medicine into standard care pathways will be essential for addressing the complexities of congenital heart disease.
While this systematic review offers comprehensive insights into perioperative management and outcomes in congenital heart surgery, several limitations should be considered to contextualize the findings: Heterogeneity in study designs The included studies employed various methodologies, such as retrospective observational studies, prospective cohort designs, and case reports. This heterogeneity makes direct comparisons challenging and limits the ability to establish causality between interventions and outcomes. For example, predictive factors identified in a large retrospective study on TOF may not fully align with findings from smaller, single-center studies such as those examining PDA closure in neonates . Limited long-term data Many studies focused on short-term postoperative outcomes, with limited exploration of long-term impacts such as neurodevelopmental trajectories or quality of life. For instance, while aEEG monitoring was identified as an early marker for brain injury , its correlation with long-term cognitive or developmental outcomes remains underexplored. Similarly, studies examining fast-track protocols emphasized immediate recovery metrics but lacked longitudinal follow-up to assess sustained benefits. Furthermore, while studies on early neurodevelopmental biomarkers (such as GFAP and aEEG) have demonstrated potential for early detection of brain injury, their predictive value for long-term cognitive and functional outcomes remains uncertain. The lack of longitudinal studies tracking CHD patients into adolescence and adulthood hinders our understanding of the full impact of surgical interventions on neurodevelopment. Generalizability of findings The populations and healthcare settings varied significantly across studies, potentially limiting generalizability. For example: The study by Murin et al. focused on a German healthcare system where economic incentives influence clinical decisions, which may not apply universally. Case reports, such as the management of Fontan circulation during cesarean sections , provide valuable insights but are inherently limited by their specificity and sample size. Underrepresentation of developing healthcare settings Most included studies were conducted in high-resource settings, leaving gaps in understanding how these findings translate to low-resource environments. For instance, advanced technologies like aEEG monitoring or catheter-based PDA closure may not be widely accessible in developing regions, limiting their applicability. Additionally, studies from developing countries often face methodological constraints, such as smaller sample sizes, limited access to advanced diagnostic tools, and variability in surgical expertise. These factors may influence reported outcomes and limit the generalizability of findings to low-resource settings. Future research should focus on multicenter collaborations to establish standardized perioperative protocols tailored to the challenges of resource-limited environments. Small sample sizes in critical areas Some key areas of interest were represented by studies with small sample sizes, which may reduce statistical power. For example: The study on glial fibrillary acid protein in neonates involved only 35 procedures, potentially limiting the robustness of its conclusions. Case reports, while illustrative, cannot be generalized to broader populations. Lack of standardized outcome metrics There was considerable variability in the definitions and measurement of outcomes across studies. For example, ICU stay duration and extubation protocols varied widely, making it challenging to draw unified conclusions about fast-track protocols or ICU transfer risks . A lack of standardized criteria for complications, such as neurodevelopmental delays or respiratory distress, further complicates meta-analyses. Variability in surgical training, perioperative monitoring protocols, and hospital infrastructure may introduce confounding variables that affect reported outcomes. Establishing universal guidelines for reporting perioperative complications and long-term outcomes is essential to improve comparability across studies and enhance the reliability of systematic reviews in this field. Publication bias As with any systematic review, there is a potential for publication bias, with positive or novel findings more likely to be published. Negative or null results in areas such as aEEG utility or blood conservation strategies may be underreported, skewing the overall interpretation.
The included studies employed various methodologies, such as retrospective observational studies, prospective cohort designs, and case reports. This heterogeneity makes direct comparisons challenging and limits the ability to establish causality between interventions and outcomes. For example, predictive factors identified in a large retrospective study on TOF may not fully align with findings from smaller, single-center studies such as those examining PDA closure in neonates .
Many studies focused on short-term postoperative outcomes, with limited exploration of long-term impacts such as neurodevelopmental trajectories or quality of life. For instance, while aEEG monitoring was identified as an early marker for brain injury , its correlation with long-term cognitive or developmental outcomes remains underexplored. Similarly, studies examining fast-track protocols emphasized immediate recovery metrics but lacked longitudinal follow-up to assess sustained benefits. Furthermore, while studies on early neurodevelopmental biomarkers (such as GFAP and aEEG) have demonstrated potential for early detection of brain injury, their predictive value for long-term cognitive and functional outcomes remains uncertain. The lack of longitudinal studies tracking CHD patients into adolescence and adulthood hinders our understanding of the full impact of surgical interventions on neurodevelopment.
The populations and healthcare settings varied significantly across studies, potentially limiting generalizability. For example: The study by Murin et al. focused on a German healthcare system where economic incentives influence clinical decisions, which may not apply universally. Case reports, such as the management of Fontan circulation during cesarean sections , provide valuable insights but are inherently limited by their specificity and sample size.
Most included studies were conducted in high-resource settings, leaving gaps in understanding how these findings translate to low-resource environments. For instance, advanced technologies like aEEG monitoring or catheter-based PDA closure may not be widely accessible in developing regions, limiting their applicability. Additionally, studies from developing countries often face methodological constraints, such as smaller sample sizes, limited access to advanced diagnostic tools, and variability in surgical expertise. These factors may influence reported outcomes and limit the generalizability of findings to low-resource settings. Future research should focus on multicenter collaborations to establish standardized perioperative protocols tailored to the challenges of resource-limited environments.
Some key areas of interest were represented by studies with small sample sizes, which may reduce statistical power. For example: The study on glial fibrillary acid protein in neonates involved only 35 procedures, potentially limiting the robustness of its conclusions. Case reports, while illustrative, cannot be generalized to broader populations.
There was considerable variability in the definitions and measurement of outcomes across studies. For example, ICU stay duration and extubation protocols varied widely, making it challenging to draw unified conclusions about fast-track protocols or ICU transfer risks . A lack of standardized criteria for complications, such as neurodevelopmental delays or respiratory distress, further complicates meta-analyses. Variability in surgical training, perioperative monitoring protocols, and hospital infrastructure may introduce confounding variables that affect reported outcomes. Establishing universal guidelines for reporting perioperative complications and long-term outcomes is essential to improve comparability across studies and enhance the reliability of systematic reviews in this field.
As with any systematic review, there is a potential for publication bias, with positive or novel findings more likely to be published. Negative or null results in areas such as aEEG utility or blood conservation strategies may be underreported, skewing the overall interpretation.
This systematic review underscores the remarkable advancements in congenital heart surgery and perioperative management while highlighting the persistent challenges in improving patient outcomes. This review also highlights the critical need for long-term follow-up studies to assess neurodevelopmental outcomes, including the impact of prolonged ICU stays, anesthesia exposure, and perioperative brain injury on cognitive function. Furthermore, the disparities in CHD surgical access between high- and low-income regions underscore the urgency of implementing targeted healthcare policies that address financial and infrastructural barriers. By bridging gaps in research, fostering innovation, and addressing systemic inefficiencies, healthcare providers and policymakers can build on these findings to deliver more effective and equitable care. Future advancements in surgical innovation, perioperative care, and personalized treatment approaches will require collaborative efforts from clinicians, researchers, and policymakers. By prioritizing evidence-based interventions, fostering international partnerships, and investing in outcome-driven healthcare reforms, the global medical community can work toward ensuring that all CHD patients—regardless of socioeconomic background—receive the highest standard of care.
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Flipped and Peer-Assisted teaching: a new model in virtual anatomy education | bdc98b7a-b382-4dad-bc6e-4968e8dd5da9 | 11223305 | Anatomy[mh] | Historically, anatomy has played a pivotal role in medical sciences education . The teaching of fundamental anatomical knowledge is crucial for medical students and healthcare professionals alike . Traditionally, the methods employed for teaching anatomy relied heavily on autopsies and lectures. However, advancements in educational technologies have paved the way for the integration of models, simulators, and the internet to enhance the anatomy learning experience . Despite these advancements, there is still room for improvement in the field of anatomy education . Furthermore, the global outbreak of Coronavirus Disease 2019 (COVID-19) has necessitated a shift from traditional to modern educational approaches . Consequently, the provision of virtual anatomy education has become imperative . Many active learning methods that were originally designed for face-to-face instruction have had to be adapted for virtual environments. While technologies like augmented reality, virtual reality, and 3D have shown potential in anatomy education , their widespread application may be limited by various factors, including subject matter and contextual constraints . In addition, the importance of teamwork, communication, and higher-order thinking skills has been emphasized in medical education, highlighting the limitations of traditional teaching methods in achieving these goals. As a result, there was a need to adopt educational approaches that would provide virtual anatomy education while enabling students to practice these skills and learn through effective feedback . In this context, teachers play a crucial role. Good teachers expedite the learning process by offering relevant information, assessments, guidance, and examples. They motivate and guide learners, foster interactive discussions, and leverage their experience and skills to facilitate the learning process in a positive environment . In the realm of electronic learning (e-learning), effective integration of existing technology-based methods becomes essential since there is no single, comprehensive e-learning model currently available . Numerous educational techniques and approaches rooted in constructivism have been proposed, including flipped classrooms (FC) and peer-assisted learning (PAL). The term “flipped classroom” was first coined by American educators Jonathan Bergman and Aaron Sams in 2000 . The FC Model presents a departure from the conventional teaching approach. Instead of the traditional method where teachers give lectures during class and assign homework, the FC Model delivers lectures outside of class and emphasizes in-class practice, which can be considered similar to homework. Another well-recognized framework, the FC, encompasses a set of teaching strategies that (1) move most of the direct instruction outside the classroom; (2) utilize classroom time for interactive and engaging learning activities; and (3) require students to participate in activities before and/or after class to fully leverage the benefits of classroom sessions . This model involves inverting student activities with the support of new technologies, allowing students to engage more meaningfully with their teachers and enhancing face-to-face learning experiences . Indeed, the FC, which holds great potential in e-learning for healthcare, is supported by active learning theory and promotes critical thinking, problem-solving, and experimentation . Furthermore, the FC aligns with the Theory of Educational Differentiation, which emphasizes personalized teaching to cater to the diverse needs of learners. Differentiated instruction involves adapting teaching methods based on students’ needs, interests, and abilities to enhance their learning and academic achievement . Despite its numerous advantages, the FC also faces certain challenges. One significant hurdle is ensuring that all students arrive prepared for class, having actively engaged with the pre-class material. Without this preparation, the planned active learning strategies for class time may not yield the desired results. Additionally, some students may perceive the FC as an unfair or unreasonable approach. On the other hand, teachers may find FCs demanding due to the time-consuming nature of the process, difficulties in task planning and management, and the associated increase in workload . As a potential solution to these issues, we hypothesize that peer-assisted learning could be a suitable approach. PAL, in contrast, is defined as the process of actively assisting and supporting one another among peers of equal status or matched companions. It involves individuals from similar social groups who are not professional educators, helping each other learn and, in turn, enhancing their own learning . Therefore, PAL is an approach in which students provide assistance to their peers in the learning process. It encompasses different forms, including peer tutoring, peer consulting, peer education, peer modeling, peer assessment, and peer monitoring . Against this backdrop, in this study, we present a novel virtual teaching model that combines PAL and FCs. This model was implemented and evaluated during the crisis era. Participants and study design This descriptive study aimed to examine the impacts of the FPA (Flipped Peer-Assisted) method, a novel educational model, on the neuroanatomy course at Birjand University of Medical Sciences (BUMS) over three consecutive semesters from 2020 to 2021. In this study, a total of 210 fourth-semester medical students (female students: n = 120, with an average age of 20.7 years, and male students: n = 90, with an average age of 20.9 years) were selected as participants. The inclusion criteria for this study were individuals who had successfully completed the third semester and entered the fourth semester of the medical program, as well as those who had not previously failed the neuroanatomy course. The FPA method was implemented, drawing inspiration from the flipped classroom approach, where small groups of students engaged in peer-assisted learning. Additionally, the model incorporated feedback sessions to foster reflection and learning, with the teacher assuming the role of a facilitator as needed. The implementation of the FPA method consisted of three steps. In the first step, instructional design was carried out, and electronic content was produced. The second step involved the actual implementation, which commenced with an online orientation class. Students were divided into groups of 10, and within each group, one student was chosen as the peer learning based on their educational level and communication skills. Given that each semester had 70 students, a total of 10 groups and seven peer learning were selected. The mean scores of students in different groups were equated. The educational content for each lesson was uploaded to the university’s learning management system (LMS) for one week. Three days after the content was uploaded, an online meeting was held between the teacher and the pre-teachers to ensure their understanding of the material and emphasize key points. Two days later, the remaining students who had studied the uploaded content had an online class with their respective peer learning, which focused on questions and answers and highlighting important concepts. Finally, an online session was conducted with all the groups, evaluating students’ learning through questions and providing additional explanations if necessary. The peer learning’s ‘s performance in delivering the educational content and interacting with students was also evaluated, and feedback was provided to improve their performance. This process was repeated every week, and students received feedback from both the professor. Evaluation of the study To collect students’ opinions about the teaching method, a 15-item questionnaire was administered. The questionnaire utilized a five-point Likert scale, ranging from “very high” to “very low.” The content validity of the questionnaire was established through the confirmation of ten medical educationists, and its reliability was assessed using Cronbach’s alpha, which yielded acceptable results. Additionally, an open-ended question was included in the LMS to gather students’ overall feedback and opinions regarding their learning experience with this teaching model. Instruments At the end of the semester, students’ learning was assessed using a 30 multiple choice question test designed according to the test blueprint which was a representative test of all course objectives and was approved in the anatomy department. These tests were different from each other in each semester. However, it was designed according to the blueprint of the exam, and by checking it in the anatomy department, it was ensured that the educational goals of the course were covered. This descriptive study aimed to examine the impacts of the FPA (Flipped Peer-Assisted) method, a novel educational model, on the neuroanatomy course at Birjand University of Medical Sciences (BUMS) over three consecutive semesters from 2020 to 2021. In this study, a total of 210 fourth-semester medical students (female students: n = 120, with an average age of 20.7 years, and male students: n = 90, with an average age of 20.9 years) were selected as participants. The inclusion criteria for this study were individuals who had successfully completed the third semester and entered the fourth semester of the medical program, as well as those who had not previously failed the neuroanatomy course. The FPA method was implemented, drawing inspiration from the flipped classroom approach, where small groups of students engaged in peer-assisted learning. Additionally, the model incorporated feedback sessions to foster reflection and learning, with the teacher assuming the role of a facilitator as needed. The implementation of the FPA method consisted of three steps. In the first step, instructional design was carried out, and electronic content was produced. The second step involved the actual implementation, which commenced with an online orientation class. Students were divided into groups of 10, and within each group, one student was chosen as the peer learning based on their educational level and communication skills. Given that each semester had 70 students, a total of 10 groups and seven peer learning were selected. The mean scores of students in different groups were equated. The educational content for each lesson was uploaded to the university’s learning management system (LMS) for one week. Three days after the content was uploaded, an online meeting was held between the teacher and the pre-teachers to ensure their understanding of the material and emphasize key points. Two days later, the remaining students who had studied the uploaded content had an online class with their respective peer learning, which focused on questions and answers and highlighting important concepts. Finally, an online session was conducted with all the groups, evaluating students’ learning through questions and providing additional explanations if necessary. The peer learning’s ‘s performance in delivering the educational content and interacting with students was also evaluated, and feedback was provided to improve their performance. This process was repeated every week, and students received feedback from both the professor. To collect students’ opinions about the teaching method, a 15-item questionnaire was administered. The questionnaire utilized a five-point Likert scale, ranging from “very high” to “very low.” The content validity of the questionnaire was established through the confirmation of ten medical educationists, and its reliability was assessed using Cronbach’s alpha, which yielded acceptable results. Additionally, an open-ended question was included in the LMS to gather students’ overall feedback and opinions regarding their learning experience with this teaching model. At the end of the semester, students’ learning was assessed using a 30 multiple choice question test designed according to the test blueprint which was a representative test of all course objectives and was approved in the anatomy department. These tests were different from each other in each semester. However, it was designed according to the blueprint of the exam, and by checking it in the anatomy department, it was ensured that the educational goals of the course were covered. The results of the study indicate several important findings regarding the implementation of the educational model. A total of 210 medical students experienced instruction through this method over three consecutive semesters. Table presents the students’ opinions about the teaching method. Five categories were identified based on the students’ feedback Study techniques Students mentioned that this method compelled them to utilize effective study techniques such as repetition, review, and peer review. They also emphasized the need for accurate and timely studying. Teamwork and communication skills Students reported an increase in group companionship and cooperation, as well as a sense of responsibility. They mentioned that this method allowed for task assignment among students and improved their verbal communication skills. Additionally, all students made efforts to promote the group’s success. Transformation According to the students, this teaching method successfully changed their perspective towards the anatomy course. They expressed gratitude for shifting their negative opinions to a more positive outlook, particularly regarding the fetal anatomy component. Formative assessment and feedback Students appreciated the opportunities provided by this teaching model for peer questioning and answering, evaluation by peers, interaction with the teacher through questioning and answering, and problem-solving to achieve a deep understanding of the material. They also mentioned that this method alleviated concerns about the final exam. Group evaluation was implemented, fostering a sense of competition among students. Teacher role Although the educational model was designed to be student-centered, students still recognized and appreciated the role of the teacher in its implementation. They considered the adoption of this method as a sign of respect for the student, viewing the teacher as a role model who is duty-oriented, concerned, and attentive to education. The analysis of students’ scores on the 30-point test revealed an average score of 26.75 ± 3.67. Study techniques Students mentioned that this method compelled them to utilize effective study techniques such as repetition, review, and peer review. They also emphasized the need for accurate and timely studying. Teamwork and communication skills Students reported an increase in group companionship and cooperation, as well as a sense of responsibility. They mentioned that this method allowed for task assignment among students and improved their verbal communication skills. Additionally, all students made efforts to promote the group’s success. Transformation According to the students, this teaching method successfully changed their perspective towards the anatomy course. They expressed gratitude for shifting their negative opinions to a more positive outlook, particularly regarding the fetal anatomy component. Formative assessment and feedback Students appreciated the opportunities provided by this teaching model for peer questioning and answering, evaluation by peers, interaction with the teacher through questioning and answering, and problem-solving to achieve a deep understanding of the material. They also mentioned that this method alleviated concerns about the final exam. Group evaluation was implemented, fostering a sense of competition among students. Teacher role Although the educational model was designed to be student-centered, students still recognized and appreciated the role of the teacher in its implementation. They considered the adoption of this method as a sign of respect for the student, viewing the teacher as a role model who is duty-oriented, concerned, and attentive to education. The analysis of students’ scores on the 30-point test revealed an average score of 26.75 ± 3.67. Students mentioned that this method compelled them to utilize effective study techniques such as repetition, review, and peer review. They also emphasized the need for accurate and timely studying. Students reported an increase in group companionship and cooperation, as well as a sense of responsibility. They mentioned that this method allowed for task assignment among students and improved their verbal communication skills. Additionally, all students made efforts to promote the group’s success. According to the students, this teaching method successfully changed their perspective towards the anatomy course. They expressed gratitude for shifting their negative opinions to a more positive outlook, particularly regarding the fetal anatomy component. Students appreciated the opportunities provided by this teaching model for peer questioning and answering, evaluation by peers, interaction with the teacher through questioning and answering, and problem-solving to achieve a deep understanding of the material. They also mentioned that this method alleviated concerns about the final exam. Group evaluation was implemented, fostering a sense of competition among students. Although the educational model was designed to be student-centered, students still recognized and appreciated the role of the teacher in its implementation. They considered the adoption of this method as a sign of respect for the student, viewing the teacher as a role model who is duty-oriented, concerned, and attentive to education. The analysis of students’ scores on the 30-point test revealed an average score of 26.75 ± 3.67. The COVID-19 pandemic has necessitated a shift to online learning and assessment methods. Distance learning content focusing on active learning has been a significant concern for teachers. It is crucial for educators to transition from a traditional approach of acquiring knowledge to one that emphasizes knowledge construction. In response to the COVID-19 outbreak, various studies have indicated a widespread move towards virtual education to support student learning . The flipped classroom has gained traction as a pedagogical approach in higher education, with several studies highlighting positive student outcomes . The flipped classroom model transforms anatomy teaching by replacing large-scale lectures with interactive, team-based classes. The incorporation of multimodal digital resources and multimedia group assignments in the flipped classroom model fosters digital literacy and enables students to engage in authentic learning experiences, contributing to pedagogical innovation . So, the FPA model as an active learning approach helps learners dedicate part of their time to receiving feedback, engaging in reflection, and taking action based on that feedback. The primary purpose of feedback in this model is to provide an opportunity for setting learning goals and reinforcing learning . A systematic review conducted by Kazeminia et al. in 2022 highlighted the positive impact of the FC method on teaching anatomy; the review revealed numerous advantages associated with this approach, including increased satisfaction, academic achievement, self-confidence, and overall outcomes in anatomy curricular . A study conducted in China demonstrated an increase in the adoption of active learning methods, such as FCs, individualized tutoring, and small group discussions, during the COVID-19 pandemic . Interactions in these active learning sessions primarily took place through real-time voice, text, or teaching management platforms like Rain Classroom, Xuexitong, or Blackboard. In the context of English classroom teaching, a study introduced the SPOC-based (Small Private Online Course) FC model as an effective learning approach . Consistent with our findings, one research revealed that the students exhibited a notable level of enthusiasm towards the pre-class activities, which effectively fostered their active participation and attentiveness during the in-class sessions . On the one hand, studies conducted in India comparing e-learning methods during the COVID-19 crisis have found that learners generally express agreement with online discussions facilitated through virtual classrooms . From the learners’ perspective, e-learning is seen as a complement to traditional education, forming integrated educational methods . Constructive alignment of integrated methods in an e-learning model can contribute to effective educational design. Research has shown that learners’ satisfaction is influenced by factors such as teachers’ attitudes towards e-learning, course flexibility, course quality, course utility, perceived ease of use, and variety of assessments . According to a study carried out at The College of Health-Care Professions in Bolzano, Italy, it was suggested that incorporating online learning activities can enhance the effectiveness of didactic lectures. This approach not only requires teachers to create well-structured courses but also encourages early student engagement with the course material, thereby preventing a passive role during in-class sessions . Furthermore, in a study conducted by Telford and Senior in 2017, healthcare students who experienced a combination of e-learning and flipped classroom instructional approaches reported positive outcomes and a favorable learning experience . Advancements in concurrent distance learning and shared technologies, such as blogs, bulletin boards, chats, emails, and distance conferencing, have made it easier to access shared learning experiences. Quantitative and qualitative studies in collaborative medical education have demonstrated higher levels of learner satisfaction, knowledge progression, self-awareness, understanding of concepts, achievement of course goals, and changes in practice. It is important to recognize that in “e-learning,” the e-learner plays a central role. The use of information and communication technology by the new generation of digital natives distinguishes them from previous generations of learners and teachers. Therefore, effective e-medicine learning requires a balance between real-world practice and providing adequate learning opportunities. However, it is crucial to note that many challenges related to the use of technology in medical education are not solely attributable to the technology itself but to the educational approaches employed. A significant limitation of this study was the absence of a control group for comparing the effects of the FPA model with other models. However, the application of this model over three consecutive semesters and the high satisfaction rate among students were notable strengths. Future high-quality studies are recommended to compare the effects of this method with other approaches. Additionally, exploring the applicability of this model in other fields and subjects is suggested. The FPA model is a student-centered approach that encourages students to employ diverse learning techniques. It recognizes the important mentoring role of teachers in the learning process. The FPA model demonstrates remarkable effectiveness in deconstructing traditional classroom teaching and reconstructing teaching and learning methods through the profound integration of classroom instruction and modern educational technologies. This model is particularly valuable during times of crisis, such as the ongoing pandemic. |
Prioritizing Measures That Matter Within a Person-Centered Oncology Learning Health System | e087c7a3-f0e4-445f-bd5e-ab7683fad6f2 | 9219163 | Internal Medicine[mh] | We conducted a 3-round modified Delphi process ( , ) to identify a balanced measure set to evaluate the progress and impact of a person-centered oncology LHS. The modified Delphi process was conducted between July and September 2020, with oversight by a 19-member Data, Measurement, and Scholarship Workgroup representing diverse stakeholders within the health system (researchers, people living with cancer, clinicians, leaders). Setting This work occurred in a National Cancer Institute–designated comprehensive cancer center in northern New England, serving a largely rural catchment area. The cancer center treats approximately 32 000 patients annually and includes 17 interdisciplinary clinical oncology groups serving discrete populations. At the time of this undertaking, the cancer center and its larger health system and affiliated health services research organization were preparing to launch The Promise Partnership Oncology LHS to advance the health system’s strategic plan. The Promise Partnership LHS has 3 primary aims: promoting continuous improvement of health service quality, advancing cancer research, and supporting cancer care with and for people living with cancer. It is designed to optimize care processes by fostering mutually beneficial partnerships between people living with cancer, their families and support networks, and health professionals. Initial projects are designed to enhance care experiences and joy and fulfillment in work among health professionals. Recruitment We used purposive sampling to identify a multidisciplinary group of stakeholders to participate in the modified Delphi process with the intent of achieving input from 6 stakeholder groups ( ). Potential participants were selected from the health system, cancer center, health services research organization, people living with cancer and family members, and external partners. No participation incentives were provided. Domain and Measure Identification The initial measurement framework was informed by the condition-agnostic clinical value compass domains ( , ) and complementary measurement domains that reflect the LHS ecosystem ( , ). Seven domains were identified a priori: 1) clinical outcomes; 2) functional health outcomes; 3) experience of care; 4) cost, resource use, and financial indicators; 5) team well-being and joy in work; 6) learning culture and community; and 7) scholarly engagement and productivity. An eighth domain was added following round 1 of the Delphi process, reflecting diversity, equity, inclusion, and belonging. Three rounds of blinded voting occurred in July, August, and September 2020 via online ballots (Qualtrics, www.qualtrics.com ). First-round ballots included an extensive list of subdomains within each domain. Second- and third-round voting explored, then narrowed, candidate measures. The research team provided each participant with comprehensive supplementary materials to support voting decisions and was available by phone or e-mail to answer questions. Each round of voting was followed by a 50-minute virtual video meeting to discuss voting results, creating opportunities for participants to advocate for lower-ranked measures and contribute alternate measures that may have been overlooked. Discussions were recorded with participants’ knowledge and consent. We used descriptive statistics to analyze survey results using SPSS (version 26.0). Ballot Content Ballot 1 (see the , available online) prioritized measurement subdomains within 7 LHS domains. Fifty-three subdomains were presented based on a prototype value compass for serious illness care ( ), the quadruple aim ( ), the Institute for Healthcare Improvement’s Whole System Measures ( ), and a targeted review of measurement within each domain. Participants were asked to rank importance of subdomains on a 1-9 scale (1 = extremely unimportant; 9 = extremely important). To account for potential ceiling effects in Likert ratings, participants were asked to identify the 2 most important subdomains within each domain. Ballot 1 was distributed via email and available for 7 days. Median time of completion was 17 minutes. Ballot 2 (see the , available online) identified and ranked measures within each subdomain that advanced from Ballot 1. Subdomains advanced to round 2 based on a combination of mean score, number of respondents categorizing the subdomain as a priority, and prioritization during facilitated discussion. The following sources were consulted to identify potentially relevant measures for each subdomain: National Quality Forum ( ), Consumer Assessment of Health Plans Study surveys ( ), National Committee for Quality Assurance ( ), Lown Institute Hospitals Index ( ), US News and World Report cancer-specific metrics ( ), Commission on Cancer Accreditation Measures ( ), Quality Oncology Practice Initiative ( ), Institute for Healthcare Improvement Whole System Measures white paper ( ), New Hampshire State Cancer Registry ( ), and Measures of Person-Centered Coordinated Care ( ). Measures were also identified through targeted literature reviews, input from the panel, and measures available from the cancer center or health system. Candidate measure inclusion criteria included being valid, reliable, sensitive to change, feasible to measure, and aligned with values and priorities of the LHS. In domains with limited valid measures, conceptual definitions of measurement areas were included. Respondents were asked to rank a revised list of subdomains according to importance, then rate measures using a 1-5 Likert scale (1 = not at all important; 5 = extremely important). Ballot 2 was distributed via email and available for 7 days. Median time of completion was 48 minutes. Ballot 3 (see the , available online) identified recommendations for the final set of measures. Measures that advanced to Ballot 3 had an average rating score greater than 4, were identified by more than 50% of Delphi panel members as a top priority, or were promoted during Delphi panel discussions. Ballot 3 asked respondents to rank measures within each domain. Ballot 3 was distributed via email and available for 6 days. Median time of completion was 21 minutes. An additional discussion session was held with Delphi participants living with cancer and family members to discuss Ballot 3 measures. Recommendations for the final measurement set were derived from the proportion of respondents ranking a measure in the top 3 measures within a domain. The final discussion session focused on improving the selected measure set. Synthesis of discussion informed a set of draft recommendations presented to cancer center and health system leaders.
This work occurred in a National Cancer Institute–designated comprehensive cancer center in northern New England, serving a largely rural catchment area. The cancer center treats approximately 32 000 patients annually and includes 17 interdisciplinary clinical oncology groups serving discrete populations. At the time of this undertaking, the cancer center and its larger health system and affiliated health services research organization were preparing to launch The Promise Partnership Oncology LHS to advance the health system’s strategic plan. The Promise Partnership LHS has 3 primary aims: promoting continuous improvement of health service quality, advancing cancer research, and supporting cancer care with and for people living with cancer. It is designed to optimize care processes by fostering mutually beneficial partnerships between people living with cancer, their families and support networks, and health professionals. Initial projects are designed to enhance care experiences and joy and fulfillment in work among health professionals.
We used purposive sampling to identify a multidisciplinary group of stakeholders to participate in the modified Delphi process with the intent of achieving input from 6 stakeholder groups ( ). Potential participants were selected from the health system, cancer center, health services research organization, people living with cancer and family members, and external partners. No participation incentives were provided.
The initial measurement framework was informed by the condition-agnostic clinical value compass domains ( , ) and complementary measurement domains that reflect the LHS ecosystem ( , ). Seven domains were identified a priori: 1) clinical outcomes; 2) functional health outcomes; 3) experience of care; 4) cost, resource use, and financial indicators; 5) team well-being and joy in work; 6) learning culture and community; and 7) scholarly engagement and productivity. An eighth domain was added following round 1 of the Delphi process, reflecting diversity, equity, inclusion, and belonging. Three rounds of blinded voting occurred in July, August, and September 2020 via online ballots (Qualtrics, www.qualtrics.com ). First-round ballots included an extensive list of subdomains within each domain. Second- and third-round voting explored, then narrowed, candidate measures. The research team provided each participant with comprehensive supplementary materials to support voting decisions and was available by phone or e-mail to answer questions. Each round of voting was followed by a 50-minute virtual video meeting to discuss voting results, creating opportunities for participants to advocate for lower-ranked measures and contribute alternate measures that may have been overlooked. Discussions were recorded with participants’ knowledge and consent. We used descriptive statistics to analyze survey results using SPSS (version 26.0).
Ballot 1 (see the , available online) prioritized measurement subdomains within 7 LHS domains. Fifty-three subdomains were presented based on a prototype value compass for serious illness care ( ), the quadruple aim ( ), the Institute for Healthcare Improvement’s Whole System Measures ( ), and a targeted review of measurement within each domain. Participants were asked to rank importance of subdomains on a 1-9 scale (1 = extremely unimportant; 9 = extremely important). To account for potential ceiling effects in Likert ratings, participants were asked to identify the 2 most important subdomains within each domain. Ballot 1 was distributed via email and available for 7 days. Median time of completion was 17 minutes. Ballot 2 (see the , available online) identified and ranked measures within each subdomain that advanced from Ballot 1. Subdomains advanced to round 2 based on a combination of mean score, number of respondents categorizing the subdomain as a priority, and prioritization during facilitated discussion. The following sources were consulted to identify potentially relevant measures for each subdomain: National Quality Forum ( ), Consumer Assessment of Health Plans Study surveys ( ), National Committee for Quality Assurance ( ), Lown Institute Hospitals Index ( ), US News and World Report cancer-specific metrics ( ), Commission on Cancer Accreditation Measures ( ), Quality Oncology Practice Initiative ( ), Institute for Healthcare Improvement Whole System Measures white paper ( ), New Hampshire State Cancer Registry ( ), and Measures of Person-Centered Coordinated Care ( ). Measures were also identified through targeted literature reviews, input from the panel, and measures available from the cancer center or health system. Candidate measure inclusion criteria included being valid, reliable, sensitive to change, feasible to measure, and aligned with values and priorities of the LHS. In domains with limited valid measures, conceptual definitions of measurement areas were included. Respondents were asked to rank a revised list of subdomains according to importance, then rate measures using a 1-5 Likert scale (1 = not at all important; 5 = extremely important). Ballot 2 was distributed via email and available for 7 days. Median time of completion was 48 minutes. Ballot 3 (see the , available online) identified recommendations for the final set of measures. Measures that advanced to Ballot 3 had an average rating score greater than 4, were identified by more than 50% of Delphi panel members as a top priority, or were promoted during Delphi panel discussions. Ballot 3 asked respondents to rank measures within each domain. Ballot 3 was distributed via email and available for 6 days. Median time of completion was 21 minutes. An additional discussion session was held with Delphi participants living with cancer and family members to discuss Ballot 3 measures. Recommendations for the final measurement set were derived from the proportion of respondents ranking a measure in the top 3 measures within a domain. The final discussion session focused on improving the selected measure set. Synthesis of discussion informed a set of draft recommendations presented to cancer center and health system leaders.
Participants Three-quarters (76%) of individuals invited to the measurement panel agreed to participate (77 of 103). Individuals represented 6 stakeholder groups: people living with cancer and family members, clinicians and clinical staff, health-care system or cancer center leaders, quality improvement leaders, clinician and nonclinician researchers, and policy makers or funders. Ballots were completed by 94% or more of participants in each round of voting ( ). Discussion group attendance ranged from 64% to 77%. Identification of Domains, Subdomains, and Measures Round 1 voting and discussion ( , available online) resulted in 8 domains and 13 subdomains that drove selection of candidate measures for Ballot 2 (Box 1). In Round 2, 36 of 82 measures (44%) received a score of 4 or higher from two-thirds or more of participants ( , available online). Round 3 voting and discussion ranked the importance of 50 measures. shows prioritization of measures by domain (detailed ratings in , available online). Box 1. Domains and subdomains prioritized following ballot 1 voting and discussion Health-related quality of life Patient-reported general well-being and quality of life, symptoms, or functional status Patient- or caregiver-reported burden, coping, and support Clinical health outcomes Clinician-reported clinical improvement, disease activity, or symptoms and signs of illness Mortality, safety, or preventable harm Costs, resource use, and health system financial indicators Quality measures of care at the end of life Costs of care Financial toxicity Financial health of organization Experience of care Alignment of care with patient’s goals and preferences Access to care, continuity of care, and care integration Patient and family overall satisfaction with care Team well-being and joy in work Diversity, equity, inclusion, and belonging Learning culture and community Using science and evidence to inform care decisions Culture of continuous improvement and innovation Research engagement and productivity Final Delphi panel recommendations for the value compass included 22 measures in 8 domains. Recommendations were presented to 1) the LHS data, measurement, and scholarship workgroup; and 2) senior leaders of the cancer center and health system for review and approval. These discussions resulted in 3 modifications: replacement of the claims-based total cost of care with the patient-focused economic analysis (due to availability of local data), inclusion of voluntary staff turnover (due to availability of historical data), and removal of the clinical improvement measure (due to lack of a field-defined variable within the electronic health record [EHR]). depicts a value compass comprising the final set of recommended measures to support the Promise Partnership Oncology LHS. Each domain is referenced by its “point” on the compass. Cardinal points (north, south, east, and west) represent factors associated with the patient and caregiver, and ordinal points (northeast, northwest, southeast, southwest) represent the newly emerging context and ecosystem of the LHS. Each domain includes 2 or 3 measures, except experience of care, which includes 6 measures (3 perception measures; 3 process of care measures). Measures are derived from clinical data within the EHR (n = 3), patient- or caregiver-reported data that can be embedded within the EHR or experience surveys (n = 9), administrative data (n = 6), clinician or staff data (n = 2), and registry or claims data (n = 2). Descriptions of measures, data sources, and reporting strategy are shown in . Four domains and 14 measures are associated with the patient and caregiver. “Functional health and quality of life” includes measures reflecting overall well-being of people living with cancer and their caregivers. The Patient Reported Outcomes Measurement Information System (PROMIS) Global-10 ( ) provides a global composite of health-related quality of life; Distress Thermometer ( ) identifies distress among people with cancer and caregivers, and Modified Caregiver Strain Index ( ) identifies impact of serious illness on caregivers. “Experience of care” includes shared decision making [collaboRATE ( )], coordination of care, and the PROMIS Self-efficacy Scale for Managing Symptoms ( ) as well as access to care, documentation of advance care planning, and avoidance of aggressive end-of-life care ( ). “Cost and resource use” assesses financial hardship because of illness ( , ), avoidance or delay in accessing treatment because of cost ( ), and total cost of care measured through billing codes and encounter data ( ). “Clinical outcomes” reflect clinician-rated functional status of the patient [ECOG Performance Status ( )] and population-level survival by cancer type and stage. Four domains and 8 measures are associated with the LHS context and ecosystem. “Team well-being and joy in work” measures align with system-level data collection, including the Well-Being Index ( ) and voluntary turnover rate among staff. “Diversity, equity, inclusion, and belonging” assesses the proportion of patients screened for social determinants of health with follow-up documented in the EHR and inclusivity among patients and workforce. “Learning culture and community” includes Improvement Readiness ( ), which assesses ability of the work environment to support quality improvement, and a composite score of Commission on Cancer quality of care indicators ( ). Finally, “scholarly engagement and productivity” assesses institutional commitment and support for research and academic productivity inclusive of research and teaching.
Three-quarters (76%) of individuals invited to the measurement panel agreed to participate (77 of 103). Individuals represented 6 stakeholder groups: people living with cancer and family members, clinicians and clinical staff, health-care system or cancer center leaders, quality improvement leaders, clinician and nonclinician researchers, and policy makers or funders. Ballots were completed by 94% or more of participants in each round of voting ( ). Discussion group attendance ranged from 64% to 77%.
Round 1 voting and discussion ( , available online) resulted in 8 domains and 13 subdomains that drove selection of candidate measures for Ballot 2 (Box 1). In Round 2, 36 of 82 measures (44%) received a score of 4 or higher from two-thirds or more of participants ( , available online). Round 3 voting and discussion ranked the importance of 50 measures. shows prioritization of measures by domain (detailed ratings in , available online). Box 1. Domains and subdomains prioritized following ballot 1 voting and discussion Health-related quality of life Patient-reported general well-being and quality of life, symptoms, or functional status Patient- or caregiver-reported burden, coping, and support Clinical health outcomes Clinician-reported clinical improvement, disease activity, or symptoms and signs of illness Mortality, safety, or preventable harm Costs, resource use, and health system financial indicators Quality measures of care at the end of life Costs of care Financial toxicity Financial health of organization Experience of care Alignment of care with patient’s goals and preferences Access to care, continuity of care, and care integration Patient and family overall satisfaction with care Team well-being and joy in work Diversity, equity, inclusion, and belonging Learning culture and community Using science and evidence to inform care decisions Culture of continuous improvement and innovation Research engagement and productivity Final Delphi panel recommendations for the value compass included 22 measures in 8 domains. Recommendations were presented to 1) the LHS data, measurement, and scholarship workgroup; and 2) senior leaders of the cancer center and health system for review and approval. These discussions resulted in 3 modifications: replacement of the claims-based total cost of care with the patient-focused economic analysis (due to availability of local data), inclusion of voluntary staff turnover (due to availability of historical data), and removal of the clinical improvement measure (due to lack of a field-defined variable within the electronic health record [EHR]). depicts a value compass comprising the final set of recommended measures to support the Promise Partnership Oncology LHS. Each domain is referenced by its “point” on the compass. Cardinal points (north, south, east, and west) represent factors associated with the patient and caregiver, and ordinal points (northeast, northwest, southeast, southwest) represent the newly emerging context and ecosystem of the LHS. Each domain includes 2 or 3 measures, except experience of care, which includes 6 measures (3 perception measures; 3 process of care measures). Measures are derived from clinical data within the EHR (n = 3), patient- or caregiver-reported data that can be embedded within the EHR or experience surveys (n = 9), administrative data (n = 6), clinician or staff data (n = 2), and registry or claims data (n = 2). Descriptions of measures, data sources, and reporting strategy are shown in . Four domains and 14 measures are associated with the patient and caregiver. “Functional health and quality of life” includes measures reflecting overall well-being of people living with cancer and their caregivers. The Patient Reported Outcomes Measurement Information System (PROMIS) Global-10 ( ) provides a global composite of health-related quality of life; Distress Thermometer ( ) identifies distress among people with cancer and caregivers, and Modified Caregiver Strain Index ( ) identifies impact of serious illness on caregivers. “Experience of care” includes shared decision making [collaboRATE ( )], coordination of care, and the PROMIS Self-efficacy Scale for Managing Symptoms ( ) as well as access to care, documentation of advance care planning, and avoidance of aggressive end-of-life care ( ). “Cost and resource use” assesses financial hardship because of illness ( , ), avoidance or delay in accessing treatment because of cost ( ), and total cost of care measured through billing codes and encounter data ( ). “Clinical outcomes” reflect clinician-rated functional status of the patient [ECOG Performance Status ( )] and population-level survival by cancer type and stage. Four domains and 8 measures are associated with the LHS context and ecosystem. “Team well-being and joy in work” measures align with system-level data collection, including the Well-Being Index ( ) and voluntary turnover rate among staff. “Diversity, equity, inclusion, and belonging” assesses the proportion of patients screened for social determinants of health with follow-up documented in the EHR and inclusivity among patients and workforce. “Learning culture and community” includes Improvement Readiness ( ), which assesses ability of the work environment to support quality improvement, and a composite score of Commission on Cancer quality of care indicators ( ). Finally, “scholarly engagement and productivity” assesses institutional commitment and support for research and academic productivity inclusive of research and teaching.
We identified a comprehensive and balanced set of 22 measures in 8 domains to guide the development and evaluation of a person-centered oncology LHS. The LHS value compass includes measures that matter to a diverse stakeholder group and is weighted toward experiences of care. This codesigned set of measures was developed to support evaluation, improvement, and scholarship within the developing person-centered oncology LHS, allowing data to be turned into information that answers important questions and can guide future actions. This measure set has relevance for studying care from multiple perspectives, including clinical care, health-care quality and value improvement, system performance monitoring and improvement, and population health. Measures complement and expand data regularly reported to leadership and those within CancerLinQ and state cancer registries ( , ). The person-centered oncology LHS value compass facilitates a deliberate approach to measurement and reporting, feeding data back to multiple levels of the system (eg, clinical program level, cancer center system level, and health system level), and evaluating whether a balanced set of longitudinal measures can help drive practice-level and system-level improvement. The measure set includes leading and lagging indicators of performance for improvement interventions and the larger clinical enterprise. Leading indicators provide information on factors or processes important to achieving desired results (eg, Well-Being Index), and lagging indicators measure current performance (eg, voluntary staff turnover). Our work aligns with principles for designing a learning measurement system, including scanning the landscape of existing measurement and implementation efforts, engaging key stakeholders from diverse sectors, and developing criteria for measure selection to guide care delivery, improvement, and science ( ). Our prioritization of person-centered measures aligns with the coproduction LHS model ( , ) and recent work by others to develop indicators of effective person-centered oncology care ( , ). Our measure set improves on existing measure sets because of its codesigned origins, which resulted in a balanced set of measures associated with the patient and caregiver, alongside measures associated with the LHS ecosystem. The traditional clinical value compass includes 4 domains: functional outcomes, patient experience, cost and resource use, and clinical outcomes. Functional outcomes offer opportunities to gauge the effectiveness of health interventions on patient and caregiver well-being and inform future interventions. Patient experience measures support our ability to align care with what matters most to people living with cancer and their caregivers. Cost and resource use measures emphasize financial toxicity to the patient and caregiver while enabling the health system to better understand value and variation in costs. Finally, clinical outcomes provide indicators of effectiveness of cancer care, with ECOG providing a means to stratify other analyses. The codesign process generated a novel evolution of the clinical value compass, adding 4 priority areas for measurement. Team well-being and joy in work provides short- and long-term views of employee well-being. Diversity, equity, inclusion, and belonging measures support better understanding of factors that influence access, outcomes, and disparities in care and align with the evolving concept of the quintuple aim ( ). Learning culture and community measures reflect our ability to support continuous improvement and innovation within the LHS while delivering guideline-driven care. Finally, scholarly engagement and productivity aim to measure constructs associated with the institution’s support of scholarship and associated scholarly activities. This study has both strengths and limitations. Our Delphi panel comprised a large and diverse sample of stakeholders within the cancer community and beyond who participated actively in the work. Response rates to online ballots were consistently high (>94%), and discussion groups included an average of 72% of participants. Although we view this as a strength, the large size of the group presented some challenges for ensuring that all voices were heard. To address this, discussions were conducted with smaller subgroups, which allowed time for all individuals to speak. Because this multigroup discussion strategy limited the ability for panel members to participate in every discussion, we distributed recordings and transcripts of chats to all participants after each round of discussion. A strength and key feature of our Delphi process was inclusion of 7 people living with cancer or family members on the panel. To enhance engagement and psychological safety, we conducted a series of additional email interactions and a supplemental online video meeting with this group to invite and address questions and support candid conversations. We believe this led to more balanced participation in group discussions and to a stronger set of measures. Our panel included a higher proportion of individuals in clinical and research leadership roles and lower representation of staff nurses and other members of interdisciplinary teams that support cancer care delivery. This may have influenced measures selected and may affect uptake and use of measures. To support local acceptance and implementation of measures, membership in the Delphi panel was weighted toward our local institution; more than 10% of panel members represented external institutions to support generalizability. Our measure set was larger than planned, risking loss of focus on what contributes most to a high-performing oncology LHS. We believe, however, that addition of an eighth domain (diversity, equity, inclusion, and belonging) and the higher proportion of experience of care measures represent a strength of our measure set, prioritizing previously underappreciated features of a person-centered oncology LHS. Measures are being deployed in a phased implementation process, with widespread deployment of some measures and small-scale testing of other measures. For example, at the health system level, we have incorporated collaboRATE (a measure of shared decision making) into the Consumer Assessment of Health Plans Study Clinician and Group Surveys and oncology postvisit experience surveys and have deployed employee surveys across the cancer center to capture Well-Being Index and Improvement Readiness. At a smaller scale, we have developed EHR capability to capture advance care planning and serious illness conversations and are pilot testing electronic collection of the Distress Thermometer and social determinants of health screening in several locations. The resulting data and reporting infrastructure will support regular feedback of performance trends across the identified measure set using an audit and feedback approach ( ) and will provide trends to target improvements in different domains. We are codesigning report prototypes, which highlight primary outcomes and allow users to drill down to access detailed data. A subset of Delphi panel participants is engaged in deploying measures and assessing performance of measures, with iterative adaptations over time. Our person-centered oncology LHS value compass was codesigned by a diverse group of stakeholders. It will contribute to a deliberate approach to both measurement and reporting, feeding data back to multiple levels of the system and evaluating whether a balanced set of longitudinal measures can help drive practice-level and system-level improvements in health outcomes and experience, health-care quality, the well-being of health-care teams, and enhanced person-centered clinical and health services research and scholarship.
This work was supported by the Gordon and Betty Moore Foundation (Grant #7485); the Robert Wood Johnson Foundation (Grant #75925); the National Cancer Institute at the National Institutes of Health (Grant P30 CA023108); and The Couch Fund at The Dartmouth Institute for Health Policy and Clinical Practice.
Role of the funder: The funders had no role in the study design, collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit this work for publication. Disclosures: Steven Leach is on the Medical Advisory Board of Nybo Therapeutics and is cofounder and Chair of the Scientific Advisory Board for Episteme Prognostics. Eugene Nelson holds stock in Quality Data Management, Inc. which provides information services on patient experience of care and data on quality of care. Author contributions: Conceptualization: EN, KK, AT, MBF, AVC, AMK. Data curation: AVC and AMK. Formal analysis: AVC and AMK. Funding acquisition: SR, AT, SL, MBF, MMH, KK, EN. Investigation: AVC and AMK. Methodology: EN, AMK, AVC, KD, EM, AH, MBF, AT, KK. Project administration: AMK and MMH. Supervision: EN. Visualization: AVC. Writing—original draft: AVC, AMK, KK, AT, EN. Writing—review and editing: AVC, AMK, KK, KD, SL, MBF, EM, MMH, AH, EN, SR, AT. All authors read and approved the final manuscript. Acknowledgments: The authors wish to acknowledge the contributions of The Promise Partnership Learning Health System data, measurement, and scholarship working group for their support in guiding this work and the members of the Promise Partnership Delphi Panel, including: Albert Mulley, Amber Barnato, Amelia Cullinan, Andrew Williams, Ann Bradley, Anna Tosteson, Anne Holmes, Anne Ireland, Brant Oliver, Brock Christensen, Carol Majewski, Carolyn Kerrigan, Catherine Reed, Cathy Morrow, Corey Siegel, Daniel Jantzen, David Finley, Elissa Malcolm, Elizabeth Bengtson, Elizabeth McGrath, Elizabeth Stedina, Ellen Flaherty, Elliott Fisher, Eric Henderson, Erick Lansigan, Evan Benjamin, Gabriel Brooks, Garret Wasp, George Blike, Ira Byock, Janet Haines, Jenn Alford-Teaster, Jenna Schiffelbein, Jennifer Snide, Joanna Leyenaar, Jocelyn Chertoff, Joga Ivatury, Johanna Beliveau, John Sweetenham, Judith Rees, Julia Dalphin, Julie Kim, Karen Clements, Kathryn Kirkland, Kenneth Meehan, Konstantin Dragnev, Kris Bowen, Lawrence Dacey, Linton Evans, Malavika Govindan, Marcus Thygeson, Martha Goodrich, Mary Chamberlin, MaryAnn Stump, Matthew Mackwood, Matthew Wilson, Meredith Sorensen, Michael Calderwood, Paul Barr, Polly Campion, Ralph Jean-Mary, Rian M. Hasson, Sai Cherala, Sally Kraft, Samuel Casella, Samuel Shields, Sandra Wong, Shoshana Hort, Stephanie Tomlin, Stephen Liu, Stephen LeBlanc, Steven Leach, Susan DiStasio, Susan Reeves, Virginia Reed, Wendy Wells, Whitney Hammond, and Yolanda Sanchez. Disclaimers: Not applicable. Prior presentations: Not applicable.
The dataset is a summary of the data collected over the 3 rounds of the Delphi process. It is included in the (available online).
pkac037_Supplementary_Data Click here for additional data file.
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Mapping Surface Potential in DNA Aptamer–Neurochemical and Membrane–Ion Interactions on the SOS Substrate Using Terahertz Microscopy | 043256b5-c277-42ad-b895-531d90559cf7 | 11764386 | Biochemistry[mh] | The measurement of surface potential plays a critical role in a diverse range of applications spanning chemical processes, engineering, biological research, and industrial production. Applications include advancements in sensing technologies, catalysis, corrosion prevention, cell adhesion studies, nanoparticle separation, pulp processing, and so on . A recent study suggests that surface potential is a fundamental parameter for deciphering and interpreting complex electrical activities within biological systems. It provides essential insights into electrophysiological processes, enabling researchers and practitioners to explore dynamic interactions at the molecular and cellular levels . Surface potential sensing is a powerful method for investigating molecular interactions. Small changes in surface potential can indicate binding events, such as neurotransmitters interacting with aptamers or ions interacting with selective membranes. DNA aptamers, known for their high specificity and stability, are particularly effective for targeting neurotransmitters like serotonin and dopamine. When anchored on electrochemical sensor or optical sensor surfaces, these aptamers create detectable changes in the local charge environment, allowing for label-free and highly sensitive detection of binding events . The ability to detect and map subtle changes in surface potential is vital for advancing our understanding of molecular recognition processes on solid substrates. When target molecules—such as neurotransmitters or ions—bind to the surface, they alter the local charge environment, revealing key information about their presence and behavior. DNA aptamers play a critical role in this process, providing a robust, label-free platform for accurately monitoring these interactions. Many advanced technologies have been widely developed for surface potential detection, each offering unique advantages in specific applications. These include Kelvin probe microscopy (KVM) , which enables non-contact measurement of surface potential with high spatial resolution, and field-effect transistors (FETs) , which provide highly sensitive and real-time monitoring of surface charge changes. Light-addressable potentiometric sensors (LAPS) facilitate spatially resolved measurements of potential changes using optical excitation , while electrochemical devices offer robust platforms for detecting surface charge dynamics through redox reactions and ionic conductivity . Unlike those technologies, a terahertz chemical microscope (TCM) provides a label-free and highly sensitive approach for mapping surface potential by measuring terahertz amplitude . TCM utilizes a silicon-on-sapphire (SOS) substrate and femtosecond laser pulses to generate terahertz waves, whose intensity is modulated by the underlying surface potential. This modulation enables the detection and quantification of neurotransmitters and ions by correlating their presence and concentration with changes in terahertz amplitude.
2.1. Reagents and Materials Reagents including acetone (99.5%), ethanol (99.5%), sodium hydroxide (NaOH, 200 mM in Milli-Q water), and 3-aminopropyltriethoxysilane (APTES) were purchased from Sigma-Aldrich (Saint Louis, MO, USA). Bis(sulfosuccinimidyl)suberate (BS3) and phosphate-buffered saline (PBS) were obtained from Thermo Fisher Scientific (Waltham, MA, USA) and prepared at 10 mM in PBS as cross-linkers. Serotonin- and dopamine-binding aptamers were synthesized by Fasmac Co., Ltd, Tokyo, Japan. The aptamer concentrations (1800 ppm) were prepared in PBS or artificial cerebrospinal fluid (aCSF). Surface-blocking reagent ethanolamine-HCl was purchased from GE Healthcare (Chicago, IL, USA) and diluted to 0.1 M in Milli-Q water for use. Serotonin and dopamine solutions were prepared in PBS or aCSF at various concentrations (100 ppt to 1000 ppb for serotonin). For the ion measurements, a calcium ion-selective membrane solution was prepared from polyvinyl chloride (PVC), bis(2-ethylhexyl) sebacate (DOS), sodium ionophore II, and sodium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate, dissolved in tetrahydrofuran (THF). Polyvinyl chloride was purchased from Wako Pure Chemical Industries, Ltd, Tokyo, Japan. DOS and sodium ionophore II were purchased from Sigma-Aldrich. PDMS (SYLGARD184) was purchased from Sansho Co., Ltd, Osaka, Japan. 2.2. SOS Substrate and Terahertz Chemical Microscope Optical Setup The TCM is an instrument designed to extract information on chemical reaction events occurring on a terahertz emitter, known as the sensing plate. Silicon-on-sapphire (SOS) substrate, named as the sensing plate, was used to map the surface potential using the TCM system. The sensing plate (10 cm × 10 cm) is composed of a thin SiO 2 layer, approximately a few nanometers thick, followed by a 500 nm Si layer, and a 500 μm Al 2 O 3 substrate, as shown in a. b illustrates the optical configuration of the TCM setup. The system uses a femtosecond laser with a repetition rate of 80 MHz, a pulse width of 130 fs, and a central wavelength of 780 nm. As shown in b, this laser beam is split into two paths: a pump beam and a probe beam. The pump beam, modulated at 2 kHz, is focused through a lens onto the sapphire side of the sensing plate to generate terahertz waves. These THz waves are then collected and directed by parabolic mirrors and focused on a super-hemispherical lens attached to the sensing element. Meanwhile, the probe beam is routed through a delay stage and directed into a detector to facilitate time-resolved measurements of the generated THz signals. The underlying measurement mechanism is as follows: due to doping and interface states at the Si/SiO 2 boundary, a depletion layer electric field ( E d ) is already established. When the femtosecond laser pulse excites the inside of the semiconductor of the sensing plate, carriers (electrons and/or holes) are generated and rapidly accelerated under the influence of E d , resulting in a transient current. The time-varying current, in turn, emits electromagnetic radiation—terahertz waves—whose amplitude is proportional to the time derivative of the current. More detail on the THz generation process can be found in our previous studies . Eventually, Equation (1) is derived, relating to the potential change, the depletion layer electric field, and the THz amplitude ( E T H z ): (1) E T H z ∝ E d = 2 e N ε 0 ε d ϕ S Key parameters in Equation (1) include e (the elementary charge), N (the charge density per unit area), ε 0 (the vacuum permittivity), ε d (the relative permittivity of the semiconductor), and ϕ S (the surface potential). By measuring the THz amplitude, it is possible to detect changes in surface potential and, consequently, gain insights into the chemical interactions occurring at the surface. 2.3. Substrate Cleaning and Aptamer Modification Prior to aptamer modification, the SOS substrate was sonicated in 99.5% acetone and 99.5% ethanol for 2 min each to remove surface contaminants. After sterilization, 200 mM of NaOH solution was added to the wells and shaken for 5 min to introduce hydroxyl groups on the SiO 2 surface. Following the NaOH treatment, the wells were rinsed once with Milli-Q water. APTES (2% in Milli-Q) was then added, and the wells were shaken for 30 min to form an amine-functionalized surface. After removing the APTES solution and rinsing twice with Milli-Q water, BS3 (10 mM in PBS) was added and incubated at room temperature for 1 h to introduce reactive groups for aptamer immobilization. The BS3 solution was subsequently removed, and the wells were rinsed twice with Milli-Q water. Serotonin aptamer (sequence: 5′-amnio link-CGACTGGTAGGCAGATAGGGG AAG CTG ATT CGA TGC GTG GGT CG-3′) and dopamine aptamer (sequence:5′-amnio link-CGACGCCAGTTTGAAGGTTCGTTCGCAGGTGTGGAGTGACGTCG), prepared at 1800 ppm in PBS or aCSF, were added to the wells and incubated for 6 h at room temperature, followed by 18 h at 4 °C. This procedure enabled the aptamers to covalently bind to the BS 3 -functionalized surface. The wells were then washed with PBS, and 0.1 M ethanolamine-HCl was added for 20 min at room temperature to block non-specific binding sites. After removal of the ethanolamine-HCl solution and washing with PBS, the sensing plates were ready for the neurotransmitter detection experiments. a shows the modification process, and b presents an AFM image of serotonin-binding DNA aptamers immobilized on an SOS substrate. The image reveals the nanoscale roughness and morphology of the functionalized surface, with the white dot structures representing the individual aptamers. The tertiary structures of DNA aptamers in PBS and aCSF were predicted using Alphafold 3 . 2.4. For Surface Potential Mapping and Real-Time Aptamer–Serotonin Interaction Monitoring To evaluate the surface potential mapping of aptamer–serotonin/dopamine complexes, serotonin and dopamine solutions, varying from 100 ppt to 1000 ppb, were then sequentially introduced into the solution wells. After each addition, the samples were gently shaken and allowed to interact with the immobilized DNA aptamers for 20 min. Following incubation, the wells were rinsed with PBS, and a new THz amplitude distribution was measured. To evaluate the real-time THz amplitude response across a range of serotonin concentrations, we first recorded a baseline THz intensity distribution prior to the analyte introduction. Serotonin solutions, varying from 1 ppb to 1000 ppb, respectively, were then introduced into the solution wells. Real-time THz amplitude changes were recorded. In addition, we conducted a parallel series of measurements using artificial cerebrospinal fluid (aCSF) instead of PBS. By comparing the THz responses under these two conditions, we evaluated the influence of the divalent cations in aCSF on the sensitivity of serotonin and dopamine detection. This dual-environment approach provides valuable insights into how ionic composition can enhance or modulate the binding dynamics observed in THz amplitude maps. 2.5. 3D-Printed PDMS Microwell for Calcium Ion Measurements To measure calcium ion concentration using TCM, a selective membrane that only reacts to calcium ions is prepared. The calcium ion-selective membrane is a membrane in which an ion-sensitive substance (ionophore) that selectively reacts with the target ion is dissolved in a suitable solvent and dispersed and retained in a base material softened by a plasticizer. In the calcium ion-selective membrane, polyvinyl chloride (PVC) serves as the base material, while dioctyl sebacate (DOS) acts as the plasticizer. Sodium ionophore II functions as the ionophore, and sodium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate is used as the additive. The amounts of these materials are given in . Since the density of DOS is 0.914 g/mL, 72 μL of DOS was mixed to contain 65.45 mg of DOS. The mixture was dissolved in THF (tetrahydrofuran; Wako Pure Chemical Industries, Ltd., Osaka, Japan). The calcium ion-selective membrane solution was prepared by mixing at 50 rpm for more than 24 h in a VMR-3R variable mixer (AS ONE Corporation, Osaka, Japan). The calcium ion-selective membrane solution was dropped on the SOS substrate one day before the measurement, and the solvent (THF) was evaporated and dried in the dark to form a membrane on the sensing plate. In this study, the wells are miniaturized with PDMS, and microwell-based measurements are performed. In TCM, the sensing plate is irradiated with a femtosecond laser pulse, and the potential change at the irradiated area is measured. The measurement area is therefore approximately the size of the laser focal spot (1 μm). Therefore, the measurement can be performed even if the well size is as small as the laser size. To measure calcium ion concentrations without a reference electrode, a calcium ion-sensitive membrane was applied to the sensing plate. PDMS wells (1 μL volume) were fabricated to minimize the sample volumes. Prior to the sample addition, a background THz amplitude was acquired. Then, 1 μL samples containing varying calcium ion concentrations (sodium ions: 1.4 × 10 −1 mol/L; potassium ions: 4 × 10 −3 mol/L) were introduced into the PDMS wells, and the THz amplitude was measured. The difference in THz amplitude before and after the sample addition was used to quantify the calcium ion concentration.
Reagents including acetone (99.5%), ethanol (99.5%), sodium hydroxide (NaOH, 200 mM in Milli-Q water), and 3-aminopropyltriethoxysilane (APTES) were purchased from Sigma-Aldrich (Saint Louis, MO, USA). Bis(sulfosuccinimidyl)suberate (BS3) and phosphate-buffered saline (PBS) were obtained from Thermo Fisher Scientific (Waltham, MA, USA) and prepared at 10 mM in PBS as cross-linkers. Serotonin- and dopamine-binding aptamers were synthesized by Fasmac Co., Ltd, Tokyo, Japan. The aptamer concentrations (1800 ppm) were prepared in PBS or artificial cerebrospinal fluid (aCSF). Surface-blocking reagent ethanolamine-HCl was purchased from GE Healthcare (Chicago, IL, USA) and diluted to 0.1 M in Milli-Q water for use. Serotonin and dopamine solutions were prepared in PBS or aCSF at various concentrations (100 ppt to 1000 ppb for serotonin). For the ion measurements, a calcium ion-selective membrane solution was prepared from polyvinyl chloride (PVC), bis(2-ethylhexyl) sebacate (DOS), sodium ionophore II, and sodium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate, dissolved in tetrahydrofuran (THF). Polyvinyl chloride was purchased from Wako Pure Chemical Industries, Ltd, Tokyo, Japan. DOS and sodium ionophore II were purchased from Sigma-Aldrich. PDMS (SYLGARD184) was purchased from Sansho Co., Ltd, Osaka, Japan.
The TCM is an instrument designed to extract information on chemical reaction events occurring on a terahertz emitter, known as the sensing plate. Silicon-on-sapphire (SOS) substrate, named as the sensing plate, was used to map the surface potential using the TCM system. The sensing plate (10 cm × 10 cm) is composed of a thin SiO 2 layer, approximately a few nanometers thick, followed by a 500 nm Si layer, and a 500 μm Al 2 O 3 substrate, as shown in a. b illustrates the optical configuration of the TCM setup. The system uses a femtosecond laser with a repetition rate of 80 MHz, a pulse width of 130 fs, and a central wavelength of 780 nm. As shown in b, this laser beam is split into two paths: a pump beam and a probe beam. The pump beam, modulated at 2 kHz, is focused through a lens onto the sapphire side of the sensing plate to generate terahertz waves. These THz waves are then collected and directed by parabolic mirrors and focused on a super-hemispherical lens attached to the sensing element. Meanwhile, the probe beam is routed through a delay stage and directed into a detector to facilitate time-resolved measurements of the generated THz signals. The underlying measurement mechanism is as follows: due to doping and interface states at the Si/SiO 2 boundary, a depletion layer electric field ( E d ) is already established. When the femtosecond laser pulse excites the inside of the semiconductor of the sensing plate, carriers (electrons and/or holes) are generated and rapidly accelerated under the influence of E d , resulting in a transient current. The time-varying current, in turn, emits electromagnetic radiation—terahertz waves—whose amplitude is proportional to the time derivative of the current. More detail on the THz generation process can be found in our previous studies . Eventually, Equation (1) is derived, relating to the potential change, the depletion layer electric field, and the THz amplitude ( E T H z ): (1) E T H z ∝ E d = 2 e N ε 0 ε d ϕ S Key parameters in Equation (1) include e (the elementary charge), N (the charge density per unit area), ε 0 (the vacuum permittivity), ε d (the relative permittivity of the semiconductor), and ϕ S (the surface potential). By measuring the THz amplitude, it is possible to detect changes in surface potential and, consequently, gain insights into the chemical interactions occurring at the surface.
Prior to aptamer modification, the SOS substrate was sonicated in 99.5% acetone and 99.5% ethanol for 2 min each to remove surface contaminants. After sterilization, 200 mM of NaOH solution was added to the wells and shaken for 5 min to introduce hydroxyl groups on the SiO 2 surface. Following the NaOH treatment, the wells were rinsed once with Milli-Q water. APTES (2% in Milli-Q) was then added, and the wells were shaken for 30 min to form an amine-functionalized surface. After removing the APTES solution and rinsing twice with Milli-Q water, BS3 (10 mM in PBS) was added and incubated at room temperature for 1 h to introduce reactive groups for aptamer immobilization. The BS3 solution was subsequently removed, and the wells were rinsed twice with Milli-Q water. Serotonin aptamer (sequence: 5′-amnio link-CGACTGGTAGGCAGATAGGGG AAG CTG ATT CGA TGC GTG GGT CG-3′) and dopamine aptamer (sequence:5′-amnio link-CGACGCCAGTTTGAAGGTTCGTTCGCAGGTGTGGAGTGACGTCG), prepared at 1800 ppm in PBS or aCSF, were added to the wells and incubated for 6 h at room temperature, followed by 18 h at 4 °C. This procedure enabled the aptamers to covalently bind to the BS 3 -functionalized surface. The wells were then washed with PBS, and 0.1 M ethanolamine-HCl was added for 20 min at room temperature to block non-specific binding sites. After removal of the ethanolamine-HCl solution and washing with PBS, the sensing plates were ready for the neurotransmitter detection experiments. a shows the modification process, and b presents an AFM image of serotonin-binding DNA aptamers immobilized on an SOS substrate. The image reveals the nanoscale roughness and morphology of the functionalized surface, with the white dot structures representing the individual aptamers. The tertiary structures of DNA aptamers in PBS and aCSF were predicted using Alphafold 3 .
To evaluate the surface potential mapping of aptamer–serotonin/dopamine complexes, serotonin and dopamine solutions, varying from 100 ppt to 1000 ppb, were then sequentially introduced into the solution wells. After each addition, the samples were gently shaken and allowed to interact with the immobilized DNA aptamers for 20 min. Following incubation, the wells were rinsed with PBS, and a new THz amplitude distribution was measured. To evaluate the real-time THz amplitude response across a range of serotonin concentrations, we first recorded a baseline THz intensity distribution prior to the analyte introduction. Serotonin solutions, varying from 1 ppb to 1000 ppb, respectively, were then introduced into the solution wells. Real-time THz amplitude changes were recorded. In addition, we conducted a parallel series of measurements using artificial cerebrospinal fluid (aCSF) instead of PBS. By comparing the THz responses under these two conditions, we evaluated the influence of the divalent cations in aCSF on the sensitivity of serotonin and dopamine detection. This dual-environment approach provides valuable insights into how ionic composition can enhance or modulate the binding dynamics observed in THz amplitude maps.
To measure calcium ion concentration using TCM, a selective membrane that only reacts to calcium ions is prepared. The calcium ion-selective membrane is a membrane in which an ion-sensitive substance (ionophore) that selectively reacts with the target ion is dissolved in a suitable solvent and dispersed and retained in a base material softened by a plasticizer. In the calcium ion-selective membrane, polyvinyl chloride (PVC) serves as the base material, while dioctyl sebacate (DOS) acts as the plasticizer. Sodium ionophore II functions as the ionophore, and sodium tetrakis[3,5-bis(trifluoromethyl)phenyl]borate is used as the additive. The amounts of these materials are given in . Since the density of DOS is 0.914 g/mL, 72 μL of DOS was mixed to contain 65.45 mg of DOS. The mixture was dissolved in THF (tetrahydrofuran; Wako Pure Chemical Industries, Ltd., Osaka, Japan). The calcium ion-selective membrane solution was prepared by mixing at 50 rpm for more than 24 h in a VMR-3R variable mixer (AS ONE Corporation, Osaka, Japan). The calcium ion-selective membrane solution was dropped on the SOS substrate one day before the measurement, and the solvent (THF) was evaporated and dried in the dark to form a membrane on the sensing plate. In this study, the wells are miniaturized with PDMS, and microwell-based measurements are performed. In TCM, the sensing plate is irradiated with a femtosecond laser pulse, and the potential change at the irradiated area is measured. The measurement area is therefore approximately the size of the laser focal spot (1 μm). Therefore, the measurement can be performed even if the well size is as small as the laser size. To measure calcium ion concentrations without a reference electrode, a calcium ion-sensitive membrane was applied to the sensing plate. PDMS wells (1 μL volume) were fabricated to minimize the sample volumes. Prior to the sample addition, a background THz amplitude was acquired. Then, 1 μL samples containing varying calcium ion concentrations (sodium ions: 1.4 × 10 −1 mol/L; potassium ions: 4 × 10 −3 mol/L) were introduced into the PDMS wells, and the THz amplitude was measured. The difference in THz amplitude before and after the sample addition was used to quantify the calcium ion concentration.
3.1. Mapping of the Surface Potential of DNA Aptamer–Serotonin Complexes a displays a series of two-dimensional THz amplitude maps obtained under varying conditions. Each map corresponds to a different serotonin concentration exposed to the DNA aptamer-functionalized SOS surface. The sequence includes a background measurement (i.e., phosphate-buffered saline, PBS) followed by serotonin solutions at 1 ppb, 10 ppb, 100 ppb, and 1000 ppb. The color scale indicates the THz amplitude, clearly illustrating how the THz response intensifies with increasing analyte concentrations. c–e depict temporal response curves of the THz amplitude as the sensor is exposed to specific serotonin concentrations (1 ppb in (c), 100 ppb in (d), and 1000 ppb in (e)). Each graph shows the THz amplitude over time, with a vertical arrow indicating the point at which the target analyte is introduced. These time-series plots illustrate the speed and intensity of the DNA aptamer-modified SOS substrate’s reaction to increasing analyte concentrations, confirming the concentration-dependent behavior observed in earlier results. 3.2. Comparative Study of DNA Aptamer Conformational Changes and Terahertz Responses Changes in PBS and aCSF In the comparative study of DNA aptamer conformational changes, the ionic composition of the surrounding medium plays a crucial role. compares the primary ionic constituents of two commonly used physiological buffers: phosphate-buffered saline (PBS) and artificial cerebrospinal fluid (aCSF). While both solutions maintain phosphate-based buffering capacity, aCSF incorporates additional divalent ions such as Mg 2 + and Ca 2 + . These ions can influence the folding, stability, and binding affinity of DNA aptamers. By examining aptamer behavior in PBS versus aCSF, the way ionic composition affects aptamer structure and function under conditions more closely resembling the in vivo environment can be better understood. integrates structural modeling, molecular interactions, and experimental sensing data to illustrate how the ionic environment influences serotonin binding to a DNA aptamer and the resulting THz amplitude response. In a,b, molecular models generated via SwissDock simulations show the serotonin-binding DNA aptamer complexed with/without divalent cations (Mg 2 + and Ca 2 + ) . Under artificial cerebrospinal fluid (aCSF) conditions, the aptamer–serotonin complex is stabilized by a combination of hydrogen bonds, hydrophobic interactions, and π-stacking interactions. In contrast, when the complex is formed in PBS, the primary stabilizing forces are hydrogen bonds and hydrophobic interactions, without significant π-stacking contributions. The 3D renderings highlight the aptamer’s tertiary structure and the precise binding orientation of serotonin within its binding pocket, illustrating how the presence of divalent cations in aCSF can promote more diverse and potentially stronger molecular interactions. In c, a comparative bar chart shows the THz amplitude responses recorded in aCSF (red bars) versus PBS (blue bars) at various serotonin concentrations. While the PBS measurements yield higher signals at lower concentrations, the aCSF environment produces enhanced responses at elevated serotonin levels. In c, a series of THz amplitude distribution maps visualize the signal intensity upon different serotonin concentration introductions. The experimental results indicate that the THz amplitude obtained in aCSF is higher than in PBS, which aligns closely with the outcomes predicted by the modeling simulations. In , consistent results were observed for the dopamine-binding DNA aptamer and its complex with dopamine. The predicted tertiary structures of the dopamine-binding DNA aptamer in PBS and aCSF are shown in a, highlighting structural differences between the two environments. The terahertz measurement results, presented in b, indicate that the terahertz amplitude was higher in aCSF compared to PBS, suggesting an enhanced interaction in the aCSF environment. c displays terahertz amplitude distribution maps corresponding to dopamine concentrations of 20 ppb, 200 ppb, and 2000 ppb, illustrating the surface potential variations at different concentration levels. 3.3. PDMS Microwell-Based Membrane–Calcium Ion Interaction and Potential Mapping Conventional ion detection methods, such as ion-selective electrodes (ISEs) and ion-sensitive field-effect transistors (ISFETs) , rely on reference electrodes, limiting their potential for miniaturization, integration, and reduced sample volumes. In contrast, TCM operates without the need for a reference electrode; therefore, it could emerge as a promising platform for accurate, non-invasive calcium ion concentration measurements, offering enhanced scalability and versatility over traditional ion measurement methods. demonstrates a terahertz-based approach for calcium ion detection using an SOS substrate coated with an ion-selective membrane and integrated with PDMS microwell structures. In a, a schematic illustrates how the ion-selective membrane interacts with Ca 2 + ions, altering the surface charge distribution and thus modulating the THz response. The presence of Ca 2 + ions leads to a measurable change in THz wave intensity, enabling quantitative detection. To create the microwell structures, PDMS was employed. As PDMS can be molded to replicate microscale features, 3D printing technology was used to form microwells with a volume of approximately 1 μL on the SOS substrate. These wells were then filled with the calcium ion-selective membrane solution ( b). The sample solutions contained calcium ions along with controlled concentrations of sodium (1.4 × 10 −1 mol/L) and potassium (4 × 10 −3 ) mol/L) ions. First, a background of the THz amplitude distribution map was acquired from the PDMS wells before the reaction. Next, the calcium-containing sample solution (1 μL) was introduced, and a second THz amplitude distribution was obtained. By subtracting the background map, the changes attributable to calcium ions alone could be identified. c presents THz intensity distribution maps for three different SOS substrates (samples 1, 2, and 3) exposed to varying Ca 2 + concentrations (10 − 1 to 10 − 4 mol/L). The images depict how THz amplitude responds to increasing ion concentrations, demonstrating a highly linear correlation over a wide concentration range in d. The observed increase in THz amplitude with rising calcium concentration confirms that even microvolume solutions (1 μL) can be accurately assessed. By integrating an ion-selective membrane onto an SOS substrate and PDMS microwells, we achieved sensitive and linear detection of calcium ions by monitoring surface potential changes through THz measurements. This approach underscores the potential of THz sensing platforms for rapid, small-scale ion monitoring.
a displays a series of two-dimensional THz amplitude maps obtained under varying conditions. Each map corresponds to a different serotonin concentration exposed to the DNA aptamer-functionalized SOS surface. The sequence includes a background measurement (i.e., phosphate-buffered saline, PBS) followed by serotonin solutions at 1 ppb, 10 ppb, 100 ppb, and 1000 ppb. The color scale indicates the THz amplitude, clearly illustrating how the THz response intensifies with increasing analyte concentrations. c–e depict temporal response curves of the THz amplitude as the sensor is exposed to specific serotonin concentrations (1 ppb in (c), 100 ppb in (d), and 1000 ppb in (e)). Each graph shows the THz amplitude over time, with a vertical arrow indicating the point at which the target analyte is introduced. These time-series plots illustrate the speed and intensity of the DNA aptamer-modified SOS substrate’s reaction to increasing analyte concentrations, confirming the concentration-dependent behavior observed in earlier results.
In the comparative study of DNA aptamer conformational changes, the ionic composition of the surrounding medium plays a crucial role. compares the primary ionic constituents of two commonly used physiological buffers: phosphate-buffered saline (PBS) and artificial cerebrospinal fluid (aCSF). While both solutions maintain phosphate-based buffering capacity, aCSF incorporates additional divalent ions such as Mg 2 + and Ca 2 + . These ions can influence the folding, stability, and binding affinity of DNA aptamers. By examining aptamer behavior in PBS versus aCSF, the way ionic composition affects aptamer structure and function under conditions more closely resembling the in vivo environment can be better understood. integrates structural modeling, molecular interactions, and experimental sensing data to illustrate how the ionic environment influences serotonin binding to a DNA aptamer and the resulting THz amplitude response. In a,b, molecular models generated via SwissDock simulations show the serotonin-binding DNA aptamer complexed with/without divalent cations (Mg 2 + and Ca 2 + ) . Under artificial cerebrospinal fluid (aCSF) conditions, the aptamer–serotonin complex is stabilized by a combination of hydrogen bonds, hydrophobic interactions, and π-stacking interactions. In contrast, when the complex is formed in PBS, the primary stabilizing forces are hydrogen bonds and hydrophobic interactions, without significant π-stacking contributions. The 3D renderings highlight the aptamer’s tertiary structure and the precise binding orientation of serotonin within its binding pocket, illustrating how the presence of divalent cations in aCSF can promote more diverse and potentially stronger molecular interactions. In c, a comparative bar chart shows the THz amplitude responses recorded in aCSF (red bars) versus PBS (blue bars) at various serotonin concentrations. While the PBS measurements yield higher signals at lower concentrations, the aCSF environment produces enhanced responses at elevated serotonin levels. In c, a series of THz amplitude distribution maps visualize the signal intensity upon different serotonin concentration introductions. The experimental results indicate that the THz amplitude obtained in aCSF is higher than in PBS, which aligns closely with the outcomes predicted by the modeling simulations. In , consistent results were observed for the dopamine-binding DNA aptamer and its complex with dopamine. The predicted tertiary structures of the dopamine-binding DNA aptamer in PBS and aCSF are shown in a, highlighting structural differences between the two environments. The terahertz measurement results, presented in b, indicate that the terahertz amplitude was higher in aCSF compared to PBS, suggesting an enhanced interaction in the aCSF environment. c displays terahertz amplitude distribution maps corresponding to dopamine concentrations of 20 ppb, 200 ppb, and 2000 ppb, illustrating the surface potential variations at different concentration levels.
Conventional ion detection methods, such as ion-selective electrodes (ISEs) and ion-sensitive field-effect transistors (ISFETs) , rely on reference electrodes, limiting their potential for miniaturization, integration, and reduced sample volumes. In contrast, TCM operates without the need for a reference electrode; therefore, it could emerge as a promising platform for accurate, non-invasive calcium ion concentration measurements, offering enhanced scalability and versatility over traditional ion measurement methods. demonstrates a terahertz-based approach for calcium ion detection using an SOS substrate coated with an ion-selective membrane and integrated with PDMS microwell structures. In a, a schematic illustrates how the ion-selective membrane interacts with Ca 2 + ions, altering the surface charge distribution and thus modulating the THz response. The presence of Ca 2 + ions leads to a measurable change in THz wave intensity, enabling quantitative detection. To create the microwell structures, PDMS was employed. As PDMS can be molded to replicate microscale features, 3D printing technology was used to form microwells with a volume of approximately 1 μL on the SOS substrate. These wells were then filled with the calcium ion-selective membrane solution ( b). The sample solutions contained calcium ions along with controlled concentrations of sodium (1.4 × 10 −1 mol/L) and potassium (4 × 10 −3 ) mol/L) ions. First, a background of the THz amplitude distribution map was acquired from the PDMS wells before the reaction. Next, the calcium-containing sample solution (1 μL) was introduced, and a second THz amplitude distribution was obtained. By subtracting the background map, the changes attributable to calcium ions alone could be identified. c presents THz intensity distribution maps for three different SOS substrates (samples 1, 2, and 3) exposed to varying Ca 2 + concentrations (10 − 1 to 10 − 4 mol/L). The images depict how THz amplitude responds to increasing ion concentrations, demonstrating a highly linear correlation over a wide concentration range in d. The observed increase in THz amplitude with rising calcium concentration confirms that even microvolume solutions (1 μL) can be accurately assessed. By integrating an ion-selective membrane onto an SOS substrate and PDMS microwells, we achieved sensitive and linear detection of calcium ions by monitoring surface potential changes through THz measurements. This approach underscores the potential of THz sensing platforms for rapid, small-scale ion monitoring.
This study demonstrated the feasibility and effectiveness of TCM in mapping surface potential changes resulting from DNA aptamer–neurochemical and membrane–ion interactions on a silicon-on-sapphire (SOS) substrate. By leveraging femtosecond laser pulses to generate terahertz waves and correlating their amplitude with underlying surface potential, we achieved label-free, sensitive detection of molecular and ionic species in microvolume samples. The results reveal that neurochemicals like serotonin and dopamine can be reliably monitored through TCM by measuring the terahertz amplitude. DNA aptamers proved to be promising elements, enabling sensitive detection across a broad concentration range. Additionally, the inclusion of artificial cerebrospinal fluid (aCSF) in the measurement environment highlighted the role of divalent cations, such as Mg 2 + and Ca 2 + , in enhancing detection sensitivity. These observations underscore the critical influence of ionic composition on sensor performance. Results on calcium ion detection demonstrated that integrating ion-selective membranes within PDMS microwells enables precise and linear correlations between terahertz amplitude and ion concentrations, further showing the versatility of TCM for analyzing diverse analyte classes. In summary, our findings highlight TCM’s potential as a powerful diagnostic and analytical tool. By enabling direct visualization and quantification of dynamic biochemical processes, TCM is well-positioned to advance surface-potential-driven research in biomedical applications, as well as in materials science and related fields.
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Association between indoor ventilation frequency and low muscle mass among older adults in China: a national cross-sectional research | ccf343fa-b44f-443d-96e4-924c66bfc32d | 11947109 | Musculoskeletal System[mh] | Sarcopenia is a progressive, age-related systemic disease characterized by a significant loss of skeletal muscle mass, strength, and function . Globally, the prevalence of sarcopenia ranges from about 6–22%, making it a significant public health concern in aging populations . As a core indicator of clinical assessment, the quantitative measurement of muscle mass plays an essential role in diagnosing and managing sarcopenia . The muscle mass index is widely used to assess skeletal muscle health and has been validated in numerous studies , . Loss of muscle mass–a hallmark of the aging process, is strongly associated with disability, reduced mobility, falls, fractures, and increased mortality . However, despite the increasing risks of sarcopenia, specific pharmacological treatments for low muscle mass (LMM) are still under investigation. Currently, muscle mass management still relies mainly on nutritional and exercise interventions, with neuromuscular electrical stimulation therapies are increasingly being applied in clinical practice – . Notably, in addition to traditional factors such as age, exercise, and nutrition , , the influence of environmental exposures on muscle homeostasis is gaining increasing attention. Several studies have shown that the decline in muscle mass is related to air pollutants, including PM 2.5 (Particulate Matter 2.5), CO (Carbon Monoxide) and NO 2 (Nitrogen Dioxide) – . Notably, a study has shown that modern people spend around 90% of their time in indoor environments, making indoor air quality a key factor in health . A significant body of research has examined the adverse health outcomes (e.g., cardiovascular disease, respiratory diseases, and mortality) caused by indoor air pollution , , highlighting the importance of focusing on indoor air quality. Previous studies have also indicated that, in addition to the impact of outdoor air pollution on muscle mass loss, indoor air pollution may also contribute to muscle mass loss, especially for older Chinese adults who spend extended periods at home , . Using cooking fuels can seriously affect indoor air quality and increase the concentration of airborne pollutants such as PM 2.5 , . A national study revealed that the incidence of sarcopenia was 4.5% lower among individuals using clean fuel for cooking, 2.9% lower among those using it for heating, and 3.0% and 1.9% higher among solid fuel users for cooking and heating, respectively . Indoor ventilation, a key method for improving indoor air quality, effectively reduces pollutant concentrations by introducing fresh air into the indoor spaces, either naturally (e.g., through open windows) or mechanically (e.g., using air conditioning), thereby mitigating their adverse effects on health , . For example, a European study of nursing homes found that enhanced indoor ventilation was effective in mitigating the adverse effects of indoor air quality on the health of older residents and significantly improved overall quality of life . Additionally, epidemiological studies have shown that higher indoor ventilation frequency (IVF) is associated with reduced risk of allergic symptoms, respiratory diseases and cognitive function in young people in developed regions – . Currently, there are no reports examining the impact of quantifiable IVF on muscle mass. Most environmental health studies focus primarily on cardiorespiratory or metabolic outcomes, with limited exploration of muscle mass. To date, no studies have quantified the effect of IVF on LMM. To fill this research gap, this study, based on data from the 2017–2018 China Longitudinal Healthy Longevity Survey (CLHLS), aimed to explore the association between IVF and LMM, providing new ideas for the development of individualised health management strategies.
Data source and sample This study utilized data from the CLHLS, conducted by Peking University’s Research Center for Aging Health and Development. CLHLS utilized a targeted random sample design to ensure the representativeness and reliability of the sample, providing comprehensive and extensive data on the healthcare status, caregiving, and medical requirements of older individuals in China. The detailed information regarding the CLHLS has been previously published , . The 2018 CLHLS conducted interviews with a total of 15,874 participants. Excluding those participants with missing information on IVF, LMM and covariates, 9,708 participants were finally included in the analysis (Fig. ). The project has obtained approval from the Biomedical Ethics Committee of Peking University, China (IRB00001052-13074). Indoor ventilation frequency IVF was assessed based on the frequency of window opening per week in each season over the past year, as self-reported by the participants. Items were scored as follows: 0 points for 0 occurrences per week, 1 point for 1–5 occurrences per week, and 2 points for more than 5 occurrences per week. The IVF score, ranging from 0 to 8, was calculated by summing the individual IVF scores for each season. Scores of 0 to 3, 4 to 5, and 6 to 8 represent low, intermediate, and high IVF levels, respectively , . Low muscle mass According to the criteria established by the Asian Working Group for Sarcopenia, muscle mass was primarily assessed using appendicular skeletal muscle mass (ASM), measured by bioelectrical impedance analysis and dual energy X-ray absorptiometry . However, the instruments required for these methods are expensive, bulky, and necessitate rigorous training, which limits their application in community settings. Kawakami, R et al. used anthropometric and physical function parameters to develop equations for estimating muscle mass , providing a simple method for assessing muscle mass, and the method has been widely used in Chinese populations . Therefore, our study evaluated LMM using an ASM prediction equation derived from weight, height, waist circumference, and calf circumference.The ASM prediction equation was: ASM (kg) = 2.955 * sex (male = 1, female = 0) + 0.255 * weight (kg) + 0.081 * height (cm) − 0.130 * waist circumference (cm) + 0.308 * calf circumference (cm)-11.897 . LMM was defined as < 7.0 kg*m -2 in males and < 5.7 kg*m -2 in females, calculated by multiplying ASM with height squared . Covariates To ensure the authenticity and reliability of the research results and minimize the potential influence of confounding variables, we implemented control measures for several covariates associated with IVF and muscle mass, based on a review of relevant literature. Specifically, these covariates included age (65–79, ≥ 80), gender (male, female), residence (rural, urban), living arrangement (living with family, other), education (0, 1–6, > 6 years), marital status (married, widowed, single, divorced), economic situation (good, average, poor), work (manual labor, other), smoking (yes, no), drinking (yes, no), exercise (yes, no), cooking fuel (renewable clean energy, other), cooking ventilation (yes, no), life satisfaction (good, average, poor), self-rated health (good, average, poor), hypertension (yes, no), diabetes (yes, no), heart disease (yes, no), dementia (yes, no), insurance (yes, no), PM 2.5 (quartiles), NO 2 (quartiles). Detailed assignment and classification criteria are provided in Supplementary Table 1. Statistical analysis The basic characteristics of the study sample across LMM and IVF were delineated by descriptive analysis. Categorical variables that fit a normal distribution are described as percentages (n(%)). Categorical variables were compared between subjects with different demographic characteristics using chi-square tests. Binary logistic regression model was used to evaluate the association between IVF and LMM. Three models were fitted to this study: Model 1 was a crude model that did not account for any covariates; Model 2 adjusted for gender, age, residence, living arrangement, education, marital status, economic situation, work, smoking, drinking, exercise, cooking fuel, cooking ventilation; Model 3 further adjusted for life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, insurance, PM 2.5 , NO 2 . The study also conducted subgroup analyses of gender, age, residence, living arrangement, education, marital status, economic situation, work, smoking, drinking, exercise, cooking fuel, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, insurance, PM 2.5 , NO 2 based on Model 3 and calculated interaction effects of subgroup variables. We performed two sensitivity analyses to assess the robustness of the results. First, we used chained equations to interpolate missing values to ensure a thorough examination of the dataset. Second, recognizing the unreliability of self-reported data from older people with dementia, we excluded participants with dementia from the analysis. The statistical analysis was conducted using the SPSS 27.0 software package. The criterion for statistical significance was set at a level of P < 0.05.
This study utilized data from the CLHLS, conducted by Peking University’s Research Center for Aging Health and Development. CLHLS utilized a targeted random sample design to ensure the representativeness and reliability of the sample, providing comprehensive and extensive data on the healthcare status, caregiving, and medical requirements of older individuals in China. The detailed information regarding the CLHLS has been previously published , . The 2018 CLHLS conducted interviews with a total of 15,874 participants. Excluding those participants with missing information on IVF, LMM and covariates, 9,708 participants were finally included in the analysis (Fig. ). The project has obtained approval from the Biomedical Ethics Committee of Peking University, China (IRB00001052-13074).
IVF was assessed based on the frequency of window opening per week in each season over the past year, as self-reported by the participants. Items were scored as follows: 0 points for 0 occurrences per week, 1 point for 1–5 occurrences per week, and 2 points for more than 5 occurrences per week. The IVF score, ranging from 0 to 8, was calculated by summing the individual IVF scores for each season. Scores of 0 to 3, 4 to 5, and 6 to 8 represent low, intermediate, and high IVF levels, respectively , .
According to the criteria established by the Asian Working Group for Sarcopenia, muscle mass was primarily assessed using appendicular skeletal muscle mass (ASM), measured by bioelectrical impedance analysis and dual energy X-ray absorptiometry . However, the instruments required for these methods are expensive, bulky, and necessitate rigorous training, which limits their application in community settings. Kawakami, R et al. used anthropometric and physical function parameters to develop equations for estimating muscle mass , providing a simple method for assessing muscle mass, and the method has been widely used in Chinese populations . Therefore, our study evaluated LMM using an ASM prediction equation derived from weight, height, waist circumference, and calf circumference.The ASM prediction equation was: ASM (kg) = 2.955 * sex (male = 1, female = 0) + 0.255 * weight (kg) + 0.081 * height (cm) − 0.130 * waist circumference (cm) + 0.308 * calf circumference (cm)-11.897 . LMM was defined as < 7.0 kg*m -2 in males and < 5.7 kg*m -2 in females, calculated by multiplying ASM with height squared .
To ensure the authenticity and reliability of the research results and minimize the potential influence of confounding variables, we implemented control measures for several covariates associated with IVF and muscle mass, based on a review of relevant literature. Specifically, these covariates included age (65–79, ≥ 80), gender (male, female), residence (rural, urban), living arrangement (living with family, other), education (0, 1–6, > 6 years), marital status (married, widowed, single, divorced), economic situation (good, average, poor), work (manual labor, other), smoking (yes, no), drinking (yes, no), exercise (yes, no), cooking fuel (renewable clean energy, other), cooking ventilation (yes, no), life satisfaction (good, average, poor), self-rated health (good, average, poor), hypertension (yes, no), diabetes (yes, no), heart disease (yes, no), dementia (yes, no), insurance (yes, no), PM 2.5 (quartiles), NO 2 (quartiles). Detailed assignment and classification criteria are provided in Supplementary Table 1.
The basic characteristics of the study sample across LMM and IVF were delineated by descriptive analysis. Categorical variables that fit a normal distribution are described as percentages (n(%)). Categorical variables were compared between subjects with different demographic characteristics using chi-square tests. Binary logistic regression model was used to evaluate the association between IVF and LMM. Three models were fitted to this study: Model 1 was a crude model that did not account for any covariates; Model 2 adjusted for gender, age, residence, living arrangement, education, marital status, economic situation, work, smoking, drinking, exercise, cooking fuel, cooking ventilation; Model 3 further adjusted for life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, insurance, PM 2.5 , NO 2 . The study also conducted subgroup analyses of gender, age, residence, living arrangement, education, marital status, economic situation, work, smoking, drinking, exercise, cooking fuel, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, insurance, PM 2.5 , NO 2 based on Model 3 and calculated interaction effects of subgroup variables. We performed two sensitivity analyses to assess the robustness of the results. First, we used chained equations to interpolate missing values to ensure a thorough examination of the dataset. Second, recognizing the unreliability of self-reported data from older people with dementia, we excluded participants with dementia from the analysis. The statistical analysis was conducted using the SPSS 27.0 software package. The criterion for statistical significance was set at a level of P < 0.05.
Basic characteristics of the participant Table describes the presence or absence of LMM in different basic characteristics of the included participants. Of the 9,708 participants in this study, 6,048 (62.30%) suffered from LMM. 61.26% of participants were aged older than or equal to 80 years of age, 54.30% were male, and 43.16% lived in rural areas.The chi-square test showed that there was a significant difference ( p < 0.05) between those with LMM and without LMM in the gender, age, residence, education, marital status, economic situation, work, drinking, exercise, cooking fuels, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, and heart disease groups. Table shows different IVFs with different basic characteristics of the participants. More than half of the participants (59.03%) ventilated their homes six to eight times a week, 32.15% 4 to 5 times, and 8.82% only 1 to 3 times. Participants grouped with different IVF showed statistically significant differences ( p < 0.05) between gender, age, residence, living arrangement, education, marital status, economic status, work, smoking, exercise, cooking fuel, cooking ventilation, life satisfaction, self-rated health, insurance, and NO 2 . Association between indoor ventilation frequency and low muscle mass There are significant differences between seasonal and overall IVF and muscle mass ( P < 0.001) (Table ). Participants with LMM in older adults were observed to have a notably greater prevalence of low IVF and a lower prevalence of high IVF compared to those without LMM in each season. In model 3, which was adjusted for various factors, participants with intermediate IVF (OR: 0.805; 95% CI: 0.669–0.969) and high IVF (OR: 0.818; 95% CI: 0.684–0.979) were 19.5% and 18.2% less likely to develop LMM, respectively, compared with participants with low IVF (Table ). The association between LMM and IVF by season was investigated in Model 3 (Table ). Significant associations between IVF and LMM were observed only in spring and winter. Compared with the low IVF population, the probability of LMM in the spring was 25.3% (OR: 0.747; 95% CI: 0.581–0.961) and 23.3% (OR: 0.767; 95% CI: 0.597–0.985) lower in the middle and high IVF elderly populations, respectively, whereas the probability of LMM in the spring was 36.5% (OR: 0.625; 95% CI: 0.474–0.824) and 34.1% (OR: 0.659; 95% CI: 0.501–0.868), respectively. Subgroup analysis We considered 22 subgroups such as age-sex and further observed consistency in the association of IVF with LMM. The association between IVF and LMM was statistically significant ( p < 0.05) for gender, age, residence, living arrangement, marital status, economic situation, work, smoking, drinking, exercise, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, and NO 2 (Fig. ). Further interaction analyses showed a significant interaction effect between the drinking subgroup and IVF (P for interaction < 0.05). Sensitivity analyses Two sensitivity analyses conducted in the fully adjusted model 3 demonstrate the robustness of our findings. The first used chained-equation multiple interpolation to deal with missing data (Supplementary Table 2), and the second excluded participants with dementia, both of which showed that a statistically significant association between IVF and LMM existed ( P < 0.001) (Supplementary Table 3).
Table describes the presence or absence of LMM in different basic characteristics of the included participants. Of the 9,708 participants in this study, 6,048 (62.30%) suffered from LMM. 61.26% of participants were aged older than or equal to 80 years of age, 54.30% were male, and 43.16% lived in rural areas.The chi-square test showed that there was a significant difference ( p < 0.05) between those with LMM and without LMM in the gender, age, residence, education, marital status, economic situation, work, drinking, exercise, cooking fuels, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, and heart disease groups. Table shows different IVFs with different basic characteristics of the participants. More than half of the participants (59.03%) ventilated their homes six to eight times a week, 32.15% 4 to 5 times, and 8.82% only 1 to 3 times. Participants grouped with different IVF showed statistically significant differences ( p < 0.05) between gender, age, residence, living arrangement, education, marital status, economic status, work, smoking, exercise, cooking fuel, cooking ventilation, life satisfaction, self-rated health, insurance, and NO 2 .
There are significant differences between seasonal and overall IVF and muscle mass ( P < 0.001) (Table ). Participants with LMM in older adults were observed to have a notably greater prevalence of low IVF and a lower prevalence of high IVF compared to those without LMM in each season. In model 3, which was adjusted for various factors, participants with intermediate IVF (OR: 0.805; 95% CI: 0.669–0.969) and high IVF (OR: 0.818; 95% CI: 0.684–0.979) were 19.5% and 18.2% less likely to develop LMM, respectively, compared with participants with low IVF (Table ). The association between LMM and IVF by season was investigated in Model 3 (Table ). Significant associations between IVF and LMM were observed only in spring and winter. Compared with the low IVF population, the probability of LMM in the spring was 25.3% (OR: 0.747; 95% CI: 0.581–0.961) and 23.3% (OR: 0.767; 95% CI: 0.597–0.985) lower in the middle and high IVF elderly populations, respectively, whereas the probability of LMM in the spring was 36.5% (OR: 0.625; 95% CI: 0.474–0.824) and 34.1% (OR: 0.659; 95% CI: 0.501–0.868), respectively.
We considered 22 subgroups such as age-sex and further observed consistency in the association of IVF with LMM. The association between IVF and LMM was statistically significant ( p < 0.05) for gender, age, residence, living arrangement, marital status, economic situation, work, smoking, drinking, exercise, cooking ventilation, life satisfaction, self-rated health, hypertension, diabetes, heart disease, dementia, and NO 2 (Fig. ). Further interaction analyses showed a significant interaction effect between the drinking subgroup and IVF (P for interaction < 0.05).
Two sensitivity analyses conducted in the fully adjusted model 3 demonstrate the robustness of our findings. The first used chained-equation multiple interpolation to deal with missing data (Supplementary Table 2), and the second excluded participants with dementia, both of which showed that a statistically significant association between IVF and LMM existed ( P < 0.001) (Supplementary Table 3).
LMM is prevalent in older adults and is associated with many adverse outcomes, such as falls, metabolic disease, and mortality, demonstrating the value of LMM research , In the present day, individuals have allocated over 90% of their time within enclosed spaces, underscoring the significance of upholding optimal indoor air quality and mitigating potential airborne pollutants according to indoor ventilation as pivotal elements in preserving overall well-being . This nationally representative study found that higher IVF was associated with a lower risk of LMM and observed that the association between IVF and LMM varied across subgroups. Our study provides a new finding that high IVF may be a protective factor for LMM. Numerous studies have confirmed the correlation between indoor ventilation and improved home air quality , .For example, DuJ et al. showed that indoor ventilation was effective in improving indoor air quality and reducing pollutants in the absence of outdoor pollution and under favourable climatic conditions . Through a literature review, we identified several studies reporting the association and intrinsic mechanisms between indoor air quality and sarcopenia and muscle mass , . The pathophysiological mechanisms of muscle mass and sarcopenia are intricate and encompass interactions among multiple physiological systems. Possible explanations include alterations in skeletal muscle structure, myofascial dysfunction, muscle balance and resistance to growth, inflammation and impairment of mitochondrial function, as well as neural pathways, which mainly manifested as a decrease in muscle mass leading to the decline of muscle strength and worsens with age . PM 2.5 can modulate inflammation in visceral adipose tissue, lipid metabolism in the liver, and glucose utilisation in skeletal muscle occurs through both CCR2-dependent and CCR2-independent pathway . The signalling of neurotransmitters and neurotrophic factors, neuronal remodelling, and neurodegeneration are impaired by inflammation and oxidative stress induced by air pollution . Breathing under normobaric conditions attenuated carbon monoxide-induced decreases in muscle oxygenation, particularly in the intercostal muscles, without affecting endurance . In conclusion, air pollution can affect muscle through different pathways and comorbidities. Previous articles have highlighted the effects of air pollutants from solid fuels used for indoor cooking and domestic heat production on sarcopenia , . It follows that older people who rely on solid fuels for cooking and heating should prioritise ventilation to mitigate the adverse effects of fuel pollutants on muscle health. Our study showed a significant correlation between an increase in IVF in spring and autumn and a reduced likelihood of developing LMM in older adults. Many studies have reported that air quality is associated with seasonal changes in air pollutants such as PM, CO and airborne microorganisms , . Seasonal climate-induced changes in temperature, humidity, etc., and accompanying differences in airborne particulate matter, microorganisms, etc., may be influential factors in the seasonal differences in the incidence of LMM. A survey of window opening behaviour in hospital wards showed that the lower frequency of window opening in summer and winter might be due to higher or lower outdoor temperatures, whereas, in the transition season, outdoor temperatures of 20 to 25 degrees are likely to be the most comfortable, with a correspondingly higher frequency of window opening. The humidity of the outdoor air in each season is also an essential factor influencing the frequency of window openings . In addition, the results of a study investigating the effects of climate change on the infiltration of outdoor air pollution showed a clear seasonal pattern of particulate matter (PM) infiltration. Specifically, homes measured during transitional seasons, such as spring and autumn, had higher mean PM infiltration rates compared to homes measured during summer and winter , which may explain the association between IVF and LMM being significant in spring and autumn rather than summer and winter . Subgroup analyses showed that adjusted covariates were not significant modifiers of the association between IVF and LMM, but we still observed significant interactions between drinking and the association between IVF and LMM. We observed a significant association of IVF with LMM in men but not women.Previous studies have reported sex differences in muscle homeostasis , .Sex steroids promote muscle function and benefit skeletal muscle repair and metabolic function after injury. Androgens may be the main sex steroid regulating muscle homeostasis in men , which may potentially account for the sex differences in LMM and IVF observed in this study. Previous studies have confirmed that muscle mass decreases with age , however, our study found that the association between IVF and LMM showed significant age heterogeneity: a significant negative correlation was observed in the 65–79 year old group, whereas no statistically significant correlation was observed in the ≥ 80 year old group. This may be due to the severe loss of muscle mass due to multiple pathophysiological mechanisms in advanced age individuals, when the effects of IVF are masked by the systemic aging process. In our study, we observed that in cities, IVF was significantly associated with LMM, which may be due to denser buildings and poorer air quality in cities, where ventilation can more significantly improve indoor air quality. Yin J et al. also observed a significant difference in the importance of ventilation for public health between urban and rural areas, influenced by factors such as building density and height .Smoking impacts cellular-level muscle proteolysis, leading to impaired muscle mass and the increased demand for indoor ventilation to mitigate indoor air pollutants , . We observed a significant correlation between IVF and LMM in the non-smoking group, which may be due to the fact that smoke and toxins produced by smoking are more damaging to muscle mass, which is not achieved by improving indoor ventilation. This may suggest that smoking cessation is more effective in protecting muscle mass than ventilation. Previous studies have established physical exercise as a protective factor against sarcopenia, demonstrating its efficacy in preserving muscle mass and strength , . Our study further revealed a significant association between increased IVF and LMM specifically within the physically active subgroup, suggesting potential synergistic effects between exercise and optimized ventilation in muscle preservation. This finding warrants further investigation into whether exercise intensity and modality (e.g., resistance training vs. aerobic exercise) differentially modulate the protective benefits of IVF against LMM. Notably, the association between IVF and LMM was exclusively observed in individuals with favorable self-rated health status and absence of chronic comorbidities (hypertension, diabetes, cardiovascular disease, or dementia). Older adults with poor health status or chronic conditions often experience prolonged health deterioration that may lead to advanced muscle atrophy or metabolic dysregulation, potentially obscuring ventilation-related effects. Furthermore, chronic disease patients, particularly elderly or long-term sufferers, frequently exhibit diminished physiological adaptability and recovery capacity. Their muscle mass is typically compromised by disease progression or pharmacological interventions (e.g., corticosteroid use), which may attenuate ventilation-mediated impacts on musculoskeletal health. Our analysis identified a significant protective effect of IVF against LMM under elevated NO2 concentrations. Airborne pollutants including PM2.5 and NO2 have been shown to induce mitochondrial dysfunction through increased reactive oxygen species production and pro-inflammatory cascades , . Enhanced ventilation during high NO2 exposure may mitigate these effects through improved air exchange, thereby reducing pollutant concentrations and demonstrating measurable protection - an effect less apparent under low pollution conditions. Additionally, we observed significant IVF-LMM associations and notable interaction effects with alcohol consumption status in drinking populations. Extensive evidence documents alcohol’s detrimental impacts on muscle integrity through multiple pathways, including dysregulated autophagy, mitochondrial impairment, and nutrient malabsorption , . Compared to abstainers, alcohol consumers exhibited higher smoking prevalence and prolonged indoor exposure due to social habits or health limitations (e.g., chronic disease-related mobility restrictions), potentially amplifying ventilation sensitivity. Conversely, non-drinkers likely represent a health-conscious cohort (evidenced by balanced nutrition and regular exercise) whose muscle mass appears less susceptible to ventilation variations. However, our analysis was constrained by the database’s lack of alcohol consumption frequency/dosage metrics, precluding dose-response assessment and introducing potential residual confounding. Future investigations should incorporate standardized alcohol biomarkers (e.g., phosphatidylethanol) and detailed consumption patterns to elucidate alcohol-ventilation synergies.
This study examined the relationship between overall and seasonal IVF and LMM in Chinese older adults.The findings suggest that higher IVF is significantly associated with lower occurrence of LMM in Chinese older adults, especially in the Spring and Autumn seasons. This study provides valuable insights to promote successful aging and reduce the burden of LMM in the elderly population.
The current study is subject to several limitations. Firstly, as our data is derived from a national cross-sectional study that precludes the establishment of causal relationships, it is imperative to examine the interplay between IVF and LMM. Further extension of follow-up is necessary to assess the longitudinal relationship between IVF and muscle decline in older adults and to determine the causal link between these two factors. Secondly, this study exclusively examines the impact of the window opening on LMM across seasons without considering other ventilation systems, such as air conditioners and air purifiers, and neglects the influence of specific ventilation locations, the area of open windows and the duration of each ventilation session. Third, this study investigated the association between IVF and LMM in different seasons, but the questionnaire content limitations prevented the determination of muscle mass in each season.We plan to refine the seasonal tracking design in future studies to more fully reveal the relationship between LMM and IVF. Fourth, the present study assumes an ideal scenario in which indoor air quality can be enhanced through indoor ventilation; however, pollutants from the outdoor environment and adverse weather conditions may exacerbate indoor air pollution. Hence, additional research is required to explore the underlying mechanisms of the influence of window opening and ventilation on muscle mass in older individuals.
Below is the link to the electronic supplementary material. Supplementary Material 1
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Identification of Novel Viruses and Their Microbial Hosts from Soils with Long-Term Nitrogen Fertilization and Cover Cropping Management | 652c751c-6bb4-4ae2-af64-7138f1511ade | 9765229 | Microbiology[mh] | Viruses are a major driving force that regulate the microbial biomass and influence aquatic food webs ( , ). A bacteriophage is a virus which only infects and replicates within bacteria ( ). It has been proposed that much of the soluble organic carbon resulting from bacterial lysis due to bacteriophage infection can be recycled to feed other microbes instead of being transferred to higher trophic levels. This repeating cycling is called the “microbial (bacterium–phage–DOC) loop” or “viral shunt” ( ). Up to 40% of bacteria were lysed daily due to viral infection in oceans, which can release ~10 9 tons of carbon per day ( ). Comparable estimates do not exist for soil ecosystems, but a conceptual model has been proposed for the impact of virus-mediated cell impact and its impact on the distribution of soil labile carbon and recalcitrant carbon pools ( ). Soils is a complex, heterogeneous ecosystem that provides habitat for a vast array of diverse microbes and higher life forms. The microbial community is critical biological component of soil health and driver of nutrient cycling ( ). Microbial community structure and function can be modulated by the changes of environmental factors which drove by different types of cover crops. For example, vetch, having a lower C/N ratio have higher decomposition rates by microbes compared to wheat with high C/N ratio ( , ). Inorganic nitrogen fertilization can decrease the soil pH, leading to soil acidity, and in turn impact microbial enzyme activities, nutrient availability, and the solubility of metals and other toxic substances ( ). These factors and others can combine to shape microbial diversity and function ( ). Like microbial hosts, viruses also likely respond to the physicochemical changes brought about by long-term agricultural management practices. For example, cover cropping and nitrogen fertilization (N-fertilization) can increase soil organic matter and N input to soil. Organic matter can compete with viral adsorption by blocking adsorption sites on soil particles, which could prompt release of adsorbed viral particles that could subsequently increase host infection rates and produce more viruses ( ). The balance between these mechanisms is likely dependent on chemical properties of soil such as pH and ionic strength of the soil solution ( , ). N-fertilization is a supplemental N source in agricultural systems that is fundamental element for viral reproduction to synthesize amino acids, nucleotides, etc. ( ). Therefore, studying the response of viral populations and virus-host linkage under agricultural management practices is important to regulate the capability of viruses to influence microbial communities and functions in soils ( , ). In recent years, research addressing the role of viruses in soil ecosystems has steadily gained momentum ( ). Viruses can impact soil microbes through predation control (called “top-down”) in the soil environment ( , , ). First of all, viral abundances in soil can exceed 10 9 g −1 virus-like particles, which is often an order of magnitude or greater than microbial abundance in aquatic environments ( ). Second, the reproductive mode of viruses falls into two general categories: the lysogenic or the lytic cycle, which have different impacts on microbial activity. A temperate phage displays a lysogenic lifestyle and can be engaged in lytic or lysogenic reproduction ( ). In lysogenic cycles, nucleic acid usually integrates into the host genome or a plasmid, and the provirus replicates as the host grows and divides. The initiation of the lytic cycle can be triggered by environmental factors, such as UV light, toxins, temperature, and host cell density dependence ( , ). A lytic (or virulent) phage exploits the biosynthetic machinery of the host to produce, assemble, and release daughter phages by lysing the host cells immediately after infection ( ). Infection efficiencies of lytic phages is relevant to phages type and their host ( ). Lytic viruses with broad a host spectrum (i.e., myoviruses) may infect more hosts than viruses with specific host (i.e., podoviruses) ( , ). The activities of host cellular functions influence the viral growth rate and further affect viral fitness, lysis time, or even burst size ( , ). During the lytic cycle, viruses can also directly mediate host function through virus-encoded auxiliary metabolic genes (AMGs), including photosynthesis, central carbon metabolism, and nutrient cycling ( ). Bulk soil metagenomes are commonly used to study soil microbes ( ). Viral information from bulk-soil metagenome sequencing can be obtained from a variety of bioinformatics tools designed to search and identify viral from nonviral genetic information ( ). Using bulk-soil metagenome sequencing to distill the soil virus information is one of the important approaches to investigating the soil virus community and its ecological roles ( ). Most previous studies revealed that agricultural management practices influence microbial functional diversity, but the diversity of soil viruses, their dynamic interactions with host microbes, and their overall ecological role in soil food webs is not well understood. Here, we exploit the bulk-soil metagenomes prepared from 12 samples across four agricultural treatments to recover virus operational taxonomic units (vOTUs) from and investigate the effect of long-term cover crop (e.g., vetch) and N-fertilization management on viral community composition and identify how N-fertilization and cover cropping impact the link between viruses and their host. We hypothesize that (i) new viruses will be identified, (ii) greater diversity of viruses will be observed in N-fertilization with cover crops than in other treatment, and (iii) the relative abundances of viruses will be closely correlated with their host microbes. Our objective is to provide an initial view of viruses and virus-host interactions in these agricultural soils to obtain a better understanding of the ecological roles of the viruses may have in agroecosystems in relation to various conservation management practices.
Data set overview and agricultural soil viral population (vOTU) recovery. The sequences of the double-stranded DNA (dsDNA) viruses were extracted as described above from 12 agricultural soil samples from four conservation management practices. To quantify dsDNA viral diversity in long-term managed agriculture soil, we collected 12 soil metagenomes from the cores gathered from the long-term tillage, N-fertilization, and cover-cropping plots in western Tennessee. Approximate sequencing depths of 20-Gbp paired reads per metagenome were obtained by Illumina NovaSeq 6000 platform. Over 99% of raw reads per sample were passed through the quality control steps. After quality filtering, metagenome sequencing yielded a mean of 69,652,934 paired reads per library for 12 samples collected from the four agricultural management treatments. The total of 260 vOTUs were predicted by VirSorter, DeepVirfinder, and VIBRANT pipeline. A total number of high-quality paired end reads that were obtained ranged from 51,805,430 to 90,119,576 with an average of 1.15 to 1.91% were assembled into contigs greater than 1 kbp. The reads were assembled to a mean of 4,922 soil viral contigs and ranged from 27,152 to 86,666 bp ( ). All soil viral contigs from the 12 samples clustered into 56,780 unique viral contigs, but only 241 viral contigs were greater than 10 kb. No plasmids were identified in 241 vOTUs based upon manual screening. Finally, the viral OTU table with 260 of vOTUs was generated by mapping reads to the updated PIGEON database (including the 241 viruses found in this study). The 260 vOTUs recovered in this study included the 10 named “alaska_puertorico” contigs obtained from permafrost ( ), only 1 viral contig named “EarthsVirome_48737,” and 14 of the viral contigs named “gary_all20” (IMG/VR) and published by Paez-Espino et al. ( ). Two viral contigs similar to “SPRUCE_viral_seq” orginally discovered from Peatlands in northern Minnesota were also identified ( ), and one viral contig known as “virsorter_curated” recovered from the publicly available microbial genomes (RefSeq and WGS databases) ( ). The rest of 232 out of 260 vOTUs (89.23%) were without significant hits to the databases we examined (see in the supplemental material). The results indicated that the soil virosphere is undersampled and that different soil types may harbor previously unrecognized viruses. 10.1128/msystems.00571-22.3 TABLE S1 vOTUs and putative phage types and evidence. Download Table S1, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Gene-sharing network for viral taxonomy assignment. The gene-sharing network was built to assign viral taxonomy due to the lack of universal phylogenetic marker genes in viruses ( ). The 260 vOTUs were clustered with 2,617 prokaryotic viral genomes in the RefSeq database (v94). The resulting network consisted of 1,658 nodes and 32,667 edges were left in the networks. Only 6% of the vOTUs identified in this study were similar to the viruses in the database, and 11 viral clusters (VCs) were related to previously curated clusters in the reference databases ( ). The vOTU_30 grouped in the same cluster (VC_225_1) as 5 Cronobacter_phage (VC_225_0) classified as genus Cr3virus (family Myoviridae ), indicating that the two genomes were highly related at the subfamily level, which was Vequintavirinae ( ; see also ). The vOTU_63 and vOTU_93 (VC_69) clustered with 28 viruses belonging to the genus Peduovirus affiliated with the Myoviridae family and were all P2-like viruses ( ; see also ). 10.1128/msystems.00571-22.9 TABLE S7 Gene-sharing network information. Download Table S7, DOCX file, 0.4 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . With high probability, vOTU_229 was assigned to the Siphoviridae , which were grouped with Pseudomonas_phage_phiPSA1, Sinorhizobium_phage_phiLM21, and Vibrio_phage_SHOU24. vOTU_69 clustered with Ralstonia_phage_RSK1 in the same subcluster (VC_164_0), which belonging to the family Podoviridae , but the genus was unclassified due to the limitation on identification of genes. vOTU_100 and vOTU_67 connected with 2 viruses assigned to Bpp1virus , others were unclassified, but they grouped within the lineage of Podoviridae ( ; see also ). Most of the structural protein of vOTU_63 and vOTU_93 (e.g., baseplate protein, tail and head completion protein, tail tube protein, and phage major capsid protein) were similar to those of bacteriophage P2. Very late expression factor 1 (VLF-1), a member of the tyrosine recombinase family of proteins, serves the basic function during the late stage of DNA packaging and capsid assembly. This recombinase was detected in vOTU_63 and vOTU_93, indicating that the vOTU_63 and vOTU_93 might be temperate phages. A portal protein was annotated in vOTU_100, which functions as a channel for passage of viral DNA bidirectionally, in tailed bacteriophages. DNA can move in and out of the virus head using portal protein which also provides an attachment point for the tail apparatus. vOTU_149 and Brevibacillus phage were in the same subcluster (VC_108_0), which was assigned to the genus Jenstvirus in the family Siphoviridae . vOTU_9 (Virsorter_curated_4650) clustered with Bacillus phage, were in the same subcluster (VC_118_0), which belongs to genus Cecivirus of the family Siphoviridae . vOTU_145 was in the VC_337_0 with Thermoanaerobacterium _phage, which is in the family Siphoviridae . The presence of recombinase, XerC, suggested that vOTU_145 may also be a temperate phage. Distribution and diversity of vOTUs across agricultural practices. There were 8 vOTUs shared between no cover crops and vetch with no N-fertilization, and 19 vOTUs were shared by no-cover crops and vetch with N-fertilization ( ). Only 4 vOTUs were shared by N-fertilization and no fertilization under vetch cover, and 3 were shared by the N-fertilization and no fertilization under no cover ( ). These results suggest that N-fertilization may have a greater influence on shaping viral community than cover cropping and that there likely exists environmental specialization among soil viruses even at the small plot scale after long-term conservation management. A greater number of vOTUs that only exist in that treatment (i.e., that are not shared with other treatments) were found in no-cover with no N-fertilization and vetch with N-fertilization treatments compared to no-cover with N-fertilization and vetch without N-fertilization practices ( ). After annotating 260 vOTUs, only 8.5% (22 vOTUs) were possessed recombinase or recombinase-like protein, and 13.8% (36 vOTUs) were identified as prophage by BLAST and CRISPR arrays (see ), and their putative hosts were found in . Here, the numbers of vOTUs that may be identified as temperate phage were 31.6, 28.6, 33.3, and 24.4% across no cover without fertilization, no cover with N-fertilization, vetch without N-fertilization, and vetch cover with N-fertilization, respectively. The estimated proportion of phages with integrase (31.6 and 33.3%) was greater in soil without N-fertilization than in N-fertilized soil (see ). 10.1128/msystems.00571-22.5 TABLE S3 Coverage information of identified viral OTUs and potential bacterial and archaeal host. Download Table S3, DOCX file, 0.2 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.6 TABLE S4 Distribution of vOTUs across four treatments. Unique vOTUs were used in every treatment. “1” is present; “0” is absent. Download Table S4, DOCX file, 0.03 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . The alpha-diversity analyses revealed that soil with N-fertilization contained a significantly greater number of vOTUs than no N-fertilization soil ( P < 0.05; see ). Also, the estimated diversity indices revealed that Shannon diversity ( P < 0.01), for example, was significantly greater in fertilized soil than soil without N-fertilization; however, cover crops had no apparent effects on alpha-diversity ( ; see also ). Principal coordinate analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) were applied to the vOTU table (number of permutations = 2,000, P < 0.01; see ), resulting in 46.2% variation of the viral community, which could be explained by two axes of PCoA in total, suggesting that the N-fertilization-induced influence on the composition and structure of viral communities versus cover cropping was significant ( ). No significant effect of POXC, inorganic N content, pH, or soil moisture content on viral community structure was observed (see ). 10.1128/msystems.00571-22.7 TABLE S5 ANOVA on alpha diversity of vOTUs. Download Table S5, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.8 TABLE S6 PERMANOVA results of the influence of treatments and environmental factor on vOTU community structure. Download Table S6, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Identification of microbial host. We employed CRISPR and BLAST to link virus with potential microbial hosts. Fifty-two spacers within 39 spacer groups were identified from all 12 samples matched to our 260 vOTUs, and 39 direct repeats were blasted with the 13 bacterial and 7 archaeal genomes. In our study, more linkages between the virus and its host were detected by BLASTn with criteria described in Materials and Methods than by CRISPR-cas patterns. The bacterial hosts covered four bacterial phyla, including Acidobacteriota , Proteobacteria , Verrucomicrobiota , and Firmicutes , and five genera, including PSRF01 , Gp1-AA122 , Kosakonia , AV55 , and Paenibacillus _ J ( ; see also ). The most abundant are genus Kosakonia (bin35.6, 14.21%, phylum Proteobacteria ), AV55 (bin9.3, 22.23%, phylum Verrucomicrobiota ) ( ), PSRF01 (bin112.7, 25.10%, phylum Acidobacteriota ), and PSRF01 (bin16.2, 30.83%, phylum Acidobacteriota ) in no cover without fertilization, no cover with fertilization, vetch without fertilization, and vetch with fertilization treatments, respectively (see ). All seven archaeal hosts are all in the lineage of Nitrososphaeraceae (phylum Thermoproteota ) ( ). The most abundant are the genera TA-21 (bin63.4, 32.11%), UBA10452 (bin79.8, 27.02%), UBA10452 (bin112.3, 22.11%), and UBA10452 (bin79.8, 29.70%) in no cover without fertilization, no cover with fertilization, vetch without fertilization, and vetch with fertilization treatment, respectively (see ). 10.1128/msystems.00571-22.1 FIG S1 Stacked bar plot of bacterial host MAGs. Bin 16.2 and bin 9.3 contain significantly greater abundance under fertilization treatment than under no fertilization ( P < 0.05). Under no fertilization, the relative abundance of bin 37.7 decreased under vetch-covered soil ( P < 0.05) and also significantly decreased in fertilized soil than in non-fertilized soil under vetch-covered treatment ( P < 0.05) or no cover crop soil ( P < 0.01). The relative abundance of bin 112.7 significantly decreased under fertilization compared to under no fertilization with no cover cropping ( P < 0.05) and vetch cover cropping ( P < 0.001), respectively. The relative abundance of bin112.7 decreased with vetch treatment under fertilized soil ( P < 0.05) but increased with vetch treatment under nonfertilized soil ( P < 0.05). Download FIG S1, DOCX file, 1.9 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.2 FIG S2 Stacked bar plot of archaeal host MAGs. Bins 112.3, 35.3, and 63.4 displayed significantly greater abundance under fertilization treatment than under no fertilization ( P < 0.05), but bin79.8 displayed the opposite trend. Under no cover, the abundance of bin 16.10 is significantly greater in fertilization than no fertilization ( P < 0.01); under no fertilization, the vetch cover has a higher archaeal bin 16.10 than under no fertilization ( P < 0.01). Download FIG S2, DOCX file, 2.3 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.4 TABLE S2 Evidence of link putative viruses and their bacterial hosts. Download Table S2, DOCX file, 0.1 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Linkage between viruses and bacterial host. The result suggested that multiple viruses within the same viral genus were able to infect the same genus of putative host. For example, Verrucomicrobiota AV55 was identified as the putative the host of vOTU_153, vOTU_81, and vOTU_252. vOTU_153, vOTU_81, and vOTU_252 were annotated within the same genus. vOTU_63 and vOTU_93 were linked to the putative host within the Proteobacteria Kosakonia cowanii species, and vOTU_63 and vOTU_93 were clustered together in VC_69 and belong to Peduovirus (or P2virus ) in the Myoviridae lineage (see ). Novel viruses that share the same potential host may not necessarily do so within the same viral genus. For example, Acidobacteriota PSRF01 in different species (bin.112.7, bin 37.3, and bin 37.7) was linked to the potential hosts vOTU_14, vOTU_181, vOTU_3, and vOTU_152. vOTU_14 could not be assigned to a taxonomy through gene-sharing networks, and vOTU_3 did not cluster with vOTU_181, vOTU_14, and vOTU_152 at the genus level ( ; see also ). A linear mixed-effects model was built to test the effect of N-fertilization and cover crops on the abundances of viruses and their host, respectively. The relative abundances of Paenibacillus ( Acidobacteriota ) ( P < 0.05) and g_ AV55 ( Verrucomicrobiota ) ( P < 0.001) increased in N-fertilization compared to no N-fertilization. For viruses, the relative abundances of vOTU_19, vOTU_203, vOTU_81, vOTU_115, vOTU_163, and vOTU_252 were significantly greater in N-fertilized soil. No significant effect of cover crops on the relative abundance of hosts and viruses was found ( ). Furthermore, vOTU_203, vOTU_81, vOTU_115, vOTU_163, and vOTU_252 were analyzed separately based on the different N-fertilization treatments. Similarly, the abundances between virus and host were positively correlated ( ). Linkage between viruses and archaeal host. All of the taxonomy of the vOTUs connected to Nitrososphaeraceae could not be assigned using gene-sharing network due to its novelty or the lack of virus hallmark genes. We observed that Nitrososphaeraceae were significantly increased under cover crops (e.g., genus Nitrosocosmicus bin 16.5) ( P < 0.05, no significant fertilization effect) or under no N-fertilization (e.g., genus UBA10452 , TA21 , and bin35.3) ( P < 0.05, no significant cover-cropping effect). The correlation between the relative abundances of vOTUs and archaea were positively correlated like bacterial phages in our study ( ; see also ). Moreover, the correlation between abundances of the vOTUs (vOTU_128, vOTU_251, vOTU_120, and vOTU_169) and the potential Nitrososphaeraceae host significantly correlated, indicating that both cover-cropping management and N-fertilization can influence the relationship between the vOTUs and the Nitrososphaeraceae ( ).
The sequences of the double-stranded DNA (dsDNA) viruses were extracted as described above from 12 agricultural soil samples from four conservation management practices. To quantify dsDNA viral diversity in long-term managed agriculture soil, we collected 12 soil metagenomes from the cores gathered from the long-term tillage, N-fertilization, and cover-cropping plots in western Tennessee. Approximate sequencing depths of 20-Gbp paired reads per metagenome were obtained by Illumina NovaSeq 6000 platform. Over 99% of raw reads per sample were passed through the quality control steps. After quality filtering, metagenome sequencing yielded a mean of 69,652,934 paired reads per library for 12 samples collected from the four agricultural management treatments. The total of 260 vOTUs were predicted by VirSorter, DeepVirfinder, and VIBRANT pipeline. A total number of high-quality paired end reads that were obtained ranged from 51,805,430 to 90,119,576 with an average of 1.15 to 1.91% were assembled into contigs greater than 1 kbp. The reads were assembled to a mean of 4,922 soil viral contigs and ranged from 27,152 to 86,666 bp ( ). All soil viral contigs from the 12 samples clustered into 56,780 unique viral contigs, but only 241 viral contigs were greater than 10 kb. No plasmids were identified in 241 vOTUs based upon manual screening. Finally, the viral OTU table with 260 of vOTUs was generated by mapping reads to the updated PIGEON database (including the 241 viruses found in this study). The 260 vOTUs recovered in this study included the 10 named “alaska_puertorico” contigs obtained from permafrost ( ), only 1 viral contig named “EarthsVirome_48737,” and 14 of the viral contigs named “gary_all20” (IMG/VR) and published by Paez-Espino et al. ( ). Two viral contigs similar to “SPRUCE_viral_seq” orginally discovered from Peatlands in northern Minnesota were also identified ( ), and one viral contig known as “virsorter_curated” recovered from the publicly available microbial genomes (RefSeq and WGS databases) ( ). The rest of 232 out of 260 vOTUs (89.23%) were without significant hits to the databases we examined (see in the supplemental material). The results indicated that the soil virosphere is undersampled and that different soil types may harbor previously unrecognized viruses. 10.1128/msystems.00571-22.3 TABLE S1 vOTUs and putative phage types and evidence. Download Table S1, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .
The gene-sharing network was built to assign viral taxonomy due to the lack of universal phylogenetic marker genes in viruses ( ). The 260 vOTUs were clustered with 2,617 prokaryotic viral genomes in the RefSeq database (v94). The resulting network consisted of 1,658 nodes and 32,667 edges were left in the networks. Only 6% of the vOTUs identified in this study were similar to the viruses in the database, and 11 viral clusters (VCs) were related to previously curated clusters in the reference databases ( ). The vOTU_30 grouped in the same cluster (VC_225_1) as 5 Cronobacter_phage (VC_225_0) classified as genus Cr3virus (family Myoviridae ), indicating that the two genomes were highly related at the subfamily level, which was Vequintavirinae ( ; see also ). The vOTU_63 and vOTU_93 (VC_69) clustered with 28 viruses belonging to the genus Peduovirus affiliated with the Myoviridae family and were all P2-like viruses ( ; see also ). 10.1128/msystems.00571-22.9 TABLE S7 Gene-sharing network information. Download Table S7, DOCX file, 0.4 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . With high probability, vOTU_229 was assigned to the Siphoviridae , which were grouped with Pseudomonas_phage_phiPSA1, Sinorhizobium_phage_phiLM21, and Vibrio_phage_SHOU24. vOTU_69 clustered with Ralstonia_phage_RSK1 in the same subcluster (VC_164_0), which belonging to the family Podoviridae , but the genus was unclassified due to the limitation on identification of genes. vOTU_100 and vOTU_67 connected with 2 viruses assigned to Bpp1virus , others were unclassified, but they grouped within the lineage of Podoviridae ( ; see also ). Most of the structural protein of vOTU_63 and vOTU_93 (e.g., baseplate protein, tail and head completion protein, tail tube protein, and phage major capsid protein) were similar to those of bacteriophage P2. Very late expression factor 1 (VLF-1), a member of the tyrosine recombinase family of proteins, serves the basic function during the late stage of DNA packaging and capsid assembly. This recombinase was detected in vOTU_63 and vOTU_93, indicating that the vOTU_63 and vOTU_93 might be temperate phages. A portal protein was annotated in vOTU_100, which functions as a channel for passage of viral DNA bidirectionally, in tailed bacteriophages. DNA can move in and out of the virus head using portal protein which also provides an attachment point for the tail apparatus. vOTU_149 and Brevibacillus phage were in the same subcluster (VC_108_0), which was assigned to the genus Jenstvirus in the family Siphoviridae . vOTU_9 (Virsorter_curated_4650) clustered with Bacillus phage, were in the same subcluster (VC_118_0), which belongs to genus Cecivirus of the family Siphoviridae . vOTU_145 was in the VC_337_0 with Thermoanaerobacterium _phage, which is in the family Siphoviridae . The presence of recombinase, XerC, suggested that vOTU_145 may also be a temperate phage.
There were 8 vOTUs shared between no cover crops and vetch with no N-fertilization, and 19 vOTUs were shared by no-cover crops and vetch with N-fertilization ( ). Only 4 vOTUs were shared by N-fertilization and no fertilization under vetch cover, and 3 were shared by the N-fertilization and no fertilization under no cover ( ). These results suggest that N-fertilization may have a greater influence on shaping viral community than cover cropping and that there likely exists environmental specialization among soil viruses even at the small plot scale after long-term conservation management. A greater number of vOTUs that only exist in that treatment (i.e., that are not shared with other treatments) were found in no-cover with no N-fertilization and vetch with N-fertilization treatments compared to no-cover with N-fertilization and vetch without N-fertilization practices ( ). After annotating 260 vOTUs, only 8.5% (22 vOTUs) were possessed recombinase or recombinase-like protein, and 13.8% (36 vOTUs) were identified as prophage by BLAST and CRISPR arrays (see ), and their putative hosts were found in . Here, the numbers of vOTUs that may be identified as temperate phage were 31.6, 28.6, 33.3, and 24.4% across no cover without fertilization, no cover with N-fertilization, vetch without N-fertilization, and vetch cover with N-fertilization, respectively. The estimated proportion of phages with integrase (31.6 and 33.3%) was greater in soil without N-fertilization than in N-fertilized soil (see ). 10.1128/msystems.00571-22.5 TABLE S3 Coverage information of identified viral OTUs and potential bacterial and archaeal host. Download Table S3, DOCX file, 0.2 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.6 TABLE S4 Distribution of vOTUs across four treatments. Unique vOTUs were used in every treatment. “1” is present; “0” is absent. Download Table S4, DOCX file, 0.03 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . The alpha-diversity analyses revealed that soil with N-fertilization contained a significantly greater number of vOTUs than no N-fertilization soil ( P < 0.05; see ). Also, the estimated diversity indices revealed that Shannon diversity ( P < 0.01), for example, was significantly greater in fertilized soil than soil without N-fertilization; however, cover crops had no apparent effects on alpha-diversity ( ; see also ). Principal coordinate analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) were applied to the vOTU table (number of permutations = 2,000, P < 0.01; see ), resulting in 46.2% variation of the viral community, which could be explained by two axes of PCoA in total, suggesting that the N-fertilization-induced influence on the composition and structure of viral communities versus cover cropping was significant ( ). No significant effect of POXC, inorganic N content, pH, or soil moisture content on viral community structure was observed (see ). 10.1128/msystems.00571-22.7 TABLE S5 ANOVA on alpha diversity of vOTUs. Download Table S5, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.8 TABLE S6 PERMANOVA results of the influence of treatments and environmental factor on vOTU community structure. Download Table S6, DOCX file, 0.04 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .
We employed CRISPR and BLAST to link virus with potential microbial hosts. Fifty-two spacers within 39 spacer groups were identified from all 12 samples matched to our 260 vOTUs, and 39 direct repeats were blasted with the 13 bacterial and 7 archaeal genomes. In our study, more linkages between the virus and its host were detected by BLASTn with criteria described in Materials and Methods than by CRISPR-cas patterns. The bacterial hosts covered four bacterial phyla, including Acidobacteriota , Proteobacteria , Verrucomicrobiota , and Firmicutes , and five genera, including PSRF01 , Gp1-AA122 , Kosakonia , AV55 , and Paenibacillus _ J ( ; see also ). The most abundant are genus Kosakonia (bin35.6, 14.21%, phylum Proteobacteria ), AV55 (bin9.3, 22.23%, phylum Verrucomicrobiota ) ( ), PSRF01 (bin112.7, 25.10%, phylum Acidobacteriota ), and PSRF01 (bin16.2, 30.83%, phylum Acidobacteriota ) in no cover without fertilization, no cover with fertilization, vetch without fertilization, and vetch with fertilization treatments, respectively (see ). All seven archaeal hosts are all in the lineage of Nitrososphaeraceae (phylum Thermoproteota ) ( ). The most abundant are the genera TA-21 (bin63.4, 32.11%), UBA10452 (bin79.8, 27.02%), UBA10452 (bin112.3, 22.11%), and UBA10452 (bin79.8, 29.70%) in no cover without fertilization, no cover with fertilization, vetch without fertilization, and vetch with fertilization treatment, respectively (see ). 10.1128/msystems.00571-22.1 FIG S1 Stacked bar plot of bacterial host MAGs. Bin 16.2 and bin 9.3 contain significantly greater abundance under fertilization treatment than under no fertilization ( P < 0.05). Under no fertilization, the relative abundance of bin 37.7 decreased under vetch-covered soil ( P < 0.05) and also significantly decreased in fertilized soil than in non-fertilized soil under vetch-covered treatment ( P < 0.05) or no cover crop soil ( P < 0.01). The relative abundance of bin 112.7 significantly decreased under fertilization compared to under no fertilization with no cover cropping ( P < 0.05) and vetch cover cropping ( P < 0.001), respectively. The relative abundance of bin112.7 decreased with vetch treatment under fertilized soil ( P < 0.05) but increased with vetch treatment under nonfertilized soil ( P < 0.05). Download FIG S1, DOCX file, 1.9 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.2 FIG S2 Stacked bar plot of archaeal host MAGs. Bins 112.3, 35.3, and 63.4 displayed significantly greater abundance under fertilization treatment than under no fertilization ( P < 0.05), but bin79.8 displayed the opposite trend. Under no cover, the abundance of bin 16.10 is significantly greater in fertilization than no fertilization ( P < 0.01); under no fertilization, the vetch cover has a higher archaeal bin 16.10 than under no fertilization ( P < 0.01). Download FIG S2, DOCX file, 2.3 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/msystems.00571-22.4 TABLE S2 Evidence of link putative viruses and their bacterial hosts. Download Table S2, DOCX file, 0.1 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .
The result suggested that multiple viruses within the same viral genus were able to infect the same genus of putative host. For example, Verrucomicrobiota AV55 was identified as the putative the host of vOTU_153, vOTU_81, and vOTU_252. vOTU_153, vOTU_81, and vOTU_252 were annotated within the same genus. vOTU_63 and vOTU_93 were linked to the putative host within the Proteobacteria Kosakonia cowanii species, and vOTU_63 and vOTU_93 were clustered together in VC_69 and belong to Peduovirus (or P2virus ) in the Myoviridae lineage (see ). Novel viruses that share the same potential host may not necessarily do so within the same viral genus. For example, Acidobacteriota PSRF01 in different species (bin.112.7, bin 37.3, and bin 37.7) was linked to the potential hosts vOTU_14, vOTU_181, vOTU_3, and vOTU_152. vOTU_14 could not be assigned to a taxonomy through gene-sharing networks, and vOTU_3 did not cluster with vOTU_181, vOTU_14, and vOTU_152 at the genus level ( ; see also ). A linear mixed-effects model was built to test the effect of N-fertilization and cover crops on the abundances of viruses and their host, respectively. The relative abundances of Paenibacillus ( Acidobacteriota ) ( P < 0.05) and g_ AV55 ( Verrucomicrobiota ) ( P < 0.001) increased in N-fertilization compared to no N-fertilization. For viruses, the relative abundances of vOTU_19, vOTU_203, vOTU_81, vOTU_115, vOTU_163, and vOTU_252 were significantly greater in N-fertilized soil. No significant effect of cover crops on the relative abundance of hosts and viruses was found ( ). Furthermore, vOTU_203, vOTU_81, vOTU_115, vOTU_163, and vOTU_252 were analyzed separately based on the different N-fertilization treatments. Similarly, the abundances between virus and host were positively correlated ( ).
All of the taxonomy of the vOTUs connected to Nitrososphaeraceae could not be assigned using gene-sharing network due to its novelty or the lack of virus hallmark genes. We observed that Nitrososphaeraceae were significantly increased under cover crops (e.g., genus Nitrosocosmicus bin 16.5) ( P < 0.05, no significant fertilization effect) or under no N-fertilization (e.g., genus UBA10452 , TA21 , and bin35.3) ( P < 0.05, no significant cover-cropping effect). The correlation between the relative abundances of vOTUs and archaea were positively correlated like bacterial phages in our study ( ; see also ). Moreover, the correlation between abundances of the vOTUs (vOTU_128, vOTU_251, vOTU_120, and vOTU_169) and the potential Nitrososphaeraceae host significantly correlated, indicating that both cover-cropping management and N-fertilization can influence the relationship between the vOTUs and the Nitrososphaeraceae ( ).
Long-term inorganic N-fertilization influenced the viral community diversity and structure. Agricultural soils are relatively fertile, having balanced components, including minerals, soil organic matter, air, and water, which provide more nutrient and physical support for crop growth. Agricultural activities, including fertilization and cover cropping, can increase inputs of soil organic matter, soil moisture, and microbial activities ( , ), which may influence the mobility, survival rate, and distribution of soil viruses ( ). In this study, inorganic N-fertilization positively influenced viral community diversity and played a role in shaping viral community structure. It is likely N-fertilization positively influenced viral population through increasing abundance of host communities ( ). Also, a strong positive correlation between the abundances of Verrucomicrobiota and its vOTUs was observed, and N-fertilization influenced the abundance of genus PSRF01 affiliated with Blastocatellia ; the abundance of Blastocatellia was correlated with nitrogen availability in soils ( ), which might indirectly influence the viruses related to Blastocatellia . The results in this study also supported the idea that variation of the viral population may directly result from changes in the host population or abundances under N-fertilization. The survival strategy of bacteria can change (e.g., endospore formation in Firmicutes ) due to the lack of nutrients (such as N) or their surroundings ( ). Phages could respond to the bacterial signals and modify the outcome of their infection from obligately productive to temporarily reductive ( , ). For example, phages could be packed into bacterial endospores and use them as a viral genome protection shell to resist environmental stress ( ). Spore formation for septum- and coat assembly-related AMGs ( spoVS , whiB , and spoIIIE , etc.) have been reported in viral genomes ( , ). This mechanism is supported by previous studies reporting that lysogeny is an effective strategy to maintain the viral population survival in a detrimental soil microenvironment ( , , , ). Accordingly, we observed more vOTUs with integrase, which might be temperate phage in unfertilized soil, than in soils that received long-term N-fertilization. Roles of viruses in influencing C and N cycling via putative hosts. Different vOTUs linked to the same Acidobacteriota , Proteobacteria , Verrucomicrobiota , and Firmicutes as the host have been reported in other studies ( , ). Multiple vOTUs are related to Chthoniobacterales within the phylum Verrucomicrobiota . N-fertilization increased the abundance of Chthoniobacterales species. Chthoniobacterales have contributed to carbon cycling by decomposing carbohydrates, such as cellulose and xylan ( ). The results indicated that Chthoniobacterales phage could influence carbon transformations by controlling its host’s metabolism. Nitrososphaeraceae affiliated with the Thaumarchaeota phylum are ammonia oxidizers, which play important roles in nitrification ( ). It has been observed that ammonia-oxidizing archaea can grow in a wide range of ammonia concentrations ( , , ). The close positive correlation between the relative abundance of virus and its predicted host provided the evidence that the soil viruses found in long-term managed agricultural soil tend to control carbon and nitrogen cycling by infecting the functional hosts, which is consistent with results reported in other soil systems ( , , ). Limitations of using metagenomes to discover soil viruses. The recovery rate of vOTU from bulk soil metagenomes is somewhat inefficient but increases with increasing numbers of samples and/or sequencing depth. About 2,699 vOTUs across 82 bulk soil metagenomes were identified from peatland in northern Minnesota; all of these total soil metagenomes were sequenced from 6 to 15 Gbp on average per library on the NovaSeq platform ( ). In a recent study of Stordalen Mire, 1,831 vOTUs were identified from 178 bulk soil metagenomes in northern Sweden permafrost soil with an average output of 8 Gbp per metagenomic sample ( , ). In biochar-amended agricultural soil, 97 vOTUs were identified from across 16 samples at a depth of ~2 Gbp per library from bulk soil metagenome sequencing ( ). Based on the studies described above, the vOTU yield rate ranged from (normalized per gigabase pair of metagenomes) 1.30 to 3.29 number of vOTU/Gbp. To increase the efficiency of the vOTU recovery rate or to decrease the complexity of soil samples based on the purpose of types of different research, virome, stable isotope probing, and different-size filters can be combined with metagenomes to decrease the noise of the microorganism ( ), to target active viruses ( ), or to concentrate cells with specific sizes in order to study rare soil biosphere ( ). Here, the high-quality sequences obtained reached up to ~10-Gbp paired reads per library, and 260 vOTUs (including 232 novel vOTUs and 28 overlapped with PIGEON database) were identified from 12 agricultural soil DNA samples. The vOTU yield rate of this study was 2.17, which is a reasonable recovery rate for soil studies. However, the use of a virus-enriched virome is a better approach for recovering more vOTU from soils compared to bulk soil metagenomes, since they can have about 3 to 30 times more viral populations per sample, which means that >90% of the viral information can be lost when using only bulk soil metagenomic sequencing compared to viromic sequencing ( , , ). Viromics can provide the most viral information for even rare viral species, although viromes lack host information and can be lab intensive to prepare ( , ). However, combining bulk soil metagenome and viromes is an ideal way to study the links between soil viruses and their hosts. A trade-off between the number of samples and the sequencing depth should be based on the aim and budget of the researcher’s study. In the present study, the taxonomy of >90% of viruses could not be assigned according to known bacterial viruses in the RefSeq database. This finding suggests that the soil environment is home to many diverse and yet-to-be-classified viral taxa. The limited information in current viral databases is one of the challenges that restricts our understanding of soil viral communities ( , , ). Lacking marker gene present a great challenge to identifying temperate or a virulent phage. A more credible way, compared to the existence of integrase, is to identify high-frequency functional genes on a viral genome; for example, temperate viruses usually contain integrase, excisionase, and DNA polymerase ( polA ) genes with leucine substitution, etc. ( ). Relatively accurately classifying the vOTUs in our study can be further verified using novel bioinformatic tools (i.e., DeePhage) for future study ( ). Conclusion. The 260 vOTUs, including 232 novel viruses and 28 previously reported, were identified from 12 bulk soil metagenomes with 10-Gbp output per library. The samples represented a single soil type but had been treated for >40 years with various conservation management practices with combinations of inorganic N-fertilization and cover cropping. Multiple vOTUs at the genus level or at a higher level were potentially linked to the microbial genus level or higher within the same phyla. The microbial host populations were taxa that decompose carbohydrates (i.e., Chthoniobacterales ) and oxidize ammonia (i.e., Nitrososphaeraceae ). Long-term inorganic N-fertilization had a greater influence on viral alpha-diversity and community structure than did cover cropping. The findings indicated a close relationship between viruses and host microbes, suggesting that viruses could modulate abundance in hosts and may further influence the functional behavior of the host in C and N cycling. Although bulk-soil metagenomic analysis is an effective approach for detecting both viruses and their hosts, this approach may underestimate the diversity of soil viruses. Therefore, the use of viromics as a complement for studying viral ecology is suggested in future studies.
Agricultural soils are relatively fertile, having balanced components, including minerals, soil organic matter, air, and water, which provide more nutrient and physical support for crop growth. Agricultural activities, including fertilization and cover cropping, can increase inputs of soil organic matter, soil moisture, and microbial activities ( , ), which may influence the mobility, survival rate, and distribution of soil viruses ( ). In this study, inorganic N-fertilization positively influenced viral community diversity and played a role in shaping viral community structure. It is likely N-fertilization positively influenced viral population through increasing abundance of host communities ( ). Also, a strong positive correlation between the abundances of Verrucomicrobiota and its vOTUs was observed, and N-fertilization influenced the abundance of genus PSRF01 affiliated with Blastocatellia ; the abundance of Blastocatellia was correlated with nitrogen availability in soils ( ), which might indirectly influence the viruses related to Blastocatellia . The results in this study also supported the idea that variation of the viral population may directly result from changes in the host population or abundances under N-fertilization. The survival strategy of bacteria can change (e.g., endospore formation in Firmicutes ) due to the lack of nutrients (such as N) or their surroundings ( ). Phages could respond to the bacterial signals and modify the outcome of their infection from obligately productive to temporarily reductive ( , ). For example, phages could be packed into bacterial endospores and use them as a viral genome protection shell to resist environmental stress ( ). Spore formation for septum- and coat assembly-related AMGs ( spoVS , whiB , and spoIIIE , etc.) have been reported in viral genomes ( , ). This mechanism is supported by previous studies reporting that lysogeny is an effective strategy to maintain the viral population survival in a detrimental soil microenvironment ( , , , ). Accordingly, we observed more vOTUs with integrase, which might be temperate phage in unfertilized soil, than in soils that received long-term N-fertilization.
Different vOTUs linked to the same Acidobacteriota , Proteobacteria , Verrucomicrobiota , and Firmicutes as the host have been reported in other studies ( , ). Multiple vOTUs are related to Chthoniobacterales within the phylum Verrucomicrobiota . N-fertilization increased the abundance of Chthoniobacterales species. Chthoniobacterales have contributed to carbon cycling by decomposing carbohydrates, such as cellulose and xylan ( ). The results indicated that Chthoniobacterales phage could influence carbon transformations by controlling its host’s metabolism. Nitrososphaeraceae affiliated with the Thaumarchaeota phylum are ammonia oxidizers, which play important roles in nitrification ( ). It has been observed that ammonia-oxidizing archaea can grow in a wide range of ammonia concentrations ( , , ). The close positive correlation between the relative abundance of virus and its predicted host provided the evidence that the soil viruses found in long-term managed agricultural soil tend to control carbon and nitrogen cycling by infecting the functional hosts, which is consistent with results reported in other soil systems ( , , ).
The recovery rate of vOTU from bulk soil metagenomes is somewhat inefficient but increases with increasing numbers of samples and/or sequencing depth. About 2,699 vOTUs across 82 bulk soil metagenomes were identified from peatland in northern Minnesota; all of these total soil metagenomes were sequenced from 6 to 15 Gbp on average per library on the NovaSeq platform ( ). In a recent study of Stordalen Mire, 1,831 vOTUs were identified from 178 bulk soil metagenomes in northern Sweden permafrost soil with an average output of 8 Gbp per metagenomic sample ( , ). In biochar-amended agricultural soil, 97 vOTUs were identified from across 16 samples at a depth of ~2 Gbp per library from bulk soil metagenome sequencing ( ). Based on the studies described above, the vOTU yield rate ranged from (normalized per gigabase pair of metagenomes) 1.30 to 3.29 number of vOTU/Gbp. To increase the efficiency of the vOTU recovery rate or to decrease the complexity of soil samples based on the purpose of types of different research, virome, stable isotope probing, and different-size filters can be combined with metagenomes to decrease the noise of the microorganism ( ), to target active viruses ( ), or to concentrate cells with specific sizes in order to study rare soil biosphere ( ). Here, the high-quality sequences obtained reached up to ~10-Gbp paired reads per library, and 260 vOTUs (including 232 novel vOTUs and 28 overlapped with PIGEON database) were identified from 12 agricultural soil DNA samples. The vOTU yield rate of this study was 2.17, which is a reasonable recovery rate for soil studies. However, the use of a virus-enriched virome is a better approach for recovering more vOTU from soils compared to bulk soil metagenomes, since they can have about 3 to 30 times more viral populations per sample, which means that >90% of the viral information can be lost when using only bulk soil metagenomic sequencing compared to viromic sequencing ( , , ). Viromics can provide the most viral information for even rare viral species, although viromes lack host information and can be lab intensive to prepare ( , ). However, combining bulk soil metagenome and viromes is an ideal way to study the links between soil viruses and their hosts. A trade-off between the number of samples and the sequencing depth should be based on the aim and budget of the researcher’s study. In the present study, the taxonomy of >90% of viruses could not be assigned according to known bacterial viruses in the RefSeq database. This finding suggests that the soil environment is home to many diverse and yet-to-be-classified viral taxa. The limited information in current viral databases is one of the challenges that restricts our understanding of soil viral communities ( , , ). Lacking marker gene present a great challenge to identifying temperate or a virulent phage. A more credible way, compared to the existence of integrase, is to identify high-frequency functional genes on a viral genome; for example, temperate viruses usually contain integrase, excisionase, and DNA polymerase ( polA ) genes with leucine substitution, etc. ( ). Relatively accurately classifying the vOTUs in our study can be further verified using novel bioinformatic tools (i.e., DeePhage) for future study ( ).
The 260 vOTUs, including 232 novel viruses and 28 previously reported, were identified from 12 bulk soil metagenomes with 10-Gbp output per library. The samples represented a single soil type but had been treated for >40 years with various conservation management practices with combinations of inorganic N-fertilization and cover cropping. Multiple vOTUs at the genus level or at a higher level were potentially linked to the microbial genus level or higher within the same phyla. The microbial host populations were taxa that decompose carbohydrates (i.e., Chthoniobacterales ) and oxidize ammonia (i.e., Nitrososphaeraceae ). Long-term inorganic N-fertilization had a greater influence on viral alpha-diversity and community structure than did cover cropping. The findings indicated a close relationship between viruses and host microbes, suggesting that viruses could modulate abundance in hosts and may further influence the functional behavior of the host in C and N cycling. Although bulk-soil metagenomic analysis is an effective approach for detecting both viruses and their hosts, this approach may underestimate the diversity of soil viruses. Therefore, the use of viromics as a complement for studying viral ecology is suggested in future studies.
Site description and sample collection. The ongoing long-term conservation management experimental site used in this study is located at the West Tennessee Research and Education Center (WTREC; Jackson, TN), established in 1981, and the soil type was Lexington silt loam (fine-silty, mixed, 127 thermic, Ultic Hapludalf) ( ). The continuous cotton production experiment was arranged in a randomized complete block with a split-split plot design. Inorganic nitrogen fertilizer (ammonium nitrate [NH 4 NO 3 ]) is applied at two nitrogen levels (0 and 67 kg/ha) as the main plots and is divided into three subplots that contain two levels of cover crop treatments (no cover and hairy vetch, Vicia villosa Roth) and no-tillage treatment. All four treatments with three replications were sampled on 21 May 2019, shortly after the burndown of the cover crop and just before planting in the spring. The samples were coded as follows: “type of cover crop,” “no-tillage,” “N-fertilization or not,” and “serial number of replicates,” e.g., NCNTN0_1 represents no-cover, no-tilled, and no N-fertilization treatment of replicate 1, whereas VNTN60_4 is vetch-covered, no-tilled with N-fertilization of 67 N kg/ha (60 N lb/acre), replicate 4. Bulk soil metagenomic sequencing was applied to 12 samples from selected treatments. Soil properties. The soil pH was measured using an electrode (Ul-trabasic; Denver Instrument, Bohemia, NY). The water content was determined gravimetrically at room temperature (~25°C). Measurement of the NO 3 – and NH 4 + concentration was performed using microplate-based spectrophotometric determinations ( , ). Permanganate-oxidizable carbon extraction and measurement were conducted using a microplate reader (96-well microplate) at 550 nm as previously reported ( , ). DNA extraction, library construction, and metagenomic sequencing. Soil samples were collected from a depth of 0 to 10 cm at a distance of 10 to 15 cm from the center of the crop row using a 2.5-cm-diameter soil probe. About 10 to 15 subsamples were randomly taken within each plot. The samples were transported in a cooler with ice bags within 24 h to the lab freezer (–20°C). Preprocessing and DNA extraction were accomplished within 48 h after coming back from the field. First, fine rocks, roots, and other debris were removed by passing each composite soil sample through a 2-mm sieve. Second, total soil DNA was extracted using a DNeasy PowerLyzer Powersoil kit (catalog no. 12855; Qiagen) from 0.25 g of soil per sample according to the manufacturer’s instructions for the kit. The extracted DNA was dissolved in sterile DNA-free PCR-grade water. A Qubit 1× dsDNA HS (high sensitivity) assay kit (Invitrogen, catalog no. Q33230) was used to evaluate the quantity of whole soil DNA on a Qubit 2.0 fluorometer (total 200-μL reaction). A 260 / A 280 and A 230 / A 280 values were measured to examine the DNA quality using a NanoDrop OneC Microvolume UV-Vis spectrophotometer (Thermo Scientific). Genomic DNA libraries were constructed for sequencing on an Illumina platform using a KAPA library preparation kit (Kapa Biosystems, Woburn, MA). First, DNA was fragmented with a Covaris E210. Then, libraries were prepared using a modified version of the manufacturer’s protocol. DNA was purified between enzymatic reactions, and size selection of the library was performed with SPRI select beads (Beckman Coulter Genomics, Danvers, MA). For indexed samples, a PCR amplification step was performed with primers containing dual unique barcode sequences 8 nucleotides in length. Libraries were assessed for concentration and fragment size using a DNA high-sensitivity assay on a LabChip GX (Perkin-Elmer, Waltham, MA). The library concentrations were also assessed by qPCR using the KAPA library quantification kit (Complete, Universal; KAPA Biosystems). The libraries were pooled and sequenced on an Illumina NovaSeq6000 S2 using 150-bp PE reads (0.5 S2-lane, 900M read pairs, 275-Gbp yield average; Illumina, San Diego, CA) at the Institute for Genome Sciences, School of Medicine, at the University of Maryland. Reads preprocessing and assembly. Cutadapt (v1.18) was used to remove low-quality reads (the quality phred score cutoff was 20, the maximum trimming error rate was 0.1, and the reads were shorter than 50 bp) ( ). De novo assembly was performed using MEGAHIT ( , ). QUAST (v.5.0.2) was used to estimate contig statistics ( ). vOTU identification. The assemblies in each sample were clustered with PSI-CD-HIT implementation of BLASTn to cluster contigs with a global identity threshold of 0.95 to remove the redundant sequences (dereplication) ( ). Nonredundant assemblies were processed by VirSorter (v.1), DeepVirFinder ( , ), and VIBRANT (v1.2.0) ( ). Category 1, 2, 4, and 5 viral contigs, as identified by Virsorter, were retained. Categories 3 and 6 were removed due to the lack of hallmark genes or the absence of enrichment in viral or non- Caudovirales genes ( , ). Contigs with DeepVirFinder scores higher than 0.9 and a P value of < 0.05 and phages predicted by VIBRANT (v1.2.0) were considered ( ). All of the contigs were manually combined in each sample. All of contig lengths greater than 10,000 bp were clustered into vOTUs using CD-HIT with a global identity threshold of 0.95 and an alignment coverage for shorter contigs length of >85% ( ). A bbmap was used to map short-read sequences in each sample to the updated PIGEON database (viral database PIGEON v1.0; Phages and Integrated Genomes Encapsidated Or Not [ https://datadryad.org/ ]) plus the viral contigs assembled across the samples ( , ). A SAM file with alignment information for each sample was transformed to the Bam files and then sorted and indexed by SAMtools ( ). BEDtools ( ) was used to parse the Bam file generated by the last step. A coverage table was generate using BamM ( http://ecogenomics.github.io/BamM ). The vOTU table was normalized based on the contig length and library size to make it comparable among samples ( , , ). vOTUs with low coverage (<0.25×) of its length when mapped by reads were filtered and converted to zero ( , ). Square-root transformation was applied to correct the data normality for statistical analysis. Viral taxonomy assignment was performed by building the gene-sharing network in vContact2 ( ). The 260 vOTUs generated by reading mapping mentioned above was annotated by MetaProdigal ( ), and the output file with amino acid annotation was fed into vContact2 for taxonomy assignment. Nodes and edges represented viral genomes (or contigs) and significant similarities between protein cluster profiles, respectively. Similarity between sequences depends on the number of shared protein clusters ( ). vOTUs were clustered with 2,617 viral genomes in the RefSeq database (v94) based upon shared protein clusters ( ). Shared genus level viral clusters were selected manually for further analysis. Metagenome-assembled genome construction. Identified viral contigs across 12 samples were removed from all contigs assembled by MEGAHIT mentioned above. Metabat2 (v2.12.1) ( ), Maxbin2 (v2.2.6) ( , ), and concoct (1.0.0) ( ) within MetaWRAP (v1.3.2) ( ) were applied on the microbial contigs assembled by megahits >2.5 kbp on each sample to recover the microbial draft genomes. CheckM ( ) was used to assess the quality of the genome, and those with quality score of ≥50 were retained ( ). Metagenome-assembled genomes (MAGs) were deduplicated by dRep (v3.0.0) ( ), and taxonomic affiliations were classified with the GTDB-tk (v1.3.0) workflow ( ). To estimate the relative abundance of each MAG, the short-read sequences were mapped to assembled contigs before binning as described above. First, the contigs in all the samples were combined, and all of the contigs were clustered using CD-HIT with a global identity threshold of 0.95 and an alignment coverage for shorter contig length of >85%. The renamed, deduplicated, and sorted fasta file as reference contigs were indexed by using bbmap, which was similar to the approach for the viral abundance calculation. Third, all of the clean reads in every sample were mapped back to the reference contigs by using bbmap. This step was used to generate the coverage table for each sample. A final OTU table was generated using the weighted contig length in base pairs and then calculating the average of all its binned contig coverages; the MAG abundance table was normalized by the read depth for each sample as described for the vOTU table above. The square-root transformation was also applied for statistical analysis. Phylogenetic tree for the host genome. Alignment of 43 conserved maker genes with largely congruent phylogenetic histories was performed, and concatenated protein sequences of single-copy genes were generated by CheckM (v1.1.3) and used to build an unrooted phylogenetic tree ( ). Maximum-likelihood phylogenetic trees were built by using the unweighted pair-group method with arithmetic means (UPGMA) as the distance method and 500 bootstraps as the phylogeny test. The trees were constructed using the Le_Gascuel_2008 substitution model ( ) by MEGA X ( , ). The percentage of trees clustered at the nodes and the genetic divergence (branch length) are shown within the tree. Virus-host linkage based on CRISPR arrays and BLAST. We used two methods to identify the link between viruses and their hosts. First, CRISPR repeats and spacer arrays were applied for the 12 samples by Crass v1.0.1 using the default settings individually ( ). Viral contigs and spacer sequences (protospacer-spacer matches) recovered from metagenomes were compared by using BLASTn (blastn-short task, percent identity 0.95, and an E value threshold of 10e–5, mismatch ≤ 1) ( ). The direct repeats were chosen based upon the spacer matches in viral genomes, and BLASTn was used against direct repeats to bacterial and archaeal genomes (blastn-short task, percentage identity 1, and E value threshold of 10e–10, mismatch ≤ 1) to link the virus with its putative host. The second approach identified vOTU nucleotide sequences using BLAST against the MAGs in the soil samples. The vOTUs were retained if the bit score was >50, the E value was <10e–3, and the sample exhibited a ≥70% average nucleotide identity (ANI), as determined using FastANI ( ). Hits that were ≥2,500 bp and covered ≤ 90% of viral contigs in microbial genomes were considered for the most confident provirus predictions, and if the hits covered >90% they were considered less confident ( , , ). The Pearson’s product-moment correlation was determined for both viruses and their potential host normalized abundances. Normality tests were conducted using a Shapiro-Wilk test prior to correlation analysis ( ). vOTUs were categorized as temperate or virulent based upon the presence or absence of an integrase ( ). Statistical analysis. A square-root transformation was performed to correct the normality of the relative abundance of viruses and microbes. A Shapiro-Wilk normality test was performed to check the normality ( ). A mixed-effect model was built, the block was regarded as a random effect, and N-fertilization and cover crops were treated as fixed effect. Type II Wald chi-square tests were applied on the mixed model to test an alternative hypothesis. A Tukey’s HSD (honest significant difference) test was performed for the post hoc test ( ). Data availability. All sequencing data have been deposited in in National Center for Biotechnology Information database (Sequence Read Archive) under BioProject accession number is PRJNA820715 . vOTUs were deposited in GenBank database (under accession numbers ON448394 to ON448625 , see for details). The information of bacterial and archaeal draft genomes can be obtained in the NCBI database (see for the BioSample accession number). 10.1128/msystems.00571-22.10 TABLE S8 Accessions of viral contigs and bacterial and archaeal draft genome in the NCBI database. Download Table S8, DOCX file, 0.03 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .
The ongoing long-term conservation management experimental site used in this study is located at the West Tennessee Research and Education Center (WTREC; Jackson, TN), established in 1981, and the soil type was Lexington silt loam (fine-silty, mixed, 127 thermic, Ultic Hapludalf) ( ). The continuous cotton production experiment was arranged in a randomized complete block with a split-split plot design. Inorganic nitrogen fertilizer (ammonium nitrate [NH 4 NO 3 ]) is applied at two nitrogen levels (0 and 67 kg/ha) as the main plots and is divided into three subplots that contain two levels of cover crop treatments (no cover and hairy vetch, Vicia villosa Roth) and no-tillage treatment. All four treatments with three replications were sampled on 21 May 2019, shortly after the burndown of the cover crop and just before planting in the spring. The samples were coded as follows: “type of cover crop,” “no-tillage,” “N-fertilization or not,” and “serial number of replicates,” e.g., NCNTN0_1 represents no-cover, no-tilled, and no N-fertilization treatment of replicate 1, whereas VNTN60_4 is vetch-covered, no-tilled with N-fertilization of 67 N kg/ha (60 N lb/acre), replicate 4. Bulk soil metagenomic sequencing was applied to 12 samples from selected treatments.
The soil pH was measured using an electrode (Ul-trabasic; Denver Instrument, Bohemia, NY). The water content was determined gravimetrically at room temperature (~25°C). Measurement of the NO 3 – and NH 4 + concentration was performed using microplate-based spectrophotometric determinations ( , ). Permanganate-oxidizable carbon extraction and measurement were conducted using a microplate reader (96-well microplate) at 550 nm as previously reported ( , ).
Soil samples were collected from a depth of 0 to 10 cm at a distance of 10 to 15 cm from the center of the crop row using a 2.5-cm-diameter soil probe. About 10 to 15 subsamples were randomly taken within each plot. The samples were transported in a cooler with ice bags within 24 h to the lab freezer (–20°C). Preprocessing and DNA extraction were accomplished within 48 h after coming back from the field. First, fine rocks, roots, and other debris were removed by passing each composite soil sample through a 2-mm sieve. Second, total soil DNA was extracted using a DNeasy PowerLyzer Powersoil kit (catalog no. 12855; Qiagen) from 0.25 g of soil per sample according to the manufacturer’s instructions for the kit. The extracted DNA was dissolved in sterile DNA-free PCR-grade water. A Qubit 1× dsDNA HS (high sensitivity) assay kit (Invitrogen, catalog no. Q33230) was used to evaluate the quantity of whole soil DNA on a Qubit 2.0 fluorometer (total 200-μL reaction). A 260 / A 280 and A 230 / A 280 values were measured to examine the DNA quality using a NanoDrop OneC Microvolume UV-Vis spectrophotometer (Thermo Scientific). Genomic DNA libraries were constructed for sequencing on an Illumina platform using a KAPA library preparation kit (Kapa Biosystems, Woburn, MA). First, DNA was fragmented with a Covaris E210. Then, libraries were prepared using a modified version of the manufacturer’s protocol. DNA was purified between enzymatic reactions, and size selection of the library was performed with SPRI select beads (Beckman Coulter Genomics, Danvers, MA). For indexed samples, a PCR amplification step was performed with primers containing dual unique barcode sequences 8 nucleotides in length. Libraries were assessed for concentration and fragment size using a DNA high-sensitivity assay on a LabChip GX (Perkin-Elmer, Waltham, MA). The library concentrations were also assessed by qPCR using the KAPA library quantification kit (Complete, Universal; KAPA Biosystems). The libraries were pooled and sequenced on an Illumina NovaSeq6000 S2 using 150-bp PE reads (0.5 S2-lane, 900M read pairs, 275-Gbp yield average; Illumina, San Diego, CA) at the Institute for Genome Sciences, School of Medicine, at the University of Maryland.
Cutadapt (v1.18) was used to remove low-quality reads (the quality phred score cutoff was 20, the maximum trimming error rate was 0.1, and the reads were shorter than 50 bp) ( ). De novo assembly was performed using MEGAHIT ( , ). QUAST (v.5.0.2) was used to estimate contig statistics ( ).
The assemblies in each sample were clustered with PSI-CD-HIT implementation of BLASTn to cluster contigs with a global identity threshold of 0.95 to remove the redundant sequences (dereplication) ( ). Nonredundant assemblies were processed by VirSorter (v.1), DeepVirFinder ( , ), and VIBRANT (v1.2.0) ( ). Category 1, 2, 4, and 5 viral contigs, as identified by Virsorter, were retained. Categories 3 and 6 were removed due to the lack of hallmark genes or the absence of enrichment in viral or non- Caudovirales genes ( , ). Contigs with DeepVirFinder scores higher than 0.9 and a P value of < 0.05 and phages predicted by VIBRANT (v1.2.0) were considered ( ). All of the contigs were manually combined in each sample. All of contig lengths greater than 10,000 bp were clustered into vOTUs using CD-HIT with a global identity threshold of 0.95 and an alignment coverage for shorter contigs length of >85% ( ). A bbmap was used to map short-read sequences in each sample to the updated PIGEON database (viral database PIGEON v1.0; Phages and Integrated Genomes Encapsidated Or Not [ https://datadryad.org/ ]) plus the viral contigs assembled across the samples ( , ). A SAM file with alignment information for each sample was transformed to the Bam files and then sorted and indexed by SAMtools ( ). BEDtools ( ) was used to parse the Bam file generated by the last step. A coverage table was generate using BamM ( http://ecogenomics.github.io/BamM ). The vOTU table was normalized based on the contig length and library size to make it comparable among samples ( , , ). vOTUs with low coverage (<0.25×) of its length when mapped by reads were filtered and converted to zero ( , ). Square-root transformation was applied to correct the data normality for statistical analysis. Viral taxonomy assignment was performed by building the gene-sharing network in vContact2 ( ). The 260 vOTUs generated by reading mapping mentioned above was annotated by MetaProdigal ( ), and the output file with amino acid annotation was fed into vContact2 for taxonomy assignment. Nodes and edges represented viral genomes (or contigs) and significant similarities between protein cluster profiles, respectively. Similarity between sequences depends on the number of shared protein clusters ( ). vOTUs were clustered with 2,617 viral genomes in the RefSeq database (v94) based upon shared protein clusters ( ). Shared genus level viral clusters were selected manually for further analysis.
Identified viral contigs across 12 samples were removed from all contigs assembled by MEGAHIT mentioned above. Metabat2 (v2.12.1) ( ), Maxbin2 (v2.2.6) ( , ), and concoct (1.0.0) ( ) within MetaWRAP (v1.3.2) ( ) were applied on the microbial contigs assembled by megahits >2.5 kbp on each sample to recover the microbial draft genomes. CheckM ( ) was used to assess the quality of the genome, and those with quality score of ≥50 were retained ( ). Metagenome-assembled genomes (MAGs) were deduplicated by dRep (v3.0.0) ( ), and taxonomic affiliations were classified with the GTDB-tk (v1.3.0) workflow ( ). To estimate the relative abundance of each MAG, the short-read sequences were mapped to assembled contigs before binning as described above. First, the contigs in all the samples were combined, and all of the contigs were clustered using CD-HIT with a global identity threshold of 0.95 and an alignment coverage for shorter contig length of >85%. The renamed, deduplicated, and sorted fasta file as reference contigs were indexed by using bbmap, which was similar to the approach for the viral abundance calculation. Third, all of the clean reads in every sample were mapped back to the reference contigs by using bbmap. This step was used to generate the coverage table for each sample. A final OTU table was generated using the weighted contig length in base pairs and then calculating the average of all its binned contig coverages; the MAG abundance table was normalized by the read depth for each sample as described for the vOTU table above. The square-root transformation was also applied for statistical analysis.
Alignment of 43 conserved maker genes with largely congruent phylogenetic histories was performed, and concatenated protein sequences of single-copy genes were generated by CheckM (v1.1.3) and used to build an unrooted phylogenetic tree ( ). Maximum-likelihood phylogenetic trees were built by using the unweighted pair-group method with arithmetic means (UPGMA) as the distance method and 500 bootstraps as the phylogeny test. The trees were constructed using the Le_Gascuel_2008 substitution model ( ) by MEGA X ( , ). The percentage of trees clustered at the nodes and the genetic divergence (branch length) are shown within the tree.
We used two methods to identify the link between viruses and their hosts. First, CRISPR repeats and spacer arrays were applied for the 12 samples by Crass v1.0.1 using the default settings individually ( ). Viral contigs and spacer sequences (protospacer-spacer matches) recovered from metagenomes were compared by using BLASTn (blastn-short task, percent identity 0.95, and an E value threshold of 10e–5, mismatch ≤ 1) ( ). The direct repeats were chosen based upon the spacer matches in viral genomes, and BLASTn was used against direct repeats to bacterial and archaeal genomes (blastn-short task, percentage identity 1, and E value threshold of 10e–10, mismatch ≤ 1) to link the virus with its putative host. The second approach identified vOTU nucleotide sequences using BLAST against the MAGs in the soil samples. The vOTUs were retained if the bit score was >50, the E value was <10e–3, and the sample exhibited a ≥70% average nucleotide identity (ANI), as determined using FastANI ( ). Hits that were ≥2,500 bp and covered ≤ 90% of viral contigs in microbial genomes were considered for the most confident provirus predictions, and if the hits covered >90% they were considered less confident ( , , ). The Pearson’s product-moment correlation was determined for both viruses and their potential host normalized abundances. Normality tests were conducted using a Shapiro-Wilk test prior to correlation analysis ( ). vOTUs were categorized as temperate or virulent based upon the presence or absence of an integrase ( ).
A square-root transformation was performed to correct the normality of the relative abundance of viruses and microbes. A Shapiro-Wilk normality test was performed to check the normality ( ). A mixed-effect model was built, the block was regarded as a random effect, and N-fertilization and cover crops were treated as fixed effect. Type II Wald chi-square tests were applied on the mixed model to test an alternative hypothesis. A Tukey’s HSD (honest significant difference) test was performed for the post hoc test ( ).
All sequencing data have been deposited in in National Center for Biotechnology Information database (Sequence Read Archive) under BioProject accession number is PRJNA820715 . vOTUs were deposited in GenBank database (under accession numbers ON448394 to ON448625 , see for details). The information of bacterial and archaeal draft genomes can be obtained in the NCBI database (see for the BioSample accession number). 10.1128/msystems.00571-22.10 TABLE S8 Accessions of viral contigs and bacterial and archaeal draft genome in the NCBI database. Download Table S8, DOCX file, 0.03 MB . Copyright © 2022 Duan et al. 2022 Duan et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license .
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Identification of a prognostic signature in colorectal cancer using combinatorial algorithm‐driven analysis | 9c7c79bb-135a-4c04-b792-c544a4530e7a | 8977276 | Anatomy[mh] | Colorectal cancer is a common malignancy with a relatively high mortality rate and a significant negative impact on the quality of life of survivors . Although mortality rates of colorectal cancer have been declining in developed countries as a result of significant development in health care, deaths attributed to colorectal cancer, already one of the highest contributors to cancer‐related mortalities, are expected to continue rising due to ageing and diet . The main obstacle to better survival rates is the molecular heterogeneity of colorectal cancer which is reflected clinically through variations in tumour progression, prognosis, and response to treatment . The profiling of large sets of genes/proteins and the identification of molecular signatures are needed to subtype colorectal cancer and manage patients accordingly . The molecular analysis of colorectal cancer improves our understanding of tumourigenesis and uncovers novel pathways, which can be utilised in prognosis, screening, monitoring, and therapeutic interventions . Because of the complexity and the heterogeneity of colorectal cancer, multiple biomarkers are needed for the necessary prognostic power to accurately subtype this disease. However, discovery of novel biomarkers with high‐order combinatorial interactions is extremely challenging due to the combinatorial explosion (the size of genomic/proteomic data and arbitrariness of combinations) and constraints of multiple hypothesis testing for significance evaluation . This study has developed an effective method which minimises the computational complexity to identify the optimal prognostic combination from a large number of biomarkers. This method comprises a screening process to eliminate non‐relevant targets, followed by a grouping stage whereby the remaining biomarkers are divided into smaller subsets. Each subset is then incorporated into an iterative algorithm which generates and evaluates all biomarker combinations. Following this method, the study has identified a biomarker signature with a significant prognostic power to predict the overall survival of patients independent of established prognostic parameters. Furthermore, important biological pathways in colorectal cancer were revealed by analysing associations, expression patterns, and functional interactions of these biomarkers.
Discovery patient cohort To assess the expression of biomarker targets, a large and well‐characterised patient cohort of primary colorectal cancers was used. The cohort was retrospectively acquired from the Grampian Biorepository ( www.biorepository.nhsgrampian.org ), and only included patients who had undergone surgery with curative intent for primary colorectal cancers between 1994 and 2009, at Aberdeen Royal Infirmary‐NHS Grampian (Aberdeen, UK). This study also followed the Reporting Recommendations for Tumour Marker Prognostic Studies (REMARK) guidelines (checklist included in supplementary material). Only patients with Union for International Cancer Control (UICC) TNM stage I, stage II, or stage III were included in the study ( n = 650). Patients with histological evidence of distant metastasis at diagnosis or those who had received neoadjuvant chemotherapy and/or radiotherapy were not included. The histopathological reporting of the resection specimens was performed following the relevant guidelines from the Royal College of Pathologists UK for the histopathological reporting of colorectal cancer excision specimens which incorporated TNM version 5. Further details of the histopathological processing of tissue specimens are outlined in Supplementary materials and methods. The primary endpoint was overall survival which was defined as the period from 28 days after the date of surgery to the date of death from any cause. At the date of final censoring of patient outcome data, there had been no missing data in terms of follow‐up and patients who were still alive were censored. The clinicopathological characteristics, the distribution of patients within each clinicopathological parameter, and their association with survival in the discovery cohort are outlined in supplementary material, Table . The mismatch repair (MMR) protein status for all tumours was assessed by immunohistochemistry using antibodies to MLH1 and MSH2 . At the time of the censoring, there had been 309 (47.5%) deaths. The median survival was 103 months (95% CI = 86–120 months), the mean survival was 115 months (95% CI = 108–123 months), and the median follow‐up time, calculated by the ‘reverse Kaplan–Meier’ method, was 88 months (95% CI = 79–97 months). A tissue microarray was constructed from the primary colorectal tumours which also included 50 normal colon mucosal samples (acquired from at least 10 cm in distance from each tumour). The tissue microarray included two representative 1 mm cores for each sample . Ethical approval for the use of colorectal tissue samples was given by the Grampian Biorepository scientific access group committee (tissue request no. TR000169). Validation patient cohort A publicly available dataset, accession number GSE39582, was used as the validation cohort . It was accessed through the NCBI Gene Expression Omnibus ( http://www.ncbi.nlm.nih.gov/geo/ ). Data for the following clinicopathological characteristics are outlined in supplementary material, Table . For better comparison with the discovery cohort, stage IV cases ( n = 60) and cases with no survival information ( n = 4) were excluded (i.e. 502 patients included). There were 151 deaths (30.1%), the median survival was 183 months (95% CI = 92–273 months), the mean survival was 130 months (95% CI = 121–140 months), and the median follow‐up time, calculated by the ‘reverse Kaplan–Meier’ method, was 73 months (95% CI = 69–77 months). The expression values of genes (Affymetrix U133 Plus 2.0 chips) corresponding to the biomarker signature identified in the discovery cohort were obtained using Geo2R ( https://www.ncbi.nlm.nih.gov/geo/geo2r/ ). Each probe ID was mapped to the Entrez gene ID with the corresponding platform files. Only probes that are unique to the target gene were used and, if available, exemplar sequence probes were used. If more than one probe was used for the same gene, the expression values showing the most significant variations were used. To allow comparison with immunostaining scores, gene expression values were assigned to one of the four categories based on three quartiles (25th percentile, 50th percentile, and 75th percentile). The validation cohort was used to evaluate the prognostic performance of biomarkers signature after the discovery process was completed. Therefore, only values for genes in the signature were obtained and evaluated in the validation cohort. Biomarkers The study used a series of biomarkers ( n = 66) which had been evaluated in the discovery patient cohort. The names of proteins, associated pathways, immunohistochemistry platforms, methods of scoring, and corresponding antibodies are all detailed in supplementary material, Table . The biomarker list includes targets which belong to key pathways implicated in tumour progression such as immune response, metabolism, cell cycle, proliferation, cytoskeleton, and cell migration. The majority of biomarkers were evaluated using antibodies developed in our laboratory ( n = 37), while the remainder were assessed using commercially available antibodies ( n = 29). All biomarkers were assessed by immunohistochemistry, the majority of which were stained using a DAKO autostainer (Dako EnVision™ system; Dako, Ely, UK), with the remaining stained using either a Ventana BenchMark XT (Ventana Medical Systems, Oro Valley, AZ, USA) or a Leica Bond RX (Leica Biosystems, Wetzlar, Germany). Further details of materials and methods are provided in and supplementary material, Tables . The immunostaining results were assessed by either a semi‐quantitative scoring system [ , , , , ] or a quantitative automated image analysis [ , , ]. The cores were recorded as missing if they were damaged/folded during the staining process, or if they did not contain tumour cells. Details of the immunohistochemistry assessment and scoring systems are provided in . Biomarker discovery methodology Screening and grouping Before applying the iterative algorithm, screening and grouping analysis was performed on the initial series of biomarkers (Figure ). The screening process involved assessing the survival association of each individual biomarker and removing those with no prognostic power. Then, the remaining biomarkers were assembled into subsets based on a range of interrelationships: biological (homology/family, function, GO term, and pathway analysis); clinical (i.e. whether higher expression of biomarkers is associated with better or worse prognosis); and expression patterns (correlated biomarkers). For the biological groupings, biomarkers can be relevant in different pathways and therefore the same biomarker can be placed in different groups. Each subset was then entered sequentially into the programme to evaluate the best biomarker combination. This deliberate screening and subgrouping of biomarkers improves the probability of identifying robust combinations by providing a biological and clinical framework for interpreting potential discoveries. Limiting the analysis to smaller subsets of biomarkers also reduces the effect of combinatorial explosion. Combinatorial algorithm The study developed an iterative algorithm to execute the combinatorial analysis on biomarkers ( n ) and identify a combination ( C* ) with a number of biomarkers ( r ) and a maximum combined fitness ( f ). The fitness in this study represents the prognostic performance of a candidate combination and is mainly evaluated using multivariate Cox regression models which include established prognostic parameters: age, extramural venous invasion (EMVI), lymph node stage and T stage, or age and pathological classification parameter which is based on lymph node stage, T stage, EMVI, and tumour differentiation. The concordance index score was used as a fitness score to evaluate the overall performance of multivariate models (i.e. models which include candidate combination and clinical prognostic parameters), whereas the estimated coefficient, P value, and hazard ratio (HR) (default) were each used as a fitness score to determine the univariate and multivariate performance of candidate combinations. To facilitate a simple iterative evaluation of f , a composite variable was computed through the multiple linear equation W 1 * X 1 + W 2 * X 2 … + Wr * Xr : the total sum of coefficients ( W ) multiplied by the immunostaining scores ( X ) for each biomarker in a combination (coefficients are calculated using Cox regression in a multivariate model which includes r biomarkers in a candidate combination). The combinatorial algorithm first generates biomarker combinations using itertools Python module. For a number r ranging from 1 to n , and increasing by step size s , the code computes every possible combination of r biomarker from the n list of targets included in our study. We then applied a fitness function to determine the best combination and the best fitness. The number of combinations of r biomarkers is calculated by itertools function (itertools.combinations) which uses the following formula: n ! / r ! * n − r ! : r = 1 , 1 + s , … , n , s ∈ 1 − n − 1 . The same process is repeated until convergence. If s = 1, then combinations will always have size n − 1 which means one biomarker will be eliminated each iteration until convergence. If the size of the initial population is small, then larger step ( s ) is preferred because it minimises the chances of getting trapped at local optimal. The algorithm is outlined in , and the details of the implementation code are available at GitHub repository ( https://github.com/aibiologics/cancer_markers ). Future modifications and versions of the algorithm will be available at the same GitHub address. Data processing and statistical analysis The immunostaining scores of biomarkers screened in the discovery cohort were tabulated in an Excel spreadsheet. SPSS (version 25; IBM, Portsmouth, UK) and Python 3.8.6 were used for data analysis and PyCharm Community Edition 2020.3.5 x64 for code editing and testing. A probability value of ≤0.05 was regarded as significant. Further details are outlined in .
To assess the expression of biomarker targets, a large and well‐characterised patient cohort of primary colorectal cancers was used. The cohort was retrospectively acquired from the Grampian Biorepository ( www.biorepository.nhsgrampian.org ), and only included patients who had undergone surgery with curative intent for primary colorectal cancers between 1994 and 2009, at Aberdeen Royal Infirmary‐NHS Grampian (Aberdeen, UK). This study also followed the Reporting Recommendations for Tumour Marker Prognostic Studies (REMARK) guidelines (checklist included in supplementary material). Only patients with Union for International Cancer Control (UICC) TNM stage I, stage II, or stage III were included in the study ( n = 650). Patients with histological evidence of distant metastasis at diagnosis or those who had received neoadjuvant chemotherapy and/or radiotherapy were not included. The histopathological reporting of the resection specimens was performed following the relevant guidelines from the Royal College of Pathologists UK for the histopathological reporting of colorectal cancer excision specimens which incorporated TNM version 5. Further details of the histopathological processing of tissue specimens are outlined in Supplementary materials and methods. The primary endpoint was overall survival which was defined as the period from 28 days after the date of surgery to the date of death from any cause. At the date of final censoring of patient outcome data, there had been no missing data in terms of follow‐up and patients who were still alive were censored. The clinicopathological characteristics, the distribution of patients within each clinicopathological parameter, and their association with survival in the discovery cohort are outlined in supplementary material, Table . The mismatch repair (MMR) protein status for all tumours was assessed by immunohistochemistry using antibodies to MLH1 and MSH2 . At the time of the censoring, there had been 309 (47.5%) deaths. The median survival was 103 months (95% CI = 86–120 months), the mean survival was 115 months (95% CI = 108–123 months), and the median follow‐up time, calculated by the ‘reverse Kaplan–Meier’ method, was 88 months (95% CI = 79–97 months). A tissue microarray was constructed from the primary colorectal tumours which also included 50 normal colon mucosal samples (acquired from at least 10 cm in distance from each tumour). The tissue microarray included two representative 1 mm cores for each sample . Ethical approval for the use of colorectal tissue samples was given by the Grampian Biorepository scientific access group committee (tissue request no. TR000169).
A publicly available dataset, accession number GSE39582, was used as the validation cohort . It was accessed through the NCBI Gene Expression Omnibus ( http://www.ncbi.nlm.nih.gov/geo/ ). Data for the following clinicopathological characteristics are outlined in supplementary material, Table . For better comparison with the discovery cohort, stage IV cases ( n = 60) and cases with no survival information ( n = 4) were excluded (i.e. 502 patients included). There were 151 deaths (30.1%), the median survival was 183 months (95% CI = 92–273 months), the mean survival was 130 months (95% CI = 121–140 months), and the median follow‐up time, calculated by the ‘reverse Kaplan–Meier’ method, was 73 months (95% CI = 69–77 months). The expression values of genes (Affymetrix U133 Plus 2.0 chips) corresponding to the biomarker signature identified in the discovery cohort were obtained using Geo2R ( https://www.ncbi.nlm.nih.gov/geo/geo2r/ ). Each probe ID was mapped to the Entrez gene ID with the corresponding platform files. Only probes that are unique to the target gene were used and, if available, exemplar sequence probes were used. If more than one probe was used for the same gene, the expression values showing the most significant variations were used. To allow comparison with immunostaining scores, gene expression values were assigned to one of the four categories based on three quartiles (25th percentile, 50th percentile, and 75th percentile). The validation cohort was used to evaluate the prognostic performance of biomarkers signature after the discovery process was completed. Therefore, only values for genes in the signature were obtained and evaluated in the validation cohort.
The study used a series of biomarkers ( n = 66) which had been evaluated in the discovery patient cohort. The names of proteins, associated pathways, immunohistochemistry platforms, methods of scoring, and corresponding antibodies are all detailed in supplementary material, Table . The biomarker list includes targets which belong to key pathways implicated in tumour progression such as immune response, metabolism, cell cycle, proliferation, cytoskeleton, and cell migration. The majority of biomarkers were evaluated using antibodies developed in our laboratory ( n = 37), while the remainder were assessed using commercially available antibodies ( n = 29). All biomarkers were assessed by immunohistochemistry, the majority of which were stained using a DAKO autostainer (Dako EnVision™ system; Dako, Ely, UK), with the remaining stained using either a Ventana BenchMark XT (Ventana Medical Systems, Oro Valley, AZ, USA) or a Leica Bond RX (Leica Biosystems, Wetzlar, Germany). Further details of materials and methods are provided in and supplementary material, Tables . The immunostaining results were assessed by either a semi‐quantitative scoring system [ , , , , ] or a quantitative automated image analysis [ , , ]. The cores were recorded as missing if they were damaged/folded during the staining process, or if they did not contain tumour cells. Details of the immunohistochemistry assessment and scoring systems are provided in .
Screening and grouping Before applying the iterative algorithm, screening and grouping analysis was performed on the initial series of biomarkers (Figure ). The screening process involved assessing the survival association of each individual biomarker and removing those with no prognostic power. Then, the remaining biomarkers were assembled into subsets based on a range of interrelationships: biological (homology/family, function, GO term, and pathway analysis); clinical (i.e. whether higher expression of biomarkers is associated with better or worse prognosis); and expression patterns (correlated biomarkers). For the biological groupings, biomarkers can be relevant in different pathways and therefore the same biomarker can be placed in different groups. Each subset was then entered sequentially into the programme to evaluate the best biomarker combination. This deliberate screening and subgrouping of biomarkers improves the probability of identifying robust combinations by providing a biological and clinical framework for interpreting potential discoveries. Limiting the analysis to smaller subsets of biomarkers also reduces the effect of combinatorial explosion. Combinatorial algorithm The study developed an iterative algorithm to execute the combinatorial analysis on biomarkers ( n ) and identify a combination ( C* ) with a number of biomarkers ( r ) and a maximum combined fitness ( f ). The fitness in this study represents the prognostic performance of a candidate combination and is mainly evaluated using multivariate Cox regression models which include established prognostic parameters: age, extramural venous invasion (EMVI), lymph node stage and T stage, or age and pathological classification parameter which is based on lymph node stage, T stage, EMVI, and tumour differentiation. The concordance index score was used as a fitness score to evaluate the overall performance of multivariate models (i.e. models which include candidate combination and clinical prognostic parameters), whereas the estimated coefficient, P value, and hazard ratio (HR) (default) were each used as a fitness score to determine the univariate and multivariate performance of candidate combinations. To facilitate a simple iterative evaluation of f , a composite variable was computed through the multiple linear equation W 1 * X 1 + W 2 * X 2 … + Wr * Xr : the total sum of coefficients ( W ) multiplied by the immunostaining scores ( X ) for each biomarker in a combination (coefficients are calculated using Cox regression in a multivariate model which includes r biomarkers in a candidate combination). The combinatorial algorithm first generates biomarker combinations using itertools Python module. For a number r ranging from 1 to n , and increasing by step size s , the code computes every possible combination of r biomarker from the n list of targets included in our study. We then applied a fitness function to determine the best combination and the best fitness. The number of combinations of r biomarkers is calculated by itertools function (itertools.combinations) which uses the following formula: n ! / r ! * n − r ! : r = 1 , 1 + s , … , n , s ∈ 1 − n − 1 . The same process is repeated until convergence. If s = 1, then combinations will always have size n − 1 which means one biomarker will be eliminated each iteration until convergence. If the size of the initial population is small, then larger step ( s ) is preferred because it minimises the chances of getting trapped at local optimal. The algorithm is outlined in , and the details of the implementation code are available at GitHub repository ( https://github.com/aibiologics/cancer_markers ). Future modifications and versions of the algorithm will be available at the same GitHub address. Data processing and statistical analysis The immunostaining scores of biomarkers screened in the discovery cohort were tabulated in an Excel spreadsheet. SPSS (version 25; IBM, Portsmouth, UK) and Python 3.8.6 were used for data analysis and PyCharm Community Edition 2020.3.5 x64 for code editing and testing. A probability value of ≤0.05 was regarded as significant. Further details are outlined in .
Before applying the iterative algorithm, screening and grouping analysis was performed on the initial series of biomarkers (Figure ). The screening process involved assessing the survival association of each individual biomarker and removing those with no prognostic power. Then, the remaining biomarkers were assembled into subsets based on a range of interrelationships: biological (homology/family, function, GO term, and pathway analysis); clinical (i.e. whether higher expression of biomarkers is associated with better or worse prognosis); and expression patterns (correlated biomarkers). For the biological groupings, biomarkers can be relevant in different pathways and therefore the same biomarker can be placed in different groups. Each subset was then entered sequentially into the programme to evaluate the best biomarker combination. This deliberate screening and subgrouping of biomarkers improves the probability of identifying robust combinations by providing a biological and clinical framework for interpreting potential discoveries. Limiting the analysis to smaller subsets of biomarkers also reduces the effect of combinatorial explosion.
The study developed an iterative algorithm to execute the combinatorial analysis on biomarkers ( n ) and identify a combination ( C* ) with a number of biomarkers ( r ) and a maximum combined fitness ( f ). The fitness in this study represents the prognostic performance of a candidate combination and is mainly evaluated using multivariate Cox regression models which include established prognostic parameters: age, extramural venous invasion (EMVI), lymph node stage and T stage, or age and pathological classification parameter which is based on lymph node stage, T stage, EMVI, and tumour differentiation. The concordance index score was used as a fitness score to evaluate the overall performance of multivariate models (i.e. models which include candidate combination and clinical prognostic parameters), whereas the estimated coefficient, P value, and hazard ratio (HR) (default) were each used as a fitness score to determine the univariate and multivariate performance of candidate combinations. To facilitate a simple iterative evaluation of f , a composite variable was computed through the multiple linear equation W 1 * X 1 + W 2 * X 2 … + Wr * Xr : the total sum of coefficients ( W ) multiplied by the immunostaining scores ( X ) for each biomarker in a combination (coefficients are calculated using Cox regression in a multivariate model which includes r biomarkers in a candidate combination). The combinatorial algorithm first generates biomarker combinations using itertools Python module. For a number r ranging from 1 to n , and increasing by step size s , the code computes every possible combination of r biomarker from the n list of targets included in our study. We then applied a fitness function to determine the best combination and the best fitness. The number of combinations of r biomarkers is calculated by itertools function (itertools.combinations) which uses the following formula: n ! / r ! * n − r ! : r = 1 , 1 + s , … , n , s ∈ 1 − n − 1 . The same process is repeated until convergence. If s = 1, then combinations will always have size n − 1 which means one biomarker will be eliminated each iteration until convergence. If the size of the initial population is small, then larger step ( s ) is preferred because it minimises the chances of getting trapped at local optimal. The algorithm is outlined in , and the details of the implementation code are available at GitHub repository ( https://github.com/aibiologics/cancer_markers ). Future modifications and versions of the algorithm will be available at the same GitHub address.
The immunostaining scores of biomarkers screened in the discovery cohort were tabulated in an Excel spreadsheet. SPSS (version 25; IBM, Portsmouth, UK) and Python 3.8.6 were used for data analysis and PyCharm Community Edition 2020.3.5 x64 for code editing and testing. A probability value of ≤0.05 was regarded as significant. Further details are outlined in .
Screening and grouping of biomarkers Survival associations of biomarkers and optimal cut‐off points are shown in supplementary material, Table . In the initial biomarker population ( n = 66), 28 showed significant univariate association with survival and were retained for combinatorial analysis while 38 biomarkers were excluded from further analysis. The majority of biomarkers ( n = 19) had high expression that was associated with better survival, while the remaining biomarkers had high expression that was associated with poor survival. The best performance of biomarkers as an individual prognostic parameter (i.e. the ability to distinguish between prognostic groups, chi‐square value, P value, HR, and finally the prognostic independence in relation to clinical parameters) was observed in relation to CD3, FOXP3, ICOS, CYP8B1, CYP39A1, LIMK2, PTEN, STAT1, and UCP1. The expression profiles of biomarkers in primary tumour, normal colonic mucosa, and in different tumour stages are highlighted in , , and supplementary material, Figure and Table . Before performing any combinatorial analysis on the remaining biomarkers, they were assembled into subsets. Pathway and GO term analysis showed that biomarkers could be incorporated into six biomarker subsets: metabolism, immune response, response to environment, development, cell death and proliferation, and amalgamation group (adhesion and migration, signalling, phosphorylation, and cytoskeleton) (supplementary material, Figure ). SPATA2L was excluded due to lack of association with any of the above pathways. Correlation analysis identified four main groups of correlated biomarkers (supplementary material, Figure ). Based on their survival association (i.e. association of higher expression or lower expression with better or worse survival), biomarkers were divided into two subsets: the majority of biomarkers ( n = 19) with higher expression that is associated with better prognosis and a smaller group ( n = 8) mainly composed of cytochromes P450, with higher expression that is associated with worse prognosis (supplementary material, Table ). Therefore, the iterative algorithm was performed on each of the six biological/pathways subsets, the four main correlations subsets, and the two subsets based on the direction of survival associations. Analysis was also performed on proteins from associated subsets such as response to microenvironment and immune response. Optimal biomarker signature Running the iterative algorithm employing a range of parameters and manually evaluating the solutions based on predetermined criteria (supporting information material and methods S2), an optimal biomarker combination was identified from the biological subset: ‘response to environment’ (supplementary material, Figure ). The biomarker signature consists of six biomarkers: FOXP3, ICOS, LIMK2, p‐cofilin, STAT1, and UCP1. The signature is represented by a composite variable computed with the following equation: − 0.148 * FOXP 3 − 0.158 * ICOS − 0.091 * LIMK 2 + 0.137 * p ‐ cofilin − 0.038 * STAT 1 − 0.164 * UCP 1 (each biomarker is replaced by its corresponding immunostaining score). The composite variable (computed with the above linear formula) was divided into five different patient groups using four cut‐off points of equal percentiles. The signature composite variable was significantly associated with survival ( χ 2 = 53.183, p < 0.001; Figure ). There were significant differences in prognosis between group 1 and group 3 (HR = 2.422, 95% CI = 1.475–3.977, χ 2 = 13.442, p < 0.001), group 1 versus group 4 (HR = 3.061, 95% CI = 1.866–5.021, χ 2 = 21.646, p < 0.001), and group 1 versus group 5 (HR = 4.383, 95% CI = 2.708–7.095, χ 2 = 43.098, p < 0.001). Hierarchical cluster analysis was also performed to evaluate the expression profile of biomarkers in the above signature. Five prognostic cluster groups with significant differences in survival were identified based on their expression patterns and survival associations ( χ 2 = 67.625, p < 0.001; Figure ). Tumours displaying stronger or higher expression of these biomarkers were associated with better prognosis relative to the those with weaker expression. The median survival of patients was undefined (i.e. if the cumulative survival is more than 50% of patients at the last time point, the median survival cannot be calculated) for group 1 ( n = 181), 103 months (95% CI = 73–133 months) for group 2 ( n = 101), 53 months (95% CI = 30–76 months) for group 3 ( n = 84), 51 months (95% CI = 18–84 months) for group 4 ( n = 69), and 28 months (95% CI = 13–43 months) for group 5 ( n = 43). The HR of the patients in cluster group 5 (the worst group in terms of survival) was 4.678 (95% CI = 3.005–7.284) relative to group 1 which has the best prognosis (Figure ). Multivariate analysis using four models showed that this biomarker signature was independently prognostic in relation to clinical and pathological parameters (Tables and ). In the first model, the biomarker signature was significantly associated with survival independent of age, T stage, lymph node stage, and EMVI (linear variable; Wald = 32.898, p < 0.001 and cluster variable; Wald = 34.014, p < 0.001). Further analysis also showed the signature was significantly independent of age, EMVI, and UICC stage in the second multivariate model (linear variable; Wald = 29.438, p < 0.001 and cluster variable; Wald = 28.081, p < 0.001), and independent of age and the pathological risk parameter in the third model (linear variable; Wald = 35.607, p < 0.001 and cluster variable; Wald = 36.620, p < 0.001). Finally, in the fourth model, a multivariate analysis was performed using only parameters that would be available at pre‐tumour resection (i.e. biopsy stage where no pathological information is available about tumour stage, lymph node metastasis, or EMVI). In this model, the signature was highly significant and was the best prognostic indicator compared to age, anatomical site of tumour, and tumour differentiation (linear variable; Wald = 51.359, p < 0.001 and cluster variable; Wald = 65.708, p < 0.001). The composite biomarker signature developed using the discovery cohort was next applied to the external validation cohort to stratify patients into prognostic groups. The signature variable was significantly associated with survival ( χ 2 = 14.217, p = 0.007; supplementary material, Figure ) and was prognostically independent in a multivariate model including age, tumour stage, and lymph node stage (Wald = 9.849, p = 0.043) and a model including age and TNM stage (Wald = 13.077, p = 0.011). The relationships between the biomarker signature and clinicopathological parameters were also investigated (supplementary material, Figures , Figure , and Table ). A proportion of patients, classified based on clinically established pathological parameters, would have different prognosis using the biomarker signature (supplementary material, Figure and Table ). Groups 1 and 2 identified through the biomarker signature as good prognostic groups include 35% of patients who are classified as high risk based on the established pathological evaluation. Similarly, the prognostic evaluation of a proportion of patients using tumour stage, lymph node involvement, or UICC stage would be significantly different if the biomarker signature is considered (supplementary material, Figure , Table , and Table ).
Survival associations of biomarkers and optimal cut‐off points are shown in supplementary material, Table . In the initial biomarker population ( n = 66), 28 showed significant univariate association with survival and were retained for combinatorial analysis while 38 biomarkers were excluded from further analysis. The majority of biomarkers ( n = 19) had high expression that was associated with better survival, while the remaining biomarkers had high expression that was associated with poor survival. The best performance of biomarkers as an individual prognostic parameter (i.e. the ability to distinguish between prognostic groups, chi‐square value, P value, HR, and finally the prognostic independence in relation to clinical parameters) was observed in relation to CD3, FOXP3, ICOS, CYP8B1, CYP39A1, LIMK2, PTEN, STAT1, and UCP1. The expression profiles of biomarkers in primary tumour, normal colonic mucosa, and in different tumour stages are highlighted in , , and supplementary material, Figure and Table . Before performing any combinatorial analysis on the remaining biomarkers, they were assembled into subsets. Pathway and GO term analysis showed that biomarkers could be incorporated into six biomarker subsets: metabolism, immune response, response to environment, development, cell death and proliferation, and amalgamation group (adhesion and migration, signalling, phosphorylation, and cytoskeleton) (supplementary material, Figure ). SPATA2L was excluded due to lack of association with any of the above pathways. Correlation analysis identified four main groups of correlated biomarkers (supplementary material, Figure ). Based on their survival association (i.e. association of higher expression or lower expression with better or worse survival), biomarkers were divided into two subsets: the majority of biomarkers ( n = 19) with higher expression that is associated with better prognosis and a smaller group ( n = 8) mainly composed of cytochromes P450, with higher expression that is associated with worse prognosis (supplementary material, Table ). Therefore, the iterative algorithm was performed on each of the six biological/pathways subsets, the four main correlations subsets, and the two subsets based on the direction of survival associations. Analysis was also performed on proteins from associated subsets such as response to microenvironment and immune response.
Running the iterative algorithm employing a range of parameters and manually evaluating the solutions based on predetermined criteria (supporting information material and methods S2), an optimal biomarker combination was identified from the biological subset: ‘response to environment’ (supplementary material, Figure ). The biomarker signature consists of six biomarkers: FOXP3, ICOS, LIMK2, p‐cofilin, STAT1, and UCP1. The signature is represented by a composite variable computed with the following equation: − 0.148 * FOXP 3 − 0.158 * ICOS − 0.091 * LIMK 2 + 0.137 * p ‐ cofilin − 0.038 * STAT 1 − 0.164 * UCP 1 (each biomarker is replaced by its corresponding immunostaining score). The composite variable (computed with the above linear formula) was divided into five different patient groups using four cut‐off points of equal percentiles. The signature composite variable was significantly associated with survival ( χ 2 = 53.183, p < 0.001; Figure ). There were significant differences in prognosis between group 1 and group 3 (HR = 2.422, 95% CI = 1.475–3.977, χ 2 = 13.442, p < 0.001), group 1 versus group 4 (HR = 3.061, 95% CI = 1.866–5.021, χ 2 = 21.646, p < 0.001), and group 1 versus group 5 (HR = 4.383, 95% CI = 2.708–7.095, χ 2 = 43.098, p < 0.001). Hierarchical cluster analysis was also performed to evaluate the expression profile of biomarkers in the above signature. Five prognostic cluster groups with significant differences in survival were identified based on their expression patterns and survival associations ( χ 2 = 67.625, p < 0.001; Figure ). Tumours displaying stronger or higher expression of these biomarkers were associated with better prognosis relative to the those with weaker expression. The median survival of patients was undefined (i.e. if the cumulative survival is more than 50% of patients at the last time point, the median survival cannot be calculated) for group 1 ( n = 181), 103 months (95% CI = 73–133 months) for group 2 ( n = 101), 53 months (95% CI = 30–76 months) for group 3 ( n = 84), 51 months (95% CI = 18–84 months) for group 4 ( n = 69), and 28 months (95% CI = 13–43 months) for group 5 ( n = 43). The HR of the patients in cluster group 5 (the worst group in terms of survival) was 4.678 (95% CI = 3.005–7.284) relative to group 1 which has the best prognosis (Figure ). Multivariate analysis using four models showed that this biomarker signature was independently prognostic in relation to clinical and pathological parameters (Tables and ). In the first model, the biomarker signature was significantly associated with survival independent of age, T stage, lymph node stage, and EMVI (linear variable; Wald = 32.898, p < 0.001 and cluster variable; Wald = 34.014, p < 0.001). Further analysis also showed the signature was significantly independent of age, EMVI, and UICC stage in the second multivariate model (linear variable; Wald = 29.438, p < 0.001 and cluster variable; Wald = 28.081, p < 0.001), and independent of age and the pathological risk parameter in the third model (linear variable; Wald = 35.607, p < 0.001 and cluster variable; Wald = 36.620, p < 0.001). Finally, in the fourth model, a multivariate analysis was performed using only parameters that would be available at pre‐tumour resection (i.e. biopsy stage where no pathological information is available about tumour stage, lymph node metastasis, or EMVI). In this model, the signature was highly significant and was the best prognostic indicator compared to age, anatomical site of tumour, and tumour differentiation (linear variable; Wald = 51.359, p < 0.001 and cluster variable; Wald = 65.708, p < 0.001). The composite biomarker signature developed using the discovery cohort was next applied to the external validation cohort to stratify patients into prognostic groups. The signature variable was significantly associated with survival ( χ 2 = 14.217, p = 0.007; supplementary material, Figure ) and was prognostically independent in a multivariate model including age, tumour stage, and lymph node stage (Wald = 9.849, p = 0.043) and a model including age and TNM stage (Wald = 13.077, p = 0.011). The relationships between the biomarker signature and clinicopathological parameters were also investigated (supplementary material, Figures , Figure , and Table ). A proportion of patients, classified based on clinically established pathological parameters, would have different prognosis using the biomarker signature (supplementary material, Figure and Table ). Groups 1 and 2 identified through the biomarker signature as good prognostic groups include 35% of patients who are classified as high risk based on the established pathological evaluation. Similarly, the prognostic evaluation of a proportion of patients using tumour stage, lymph node involvement, or UICC stage would be significantly different if the biomarker signature is considered (supplementary material, Figure , Table , and Table ).
Colorectal cancer is a common tumour with an incidence rate that is rising and with a mortality rate that is still relatively high . There have been considerable improvements to our understanding of the molecular pathways underpinning the development and progression of colorectal cancer . However, only a small number of biomarkers (e.g. KRAS mutations, BRAF mutations, and microsatellite instability status) have been translated into routine clinical practice. Therefore, there is a clear requirement to identify molecular signatures that are clinically useful in improving the accuracy of prognosis and potentially applied as tools for screening, early diagnosis, and therapy of colorectal cancer . In this study, a set of novel biomarkers was assessed by immunohistochemistry using well‐characterised cohort of colorectal cancers. The results of immunostaining provided valuable insight into the expression profiles of proteins, many of which are studied for the first time in colorectal cancer. Significant patterns of increased and decreased expression were observed for a number of biomarkers in primary colorectal cancer compared to normal colonic mucosa. A number of proteins showed significant univariate association with overall survival: CDX2, cytochrome P450, LMK2, PTEN, STAT1, T‐cell markers, and UCP1. This is consistent with previous studies implicating these biomarkers in tumour progression and prognosis [ , , , , , , ]. Due to the large number of molecules that can be classified as a biomarker, an extremely large number of combinations would have to be evaluated to identify the relevant combination. This study developed an effective approach for performing combinatorial analysis and the selection of optimal prognostic combinations. The method consists of a screening and grouping analysis, which is designed to minimise the ‘combinatorial explosion’ and reduce the false discovery rate. The screening restricts the combinatorial analysis to biomarkers with significant individual performance . The grouping step further reduces the number of potential combinations by allocating targets into smaller subsets based on their biological relationships, clinical associations, and expression patterns. This also provides a clinical, biological, and molecular framework for interpreting biomarker combinations within each subset. The second element of the discovery approach involves inputting each biomarker subset into a combinatorial programme, which computes all combinations using itertools Python module and assesses their prognostic power. Using this method, the optimal solution is found when using the global approach (generating all combinations with the formula n ! / r ! * n − r ! , where the number of marker r in each combination ranging from 1 to all markers in subset [ n ]). This approach is computationally intensive and may not be possible with larger number of variables. Therefore, this study customised the algorithm to incorporate a gradient approach whereby one biomarker is removed at each stage meaning combinations will always have size n − 1. The gradient approach is much quicker, but the solution is not the best, as the algorithm is normally trapped at local optimum. In addition to gradient and global parameters, the programme incorporated a wide range of parameters for missing interpolation, multivariate and univariate analysis, model versus single variable evaluation, and internal validation. This algorithm provides a comprehensive exploration of data and can efficiently generate solutions that can be relevant in a wide range of biomarker studies. However, additional customisation, optimisation, and more automation are needed to improve the efficiency and applicability of the algorithmic programme. Specific consideration is needed to the computation of the composite variable which is currently calculated using either a linear equation or a clustering. Alternative methods can be easily implemented using a range of multidimensionality reduction methods such as factor analysis and structural equation modelling. Another issue is the identification of an optimal number of groups (i.e. optimal dichotomisation of the patients) and cut‐off points. In this study, to avoid bias, the variables were all dichotomised using the same method (i.e. equal binning). Using the above algorithm, the study identified a prognostic biomarker signature which can divide tumours into different risk subtypes in terms of outcome. The biomarker signature comprised of proteins with complex biological and functional networks mainly associated with immune response, cytoskeletal organisation, and metabolic pathways (Figure ). The relationships between molecules across these different pathways illustrate the complex nature of microenvironment, especially the immune response and its impact on the outcome of tumour. The expression of certain proteins can signify whether a specific immune response has either a pro‐tumour or anti‐tumour effects. In our signature, the expression of STAT1 and FOXP3 is the main indicator of anti‐tumour response through sustaining T‐cell population which is tumour suppressive . On the other hand, the expression of ICOS, its association with FOXP3, and its effect on tumour progression are far more complicated. While some studies presented ICOS as a negative predictor of prognosis especially in FOXP3+ T‐regs cells, others demonstrated that higher ICOS expression was associated with better survival in colorectal cancer and lung cancer, when its expression is examined in the context of T‐helper (Th1)/cytotoxic T lymphocytes and in the context of higher CD3 expression rather than T‐regs [ , , , ]. The association of this biomarker signature with survival is also affected by rearrangements in the cytoskeleton which is closely linked to the immune response in tumour microenvironment . Higher expression of LIMK2 and p‐cofilin has been associated with anti‐tumour effect through inhibition of stem cell proliferation and tumour cells invasiveness . Furthermore, this signature has a metabolic characteristic which is an established pathway in carcinogenesis . Positive outcome was observed in tumours with higher expression of uncoupling proteins implicated in mitochondrial dysfunction and ATP production [ , , ]. Multivariate analysis confirmed the biomarker signature was prognostically independent of current prognostic methods that are used clinically. There were significant differences in the risk groups of the biomarker signature in terms of median survival and HR. The biomarker signature also showed there could be significant improvement to the accuracy of risk classifications compared to current pathological parameters (tumour differentiation, tumour stage, lymph node stage, and EMVI). Therefore, this signature can potentially be incorporated in the clinical practice as a complimentary factor to the current prognostic methods. This biomarker signature is even more relevant at the biopsy stage where it demonstrated a strong performance compared to all prognostic parameters that would be available at that stage. This is currently important in rectal cancer due to the increasing use of neoadjuvant therapy followed by either active surveillance follow‐up or salvage surgery . Prognostic molecular tools could be essential for determining initial treatment for cases based on biopsies. Furthermore, the biomarker signature was prognostically significant in MMR‐proficient tumours, which represents the majority of colorectal cancer. Most of the existing and ongoing immunotherapies (e.g. anti‐CTLA4 and anti‐PD1) are directed towards MMR‐defective tumours . Therefore, the identification of subsets of MMR‐proficient tumours with specific molecular signatures will help guide potential treatment strategies and novel targeted therapies in this group. The findings of this study might be limited by the inclusion of biomarkers with different scoring methods (quantitative versus semi‐quantitative) and hence the resulting dichotomisation of quantitative scores might not accurately mirror the semi‐quantitative scores of negative, weak, moderate, and strong. Moreover, the algorithm and corresponding codes need further customisation and optimisation before efficiently identifying optimal combinations without manual adjustments of input and parameters based on outputs. The code is publicly available on GitHub to use, optimise, adapt, comment upon, and provide feedback. Future modifications and new versions of the code will be available at the following GitHub address ( https://github.com/aibiologics/cancer_markers ). To conclude, this study has developed an effective exploratory method with a range of algorithmic parameters designed to identify optimal combinations of biomarkers based on their prognostic power in terms of subtyping tumours prognostically. Using this method, a novel biomarker signature with strong prognostic power in colorectal cancer was identified. This signature could potentially act as a prognostic parameter which is complimentary to the existing prognostic methods. Furthermore, the findings further highlight the molecular complexity of cancer and its microenvironment and provide a panel of actionable targets that can be manipulated therapeutically to supress tumour progression.
AbA wrote the first draft and edited the manuscript, performed the experimental work (immunohistochemistry and scoring), processed and analysed the data, developed the algorithm, and wrote the corresponding Python codes. WP and MI edited, optimised, and consolidated the Python codes in GitHub. TW and AyA performed and supervised the experimental work in relation to antibody development and validation. SGC, MPH, KM, and MST performed the experimental work (immunohistochemistry and immunostaining scoring) in relation to the immune markers and contributed to editing of the manuscript. GIM initiated, supervised, and led the project; designed the experiments; edited and revised the manuscript; and guided all aspects of this study.
Supplementary materials and methods Supplementary results Figure S1. Frequency distribution of the immunostaining scores in primary colorectal cancer and normal colon mucosa for antibodies that have not been previously published Figure S2. Treemap representation of the main pathways associated with 29 biomarker targets included in the combinatorial analysis Figure S3. Correlation matrix of biomarkers included in combinatorial analysis Figure S4. Kaplan–Meier survival analysis of the biomarker signature in the validation cohort Figure S5. Distribution of the pathological risk groups across the prognostic groups of biomarker signature Figure S6. Distribution of UICC stage, T stage, lymph node stage, and MMR status across the prognostic groups of the signature Table S1. Clinicopathological characteristics of patients in the discovery cohort (Grampian cohort), their tumours, and the relationship of each variable with overall survival Table S2. Clinicopathological characteristics of patients in the validation cohort, their tumours, and the relationship of each variable with overall survival Table S3. Biomarkers screened in the discovery cohort of colorectal cancer Table S4. Peptide sequences used as immunogens to generate monoclonal antibodies which have not been previously tested on the Grampian patient cohort Table S5. The numbers of normal and tumour tissue samples in the multi‐tissue microarray Table S6. Dilutions, antigen retrieval conditions, and subcellular localisation of antibodies which have not been previously published T able S7. Comparison of the expression of each protein in normal colonic mucosa and different UICC stages in primary colorectal cancer using antibodies that have not been previously published in the discovery cohort Table S8. Starting list of biomarkers included in the biomarker combinatorial analysis Table S9. Associations of the biomarker signature and clinicopathological variables. Survival analysis of the biomarker signature was stratified by clinicopathological variables Table S10. Comparisons of the clinicopathological characteristics of cases for which current pathological risk classifications differ from the risk groups of the biomarker signature Remark checklist Click here for additional data file.
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Medication – A boon or bane: Emergencies due to medication-related visits | 8b1f88da-9226-41af-b21f-2f0100a7f78e | 8265416 | Patient Education as Topic[mh] | The use of medication is increasing worldwide, this could be due to the launch of wide range of drugs by the expanding pharmaceutical companies to address large variety of diseases that mandated escalating therapeutic challenges. An array of outcomes are possible when people use medications. Any deviance from the anticipated favourable effect of a medicine would lead to drug-related crisis and visits to the Emergency Department (ED) for those issues are deemed as medication-related visits (MRV). Previous studies on MRVs to the ED demonstrated that 16%–30% of overall visits were attributed to inappropriate use of drugs. The majority of details available on MRVs were from developed countries and such data are lacking from India. Most data were retrospective studies which may underestimate the true prevalence. To achieve a realistic portrayal of ED related MRV, we have conducted a prospective interviewing of patient or their accompanying relatives during patient triaging and treatment. The idea of this study is to ascertain the prevalence of MRV, classify them according to the severity and identifying the most common group of drugs implicated to such visits, preventability and outcomes of the same. By doing so we can reduce the incidence of such deleterious event.
Design This was a prospective observational study performed over a span of 4 weeks in a tertiary care centre. Convenient cross-sectional sampling was done by interviewing patients after obtaining informed written consent during a fixed time of 1 h every day (10 AM or 3 PM). The factors contributing to MRV were recorded and the data were analyzed using Hepler and Strand classification. Setting We carried out this study in the Adult ED of Christian Medical College and Hospital, a 2900 bedded tertiary care centre in Vellore, Tamil Nadu, South India during August 2018. Participant All patients aged above 18 years presenting to triage priority 1 and 2 of ED with MRV during the study period were included in the study. All non-MRV, priority 3 and trauma patients were excluded from the study. Variables Patient details were collected by direct patient interview with the patient and/or their relatives, while medication history was collected from prescriptions or through hospital's electronic database. Demographics, examination findings and history of the patients were documented on standard data collection proforma. The variables such as age, gender, presenting complaints, comorbidities, drug history, and physical findings were included in this study. Triage priority are classified as: Patients with Priority-1: Airway, breathing, or circulatory compromise Priority-2: Stable airway, breathing, and circulation with medical emergencies requiring ED admission. Severity of MRV was outlined as: Mild–laboratory derangement/symptoms not warranting intervention Moderate–laboratory derangement or symptom requiring admission in a hospital/temporary disability Severe–life-threatening symptoms/Permanent disability. MRV is grouped based on Hepler and Strand classification into eight categories as: Untreated indications Subtherapeutic dosage Drug use without indication Drug interactions Improper drug selection Failure to receive drugs Adverse drug reaction Overdosage. Outcome variables Outcome measures were prevalence, severity of MRV, preventability of MRV, and ED outcomes of MRV. Preventability of MRV was assessed by an independent ED consultant. Bias Consecutive sampling was not done due to the arduous task of recruiting patients throughout the day in the ED and hence we adopted a convenient cross-sectional sampling technique. Study size Based on the research by Zed et al ., using a 10.5% prevalence of MRV to ED, with a precision of 5% and 95% confidence, the required sample size calculated was 156. Statistical analysis Statistical Package for Social Sciences for Windows (SPSS Inc. Released 2015, version 23.0. Armonk, NY, USA) was used to analyze the data. Continuous variables are described as mean (standard deviation [SD]). Categorical and nominal variables are described as percentages. Ethical consideration Institutional Review Board (IRB Min. No. 10524 dated 01/Feb/2017) certified and approved, patient privacy was ensured using unique identifiers and password secured data entry software with regulated users.
This was a prospective observational study performed over a span of 4 weeks in a tertiary care centre. Convenient cross-sectional sampling was done by interviewing patients after obtaining informed written consent during a fixed time of 1 h every day (10 AM or 3 PM). The factors contributing to MRV were recorded and the data were analyzed using Hepler and Strand classification.
We carried out this study in the Adult ED of Christian Medical College and Hospital, a 2900 bedded tertiary care centre in Vellore, Tamil Nadu, South India during August 2018.
All patients aged above 18 years presenting to triage priority 1 and 2 of ED with MRV during the study period were included in the study. All non-MRV, priority 3 and trauma patients were excluded from the study.
Patient details were collected by direct patient interview with the patient and/or their relatives, while medication history was collected from prescriptions or through hospital's electronic database. Demographics, examination findings and history of the patients were documented on standard data collection proforma. The variables such as age, gender, presenting complaints, comorbidities, drug history, and physical findings were included in this study.
Patients with Priority-1: Airway, breathing, or circulatory compromise Priority-2: Stable airway, breathing, and circulation with medical emergencies requiring ED admission. Severity of MRV was outlined as: Mild–laboratory derangement/symptoms not warranting intervention Moderate–laboratory derangement or symptom requiring admission in a hospital/temporary disability Severe–life-threatening symptoms/Permanent disability. MRV is grouped based on Hepler and Strand classification into eight categories as: Untreated indications Subtherapeutic dosage Drug use without indication Drug interactions Improper drug selection Failure to receive drugs Adverse drug reaction Overdosage.
Priority-1: Airway, breathing, or circulatory compromise Priority-2: Stable airway, breathing, and circulation with medical emergencies requiring ED admission. Severity of MRV was outlined as: Mild–laboratory derangement/symptoms not warranting intervention Moderate–laboratory derangement or symptom requiring admission in a hospital/temporary disability Severe–life-threatening symptoms/Permanent disability. MRV is grouped based on Hepler and Strand classification into eight categories as: Untreated indications Subtherapeutic dosage Drug use without indication Drug interactions Improper drug selection Failure to receive drugs Adverse drug reaction Overdosage.
Outcome measures were prevalence, severity of MRV, preventability of MRV, and ED outcomes of MRV. Preventability of MRV was assessed by an independent ED consultant.
Consecutive sampling was not done due to the arduous task of recruiting patients throughout the day in the ED and hence we adopted a convenient cross-sectional sampling technique.
Based on the research by Zed et al ., using a 10.5% prevalence of MRV to ED, with a precision of 5% and 95% confidence, the required sample size calculated was 156.
Statistical Package for Social Sciences for Windows (SPSS Inc. Released 2015, version 23.0. Armonk, NY, USA) was used to analyze the data. Continuous variables are described as mean (standard deviation [SD]). Categorical and nominal variables are described as percentages.
Institutional Review Board (IRB Min. No. 10524 dated 01/Feb/2017) certified and approved, patient privacy was ensured using unique identifiers and password secured data entry software with regulated users.
Overall, 6372 patients attended the ED during the study period. We screened 443 patients due to convenient cross-sectional sampling method and after the exclusion, 120 visits were deemed MRV and the prevalence was 27.1% . The mean age was 55 (SD: 15) years with a male preponderance (73 [60.8%]). Triage priority 1 comprised 47 (39.1%) and rest 73 (60.8%) were priority 2. The most common comorbidity was hypertension 66 (55%) followed by diabetes 53 (44.2%), alcohol consumption 22 (18.3%), and smoking 22 (18.3%) . Common presenting complaints included vomiting 30 (25%), breathing difficulty 25 (20.8%), giddiness 24 (20%), seizure 21 (17.5%), and abdomen pain 19 (17.5%) . Most commonly implicated drug was antihypertensives 41 (34.1%) followed by oral hypoglycemics 25 (20.8%) and anticonvulsants 19 (15.8%) . Only half i.e., 52 (43.3%) were compliant to prescribed medication. The most common reasons for MRV were failure to receive drugs 57 (47.5%), subtherapeutic dosage 30 (25%) and adverse drug reaction 20 (16.7%) . Severity of MRV was classified as mild 60 (50%), moderate 46 (38.3%), and severe in 14 (11.7%). Out of these visits, 71/120 (59.2%) were deemed preventable. Three-fourths (73.3%) were discharged stable from the ED .
MRVs are substantial problem and influence to the overall burden of our health care sector. Prospective study design in adult population have shown greater incidence rate than retrospective study design as latter would underestimate the true incidence due to missing data or inaccurate documentation. This study is designed as a prospective observational study to analyze complete medication history captured from routine chart information and brief questionnaire. Thus prospective model, randomization and adequate sample size enhance the probability that our valuations are precise and applicable to general population. Prevalence from earlier prospective studies done in ED visits was consistent with our results. Arifri et al . conducted a study in Saudi Arabia which showed a lesser prevalence compared to our study and this would reflect our country's position among developing nations. In most studies, MRV is limited to adverse medication reaction stated by the World Health Organization as “any noxious, unintended, or undesired effect of a drug, which occurs at doses used in humans for prophylaxis, diagnosis, or treatment.” Helper and Strand's description of MRV is more complete and reproducible. We have adopted the same for meaningful characterization of MRV to the ED. In our study majority of MRVs were due to failure to receive drugs which is contrary to Pepe et al . where untreated indication and overdosage topped the list. Most patients in our study were noncompliant to drug regimen as seen in the previous international study. Adequate health education to the patient and/or accompanying relative regarding side effects of medicine and the pros and cons of treatment schedule can minimize noncompliance. Antihypertensives, oral hypoglycemics, and anticonvulsants were the commonly implicated drugs in our study, matching other studies. This implies medications used for chronic illnesses are to be monitored closely by emphasising regular outpatient department visits, enforced counselling and education are needed for patients receiving chronic drugs. Percentage of preventability of MRV in our study was similar to studies in literature. In general, the soaring rate of preventability encourages researchers to foresee ideas to confront this issue. On contrary to Singh et al . study, where three fourth MRVs were moderate, our study recorded higher rates of severe outcomes. These ill outcomes can be avoided by patient-centerd care model which includes guided patient care by family physicians and pharmacists. According to existing literature, this is the most efficient way of providing safe and effective therapy. MRVs are directly related to total number of drugs prescribed per patient, as multiple drugs invite the possibility of poor adherence and adverse drug interactions. For that reason, reducing the total number of medicines using fixed-dose combination might help in addressing this issue. It is worthy to investigate the root cause of every such event to allow for suitable mediation in these patients. In conclusion, drug compliance, insight of health provider on prescription medication, monitoring of routine medicine and patient health education are the areas recognized for improvement. Family doctors and pharmacists should work together to fortify care plans and inspect patients at regular intervals to prevent MRVs. Limitations A few patients with minor MRVs were excluded due to lower triage priorities as only patients requiring ED admission were recruited. Brief study duration and all data being collected in a single department and hospital are the limitations of our work.
A few patients with minor MRVs were excluded due to lower triage priorities as only patients requiring ED admission were recruited. Brief study duration and all data being collected in a single department and hospital are the limitations of our work.
The fact that a quarter of the ED visits are due to MRV and that more than half was preventable is quite alarming. Counteractive, anticipatory and instructive strategies should focus on the most common drug, illness, and particular population. This study encourages the appropriate use of medications to warrant the best result of pharmacological mediation. Further studies with extensive duration focusing on MRVs are needed to prevent this malicious issue. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
Nil.
There are no conflicts of interest.
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Carbohydrate intake and activation of gastric acid secretion decrease gastric estrogen secretion | 2c18bf3c-3adb-4de0-a766-d319ee119a54 | 11953264 | Digestive System[mh] | Maintaining energy homeostasis, especially keeping blood glucose and lipid (triglycerides [TG] and fatty acids [FFA]) levels within appropriate ranges, is critical for life. Since the discovery of insulin in 1921, the regulation of blood glucose levels has been studied in detail . However, until recently, it was unclear which organs monitor blood lipid levels or which hormones lower elevated blood lipid levels. In 2021, we reported that gastric parietal cells (the cells that secrete gastric acid) secrete estrogen in response to blood lipid levels, using male and ovariectomized female rats . Estrogen, synthesized from testosterone by aromatase, is secreted from adipocytes and gastric parietal cells, besides from the ovaries – . Whole-body aromatase PET and immunostaining revealed that the stomach—particularly gastric parietal cells—represents a significant tissue expressing this enzyme . Aromatase requires energy to produce estrogen (3x NADPH / estrogen), 3 and gastric parietal cells generate energy using FFA, not glucose . When TG is administered orally, blood estrogen levels increase in response to the increase in blood TG levels but remain unchanged in gastrectomized rats . Estrogen levels in stomach tissues correlate with blood TG levels, and isolated gastric gland epithelia produce estrogen in a FFA-dependent manner . Estrogen is not just a sex hormone— it is a multi-target and multi-functional hormone. In addition to follicular growth and ovulation, estrogen regulates energy homeostasis, bone metabolism, brain function, and skeletal growth . Above all, estrogen suppresses feeding behavior, lipogenesis, and lipolysis while enhancing lipid storage and consumption – , all contribute to lower blood lipid levels. Women’s blood triglyceride levels are lower than men’s but increase after menopause . We therefore previously proposed a model in which gastric parietal cells secrete estrogen in response to blood lipid levels to lower elevated blood lipid levels . Unlike estrogen from other organs, such as the ovaries, gastric estrogen enters the liver directly in high concentrations, similar to insulin from the pancreas, regardless of gender , , . Insulin enhances the liver’s uptake of blood glucose, storing it as glycogen and lipids converted through de novo lipogenesis, while estrogen suppresses the latter lipogenesis , . Just as insulin dysfunction can cause hyperglycemia, gastric estrogen dysfunction could cause hyperlipidemia and fatty liver. Since the number of gastric parietal cells and blood testosterone levels decrease with age , , gastric estrogen production is likely to decrease as well. Indeed, hyperlipidemia and fatty liver are common among the elderly . Thus, a new subcategory of “gastric estrogen dysfunction” may be added to hyperlipidemia and fatty liver diseases. However, because gastric parietal cells use energy derived from lipids for acid secretion and estrogen production, it is important to clarify how postprandial changes in blood lipid levels and gastric acid secretion affect gastric estrogen to understand its dynamics and role in daily life. Here, we show that carbohydrate intake and the activation of gastric acid secretion decrease gastric estrogen production and the subsequent blood estrogen levels. We first used male rats to investigate the effects of diet and gastric acid secretion on gastric estrogen production and blood estrogen levels. Blood estrogen levels decrease after meals, especially after carbohydrate intake. Blood FFA levels also decrease, and direct elevation of blood FFA levels by intravenous lipid injection partially restores the postprandially decreased blood estrogen levels. Estrogen levels in the portal vein, about 3.8 times those in the systemic vein, also decrease after meals. Hormones that enhance and suppress gastric acid secretion lead to decreased and increased estrogen production in isolated gastric gland epithelia, respectively. Suppression of gastric acid secretion restores the decreased estrogen production caused by hormones that enhance gastric acid secretion in vitro and the postprandially decreased blood estrogen levels in vivo. Finally, we conducted key experiments using female rats in the metestrous phase and confirmed results similar to those observed in male rats. Diet activates gastric acid secretion, and carbohydrate intake reduces blood FFA levels via insulin . Both processes decrease gastric estrogen production, leading to an increase in hepatic lipogenesis. Conversely, lipid intake not only increases blood TG levels but also promotes the release of hormones that suppress gastric acid secretion, such as glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide-1 (GLP-1), and cholecystokinin (CCK) . Both processes increase gastric estrogen production, resulting in a decrease in hepatic lipogenesis. The more lipids ingested, the less lipogenesis is required. Therefore, gastric estrogen, along with insulin, would play an important role in proper hepatic lipogenesis based on the ingested carbohydrates and lipids.
Blood Estrogen decreases after meals, especially after carbohydrate intake in males First, we examined the changes in blood estrogen levels after feeding a high-fat diet (HFD) and a normal diet (ND). Rats fed HFD were given a week to adapt to the diet before the experiment. Eight-week-old male rats fasted for 12 h were fed either HFD or ND ad libitum for 30 min. We monitored the levels of blood TG, FFA, glucose, and estradiol (E2), the most potent estrogen (Fig. a). Blood TG levels increased and peaked 2 h after feeding in HFD-fed rats, but exhibited a decreasing trend—though not significantly—in ND-fed rats. Because blood E2 levels increase in response to the increase in blood TG levels elevated by oral or intravenous TG administration , we expected that blood E2 levels would increase in HFD-fed rats but not in ND-fed rats. However, in both rats, blood E2 levels decreased immediately after feeding, with increased blood glucose and decreased blood FFA levels. According to the manufacturer’s instructions, HFD and ND are mainly composed of carbohydrates, TG, and proteins, and their content ratios were 10:5:5 in HFD and 10:1:5 in ND. To determine which nutrient is key to lowering blood estrogen levels, rats were orally administered carbohydrates (4 g of starch per kg of body weight), TG (2.5 mL of olive oil per kg of body weight) , or protein (2 g of casein per kg of body weight), and we monitored their blood TG, FFA, glucose, and E2 levels (Fig. b). The amounts of nutrients administered were based on their content in HFD. Protein-administered rats did not show significant changes in blood E2 levels. TG-administered rats exhibited increased blood TG and E2 levels, as previously observed . Carbohydrate-administered rats showed decreased blood E2 levels, alongside increased glucose and decreased FFA levels. Insulin decreases blood FFA levels , and gastric gland epithelia produce estrogen in a FFA-dependent manner . We thus analyzed the relationship between blood FFA and E2 levels. We found a positive correlation between them in rats at 1 h after carbohydrate administration, when blood glucose levels peaked (Fig. c). These data suggest that the insulin-induced reduction in blood FFA levels decreases blood E2 levels after meals. Gastric estrogen enters the liver directly through the portal vein in high concentrations without being diluted in systemic blood, where it suppresses hepatic de novo lipogenesis . Indeed, estrogen levels in portal blood are 2 to 10 times higher than in systemic blood , . However, after gastrectomy, estrogen levels in portal blood become similar to those in systemic blood, and blood estrogen levels remain unchanged even when blood TG levels are elevated by oral TG administration , , . Therefore, elevated levels of blood estrogen in the portal vein, resulting from gastric estrogen, would play an important role in the regulation of hepatic lipogenesis. We then examined blood E2 levels in the portal and tail veins of fasted (deprived of food for 12 h) and postprandial (ND-fed: 2 h after a 0.5 h ND feeding) rats (Fig. d). In postprandial rats, blood glucose levels in the tail vein were higher compared to fasted rats, whereas their blood TG and FFA levels were lower than those in fasted rats, as observed in ND-fed rats in Fig. a. Blood E2 levels in the portal vein (fasted: ~200 pg/mL, ND-fed: ~120 pg/mL) were about 3.8 times those in the tail vein (fasted: ~53 pg/mL, ND-fed: ~30 pg/mL), regardless of feeding status. Blood E2 levels in ND-fed rats were about 0.6 times those in fasted rats in both veins. Therefore, gastric estrogen would maintain higher estrogen levels in portal blood than in systemic blood, and the postprandial decrease in blood lipid levels would decrease both portal and systemic blood estrogen levels. These data suggest that gastric estrogen plays a crucial role in suppressing hepatic lipogenesis and that the postprandial decrease in blood FFA levels increases hepatic lipogenesis by decreasing gastric estrogen production. Intravenous injection of lipids partially recovers postprandially decreased blood Estrogen levels in males To confirm that the postprandial decrease in blood estrogen levels was due to the decrease in blood FFA levels, we directly increased blood TG or FFA levels by intravenous injection (Fig. ). Gastric parietal cells uptake FFA and generate energy with the help of heart-type fatty acid binding protein (H-FABP), which can process FFAs ranging from C10 to C18 , . On the other hand, certain types of cells in the stomach express GPR120 and CD36, which respond to FFAs of C14 or above and C20 or above, respectively , , . These suggest that capric acid (C10-FFA) and lauric acid (C12-FFA) can serve as energy sources for gastric parietal cells without activating GPR120- or CD36-positive cells. We previously used C12-FFA in the in vitro E2 production assay using isolated gastric gland epithelia (Fig. a, left) . However, C12-FFA was unsuitable for the injection study because of its low water solubility, so we considered using C10-FFA instead, which has high water solubility. Gastric gland epithelia were isolated from male rats aged 11 to 15 weeks after being deprived of food for 4 h. We incubated the epithelia with C10-FFA in the presence of testosterone and confirmed that the epithelia produced E2 in a C10-FFA concentration-dependent manner (Fig. a, middle and right), so we used C10-FFA for the injection study. Eight-week-old male rats were fasted for 12 h before the experiment. Postprandial (ND-fed: 2 h after a 0.5 h ND feeding) and control fasted rats were intravenously injected with TG (2 mL of 20% soy oil emulsion per kg of body weight) or C10-FFA (2 mL of 150 mM C10-FFA [pH 7.8] per kg of body weight). We monitored their blood TG, FFA, and E2 levels (Figs. b and c). When rats were injected with TG, blood TG, FFA, and E2 levels peaked immediately after the injection and returned to baseline levels 1 h later, regardless of their feeding conditions (Fig. b). Blood FFA and E2 levels in C10-FFA injected rats also peaked immediately after the injection but returned to baseline levels at a slower rate, while there were no significant changes in blood TG levels (Fig. c). Thus, blood E2 levels would be related to blood FFA levels, including those generated by the lipolysis of blood TG. To investigate the effects of diet on the blood FFA-dependent increase in blood E2 levels, we compared the changes in blood FFA and E2 levels from before (0 h) to 0.25 h after the injection of TG or C10-FFA between ND-fed and fasted rats (Fig. d). While not significant, ND-fed rats showed smaller increases in blood E2 levels compared to fasted rats after either lipid injection. These data suggest that the postprandial decrease in blood FFA levels significantly contributes to the decrease in blood estrogen levels; however, other factors should also be considered. Activation of gastric acid secretion decreases gastric Estrogen production in males Gastric parietal cells use energy for acid secretion and estrogen production. Thus, when gastric acid secretion is stimulated, the energy available for producing gastric estrogen may decrease. Diet stimulates acid secretion through nerves and hormones , so we investigated the effects of 15 hormones related to the stomach and metabolism, including autonomic neurotransmitters, on gastric estrogen production using isolated gastric gland epithelia (Fig. ) . We also examined the effects of an antacid, lansoprazole (LPZ) . Gastric gland epithelia were isolated from male rats aged 11–15 weeks after being deprived of food for 4 h (neither fully fed nor fasting). The epithelia were cultured with a series of concentrations of hormones or LPZ in the presence of testosterone and C12-FFA. Epithelia cultured only with testosterone served as non-E2-producing controls to evaluate the E2 production during the culture . We evaluated their relative E2 production levels, normalizing the E2 production levels without hormones to 1. E2 production was decreased by ghrelin, gastrin, histamine, and acetylcholine (ACh), all of which enhance gastric acid secretion (Fig. a) . In contrast, des-acyl ghrelin, somatostatin, glucagon, GIP, GLP-1, CCK, cortisol, adrenaline, and LPZ increased E2 production; all, except cortisol, suppress gastric acid secretion (Fig. b) – . Insulin, leptin, and triiodothyronine (T3) did not affect E2 production (Fig. c). Furthermore, LPZ restored the decreased E2 production caused by gastrin, histamine, or ACh (Fig. d). These data indicate that the activation and suppression of gastric acid secretion lead to a decrease and an increase in gastric estrogen production, respectively. Suppression of gastric acid secretion increases postprandially decreased blood Estrogen levels in males We then investigated the effects of suppression of gastric acid secretion on blood estrogen levels in postprandial rats, which are active in gastric acid secretion. GLP-1 showed the most significant increase in gastric E2 production among the hormones examined that suppress gastric acid secretion (Fig. b). Thus, we used GLP-1 (hormone) and LPZ (drug) to suppress gastric acid secretion through different mechanisms , . Eight-week-old male rats were fasted for 12 h before the experiment. Postprandial (ND-fed: 2 h after a 0.5 h ND feeding) rats and control fasted rats were intravenously injected with GLP-1 (2 mL of 12 ng/mL GLP-1 per kg of body weight) or LPZ (2 mL of 4 µM LPZ per kg of body weight). Their blood TG, FFA, and E2 levels were monitored (Fig. ). GLP-1 and LPZ increased the decreased blood E2 levels in ND-fed rats 15 min after injection, whereas no significant changes were observed in blood E2 levels in fasted rats. On the other hand, blood TG and FFA levels did not show significant changes in either group of rats. These data suggest that suppression of gastric acid secretion increases the postprandially decreased blood estrogen levels. Blood estrogen decreases after meals and activation of gastric acid secretion decreases gastric estrogen production in females We showed that a postprandial decrease in blood FFA levels and the activation of gastric acid secretion reduce gastric estrogen production using male rats. Gastric parietal cells secrete estrogen in response to blood lipid levels, regardless of gender . However, blood estrogen levels in females are higher than in males and fluctuate during their estrous cycle , . We then performed the key experiments using female rats in the metestrous phase, when blood estrogen levels are stable (Fig. ). Estrous cycles were monitored using the vaginal impedance measurement technique . We first examined the changes in blood estrogen levels in ND-fed female rats and compared them to those in male rats (Fig. a, ND) (Fig. a). Eight-week-old female rats in the metestrous phase were fasted for 12 h. The rats were fed ND ad libitum for 30 min, and their blood TG, FFA, glucose, and E2 levels were monitored. Blood E2 levels decreased after feeding, with increased glucose and decreased FFA levels, while blood TG levels showed a slight downward trend. These results are consistent with those observed in male rats, even though female rats exhibited higher blood E2 levels and lower blood TG levels compared to male rats. Next, we examined the blood E2 levels in the portal and tail veins of fasted (deprived of food for 12 h) and postprandial (ND-fed: 2 h after a 0.5 h ND feeding) female rats (Fig. b). Blood glucose levels in the tail vein were higher in postprandial rats than in fasted rats, while their blood TG and FFA levels were lower than those in fasted rats, as observed in ND-fed rats in Fig. a. Blood E2 levels in the portal vein (fasted: ~310 pg/mL, ND-fed: ~240 pg/mL) were about 4.5 times (fasted: ~4.2 times, ND-fed: ~4.8 times) those in the tail vein (fasted: ~74 pg/mL, ND-fed: ~50 pg/mL) under both feeding conditions. Blood E2 levels in ND-fed rats were about 0.73 times (portal vein: ~0.77 times, tail vein: ~0.68 times) those of fasted rats in both veins. These results are also consistent with those observed in male rats, albeit blood E2 levels in the portal vein were higher in female rats compared to male rats (Fig. c). Therefore, regardless of gender, blood FFA and E2 levels decrease after meals, and blood estrogen levels are higher in the portal vein than in the tail vein, although female rats show higher blood E2 levels and lower blood TG levels than male rats. Finally, we examined the effects of hormones on gastric estrogen production in females. We used gastrin and histamine, which reduced gastric E2 production in males, as well as glucagon, GLP-1, and LPZ, which enhanced it, along with insulin as an ineffective control (Fig. ). Female rats aged 11 to 15 weeks in the metestrous phase were deprived of food for 4 h. Gastric gland epithelia isolated from the rats were cultured with testosterone and C12-FFA, either alone or in the presence of the hormones or LPZ. We evaluated their relative E2 production levels, normalizing the E2 production levels without hormones to 1 (Fig. d). Epithelia cultured only with testosterone served as non-E2-producing controls. The concentrations of hormones and LPZ were determined based on the results obtained from male rats (Fig. ). As observed in male rats in Fig. , gastrin and histamine decreased gastric E2 production, while glucagon, GLP-1, and LPZ increased it; insulin had no effect. Therefore, the activation and suppression of gastric acid secretion decrease and increase the production of gastric estrogen, respectively, in females as they do in males.
First, we examined the changes in blood estrogen levels after feeding a high-fat diet (HFD) and a normal diet (ND). Rats fed HFD were given a week to adapt to the diet before the experiment. Eight-week-old male rats fasted for 12 h were fed either HFD or ND ad libitum for 30 min. We monitored the levels of blood TG, FFA, glucose, and estradiol (E2), the most potent estrogen (Fig. a). Blood TG levels increased and peaked 2 h after feeding in HFD-fed rats, but exhibited a decreasing trend—though not significantly—in ND-fed rats. Because blood E2 levels increase in response to the increase in blood TG levels elevated by oral or intravenous TG administration , we expected that blood E2 levels would increase in HFD-fed rats but not in ND-fed rats. However, in both rats, blood E2 levels decreased immediately after feeding, with increased blood glucose and decreased blood FFA levels. According to the manufacturer’s instructions, HFD and ND are mainly composed of carbohydrates, TG, and proteins, and their content ratios were 10:5:5 in HFD and 10:1:5 in ND. To determine which nutrient is key to lowering blood estrogen levels, rats were orally administered carbohydrates (4 g of starch per kg of body weight), TG (2.5 mL of olive oil per kg of body weight) , or protein (2 g of casein per kg of body weight), and we monitored their blood TG, FFA, glucose, and E2 levels (Fig. b). The amounts of nutrients administered were based on their content in HFD. Protein-administered rats did not show significant changes in blood E2 levels. TG-administered rats exhibited increased blood TG and E2 levels, as previously observed . Carbohydrate-administered rats showed decreased blood E2 levels, alongside increased glucose and decreased FFA levels. Insulin decreases blood FFA levels , and gastric gland epithelia produce estrogen in a FFA-dependent manner . We thus analyzed the relationship between blood FFA and E2 levels. We found a positive correlation between them in rats at 1 h after carbohydrate administration, when blood glucose levels peaked (Fig. c). These data suggest that the insulin-induced reduction in blood FFA levels decreases blood E2 levels after meals. Gastric estrogen enters the liver directly through the portal vein in high concentrations without being diluted in systemic blood, where it suppresses hepatic de novo lipogenesis . Indeed, estrogen levels in portal blood are 2 to 10 times higher than in systemic blood , . However, after gastrectomy, estrogen levels in portal blood become similar to those in systemic blood, and blood estrogen levels remain unchanged even when blood TG levels are elevated by oral TG administration , , . Therefore, elevated levels of blood estrogen in the portal vein, resulting from gastric estrogen, would play an important role in the regulation of hepatic lipogenesis. We then examined blood E2 levels in the portal and tail veins of fasted (deprived of food for 12 h) and postprandial (ND-fed: 2 h after a 0.5 h ND feeding) rats (Fig. d). In postprandial rats, blood glucose levels in the tail vein were higher compared to fasted rats, whereas their blood TG and FFA levels were lower than those in fasted rats, as observed in ND-fed rats in Fig. a. Blood E2 levels in the portal vein (fasted: ~200 pg/mL, ND-fed: ~120 pg/mL) were about 3.8 times those in the tail vein (fasted: ~53 pg/mL, ND-fed: ~30 pg/mL), regardless of feeding status. Blood E2 levels in ND-fed rats were about 0.6 times those in fasted rats in both veins. Therefore, gastric estrogen would maintain higher estrogen levels in portal blood than in systemic blood, and the postprandial decrease in blood lipid levels would decrease both portal and systemic blood estrogen levels. These data suggest that gastric estrogen plays a crucial role in suppressing hepatic lipogenesis and that the postprandial decrease in blood FFA levels increases hepatic lipogenesis by decreasing gastric estrogen production.
To confirm that the postprandial decrease in blood estrogen levels was due to the decrease in blood FFA levels, we directly increased blood TG or FFA levels by intravenous injection (Fig. ). Gastric parietal cells uptake FFA and generate energy with the help of heart-type fatty acid binding protein (H-FABP), which can process FFAs ranging from C10 to C18 , . On the other hand, certain types of cells in the stomach express GPR120 and CD36, which respond to FFAs of C14 or above and C20 or above, respectively , , . These suggest that capric acid (C10-FFA) and lauric acid (C12-FFA) can serve as energy sources for gastric parietal cells without activating GPR120- or CD36-positive cells. We previously used C12-FFA in the in vitro E2 production assay using isolated gastric gland epithelia (Fig. a, left) . However, C12-FFA was unsuitable for the injection study because of its low water solubility, so we considered using C10-FFA instead, which has high water solubility. Gastric gland epithelia were isolated from male rats aged 11 to 15 weeks after being deprived of food for 4 h. We incubated the epithelia with C10-FFA in the presence of testosterone and confirmed that the epithelia produced E2 in a C10-FFA concentration-dependent manner (Fig. a, middle and right), so we used C10-FFA for the injection study. Eight-week-old male rats were fasted for 12 h before the experiment. Postprandial (ND-fed: 2 h after a 0.5 h ND feeding) and control fasted rats were intravenously injected with TG (2 mL of 20% soy oil emulsion per kg of body weight) or C10-FFA (2 mL of 150 mM C10-FFA [pH 7.8] per kg of body weight). We monitored their blood TG, FFA, and E2 levels (Figs. b and c). When rats were injected with TG, blood TG, FFA, and E2 levels peaked immediately after the injection and returned to baseline levels 1 h later, regardless of their feeding conditions (Fig. b). Blood FFA and E2 levels in C10-FFA injected rats also peaked immediately after the injection but returned to baseline levels at a slower rate, while there were no significant changes in blood TG levels (Fig. c). Thus, blood E2 levels would be related to blood FFA levels, including those generated by the lipolysis of blood TG. To investigate the effects of diet on the blood FFA-dependent increase in blood E2 levels, we compared the changes in blood FFA and E2 levels from before (0 h) to 0.25 h after the injection of TG or C10-FFA between ND-fed and fasted rats (Fig. d). While not significant, ND-fed rats showed smaller increases in blood E2 levels compared to fasted rats after either lipid injection. These data suggest that the postprandial decrease in blood FFA levels significantly contributes to the decrease in blood estrogen levels; however, other factors should also be considered.
Gastric parietal cells use energy for acid secretion and estrogen production. Thus, when gastric acid secretion is stimulated, the energy available for producing gastric estrogen may decrease. Diet stimulates acid secretion through nerves and hormones , so we investigated the effects of 15 hormones related to the stomach and metabolism, including autonomic neurotransmitters, on gastric estrogen production using isolated gastric gland epithelia (Fig. ) . We also examined the effects of an antacid, lansoprazole (LPZ) . Gastric gland epithelia were isolated from male rats aged 11–15 weeks after being deprived of food for 4 h (neither fully fed nor fasting). The epithelia were cultured with a series of concentrations of hormones or LPZ in the presence of testosterone and C12-FFA. Epithelia cultured only with testosterone served as non-E2-producing controls to evaluate the E2 production during the culture . We evaluated their relative E2 production levels, normalizing the E2 production levels without hormones to 1. E2 production was decreased by ghrelin, gastrin, histamine, and acetylcholine (ACh), all of which enhance gastric acid secretion (Fig. a) . In contrast, des-acyl ghrelin, somatostatin, glucagon, GIP, GLP-1, CCK, cortisol, adrenaline, and LPZ increased E2 production; all, except cortisol, suppress gastric acid secretion (Fig. b) – . Insulin, leptin, and triiodothyronine (T3) did not affect E2 production (Fig. c). Furthermore, LPZ restored the decreased E2 production caused by gastrin, histamine, or ACh (Fig. d). These data indicate that the activation and suppression of gastric acid secretion lead to a decrease and an increase in gastric estrogen production, respectively.
We then investigated the effects of suppression of gastric acid secretion on blood estrogen levels in postprandial rats, which are active in gastric acid secretion. GLP-1 showed the most significant increase in gastric E2 production among the hormones examined that suppress gastric acid secretion (Fig. b). Thus, we used GLP-1 (hormone) and LPZ (drug) to suppress gastric acid secretion through different mechanisms , . Eight-week-old male rats were fasted for 12 h before the experiment. Postprandial (ND-fed: 2 h after a 0.5 h ND feeding) rats and control fasted rats were intravenously injected with GLP-1 (2 mL of 12 ng/mL GLP-1 per kg of body weight) or LPZ (2 mL of 4 µM LPZ per kg of body weight). Their blood TG, FFA, and E2 levels were monitored (Fig. ). GLP-1 and LPZ increased the decreased blood E2 levels in ND-fed rats 15 min after injection, whereas no significant changes were observed in blood E2 levels in fasted rats. On the other hand, blood TG and FFA levels did not show significant changes in either group of rats. These data suggest that suppression of gastric acid secretion increases the postprandially decreased blood estrogen levels.
We showed that a postprandial decrease in blood FFA levels and the activation of gastric acid secretion reduce gastric estrogen production using male rats. Gastric parietal cells secrete estrogen in response to blood lipid levels, regardless of gender . However, blood estrogen levels in females are higher than in males and fluctuate during their estrous cycle , . We then performed the key experiments using female rats in the metestrous phase, when blood estrogen levels are stable (Fig. ). Estrous cycles were monitored using the vaginal impedance measurement technique . We first examined the changes in blood estrogen levels in ND-fed female rats and compared them to those in male rats (Fig. a, ND) (Fig. a). Eight-week-old female rats in the metestrous phase were fasted for 12 h. The rats were fed ND ad libitum for 30 min, and their blood TG, FFA, glucose, and E2 levels were monitored. Blood E2 levels decreased after feeding, with increased glucose and decreased FFA levels, while blood TG levels showed a slight downward trend. These results are consistent with those observed in male rats, even though female rats exhibited higher blood E2 levels and lower blood TG levels compared to male rats. Next, we examined the blood E2 levels in the portal and tail veins of fasted (deprived of food for 12 h) and postprandial (ND-fed: 2 h after a 0.5 h ND feeding) female rats (Fig. b). Blood glucose levels in the tail vein were higher in postprandial rats than in fasted rats, while their blood TG and FFA levels were lower than those in fasted rats, as observed in ND-fed rats in Fig. a. Blood E2 levels in the portal vein (fasted: ~310 pg/mL, ND-fed: ~240 pg/mL) were about 4.5 times (fasted: ~4.2 times, ND-fed: ~4.8 times) those in the tail vein (fasted: ~74 pg/mL, ND-fed: ~50 pg/mL) under both feeding conditions. Blood E2 levels in ND-fed rats were about 0.73 times (portal vein: ~0.77 times, tail vein: ~0.68 times) those of fasted rats in both veins. These results are also consistent with those observed in male rats, albeit blood E2 levels in the portal vein were higher in female rats compared to male rats (Fig. c). Therefore, regardless of gender, blood FFA and E2 levels decrease after meals, and blood estrogen levels are higher in the portal vein than in the tail vein, although female rats show higher blood E2 levels and lower blood TG levels than male rats. Finally, we examined the effects of hormones on gastric estrogen production in females. We used gastrin and histamine, which reduced gastric E2 production in males, as well as glucagon, GLP-1, and LPZ, which enhanced it, along with insulin as an ineffective control (Fig. ). Female rats aged 11 to 15 weeks in the metestrous phase were deprived of food for 4 h. Gastric gland epithelia isolated from the rats were cultured with testosterone and C12-FFA, either alone or in the presence of the hormones or LPZ. We evaluated their relative E2 production levels, normalizing the E2 production levels without hormones to 1 (Fig. d). Epithelia cultured only with testosterone served as non-E2-producing controls. The concentrations of hormones and LPZ were determined based on the results obtained from male rats (Fig. ). As observed in male rats in Fig. , gastrin and histamine decreased gastric E2 production, while glucagon, GLP-1, and LPZ increased it; insulin had no effect. Therefore, the activation and suppression of gastric acid secretion decrease and increase the production of gastric estrogen, respectively, in females as they do in males.
We demonstrated that carbohydrate intake and the activation of gastric acid secretion decrease gastric estrogen production and blood estrogen levels in both male and female rats. Gastric parietal cells generate energy from FFA, including those lipolyzed from TG, and use it for estrogen production and acid secretion (Fig. a) , . Diets rich in carbohydrates stimulate insulin release and increase gastric acid secretion. Insulin lowers blood FFA levels , though it does not directly affect gastric estrogen production (Fig. c). Thus, decreased blood FFA levels and increased gastric acid secretion after meals would lead to a decrease in gastric estrogen production (Fig. b, left). On the other hand, lipid intake raises blood TG levels and stimulates the secretion of hormones that suppress gastric acid secretion, such as GIP, GLP-1, and CCK , , leading to an increase in gastric estrogen production (Fig. b, right). Insulin and gastric estrogen directly enter the liver at high concentrations before being diluted in systemic blood, enhancing and suppressing hepatic de novo lipogenesis, respectively (Fig. d) , . The more lipid ingested, the less lipogenesis is required. Therefore, we propose that gastric estrogen, in conjunction with insulin, regulates hepatic lipogenesis based on the levels of ingested carbohydrates and lipids (Fig. ). Conventional exercise, fasting, the newly introduced GLP-1 receptor agonists (GLP-1 RAs), and low-carbohydrate diets are recommended for patients with fatty liver disease , , . These therapies are considered to aid in the prevention or treatment of fatty liver by enhancing energy expenditure (exercise), limiting energy intake (fasting), suppressing appetite (GLP-1 RAs), decreasing insulin-induced lipogenesis from carbohydrates (low-carbohydrate diet), and/or utilizing pathways unrelated to gastric estrogen. In this study, we demonstrated that blood estrogen levels are high in fasted rats, decreasing after meals, particularly following carbohydrate intake (Fig. ). Additionally, we found that glucagon (released during fasting) , adrenaline (released during fasting and exercise) , , and GLP-1 enhance gastric estrogen production (Fig. ). Therefore, these therapies may help reduce hepatic lipogenesis, at least in part, by increasing gastric estrogen secretion. In contrast, dietary habits that consistently lower blood FFA levels and increase gastric acid secretion- such as “carbohydrate snacking”- would continuously promote hepatic lipogenesis by persistently suppressing gastric estrogen production. Furthermore, hyperlipidemia and fatty liver are prevalent among the elderly , . Since gastric parietal cells and blood testosterone decrease with age, gastric estrogen production is expected to decrease as well , . A new subcategory of “gastric estrogen dysfunction” may be added to hyperlipidemia and fatty liver disease in the future. Therefore, this study will shed new light on the field of lipid metabolism, especially regarding the prevention and treatment of fatty liver disease. Blood estrogen levels in females are higher than in males and fluctuate during their estrous cycle , . Indeed, blood E2 levels in both the portal and tail veins were higher in female rats than in male rats, and female rats showed lower blood TG levels than male rats (Fig. ). However, in female rats, as in male rats, blood E2 levels decreased with a decrease in blood FFA levels after meals, and the activation of gastric acid secretion leads to a decrease in gastric estrogen production. Therefore, the effects of diets on gastric estrogen would essentially be the same, regardless of gender. However, since we used females in the metestrous phase, further investigation is required to understand how different estrous phases influence the regulation of gastric estrogen production in female rats. There are still other questions that remain to be clarified. Firstly, the indirect effects of hormones on gastric estrogen production, including their crosstalk, should be investigated. Indeed, insulin did not affect gastric estrogen production “directly” (Fig. c) but decreased it “indirectly” by lowering blood FFA levels (Fig. ). Secondly, it is crucial to understand how hormones influence aromatase activity and energy production in gastric parietal cells at the intracellular level. Gastrin, histamine, and ACh stimulate gastric acid secretion through phosphorylation pathways , and phosphorylation both positively (Y361) and negatively (S118) regulates aromatase activity. Phosphorylation may also affect energy production in gastric parietal cells through H-FABP . Thirdly, it is important to investigate the developmental and age-dependent changes in the regulation of gastric estrogen, as these changes influence aromatase levels in gastric parietal cells and blood testosterone levels , . Finally, studies using gastric parietal cell-specific aromatase knockout animals will genetically confirm this study and explore the role of gastric estrogen in hepatic lipogenesis and hyperlipidemia in live animals.
Animals Wistar rats, purchased from Kiwa Laboratory Animals (Japan), were housed in an air-conditioned environment (24 ± 2 °C and 50–60% humidity) with 12 h light/dark cycle (lights on at 8:00 AM) and had ad libitum access to food (normal diet [ND, CE-2 diet, CLEA-Japan (Tokyo, Japan); carbohydrate: TG: protein = 10: 1: 5]) and water unless stated otherwise. In studies feeding a high-fat diet (HFD, D12451, Research Diets; carbohydrate: TG: protein = 10: 5: 5), the rats were fed a HFD for one week before the experiment to acclimate. In studies with female rats, we selected those in the metestrous phase, determined using the vaginal impedance measurement method with MK-10-B (Muromachi Kikai, Tokyo, Japan) according to the manufacturer’s instructions . All experiments were conducted in accordance with the protocol approved by the Wakayama Medical University Animal Care and Use Committee (approval number: 1104) and followed the ARRIVE guidelines ( https://arriveguidelines.org ). Hormones and antacid Ghrelin (334-43731), des-acyl ghrelin (332-44371), insulin (093-06471), glucagon (339-40981), leptin (120–06591), cholecystokinin (CCK, 333-41001), gastric inhibitory polypeptide (GIP, 331-41781), glucagon-like peptide 1 (GLP-1, 333-43441), somatostatin (332-40231), gastrin (338-41431), histamine (088–00641) and acetylcholine (ACh, 011–00592) were purchased from FujiFilm (Tokyo, Japan). Triiodothyronine (T3, T2887), cortisol (H4001), and adrenaline (E4642) were purchased from Merck (Amsterdam, Netherlands). Lansoprazole (LPZ, 123–05861), a proton pump inhibitor, was purchased from FujiFilm. Feeding study Eight-week-old male or female (metestrous phase) rats were deprived of food for 12 h. The rats were fed ND (or HFD when indicated) ad libitum for 30 min (from − 0.5 to 0 h), and their blood samples were collected from the tail vein before (−0.5) and at 0, 1, 2, 3, 4, and 5 h after feeding. In the experiments examining portal blood E2 levels, the rats were anesthetized by isoflurane inhalation. After confirming deep anesthesia, blood was collected from the tail and portal veins. Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study. Oral administration of carbohydrate, TG, and protein Oral administration studies were performed as previously described, with slight modifications . Eight-week-old male rats were deprived of food for 12 h. Carbohydrate (4 g starch [10 mL of 40% starch solution] per kg of body weight), TG (2.5 mL olive oil per kg of body weight), or protein (2 g casein [12.5 mL of 16% casein solution] per kg of body weight) were administered orally to rats using the intragastric gavage technique. Their blood samples were collected from the tail vein before (0) and at 1, 2, 3, 4, and 5 h after the administration. The amounts of carbohydrate, TG, and, protein administered were determined according to their content in HFD (carbohydrate : TG : protein = 10 : 5 : 5). Starch (191–03985) and casein (030-01505) were purchased from FujiFilm. Olive oil (Yoshida) was purchased from Yoshida Pharmaceutical Company (Tokyo, Japan). Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study. Intravenous injection of TG, FFA, and LPZ Intravenous injection studies were performed as previously described, with modified conditions . Eight-week-old male rats were deprived of food for 12 h. TG emulsion (2 mL of 20% soy oil emulsion per kg of body weight; Intralipos Injection 20%, Otsuka, Tokyo, Japan), C10-FFA (2 mL of 150 mM capric acid [pH 7.8] per kg of body weight; D0024, Tokyo Chemical Industry, Tokyo, Japan), or LPZ (2 mL of 4 µM LPZ per kg of body weight) was injected intravenously into fasted rats or rats fed ND ad libitum for 30 min followed by 2 h rest. Blood samples were collected from the tail vein before (at 0 h [fasted] or at −2.5, −2, −1, 0 h [ND fed]) and at 0.25, 0.5, 1, 2, and 3 h after the injection. Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study. In vitro gastric estrogen production assay Gastric gland epithelia were isolated as previously described with slight modifications . Male or female (metestrous phase) rats aged 11–15 weeks were deprived of food for 4 h. After euthanasia by isoflurane inhalation, the stomachs of the rats were removed, opened along the greater curvature, and washed with ice-cold phosphate-buffered saline (PBS). After removal of the serosal muscle, the fundic region was cut into < 5 mm pieces and shaken in the chelating buffer (5 mM EDTA in PBS) supplemented with Tosyl-L-lysyl-chloromethane hydrochloride (TLCK, 147 ng/mL, 200-20141, FujiFilm) for 2 h on ice. The supernatant was changed with the dissociation buffer (54.9 mM D-sorbitol and 43.4 mM sucrose in PBS), and the tube was shaken vigorously for 2 min to dissociate epithelia from the mucosa. After centrifugation at 160 g for 10 min at 4 ºC, the pellet was dissolved in DMEM (044-32955, FujiFilm) and filtered through a 100 μm cell strainer (VCS-100, Azwan) to obtain isolated gastric epithelia. Isolated gastric gland epithelia were observed under an Eclipse Ti microscope equipped with Plan Fluor 10/0.30 lens and DS-Fi1 camera (Nikon, Tokyo, Japan). Image processing was performed with ImageJ 2 2.3.0 (National Institutes of Health). The epithelia were then aliquoted and incubated for 1 h at 37 °C in DMEM supplemented with testosterone (20 nM, T-1500, Sigma) and TLCK (147 ng/mL) in the presence or absence of lauric acid (C12-FFA, L0016, Tokyo Chemical Industry), capric acid (C10-FFA, D0024, Tokyo Chemical Industry), hormones, or a drug. Epithelia incubated in DMEM supplemented with testosterone and TLCK only were used as non-E2 producing controls, as FFA is required for the epithelia to produce E2 . After incubation, E2 and phospholipid (PL) levels were measured in the epithelium-containing culture medium. Since PL amounts are proportional to cell membrane quantities, E2 levels were adjusted based on PL levels to account for variations in cell volume among aliquoted samples (“corrected total E2 levels”). In the experiments to evaluate the use of C10-FFA by gastric parietal cells, the epithelia were aliquoted into four and incubated in DMEM supplemented with testosterone and TLCK in the absence or presence of C10-FFA (0, 250, 500, or 1000 µM) (Fig. a, see also Supplementary Data 2). We obtained “relative total E2 levels” by normalizing “corrected total E2 levels” to that of the non-E2 producing control (C10-FFA: 0 µM). In the experiments investigating the effects of hormones or a drug on gastric estrogen production, we compared the levels of E2 produced (Figs. and d, see also Supplementary Data 3 and 5). Epithelia were aliquoted into eight (Figs. a-c and d) or nine (Fig. d). Seven (former) or eight (latter) aliquots were incubated in DMEM supplemented with testosterone, TLCK, and C12-FFA (500 µM) in the absence and presence of hormones or a drug. An aliquot incubated in DMEM supplemented with only testosterone and TLCK served as a “non-E2 producing control”. “Relative total E2 level” consists of “E2 newly produced during incubation (E2 production level)” and “E2 already present before incubation (“relative total E2 level” of the “non-E2 producing control”)”. Then, “E2 production levels” were determined by subtracting the “relative total E2 level” of the “non-E2 producing control” from the “relative total E2 levels”. We obtained “relative E2 production levels” by normalizing “E2 production levels” to that of the hormone or drug-free control. Measurement of TG, glucose, FFA, E2, and PL concentrations Measurements of TG, E2, and PL concentrations were performed as previously described . Plasma glucose and FFA concentrations were measured using a LabAssay Glucose and a NEFA C (FujiFilm) according to the manufacturer’s instructions. Statistics and reproducibility Data are mean ± s.d. P values for two groups were determined by a two-sided Student’s t-test. P values between multiple groups and a control group were determined by Steel’s multiple comparison test. R and P values were determined by Pearson’s product-moment correlation with a 95% density ellipse. Statistical analyses were performed using JMP Pro ver. 16 (SAS Institute Japan, Tokyo, Japan). P values < 0.05 were considered to be significant. R values > 0.5 and < −0.5 were considered to be positively and negatively correlated, respectively. Every experiment was repeated multiple times with essentially the same results.
Wistar rats, purchased from Kiwa Laboratory Animals (Japan), were housed in an air-conditioned environment (24 ± 2 °C and 50–60% humidity) with 12 h light/dark cycle (lights on at 8:00 AM) and had ad libitum access to food (normal diet [ND, CE-2 diet, CLEA-Japan (Tokyo, Japan); carbohydrate: TG: protein = 10: 1: 5]) and water unless stated otherwise. In studies feeding a high-fat diet (HFD, D12451, Research Diets; carbohydrate: TG: protein = 10: 5: 5), the rats were fed a HFD for one week before the experiment to acclimate. In studies with female rats, we selected those in the metestrous phase, determined using the vaginal impedance measurement method with MK-10-B (Muromachi Kikai, Tokyo, Japan) according to the manufacturer’s instructions . All experiments were conducted in accordance with the protocol approved by the Wakayama Medical University Animal Care and Use Committee (approval number: 1104) and followed the ARRIVE guidelines ( https://arriveguidelines.org ).
Ghrelin (334-43731), des-acyl ghrelin (332-44371), insulin (093-06471), glucagon (339-40981), leptin (120–06591), cholecystokinin (CCK, 333-41001), gastric inhibitory polypeptide (GIP, 331-41781), glucagon-like peptide 1 (GLP-1, 333-43441), somatostatin (332-40231), gastrin (338-41431), histamine (088–00641) and acetylcholine (ACh, 011–00592) were purchased from FujiFilm (Tokyo, Japan). Triiodothyronine (T3, T2887), cortisol (H4001), and adrenaline (E4642) were purchased from Merck (Amsterdam, Netherlands). Lansoprazole (LPZ, 123–05861), a proton pump inhibitor, was purchased from FujiFilm.
Eight-week-old male or female (metestrous phase) rats were deprived of food for 12 h. The rats were fed ND (or HFD when indicated) ad libitum for 30 min (from − 0.5 to 0 h), and their blood samples were collected from the tail vein before (−0.5) and at 0, 1, 2, 3, 4, and 5 h after feeding. In the experiments examining portal blood E2 levels, the rats were anesthetized by isoflurane inhalation. After confirming deep anesthesia, blood was collected from the tail and portal veins. Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study.
Oral administration studies were performed as previously described, with slight modifications . Eight-week-old male rats were deprived of food for 12 h. Carbohydrate (4 g starch [10 mL of 40% starch solution] per kg of body weight), TG (2.5 mL olive oil per kg of body weight), or protein (2 g casein [12.5 mL of 16% casein solution] per kg of body weight) were administered orally to rats using the intragastric gavage technique. Their blood samples were collected from the tail vein before (0) and at 1, 2, 3, 4, and 5 h after the administration. The amounts of carbohydrate, TG, and, protein administered were determined according to their content in HFD (carbohydrate : TG : protein = 10 : 5 : 5). Starch (191–03985) and casein (030-01505) were purchased from FujiFilm. Olive oil (Yoshida) was purchased from Yoshida Pharmaceutical Company (Tokyo, Japan). Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study.
Intravenous injection studies were performed as previously described, with modified conditions . Eight-week-old male rats were deprived of food for 12 h. TG emulsion (2 mL of 20% soy oil emulsion per kg of body weight; Intralipos Injection 20%, Otsuka, Tokyo, Japan), C10-FFA (2 mL of 150 mM capric acid [pH 7.8] per kg of body weight; D0024, Tokyo Chemical Industry, Tokyo, Japan), or LPZ (2 mL of 4 µM LPZ per kg of body weight) was injected intravenously into fasted rats or rats fed ND ad libitum for 30 min followed by 2 h rest. Blood samples were collected from the tail vein before (at 0 h [fasted] or at −2.5, −2, −1, 0 h [ND fed]) and at 0.25, 0.5, 1, 2, and 3 h after the injection. Rats with initial blood TG levels in the tail vein exceeding 200 mg/dL were excluded from the study.
Gastric gland epithelia were isolated as previously described with slight modifications . Male or female (metestrous phase) rats aged 11–15 weeks were deprived of food for 4 h. After euthanasia by isoflurane inhalation, the stomachs of the rats were removed, opened along the greater curvature, and washed with ice-cold phosphate-buffered saline (PBS). After removal of the serosal muscle, the fundic region was cut into < 5 mm pieces and shaken in the chelating buffer (5 mM EDTA in PBS) supplemented with Tosyl-L-lysyl-chloromethane hydrochloride (TLCK, 147 ng/mL, 200-20141, FujiFilm) for 2 h on ice. The supernatant was changed with the dissociation buffer (54.9 mM D-sorbitol and 43.4 mM sucrose in PBS), and the tube was shaken vigorously for 2 min to dissociate epithelia from the mucosa. After centrifugation at 160 g for 10 min at 4 ºC, the pellet was dissolved in DMEM (044-32955, FujiFilm) and filtered through a 100 μm cell strainer (VCS-100, Azwan) to obtain isolated gastric epithelia. Isolated gastric gland epithelia were observed under an Eclipse Ti microscope equipped with Plan Fluor 10/0.30 lens and DS-Fi1 camera (Nikon, Tokyo, Japan). Image processing was performed with ImageJ 2 2.3.0 (National Institutes of Health). The epithelia were then aliquoted and incubated for 1 h at 37 °C in DMEM supplemented with testosterone (20 nM, T-1500, Sigma) and TLCK (147 ng/mL) in the presence or absence of lauric acid (C12-FFA, L0016, Tokyo Chemical Industry), capric acid (C10-FFA, D0024, Tokyo Chemical Industry), hormones, or a drug. Epithelia incubated in DMEM supplemented with testosterone and TLCK only were used as non-E2 producing controls, as FFA is required for the epithelia to produce E2 . After incubation, E2 and phospholipid (PL) levels were measured in the epithelium-containing culture medium. Since PL amounts are proportional to cell membrane quantities, E2 levels were adjusted based on PL levels to account for variations in cell volume among aliquoted samples (“corrected total E2 levels”). In the experiments to evaluate the use of C10-FFA by gastric parietal cells, the epithelia were aliquoted into four and incubated in DMEM supplemented with testosterone and TLCK in the absence or presence of C10-FFA (0, 250, 500, or 1000 µM) (Fig. a, see also Supplementary Data 2). We obtained “relative total E2 levels” by normalizing “corrected total E2 levels” to that of the non-E2 producing control (C10-FFA: 0 µM). In the experiments investigating the effects of hormones or a drug on gastric estrogen production, we compared the levels of E2 produced (Figs. and d, see also Supplementary Data 3 and 5). Epithelia were aliquoted into eight (Figs. a-c and d) or nine (Fig. d). Seven (former) or eight (latter) aliquots were incubated in DMEM supplemented with testosterone, TLCK, and C12-FFA (500 µM) in the absence and presence of hormones or a drug. An aliquot incubated in DMEM supplemented with only testosterone and TLCK served as a “non-E2 producing control”. “Relative total E2 level” consists of “E2 newly produced during incubation (E2 production level)” and “E2 already present before incubation (“relative total E2 level” of the “non-E2 producing control”)”. Then, “E2 production levels” were determined by subtracting the “relative total E2 level” of the “non-E2 producing control” from the “relative total E2 levels”. We obtained “relative E2 production levels” by normalizing “E2 production levels” to that of the hormone or drug-free control.
Measurements of TG, E2, and PL concentrations were performed as previously described . Plasma glucose and FFA concentrations were measured using a LabAssay Glucose and a NEFA C (FujiFilm) according to the manufacturer’s instructions.
Data are mean ± s.d. P values for two groups were determined by a two-sided Student’s t-test. P values between multiple groups and a control group were determined by Steel’s multiple comparison test. R and P values were determined by Pearson’s product-moment correlation with a 95% density ellipse. Statistical analyses were performed using JMP Pro ver. 16 (SAS Institute Japan, Tokyo, Japan). P values < 0.05 were considered to be significant. R values > 0.5 and < −0.5 were considered to be positively and negatively correlated, respectively. Every experiment was repeated multiple times with essentially the same results.
Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5
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Study on health education methods based on rural residents’ infectious disease-specific health literacy in Shandong, China | fc5d8bfd-fe96-497b-be26-5a2031cc7025 | 11315526 | Health Literacy[mh] | Infectious diseases have exerted a significant impact on global health, economic progress, and social stability. Infectious diseases have been a principal cause of death for centuries, claiming the lives of 10 to 15 million people each year. Infectious diseases are still one of the top 10 causes of global death. The coronavirus disease 2019 (COVID-19) pandemic, in particular, has caused hundreds of millions of infections and deaths worldwide and nearly $10 trillion in economic losses. Moreover, the implementation of measures such as keeping social distance, home isolation, travel restrictions, and work stoppages compelled a shortage of workers in numerous sectors and caused an increase in unemployment. These seriously affected public health, national economic development, and social stability. Therefore, it is imperative to take effective measures to control the occurrence and prevalence of infectious diseases. Health literacy, as a significant approach to coping with infectious diseases, is an effect reflection of the health status of individuals and society. Recently, more and more studies have emphasized the importance of health literacy in preventing the COVID-19 pandemic, but there are very few studies regarding the prevention and control of infectious disease. Infectious disease-specific health literacy (IDSHL) reflects residents’ ability to maintain and promote their own health by comprehending and applying relevant knowledge of the occurrence, prevention, and treatment of infectious diseases. IDSHL was closely related to reducing the symptoms of relevant infectious diseases among residents. A study showed that a high level of IDSHL in individuals was an objective need for the normalization of COVID-19 epidemic prevention and control, and it was also a powerful weapon in the face of the unknown challenges of infectious disease prevention and control in the future. Another study indicated that adequate IDSHL was beneficial to decreasing the occurrence and prevalence of infectious diseases and promoting the cultivation of healthy lifestyles among residents. On the contrary, inadequate IDSHL would lead to a decline in the utilization rate of infectious disease prevention and control services and the adverse consequences of residents health, which may result in more hospitalization, a greater degree of emergency care, a higher mortality and disability rate, poorer cognitive and social ability to acquire knowledge related to infectious diseases, and worse overall health status. Although health literacy and/or IDSHL are useful to deal with infectious diseases, the levels of health literacy and/or IDSHL among residents in most countries were not optimistic. A nation-wide cross-sectional survey in Arab countries revealed that only 23.9% of participants possessed adequate health literacy. Nearly 63.28% of older adults in Hong Kong were regarded as having inadequate health literacy. Only 27.60% of China’s national residents had an adequate IDSHL level in 2021. As a vulnerable group, rural residents’ IDSHL level was even less optimistic because of the backwardness of their education level and medical resources, their weak sense of self-health protection, etc. In 2021, 77.64% of rural residents in Shandong Province were considered to have inadequate IDSHL and only 9.58% of rural residents in Fujian Province possessed adequate IDSHL. Hence, the level of health literacy among rural residents, especially IDSHL, needs to be enhanced. IDSHL, as a comprehensive embodiment to measure residents’ ability to prevent and control infectious diseases, played a crucial role in evaluating the effect of infectious disease health education activities. According to previous studies, IDSHL was significantly associated with health education, and the implementation of health education could effectively improve residents’ IDSHL level. Health education serving as a planned, organized, and systematic social education activity, can transform health knowledge into health behavior to promote residents’ health. A study conducted by Zhang manifested that health education could be carried out through various methods, including school curriculum, community activities, and new media publicity, which could further improve the IDSHL and self-management abilities of individuals and groups. An Internet-based health education study revealed that digital information technologies (computers, smartphones, Internet, email, and apps) access and use were valid methods for individuals to obtain health information and advice. Therefore, it is very necessary to evaluate the effect of different health education methods on the IDSHL level among rural residents and then adopt effective methods to conduct health education for the sake of enhancing the level of rural residents’ IDSHL. Considering the significance of IDSHL and health education in adult groups and the lack of association studies on both in rural areas of Shandong Province, China, this study aimed to investigate the IDSHL level of rural residents and explore whether the utilization of traditional health education methods and Internet publicity platforms could help to improve rural residents’ IDSHL level.
2.1. Definition of participants The current cross-sectional study was conducted in rural areas of Shandong Province, China, in 2022. The participants in this study were rural residents aged 18 to 71 years old in Shandong Province, China. Rural residents referred to residents with a rural household registration who lived in rural areas for over half of the year in 1 year. The inclusion criteria were rural residents aged 18 to 71 years old with consent to participate in the study and the ability to complete the questionnaire. The exclusion criteria were incomplete questionnaires, refusal to participate in the study, rural residents who lived in rural areas for no more than half of the year in 1 year, and students with rural household registration who lived in rural areas for less than half of the year in 1 year. 2.2. Sample size The formula was adopted to calculate the sample size as follows: N = 400 × q / p. In this formula, N represents the sample size, and p is the incidence rate of a certain event. q = 1 ‐ p . A previous study in 2018 showed that Chinese residents’ possession rate of adequate IDSHL was 17.05%. Then, p was set to 17.05% and entered into the formula to calculate the sample size as 1946. Considering the potential rate of loss to follow-up, the sample size for the investigation was increased by 10% based on the calculated sample size, which was then calculated to be 2140. 2.3. Sampling strategy Participants were recruited from rural areas by multistage sampling. First, 16 cities in Shandong Province, China, were divided into 3 groups according to social, cultural, and economic conditions. Second, 2 cities were randomly selected from each group as the sample cities. Jinan (the first group), Qingdao (the first group), Weifang (the second group), Linyi (the second group), Dezhou (the third group), and Jining (the third group) were selected as the sample cities. Third, 1 county was randomly selected as the sample county in each city. Huaiyin (in Jinan city), Laixi (in Qingdao city), Anqiu (in Weifang city), Pingyi (in Linyi city), Qihe (in Dezhou city), and Qufu (in Jining city) were selected as the sample counties. Fourth, 1 town was randomly selected as the sample town in each county. Yuqing Hu (in Huaiyin County), Wangcheng (in Laixi County), Jingzhi (in Anqiu County), Fengyang (in Pingyi County), Zhaoguan (in Qihe County), and Xiaoxue (in Qufu County) were selected as the sample towns. Fifth, cluster sampling was conducted separately in each town to randomly sample villages, and the rural residents who met the inclusion criteria in the sample villages were included in the sample. Two villages in each town were selected as the sample villages. After cluster sampling, 2283 rural residents were included in this study. This study was approved by the Ethics Review Committee of Shandong Second Medical University (No. 2023YX-138), and all participants voluntarily provided informed consents. 2.4. Questionnaire The cognitive questionnaire regarding knowledge about infectious disease prevention and control (the IDPC knowledge cognitive questionnaire) was used to collect the following data. A brief description of the questionnaire was as follows: The questionnaire was developed based on the National Residents’ Health Literacy Monitoring Questionnaire developed in China. IDSHL is 1 of the 6 categories of health literacy on the National Residents’ Health Literacy Monitoring Questionnaire. All questions in the questionnaire were rigorously discussed and evaluated by epidemiologists, statisticians, and sociologists. All participants independently completed the questionnaire. The questionnaire included participants’ sociodemographic information, cognitive abilities regarding IDPC knowledge, and the participants’ demand for IDPC knowledge. Sociodemographic information mainly included participants’ age, region, gender, education, occupation, annual family income, “whether IDPC knowledge can be acquired?,” “whether IDPC knowledge can be acquired conveniently?,” “whether to use smartphones?,” and methods to acquire IDPC knowledge, etc. Cognitive ability regarding IDPC knowledge consisted of 47 items and 2 dimensions: (1) cognition regarding IDPC common knowledge (13 items) was measured by answering each question correctly. The total score ranged from 0 to 13. The higher scores represented a higher level of IDPC common knowledge. (2) Cognition regarding IDPC knowledge about air-borne (6 items), water-borne (3 items), food-borne (3 items), contact (5 items), arthropod-borne (4 items), soil-borne (4 items), iatrogenic (5 items), and vertical transmission (4 items) was designed to measure the level of knowledge of infectious disease transmission routes, and the total scores for this dimension ranged from 0 to 34. Besides, the participants’ demand for IDPC knowledge (2 items) was utilized to evaluate the participants’ demand rate for IDPC knowledge. In brief, if a participant correctly answered 1 question about their cognitive abilities regarding IDPC knowledge, he or she received 1 point. The total score of each participant was determined by the number of questions that the participant correctly answered. If a participant’s score was equal to or more than 80% of the total score of all questions, it meant that this participant possessed adequate IDSHL and he or she would be included in the case group. Otherwise, it meant that this participant did not have adequate IDSHL and would be embraced in the control group. The questionnaire used in this study had acceptable levels of reliability and validity. The internal consistency reliability test showed that the Cronbach alpha coefficient was 0.73. The construct validity test showed that the Kaiser–Meyer–Olkin value was 0.97, and Bartlett test of sphericity produced a result of χ 2 = 171,567.24 ( P < .001). 2.5. Statistical analysis The database was established using Epidata version 3.1 software (The Epidata Association, Odense, Denmark). Continuous data were expressed as the mean ± standard deviation. Categorical data expressed by frequency . If the variance between the case and control groups was equal, Student t tests were used to examine the difference between the means of continuous variables; otherwise, Wilcoxon rank sum tests were used. Chi-square analyses were performed to compare the distribution of the categorical variables between the case and control groups. Stata version 15.0 statistical software (StataCorp LLC, College Station, TX) was used for statistical analyses. All reported probabilities ( P values) were two-sided, and statistical significance was defined as P < .05. 2.6. Quality control There were some measures to control possible bias. Firstly, the size of the investigating sample was increased by 10% of the calculated sample size to control the follow-up bias. Secondly, investigators were trained and demanded to investigate participants with the same standard in order to control investigation bias. Thirdly, the operation about data input was carried out by 2 people to control input errors.
The current cross-sectional study was conducted in rural areas of Shandong Province, China, in 2022. The participants in this study were rural residents aged 18 to 71 years old in Shandong Province, China. Rural residents referred to residents with a rural household registration who lived in rural areas for over half of the year in 1 year. The inclusion criteria were rural residents aged 18 to 71 years old with consent to participate in the study and the ability to complete the questionnaire. The exclusion criteria were incomplete questionnaires, refusal to participate in the study, rural residents who lived in rural areas for no more than half of the year in 1 year, and students with rural household registration who lived in rural areas for less than half of the year in 1 year.
The formula was adopted to calculate the sample size as follows: N = 400 × q / p. In this formula, N represents the sample size, and p is the incidence rate of a certain event. q = 1 ‐ p . A previous study in 2018 showed that Chinese residents’ possession rate of adequate IDSHL was 17.05%. Then, p was set to 17.05% and entered into the formula to calculate the sample size as 1946. Considering the potential rate of loss to follow-up, the sample size for the investigation was increased by 10% based on the calculated sample size, which was then calculated to be 2140.
Participants were recruited from rural areas by multistage sampling. First, 16 cities in Shandong Province, China, were divided into 3 groups according to social, cultural, and economic conditions. Second, 2 cities were randomly selected from each group as the sample cities. Jinan (the first group), Qingdao (the first group), Weifang (the second group), Linyi (the second group), Dezhou (the third group), and Jining (the third group) were selected as the sample cities. Third, 1 county was randomly selected as the sample county in each city. Huaiyin (in Jinan city), Laixi (in Qingdao city), Anqiu (in Weifang city), Pingyi (in Linyi city), Qihe (in Dezhou city), and Qufu (in Jining city) were selected as the sample counties. Fourth, 1 town was randomly selected as the sample town in each county. Yuqing Hu (in Huaiyin County), Wangcheng (in Laixi County), Jingzhi (in Anqiu County), Fengyang (in Pingyi County), Zhaoguan (in Qihe County), and Xiaoxue (in Qufu County) were selected as the sample towns. Fifth, cluster sampling was conducted separately in each town to randomly sample villages, and the rural residents who met the inclusion criteria in the sample villages were included in the sample. Two villages in each town were selected as the sample villages. After cluster sampling, 2283 rural residents were included in this study. This study was approved by the Ethics Review Committee of Shandong Second Medical University (No. 2023YX-138), and all participants voluntarily provided informed consents.
The cognitive questionnaire regarding knowledge about infectious disease prevention and control (the IDPC knowledge cognitive questionnaire) was used to collect the following data. A brief description of the questionnaire was as follows: The questionnaire was developed based on the National Residents’ Health Literacy Monitoring Questionnaire developed in China. IDSHL is 1 of the 6 categories of health literacy on the National Residents’ Health Literacy Monitoring Questionnaire. All questions in the questionnaire were rigorously discussed and evaluated by epidemiologists, statisticians, and sociologists. All participants independently completed the questionnaire. The questionnaire included participants’ sociodemographic information, cognitive abilities regarding IDPC knowledge, and the participants’ demand for IDPC knowledge. Sociodemographic information mainly included participants’ age, region, gender, education, occupation, annual family income, “whether IDPC knowledge can be acquired?,” “whether IDPC knowledge can be acquired conveniently?,” “whether to use smartphones?,” and methods to acquire IDPC knowledge, etc. Cognitive ability regarding IDPC knowledge consisted of 47 items and 2 dimensions: (1) cognition regarding IDPC common knowledge (13 items) was measured by answering each question correctly. The total score ranged from 0 to 13. The higher scores represented a higher level of IDPC common knowledge. (2) Cognition regarding IDPC knowledge about air-borne (6 items), water-borne (3 items), food-borne (3 items), contact (5 items), arthropod-borne (4 items), soil-borne (4 items), iatrogenic (5 items), and vertical transmission (4 items) was designed to measure the level of knowledge of infectious disease transmission routes, and the total scores for this dimension ranged from 0 to 34. Besides, the participants’ demand for IDPC knowledge (2 items) was utilized to evaluate the participants’ demand rate for IDPC knowledge. In brief, if a participant correctly answered 1 question about their cognitive abilities regarding IDPC knowledge, he or she received 1 point. The total score of each participant was determined by the number of questions that the participant correctly answered. If a participant’s score was equal to or more than 80% of the total score of all questions, it meant that this participant possessed adequate IDSHL and he or she would be included in the case group. Otherwise, it meant that this participant did not have adequate IDSHL and would be embraced in the control group. The questionnaire used in this study had acceptable levels of reliability and validity. The internal consistency reliability test showed that the Cronbach alpha coefficient was 0.73. The construct validity test showed that the Kaiser–Meyer–Olkin value was 0.97, and Bartlett test of sphericity produced a result of χ 2 = 171,567.24 ( P < .001).
The database was established using Epidata version 3.1 software (The Epidata Association, Odense, Denmark). Continuous data were expressed as the mean ± standard deviation. Categorical data expressed by frequency . If the variance between the case and control groups was equal, Student t tests were used to examine the difference between the means of continuous variables; otherwise, Wilcoxon rank sum tests were used. Chi-square analyses were performed to compare the distribution of the categorical variables between the case and control groups. Stata version 15.0 statistical software (StataCorp LLC, College Station, TX) was used for statistical analyses. All reported probabilities ( P values) were two-sided, and statistical significance was defined as P < .05.
There were some measures to control possible bias. Firstly, the size of the investigating sample was increased by 10% of the calculated sample size to control the follow-up bias. Secondly, investigators were trained and demanded to investigate participants with the same standard in order to control investigation bias. Thirdly, the operation about data input was carried out by 2 people to control input errors.
3.1. Analysis of demographic characteristics A total of 2283 rural residents in Shandong Province, China, were eligible to be included in this study, and 2283 valid questionnaires were obtained. The valid response rate for questionnaires was 100%. The analyses in this study were based on the data extracted from these 2283 questionnaires. The results of the demographic characteristics analysis are shown in Table . Among the 2283 participants, 31.80% possessed adequate IDSHL, and the average age of participants with adequate IDSHL was 42.77 ± 13.00. Only 29.37% of male participants, 20.75% of participants with primary school or below, 22.62% of participants engaged in agriculture, and 16.36% of participants with annual family income >10,000 RMB had adequate IDSHL levels. Age ( P < .001), region ( P < .001), sex ( P = .02), education ( P < .001), occupation ( P < .001), and annual family income ( P < .001) all had statistically significant associations with IDSHL level. The possession rate of participants with adequate IDSHL increased following the improvement of education levels and annual family income, from 20.75% to 58.82% and 16.36% to 40.89%, respectively. Additionally, Table shows that “whether IDPC knowledge can be acquired conveniently?” ( P < .001), “whether to use smartphones” ( P < .001), “whether to browse WeChat on smartphones” ( P < .001), “whether to browse apps on smartphones except WeChat” ( P < .001), and “whether to accept WeChat and apps to publicize IDPC knowledge?” ( P < .001) all revealed statistically significant associations with IDSHL level. The participants’ self-evaluation of IDPC knowledge showed that more than half of participants had a good grasp of IDPC knowledge. And participants’ demand rate for IDPC knowledge was as high as over 95%. 3.2. Comparisons about the proportion of participants with adequate IDSHL among rural residents who did or did not adopt a specific method to acquire IDPC knowledge Table indicates that whether to adopt specific methods to acquire IDPC knowledge had significant associations with IDSHL ( P < .05). The proportion of participants with adequate IDSHL among rural residents who adopted a specific method to acquire IDPC knowledge was significantly higher than that among rural residents who did not adopt a specific method to acquire IDPC knowledge. 3.3. Adoption percentages of rural residents to acquire IDPC knowledge by specific methods Figure shows the adoption percentages of participants to acquire IDPC knowledge by specific methods. The adoption percentages of practical methods for participants to acquire IDPC knowledge were significantly different (χ 2 = 3693.57, P < .001). The first 3 practical methods adopted by participants to acquire IDPC knowledge were television (79.97%), WeChat on smartphones (63.70%), and propaganda of infectious disease prevention and control (41.79%). The adoption proportions of expected methods for participants to acquire IDPC knowledge were significantly different (χ 2 = 3846.86, P < .001). The top 3 expected methods for participants to acquire IDPC knowledge in sequence were television (70.75%), WeChat on smartphones (57.60%), and propaganda of infectious disease prevention and control (36.22%). The adoption percentages of the most expected methods for participants to acquire IDPC knowledge were found to be significantly different (χ 2 = 3713.92, P < .001). The first 3 most expected methods for participants to acquire IDPC knowledge sequentially were television (33.68%), WeChat on smartphones (32.41%), and apps on smartphones except WeChat (13.27%). 3.4. Comparisons about whether demographic characteristics had influences on participants to adopt specific methods to acquire IDPC knowledge Table displays that age, gender, education, occupation, and annual family income all exhibited statistically significant associations with methods to acquire IDPC knowledge ( P < .05). Participants with television to acquire IDPC knowledge were of an advanced age compared to those without television to acquire IDPC knowledge (t = 3.28, P = .001). Compared with men, there were more proportions of women who adopted specific methods to acquire IDPC knowledge (books: χ 2 = 6.32, P = .012; WeChat on smartphones: χ 2 = 7.35, P = .007; propaganda of infectious disease prevention and control: χ 2 = 13.79, P < .001). There were higher proportions of participants with junior high school education or above who adopted WeChat on smartphones to acquire IDPC knowledge than those who did not adopt this method to get IDPC knowledge (χ 2 = 102.09, P < .001). Additionally, Table shows that among different occupation levels, the proportion of participants with specific methods to acquire IDPC knowledge was significantly greater than that of those without specific methods to acquire IDPC knowledge (television: χ 2 = 25.56, P < .001; WeChat on smartphones: χ 2 = 101.08, P < .001). There were higher proportions of participants who adopted specific methods to acquire IDPC knowledge with the increase of participants’ annual family income levels from >10,000 RMB to <9 10,000 RMB (computer: χ 2 = 40.61, P < .001; WeChat on smartphones: χ 2 =84.00, P < .001; apps on smartphones except WeChat: χ 2 = 59.68, P < .001).
A total of 2283 rural residents in Shandong Province, China, were eligible to be included in this study, and 2283 valid questionnaires were obtained. The valid response rate for questionnaires was 100%. The analyses in this study were based on the data extracted from these 2283 questionnaires. The results of the demographic characteristics analysis are shown in Table . Among the 2283 participants, 31.80% possessed adequate IDSHL, and the average age of participants with adequate IDSHL was 42.77 ± 13.00. Only 29.37% of male participants, 20.75% of participants with primary school or below, 22.62% of participants engaged in agriculture, and 16.36% of participants with annual family income >10,000 RMB had adequate IDSHL levels. Age ( P < .001), region ( P < .001), sex ( P = .02), education ( P < .001), occupation ( P < .001), and annual family income ( P < .001) all had statistically significant associations with IDSHL level. The possession rate of participants with adequate IDSHL increased following the improvement of education levels and annual family income, from 20.75% to 58.82% and 16.36% to 40.89%, respectively. Additionally, Table shows that “whether IDPC knowledge can be acquired conveniently?” ( P < .001), “whether to use smartphones” ( P < .001), “whether to browse WeChat on smartphones” ( P < .001), “whether to browse apps on smartphones except WeChat” ( P < .001), and “whether to accept WeChat and apps to publicize IDPC knowledge?” ( P < .001) all revealed statistically significant associations with IDSHL level. The participants’ self-evaluation of IDPC knowledge showed that more than half of participants had a good grasp of IDPC knowledge. And participants’ demand rate for IDPC knowledge was as high as over 95%.
Table indicates that whether to adopt specific methods to acquire IDPC knowledge had significant associations with IDSHL ( P < .05). The proportion of participants with adequate IDSHL among rural residents who adopted a specific method to acquire IDPC knowledge was significantly higher than that among rural residents who did not adopt a specific method to acquire IDPC knowledge.
Figure shows the adoption percentages of participants to acquire IDPC knowledge by specific methods. The adoption percentages of practical methods for participants to acquire IDPC knowledge were significantly different (χ 2 = 3693.57, P < .001). The first 3 practical methods adopted by participants to acquire IDPC knowledge were television (79.97%), WeChat on smartphones (63.70%), and propaganda of infectious disease prevention and control (41.79%). The adoption proportions of expected methods for participants to acquire IDPC knowledge were significantly different (χ 2 = 3846.86, P < .001). The top 3 expected methods for participants to acquire IDPC knowledge in sequence were television (70.75%), WeChat on smartphones (57.60%), and propaganda of infectious disease prevention and control (36.22%). The adoption percentages of the most expected methods for participants to acquire IDPC knowledge were found to be significantly different (χ 2 = 3713.92, P < .001). The first 3 most expected methods for participants to acquire IDPC knowledge sequentially were television (33.68%), WeChat on smartphones (32.41%), and apps on smartphones except WeChat (13.27%).
Table displays that age, gender, education, occupation, and annual family income all exhibited statistically significant associations with methods to acquire IDPC knowledge ( P < .05). Participants with television to acquire IDPC knowledge were of an advanced age compared to those without television to acquire IDPC knowledge (t = 3.28, P = .001). Compared with men, there were more proportions of women who adopted specific methods to acquire IDPC knowledge (books: χ 2 = 6.32, P = .012; WeChat on smartphones: χ 2 = 7.35, P = .007; propaganda of infectious disease prevention and control: χ 2 = 13.79, P < .001). There were higher proportions of participants with junior high school education or above who adopted WeChat on smartphones to acquire IDPC knowledge than those who did not adopt this method to get IDPC knowledge (χ 2 = 102.09, P < .001). Additionally, Table shows that among different occupation levels, the proportion of participants with specific methods to acquire IDPC knowledge was significantly greater than that of those without specific methods to acquire IDPC knowledge (television: χ 2 = 25.56, P < .001; WeChat on smartphones: χ 2 = 101.08, P < .001). There were higher proportions of participants who adopted specific methods to acquire IDPC knowledge with the increase of participants’ annual family income levels from >10,000 RMB to <9 10,000 RMB (computer: χ 2 = 40.61, P < .001; WeChat on smartphones: χ 2 =84.00, P < .001; apps on smartphones except WeChat: χ 2 = 59.68, P < .001).
The findings of this study revealed that only 31.80% of rural residents had adequate IDSHL in Shandong Province, China. Nearly 95.80% of rural residents expressed a high demand for IDPC knowledge. Different methods of health education included in this study were helpful in enhancing their IDSHL levels. Additionally, some demographic features influenced individuals to adopt specific methods to acquire IDPC knowledge. The result of the study found that rural residents’ IDSHL level needed to be emphasized and improved. In this study, rural residents’ IDSHL level (31.80%) was higher than the IDSHL levels among residents reported by previous studies in China (i.e., 27.60% of national residents in 2021, 19.04% of residents in Fujian Province in 2021, 20.58% of rural residents in Anhui Province in 2019, 29.62% of urban residents and 18.29% of rural residents in Tai’an city in Shandong Province in 2020, and17.47% of residents in Qingdao city in Shandong Province in 2019. ). However, the proportion of IDSHL (31.80%) was lower compared with 33.13% of rural residents in Zhejiang Province in 2020 and 36.98% of residents in Shanghai City in 2021. There were some possible reasons for the inconsistent results. First, more attention has been paid to health education than before. It could further encourage residents to comprehensively grasp knowledge about infectious diseases, to keep their living environment clean and ventilated, and to cultivate scientific diet and exercise habits so as to take preventive and control measures. The outbreak of COVID-19 strengthened the government’s implementation of health education for residents, which was conducive to the popularization of IDPC knowledge. Besides, the promulgation of relevant policies named Healthy China Initiative (2019–2030) and the planning outline of “Healthy Shandong 2030” was also a major reason for why rural residents’ IDSHL level was higher than before. Second, local economic income, education level, medical resources, and other factors were also the main reasons that caused differences in IDSHL levels in different regions of China. Generally speaking, areas with a developed economy, rich education, and medical resources have a higher IDSHL level. This may be the reason why the proportion of adequate IDSHL among rural residents in Shandong Province was higher than that in Fujian Province and Anhui Province. Third, as the eastern coastal area, the IDSHL level (31.80%) of rural residents in Shandong Province in this study was lower than that in Zhejiang Province (33.13%) and Shanghai City (36.98%). The main reason may be related to the lack of attention paid by government departments to the promotion of health knowledge and awareness of infectious disease prevention and control among rural residents. According to the results of this research, IDSHL level was associated with some demographic characteristics, including age, gender, education, occupation, and family income. These findings were consistent with the previous studies. In this study, lower IDSHL levels were influenced by elder groups, males, low education levels, engaged agriculture, and lower family incomes. The cognitive ability, comprehension, and remembering of elder groups would be diminished as age increased, which led to a lower IDSHL level. Females were more likely to seek, comprehend, and apply health-related information to evaluate their health problems than males. Therefore, females tend to have better IDSHL than males. However, there were different results from previous studies in the association between the gender variable and IDSHL. The difference may be related to the diversity of culture and social background of regions or countries and different goal groups in studies. A study was conducted in Khalkhal, which demonstrated that low levels of education and family income hindered achieving e-health literacy. E-health literacy is an effective approach to enhancing health-related information seeking. Individuals with low education levels, low family incomes, and those engaged in agriculture were less likely to acquire IDPC knowledge through electronic information resources. Moreover, rural residents’ demand rate for IDPC knowledge was 95.80% in this study, which was similar to the previous results. The phenomenon embodied the fact that residents were eager to acquire relevant IDPC knowledge. Thus, effective popularization and publicity of IDPC knowledge should be developed among these high-risk residents to promote the cultivation of preventive behavior. There was a statistically significant association between methods to acquire IDPC knowledge and IDSHL. In this study, a high level of IDSHL was affected by the methods used to actively seek IDPC knowledge. This finding was consistent with the previous studies. A study on e-health literacy stressed that electronic sources played a key role in acquiring infectious disease information during the coronavirus pandemic. In the era of the Internet, an increasing number of institutions, groups, and individuals are more inclined to publish, disseminate, and learn health knowledge on online platforms. According to a recent cross-sectional study, in the United States, nearly 90% of adults used the Internet to look for health or medical information. In this study, approximately two-thirds of rural residents adopted WeChat on smartphones to acquire IDPC knowledge. The results of these studies demonstrated that the Internet gradually penetrated into the daily lives of residents. However, television was still a premier choice among residents in this study, which was consistent with previous study results. It may have a bearing on the high television penetration rate and the relative habit of rural residents to watch television in China. Higher levels of health-related information-seeking behavior were associated with higher health literacy. Thus, effective methods to seek IDPC knowledge, including traditional methods and Internet publicity platforms, should be adopted to improve residents’ IDSHL levels. Demographic characteristics including age, gender, education, occupation, and family income had statistically significant associations with methods to acquire IDPC knowledge. The young population, female groups, high education levels, good occupational status, and high family incomes were more inclined to use electronic devices to acquire IDPC knowledge. These results were similar to the findings of other studies. Although a growing number of middle-aged and elderly adults are using the Internet more than in the past, they are still less likely than younger adults to use the Internet to actively acquire IDPC knowledge in this study. A study conducted by Link et al in Germany demonstrated that individuals having current health problems and possessing information-seeking skills were more likely to utilize health information platforms to search for health information. A previous study indicated that individuals in low socioeconomic status groups were more likely to have unstable work conditions and incomes, which may further lead to poorer health outcomes, a greater risk of one’s virus exposure, and a lack of methods to acquire IDPC knowledge. Therefore, in order to increase residents’ IDSHL level, more targeted IDSHL health education in the future should be conducted according to different demographic factors and individuals with low demographic status. There were some strengths in this study. First, a study on the association between sociodemographic factors and IDSHL was beneficial to realize different groups’ IDSHL levels. To overcome the weakness in self-health protection among rural vulnerable groups, it was necessary to address all these factors. Second, the relationship between health education methods and IDSHL has been evaluated, which could be a guideline for health education providers to design targeted strategies to improve residents’ IDSHL levels. Noticeably, the results of this study could assist local governments in formulating policies to enhance the response of rural residents to crises caused by infectious diseases. There were also some potential limitations in this study that needed to be considered. First, the presence of bias, such as recall bias, may distort the results as this was a cross-sectional study. Second, the analysis in this study was based on individuals aged 18 to 71 years from rural areas in Shandong Province, China. It may limit the extrapolation of our findings to groups made up of different age groups. Third, although the questionnaire used in this study had acceptable levels of reliability and validity, it was not exactly the same as that used in previous studies, which may affect the comparison among results.
The rural residents’ adequate IDSHL level in Shandong Province, China, needs to be improved. More targeted health education measures are needed for middle-aged and elderly groups, residents with low education levels, individuals engaged in agriculture, and low-income populations. The combination of traditional methods and Internet publicity platforms should take greater responsibility for IDSHL health education among the rural population. In the future, more health education regarding IDPC knowledge should be implemented by different publicity platforms to heighten rural residents’ IDSHL levels.
We thank all authors for their contributions to the article.
Conceptualization: Xueli Zhang, Qiang Wang. Data curation: Shuyu Chen, Bin Wang. Formal analysis: Shuyu Chen, Bin Wang, Xin Wang, Keqing Shi, Wenhui Cui, Yuwei Liu Funding acquisition: Xueli Zhang, Qiang Wang. Investigation: Xin Wang, Keqing Shi, Wenhui Cui, Yuwei Liu. Methodology: Shuyu Chen, Bin Wang. Project administration: Xueli Zhang, Qiang Wang. Resources: Xueli Zhang, Qiang Wang. Software: Shuyu Chen, Bin Wang. Supervision: Xueli Zhang, Qiang Wang. Validation: Shuyu Chen. Writing – original draft: Shuyu Chen, Bin Wang. Writing – review & editing: Shuyu Chen, Bin Wang, Xueli Zhang, Qiang Wang.
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Piezo1 deletion mitigates diabetic cardiomyopathy by maintaining mitochondrial dynamics via ERK/Drp1 pathway | 1ec0275b-7869-4d22-a7f9-3b4e825c1306 | 11927149 | Cardiovascular System[mh] | The incidence of both type 1 and type 2 diabetes mellitus (T1DM and T2DM) continues to rise globally. DM complications, including neuropathy, cardiovascular changes and nephropathy, are major causes of mortality and morbidity among diabetic patients, placing a substantial burden on global public health. Of particular concern is diabetic cardiomyopathy (DCM), characterized by a series of abnormalities in myocardial structure and function due to insulin resistance, inflammation, altered lipid metabolism, and mitochondrial impairment. These manifest as myocardial hypertrophy, interstitial fibrosis, and diastolic dysfunction . Thus, there is an urgent need to identify novel therapeutic targets and deepen our understanding of the pathological and molecular mechanisms underlying DCM. Piezo1, identified as a mechanosensitive ion channel within the past decade , plays a vital role in a multitude of physiological processes, such as innate immunity , blood pressure regulation , stem cell aging , cell fate determination and cardiovascular homeostasis [ – ]. The Piezo1 protein is abundantly expressed in myocardial tissue, where it converts mechanical stress into Ca 2+ signaling . Hydrophobic Yoda1 can directly bind to Piezo1, resulting in Piezo1 activation; but non-specific blockers including spider toxin GsMTx4 and ruthenium red can block Piezo1 activation . Previous study has demonstrated a significant increase in Piezo1 levels in adult mice subject to pressure overload-induced cardiac hypertrophy . Moreover, cardiac-specific deletion of Piezo1 inhibited the activation of the Ca 2+ /calmodulin-dependent protein kinase II (CaMKII), thereby preventing a decline in cardiac function. Notably, Piezo1 expression is elevated in islets from humans and mice with T2DM, as well, impaired glucose tolerance and reduced insulin secretion present in β-cell-specific Piezo1 -knockout mice . Hence, investigating the role of Piezo1 in cardiac dysfunction associated with DCM is imperative in future study. Mitochondrial dysfunction exerts a crucial role in the pathogenesis of DCM . Mitochondria, the double-membrane organelles, produce adenosine triphosphate (ATP) using glucose and oxygen in cardiomyocyte. Emerging evidence suggests that hyperglycemia and insulin resistance disrupt mitochondrial dynamics by promoting mitochondrial fission and inhibiting mitochondrial fusion . Mitochondrial fusion is modulated by mitofusin-1 (Mfn1), mitofusin-2 (Mfn2), and optic atrophy 1 (Opa-1), while fission is primarily controlled by mitochondrial fission protein 1 (Fis1), dynamin-related protein 1 (Drp1) and mitochondrial fission factor (Mff) . Excessive mitochondrial fission in diabetic hearts increases mitochondrial numbers while reducing their size, leading to excessive reactive oxygen species (ROS) production and contributing to mitochondrial dysfunction . In this study, we demonstrated the cardioprotective effect of Piezo1 in DCM by improving diastolic and systolic function, and ameliorating cardiac fibrosis. Our findings indicate that increased Piezo1 expression leads to calcium influx in cardiomyocytes, subsequently elevating calpain activity and activating extracellular signal-regulated kinase (ERK1/2) signaling. These result in Drp1 phosphorylation, which promotes mitochondrial fission and mitochondrial dysfunction. Cardiac-specific deletion of Piezo1 ameliorates cardiac remodeling and mitochondrial dysfunction, uncovering a Piezo1-regulated mitochondrial homeostasis mechanism linked to ERK/Drp1 axis in diabetic hearts, thus highlighting Piezo1 as a therapeutic potential target in DCM treatment.
Animal studies and ethics Conditional cardiac-specific Piezo1 knockout mice ( Piezo1 ∆Myh6 ) were created by crossing Piezo1 fl/fl mice (Piezo1tm2.1Apat/J) from Jackson Laboratory with Myh6-Cre transgenic mice (A1cf Tg(Myh6−cre/Esr1*)1Jmk / J). Additionally, mice expressing a C-terminal fusion of Piezo1 with a tandem-dimer Tomato sequence ( dtT ; Piezo1 dtT/dtT mice) were also sourced from Jackson Laboratory. All animal experiments were adhered to the guidelines of the Care and Use of Laboratory Animals and were permitted by the Animal Care and Use Committee of Shandong University of Traditional Chinese Medicine (approval number: SDUTCM20230215211). Mice was genotyped using PCR with genomic DNA isolated from mouse tails with the following primers: Myh6-cre 5’-ATGACAGACAGATCCCTCCTATCTCC-3’ (forward); Myh6-cre 5’-CTCATCACTCGTTGCATCATCGAC-3’ (reverse); mouse Tomato (mutant) 5’- CACCTGTTCCTGTACGGCATGGAC − 3’, Tomato (common) 5’- GTCCCTTTGACAGCAGCATC − 3’, (wildtype) 5’ - ACGCCAAGCTCATCTTCCT − 3’. Experimental animal models All mice were maintained under specific-pathogen-free conditions (12 h day-night cycle) at appropriate temperature and humidity, with unrestricted access to sterilized water and food. T1DM mice The experimental design flowchart was illustrated in Fig. A. To examine the expression level of Piezo1 in DCM, twenty 8-week old male Piezo1 dtT/dtT mice were utilized to construct diabetic models via intraperitoneal injections of streptozotocin (STZ, dissolved in citrate buffer, 0.1 mM, pH = 4.5, MCE, USA) at a dosage of 55 mg/kg daily for 5 consecutive days. Mice in the control group received intraperitoneal injection of citrate buffer. After 2 weeks, T1DM mice were confirmed in mice exhibiting fasting blood glucose (FBG) ≥ 16.7 mM/L for two consecutive days. All mice were subsequently maintained for an additional 14 weeks prior to sample collection. To further investigate the role of Piezo1 in DCM, C57BL/6J mice (Vital River Laboratory Animal Technology Co., Ltd, China) were also used to establish T1DM (Fig. A). Twelve weeks after DCM induction, the Piezo1 agonist Yoda1 (MCE, USA) was administrated to diabetic mice via intraperitoneal injection (80 µg/kg, once daily for 4 weeks) . HFD/STZ induced diabetic mice To estimate the levels of Piezo1 in T2DM and assess the impact of Piezo1 knockout on cardiac function in diabetic context, Piezo1 dtT/dtT , Piezo1 ∆Myh6 and Piezo1 fl/fl mice aged 3 weeks were subjected to construct T2DM model through high-fat diet (HFD, 60 kcal% fat; Research Diets, Inc, USA; Supplementary file 3: Table ) for 6 weeks followed by intraperitoneal STZ injections at a dose of 35 mg/kg for three consecutive days. All mice were randomly divided into six groups ( n = 10 per group): Piezo1 dtT/dtT mice fed chow diet group ( Piezo1 dtT/dtT control group), Piezo1 dtT/dtT mice fed HFD group ( Piezo1 dtT/dtT T2DM group), Piezo1 fl/fl fed chow diet group ( Piezo1 fl/fl + control), Piezo1 fl/fl fed HFD group ( Piezo1 fl/fl + HFD), Piezo1 ∆Myh6 fed chow diet group ( Piezo1 ∆Myh6 + control), Piezo1 ∆Myh6 fed HFD group ( Piezo1 ∆Myh6 + HFD). Mice with random blood glucose ≥ 16.7 mM were selected for subsequent studies and continued fed with HFD diet for additional 16 weeks. Intraperitoneal glucose tolerance test (IPGTT) At the end of treatment, IPGTT was performed in all mice after overnight fasting. All T2DM mice were received a 2 mg/g intraperitoneal glucose injection, with blood glucose levels monitored pre-injection (0 min) as well as at 30, 60, 90 and 120 min post-injection. Echocardiography Following anesthesia with 2% inhaled isoflurane, transthoracic echocardiography was conducted at the end of the experiment using a VINNO ultrasound diagnostic instrument (VINNO, Suzhou, China). Parasternal long-axis M-mode images were collected and parameters recorded to assess systolic and diastolic cardiac function, including left ventricular (LV) ejection fraction (EF%), LV shortening fraction (FS%), LV internal dimension at diastole (LVID; d), LV internal dimension at systole (LVID; s), LV anterior wall thickness at diastole (LVAW; d), LV anterior wall thickness at systole (LVAW; s), LV posterior wall thickness at diastole (LVPW; d) and LV posterior wall thickness at systole (LVPW; s). Histological analysis Heart weight (HW) and tibial length (TL) of all mice were measured to calculate the HW/TL ratio. Following fixation in 4% paraformaldehyde, heart tissues of mice were embedded in paraffin and sectioned to a thickness of 4 μm. Deparaffinized and rehydrated sections were stained with hematoxylin and eosin (H&E, Beyotime Biotech, China), Masson’s trichrome (Solarbio, China) and Alexa Fluor 488 labeled wheat germ agglutinin (WGA, Thermo Fisher, USA) staining to assess collagen content and myocardial atrophy according to the manufacturer’s instruction. Immunofluorescence (IF) staining of tissue was conducted to detect Piezo1 expression and collagen levels in cardiomyocytes. Sections were deparaffinized and rehydrated before being blocked with 5% goat serum (Solarbio, China) for 30 min, then incubated with primary antibodies RFP, collagen I and collagen III at 4ºC overnight. Subsequent treatments included incubation with secondary antibodies in the following morning, and sections stained with RFP were then incubated with α-actinin antibody to label myocardical tissue. Cells seeded on glass coverslips were fixed in 4% paraformaldehyde for 15 min, blocked with 5% goat serum for 30 min and then incubated with primary antibodies against Piezo1, Tomm20, p-Drp1 (ser616) and OPA1 at 4 ºC overnight. Images were acquired with a fluorescent microscope (BZ-X710, KEYENCE, Japan). Cell culture and treatment The embryonic rat heart-derived cardiomyocyte-like H9C2 cell line was obtained from the Wuhan Servicebio Technology Co., Ltd. and primary neonatal mouse cardiomyocytes (NMCMs) were isolated from neonatal mice aged 1–3 days. Mouse hearts were obtained and ventricular sections were diced into small pieces, followed by digestion for 8 h at 4 ºC with 0.125% trypsin and then for 30 min at 37 ºC with 0.5% collagenase II. Cell suspension was obtained via filtering tissue fragments with 40-µm cell strainers (Falcon, USA). Purified cardiomyocytes were collected and culture medium was replaced 24 h later . All cells were cultured in Dulbecco’s modified Eagle medium (DMEM) medium (Gibco, Germany) which contained 1 g/L of D-glucose and supplemented with 100 U/ml of penicillin and streptomycin, and 10% fetal bovine serum. In the first part of the in vitro study, to estimate the effect of Piezo1 inhibition on mitochondrial function, after plated in six-well plates or glass coverslips and then starved for 12 h, H9C2 cells were treated with 35 mM D-glucose (Sigma, USA) with 500 µM palmitate (Sigma, USA) in the presence or absence of GsMTx4 (10 µM, MCE, USA) for additional 48 h as HG + PA or GsMTx4 groups, identical concentrations of mannitol as normal glucose (NG) group. In the subsequent phase of the in vitro study, to investigate the effect of Piezo1 deficiency on mitochondrial function, the primary NMCMs were treated with 35 mM D-glucose and 500 µM palmitate or NG for 48 h. Quantitative real-time polymerase chain reaction (RT-PCR) Total RNA was extracted from cardiomyocytes or heart tissues using TRIzol Reagent (Invitrogen, USA) following the manufacturer’s instructions. Total RNA was reversed into cDNA using ReverTra Ace qPCR RT Kit (Takara, Japan) and quantitative RT-PCR was conducted using SYBR Green Realtime PCR Master Mix (Takara, Japan) on a LightCycler 480 instrument (Roche, Switzerland). β-actin was used as control, and relative gene expression was calculated through the 2 −ΔΔCt method. All samples were examined in triplicates. Primer sequences for RT-PCR were listed in Supplementary file 3: Table . Transmission electron microscopy (TEM) Mitochondrial ultrastructure in myocardial samples was examined by fixing mouse heart tissues with glutaraldehyde, sectioning, and staining with 2% uranyl acetate and Reynolds lead citrate. Sections were observed under an 80-kV transmission electron microscope (JEM-1230, JOEL, Japan). Mitochondrial size was measured with Image J software. Measurement of calpain activity The cleavage of the calpain substrate was measured using a calpain activity assay kit (Abcam, UK) as described in a previous study . Tissue or cell proteins were extracted and concentration was measured by the BCA protein assay kit, followed by sample dilution in 85 µL extraction buffer. Calpain activity was examined with calpain substrate and reaction buffer. Then, absorbance was measured at 400 nm excitation and 505 nm emission wavelengths. Mitochondrial function detection To measure mitochondrial membrane potential (MMP), cultured cells were determined with a JC-10 kit (Solarbio, China) and mitochondrial ROS was estimated with MitoSox Red superoxide indicator (Cell Signaling Technology, USA). For ROS detection, frozen tissue sections or cultured cells were stained with 2’,7’-Dichlorofluorescin diacetate (DCFH-DA) or dihydroethidium (DHE) (Beyotime, China). Mitochondrial oxygen consumption rate (OCR) was measured using a Seahorse XF24 analyzer (Agilent, USA) according to protocols. H9C2 cells were seeded at 40,000 cells/well on 24-well XFe24 cell culture microplates. OCR value was measured using the Seahorse XF Cell Mitochondrial Stress Test kit. Intracellular Ca 2+ entry measurement The intracellular Ca 2+ entry was measured as described in the previous study . Briefly, cells were incubated in a transparent 96-well plate for 3 days, and then treated with 2-µM Fura-2-AM (Thermo Fisher Scientific, USA) for 75 min. Intracellular Ca 2+ signal changes were estimated through the proportion of 340 nm and 380 nm wavelengths. Western blot analysis Heart tissues or cultured cells were lysed with RIPA buffer supplemented with phosphatase and protease inhibitors (Beyotime, China). Protein extractions were separated by 10-12% SDS-PAGE and then transferred to PVDF membranes (Millipore, USA). After blocking with 5% skim milk or BSA for 1 h at room temperature, the membranes were incubated with primary antibodies (all the primary antibodies were shown in Supplementary file 3: Table ) at 4 ºC overnight. Next day, the membranes were washed and incubated with peroxidase-conjugated anti-rabbit IgG (1:5000 dilution, ZSGB-BIO, Beijing, China) and anti-mouse-IgG (1:5000 dilution, ZSGB-BIO, Beijing, China) for 1 h and bands were detected with the ECL detection kit (Epizyme, China). GAPDH or β-actin was used as control indicated in figures. Protein quantification was analyzed with Image J software. Biochemical analysis Serum lipid levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were measured using an automatic biochemical analyzer (URIT-8026, China). Data collection and RNA-seq analysis RNA-seq data (GSE241166) from heart tissues of DCM and control mice, generated using the Illumina NovaSeq 6000 platform, was obtained from the Gene Expression Omnibus (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/ ). The dataset included heart samples from three DCM mice (T2DM, induced by HFD and STZ) and three normal mice. To identify differentially expressed genes associated with ion channels, RNA-seq analysis was conducted with a cutoff criterion of fold change more than 1.5 or less than 1/1.5 combined with P < 0.05. Statistical analysis All data were presented as mean ± SEM. For comparisons between two groups, unpaired Student’s t -test was conducted and for more than two groups, one-way ANOVA followed by Turkey’s post hoc test was performed. All statistical tests were conducted using GraphPad Prism software. P value less than 0.05 was considered as statistically significant.
Conditional cardiac-specific Piezo1 knockout mice ( Piezo1 ∆Myh6 ) were created by crossing Piezo1 fl/fl mice (Piezo1tm2.1Apat/J) from Jackson Laboratory with Myh6-Cre transgenic mice (A1cf Tg(Myh6−cre/Esr1*)1Jmk / J). Additionally, mice expressing a C-terminal fusion of Piezo1 with a tandem-dimer Tomato sequence ( dtT ; Piezo1 dtT/dtT mice) were also sourced from Jackson Laboratory. All animal experiments were adhered to the guidelines of the Care and Use of Laboratory Animals and were permitted by the Animal Care and Use Committee of Shandong University of Traditional Chinese Medicine (approval number: SDUTCM20230215211). Mice was genotyped using PCR with genomic DNA isolated from mouse tails with the following primers: Myh6-cre 5’-ATGACAGACAGATCCCTCCTATCTCC-3’ (forward); Myh6-cre 5’-CTCATCACTCGTTGCATCATCGAC-3’ (reverse); mouse Tomato (mutant) 5’- CACCTGTTCCTGTACGGCATGGAC − 3’, Tomato (common) 5’- GTCCCTTTGACAGCAGCATC − 3’, (wildtype) 5’ - ACGCCAAGCTCATCTTCCT − 3’.
All mice were maintained under specific-pathogen-free conditions (12 h day-night cycle) at appropriate temperature and humidity, with unrestricted access to sterilized water and food. T1DM mice The experimental design flowchart was illustrated in Fig. A. To examine the expression level of Piezo1 in DCM, twenty 8-week old male Piezo1 dtT/dtT mice were utilized to construct diabetic models via intraperitoneal injections of streptozotocin (STZ, dissolved in citrate buffer, 0.1 mM, pH = 4.5, MCE, USA) at a dosage of 55 mg/kg daily for 5 consecutive days. Mice in the control group received intraperitoneal injection of citrate buffer. After 2 weeks, T1DM mice were confirmed in mice exhibiting fasting blood glucose (FBG) ≥ 16.7 mM/L for two consecutive days. All mice were subsequently maintained for an additional 14 weeks prior to sample collection. To further investigate the role of Piezo1 in DCM, C57BL/6J mice (Vital River Laboratory Animal Technology Co., Ltd, China) were also used to establish T1DM (Fig. A). Twelve weeks after DCM induction, the Piezo1 agonist Yoda1 (MCE, USA) was administrated to diabetic mice via intraperitoneal injection (80 µg/kg, once daily for 4 weeks) . HFD/STZ induced diabetic mice To estimate the levels of Piezo1 in T2DM and assess the impact of Piezo1 knockout on cardiac function in diabetic context, Piezo1 dtT/dtT , Piezo1 ∆Myh6 and Piezo1 fl/fl mice aged 3 weeks were subjected to construct T2DM model through high-fat diet (HFD, 60 kcal% fat; Research Diets, Inc, USA; Supplementary file 3: Table ) for 6 weeks followed by intraperitoneal STZ injections at a dose of 35 mg/kg for three consecutive days. All mice were randomly divided into six groups ( n = 10 per group): Piezo1 dtT/dtT mice fed chow diet group ( Piezo1 dtT/dtT control group), Piezo1 dtT/dtT mice fed HFD group ( Piezo1 dtT/dtT T2DM group), Piezo1 fl/fl fed chow diet group ( Piezo1 fl/fl + control), Piezo1 fl/fl fed HFD group ( Piezo1 fl/fl + HFD), Piezo1 ∆Myh6 fed chow diet group ( Piezo1 ∆Myh6 + control), Piezo1 ∆Myh6 fed HFD group ( Piezo1 ∆Myh6 + HFD). Mice with random blood glucose ≥ 16.7 mM were selected for subsequent studies and continued fed with HFD diet for additional 16 weeks.
mice The experimental design flowchart was illustrated in Fig. A. To examine the expression level of Piezo1 in DCM, twenty 8-week old male Piezo1 dtT/dtT mice were utilized to construct diabetic models via intraperitoneal injections of streptozotocin (STZ, dissolved in citrate buffer, 0.1 mM, pH = 4.5, MCE, USA) at a dosage of 55 mg/kg daily for 5 consecutive days. Mice in the control group received intraperitoneal injection of citrate buffer. After 2 weeks, T1DM mice were confirmed in mice exhibiting fasting blood glucose (FBG) ≥ 16.7 mM/L for two consecutive days. All mice were subsequently maintained for an additional 14 weeks prior to sample collection. To further investigate the role of Piezo1 in DCM, C57BL/6J mice (Vital River Laboratory Animal Technology Co., Ltd, China) were also used to establish T1DM (Fig. A). Twelve weeks after DCM induction, the Piezo1 agonist Yoda1 (MCE, USA) was administrated to diabetic mice via intraperitoneal injection (80 µg/kg, once daily for 4 weeks) .
To estimate the levels of Piezo1 in T2DM and assess the impact of Piezo1 knockout on cardiac function in diabetic context, Piezo1 dtT/dtT , Piezo1 ∆Myh6 and Piezo1 fl/fl mice aged 3 weeks were subjected to construct T2DM model through high-fat diet (HFD, 60 kcal% fat; Research Diets, Inc, USA; Supplementary file 3: Table ) for 6 weeks followed by intraperitoneal STZ injections at a dose of 35 mg/kg for three consecutive days. All mice were randomly divided into six groups ( n = 10 per group): Piezo1 dtT/dtT mice fed chow diet group ( Piezo1 dtT/dtT control group), Piezo1 dtT/dtT mice fed HFD group ( Piezo1 dtT/dtT T2DM group), Piezo1 fl/fl fed chow diet group ( Piezo1 fl/fl + control), Piezo1 fl/fl fed HFD group ( Piezo1 fl/fl + HFD), Piezo1 ∆Myh6 fed chow diet group ( Piezo1 ∆Myh6 + control), Piezo1 ∆Myh6 fed HFD group ( Piezo1 ∆Myh6 + HFD). Mice with random blood glucose ≥ 16.7 mM were selected for subsequent studies and continued fed with HFD diet for additional 16 weeks.
At the end of treatment, IPGTT was performed in all mice after overnight fasting. All T2DM mice were received a 2 mg/g intraperitoneal glucose injection, with blood glucose levels monitored pre-injection (0 min) as well as at 30, 60, 90 and 120 min post-injection.
Following anesthesia with 2% inhaled isoflurane, transthoracic echocardiography was conducted at the end of the experiment using a VINNO ultrasound diagnostic instrument (VINNO, Suzhou, China). Parasternal long-axis M-mode images were collected and parameters recorded to assess systolic and diastolic cardiac function, including left ventricular (LV) ejection fraction (EF%), LV shortening fraction (FS%), LV internal dimension at diastole (LVID; d), LV internal dimension at systole (LVID; s), LV anterior wall thickness at diastole (LVAW; d), LV anterior wall thickness at systole (LVAW; s), LV posterior wall thickness at diastole (LVPW; d) and LV posterior wall thickness at systole (LVPW; s).
Heart weight (HW) and tibial length (TL) of all mice were measured to calculate the HW/TL ratio. Following fixation in 4% paraformaldehyde, heart tissues of mice were embedded in paraffin and sectioned to a thickness of 4 μm. Deparaffinized and rehydrated sections were stained with hematoxylin and eosin (H&E, Beyotime Biotech, China), Masson’s trichrome (Solarbio, China) and Alexa Fluor 488 labeled wheat germ agglutinin (WGA, Thermo Fisher, USA) staining to assess collagen content and myocardial atrophy according to the manufacturer’s instruction. Immunofluorescence (IF) staining of tissue was conducted to detect Piezo1 expression and collagen levels in cardiomyocytes. Sections were deparaffinized and rehydrated before being blocked with 5% goat serum (Solarbio, China) for 30 min, then incubated with primary antibodies RFP, collagen I and collagen III at 4ºC overnight. Subsequent treatments included incubation with secondary antibodies in the following morning, and sections stained with RFP were then incubated with α-actinin antibody to label myocardical tissue. Cells seeded on glass coverslips were fixed in 4% paraformaldehyde for 15 min, blocked with 5% goat serum for 30 min and then incubated with primary antibodies against Piezo1, Tomm20, p-Drp1 (ser616) and OPA1 at 4 ºC overnight. Images were acquired with a fluorescent microscope (BZ-X710, KEYENCE, Japan).
The embryonic rat heart-derived cardiomyocyte-like H9C2 cell line was obtained from the Wuhan Servicebio Technology Co., Ltd. and primary neonatal mouse cardiomyocytes (NMCMs) were isolated from neonatal mice aged 1–3 days. Mouse hearts were obtained and ventricular sections were diced into small pieces, followed by digestion for 8 h at 4 ºC with 0.125% trypsin and then for 30 min at 37 ºC with 0.5% collagenase II. Cell suspension was obtained via filtering tissue fragments with 40-µm cell strainers (Falcon, USA). Purified cardiomyocytes were collected and culture medium was replaced 24 h later . All cells were cultured in Dulbecco’s modified Eagle medium (DMEM) medium (Gibco, Germany) which contained 1 g/L of D-glucose and supplemented with 100 U/ml of penicillin and streptomycin, and 10% fetal bovine serum. In the first part of the in vitro study, to estimate the effect of Piezo1 inhibition on mitochondrial function, after plated in six-well plates or glass coverslips and then starved for 12 h, H9C2 cells were treated with 35 mM D-glucose (Sigma, USA) with 500 µM palmitate (Sigma, USA) in the presence or absence of GsMTx4 (10 µM, MCE, USA) for additional 48 h as HG + PA or GsMTx4 groups, identical concentrations of mannitol as normal glucose (NG) group. In the subsequent phase of the in vitro study, to investigate the effect of Piezo1 deficiency on mitochondrial function, the primary NMCMs were treated with 35 mM D-glucose and 500 µM palmitate or NG for 48 h.
Total RNA was extracted from cardiomyocytes or heart tissues using TRIzol Reagent (Invitrogen, USA) following the manufacturer’s instructions. Total RNA was reversed into cDNA using ReverTra Ace qPCR RT Kit (Takara, Japan) and quantitative RT-PCR was conducted using SYBR Green Realtime PCR Master Mix (Takara, Japan) on a LightCycler 480 instrument (Roche, Switzerland). β-actin was used as control, and relative gene expression was calculated through the 2 −ΔΔCt method. All samples were examined in triplicates. Primer sequences for RT-PCR were listed in Supplementary file 3: Table .
Mitochondrial ultrastructure in myocardial samples was examined by fixing mouse heart tissues with glutaraldehyde, sectioning, and staining with 2% uranyl acetate and Reynolds lead citrate. Sections were observed under an 80-kV transmission electron microscope (JEM-1230, JOEL, Japan). Mitochondrial size was measured with Image J software.
The cleavage of the calpain substrate was measured using a calpain activity assay kit (Abcam, UK) as described in a previous study . Tissue or cell proteins were extracted and concentration was measured by the BCA protein assay kit, followed by sample dilution in 85 µL extraction buffer. Calpain activity was examined with calpain substrate and reaction buffer. Then, absorbance was measured at 400 nm excitation and 505 nm emission wavelengths.
To measure mitochondrial membrane potential (MMP), cultured cells were determined with a JC-10 kit (Solarbio, China) and mitochondrial ROS was estimated with MitoSox Red superoxide indicator (Cell Signaling Technology, USA). For ROS detection, frozen tissue sections or cultured cells were stained with 2’,7’-Dichlorofluorescin diacetate (DCFH-DA) or dihydroethidium (DHE) (Beyotime, China). Mitochondrial oxygen consumption rate (OCR) was measured using a Seahorse XF24 analyzer (Agilent, USA) according to protocols. H9C2 cells were seeded at 40,000 cells/well on 24-well XFe24 cell culture microplates. OCR value was measured using the Seahorse XF Cell Mitochondrial Stress Test kit.
2+ entry measurement The intracellular Ca 2+ entry was measured as described in the previous study . Briefly, cells were incubated in a transparent 96-well plate for 3 days, and then treated with 2-µM Fura-2-AM (Thermo Fisher Scientific, USA) for 75 min. Intracellular Ca 2+ signal changes were estimated through the proportion of 340 nm and 380 nm wavelengths.
Heart tissues or cultured cells were lysed with RIPA buffer supplemented with phosphatase and protease inhibitors (Beyotime, China). Protein extractions were separated by 10-12% SDS-PAGE and then transferred to PVDF membranes (Millipore, USA). After blocking with 5% skim milk or BSA for 1 h at room temperature, the membranes were incubated with primary antibodies (all the primary antibodies were shown in Supplementary file 3: Table ) at 4 ºC overnight. Next day, the membranes were washed and incubated with peroxidase-conjugated anti-rabbit IgG (1:5000 dilution, ZSGB-BIO, Beijing, China) and anti-mouse-IgG (1:5000 dilution, ZSGB-BIO, Beijing, China) for 1 h and bands were detected with the ECL detection kit (Epizyme, China). GAPDH or β-actin was used as control indicated in figures. Protein quantification was analyzed with Image J software.
Serum lipid levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were measured using an automatic biochemical analyzer (URIT-8026, China).
RNA-seq data (GSE241166) from heart tissues of DCM and control mice, generated using the Illumina NovaSeq 6000 platform, was obtained from the Gene Expression Omnibus (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/ ). The dataset included heart samples from three DCM mice (T2DM, induced by HFD and STZ) and three normal mice. To identify differentially expressed genes associated with ion channels, RNA-seq analysis was conducted with a cutoff criterion of fold change more than 1.5 or less than 1/1.5 combined with P < 0.05.
All data were presented as mean ± SEM. For comparisons between two groups, unpaired Student’s t -test was conducted and for more than two groups, one-way ANOVA followed by Turkey’s post hoc test was performed. All statistical tests were conducted using GraphPad Prism software. P value less than 0.05 was considered as statistically significant.
Elevation in Piezo1 expression in DCM and HG-treated cells Previous studies have indicated the up-regulation of Piezo1 in cardiomyocytes of mice with cardiac hypertrophy and ischaemia/reperfusion injury . To determine whether Piezo1 expression is increased in DCM hearts compared to normal tissues, we downloaded RNA-seq data from the GEO dataset and compared the expression levels of ion channels genes, including Piezo1. The results revealed a significant up-regulation of Piezo1 in DCM samples relative to normal hearts (Fig. A, B). To further confirm these findings, Piezo1 dtT/dtT mice were applied to conduct T2DM and T1DM model. IF staining of heart sections indicated higher protein levels of Piezo1 in T2DM (Fig. C, D) and T1DM (Fig. E, F) mice. Similarly, H9C2 cells were treated with high glucose (HG, 35 mM), showing increased Piezo1 expression compared to normal glucose (NG, 1 g/L) conditions (Fig. G, H). Meanwhile, the results of western blot also presented higher Piezo1 level in HG-treated cells than NG group (Fig. I, J). These data underscore the notable increase in Piezo1 expression in DCM mice and HG-treated cells. Cardiac-specific knockout of Piezo1 improves cardiac function and remodeling To investigate the role of Piezo1 in diabetic hearts, we constructed Piezo1 ΔMyh6 mice. The deletion of Piezo1 was confirmed by genotyping (Supplementary file1: Fig. A). After Piezo1 deletion, there were no significant differences in the shape, body weight, or organ weight relative to body weight (heart, kidney, liver, lung, or spleen) between Piezo1 ΔMyh6 and Piezo1 fl/fl mice (Supplementary file 1: Fig. B–D). Moreover, serum levels of TC, TG and glucose did no differ between the two groups (Supplementary file 1: Fig. E–G). Piezo1 deletion also showed no significant effect on cardiac function, including EF and FS (Supplementary file 1: Fig. H–K). RT-PCR and IF staining of cardiac tissue showed Piezo1 expression was reduced in Piezo1 ΔMyh6 mice compared to Piezo1 fl/fl mice (Supplementary file 1: Fig. L–N). Calcium imaging also showed an obvious reduction in calcium influx in NMCRs isolated from Piezo1 ΔMyh6 mice in response to Yoda1 (Supplementary file 1: Fig. O, P). Further, we also validated Piezo1 deletion using western blot, and it showed that the level of Piezo1 was decreased in Piezo1 ΔMyh6 mice (Supplementary file 1: Fig. Q, R). These results demonstrated successful cardiac-specific knockout of Piezo1 in Piezo1 ΔMyh6 mice. To explore the effect of Piezo1 knockout on cardiac function, echocardiographic analysis was applied. Compared to Piezo1 fl/fl control mice, those in the Piezo1 fl/fl + HFD group displayed cardiac dysfunction, as indicated by increased heart weight and decreased LVEF, LVFS, as well as elevated LVID, d, LVID, s and LVPW (Fig. B–H). Obviously, these echocardiographic results were all reversed following Piezo1 deletion. Glucose tolerance testing indicated that mice in DCM group exhibited impaired glucose tolerance (Fig. I, J). However, there was no difference between Piezo1 fl/fl and Piezo1 ΔMyh6 mice. Additionally, serum levels of TC, TG and LDL-C were significantly elevated in Piezo1 fl/fl + HFD group relative to controls, but were normalized following Piezo1 deletion (Supplementary file 2: Fig. A–C). Although serum levels of HDL-C were lower in Piezo1 fl/fl + HFD group, there was no obvious difference compared to Piezo1 ΔMyh6 + HFD (Supplementary file 2: Fig. D). Natriuretic peptides including atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) have been considered as cardioprotective factors. RT-PCR results showed that the levels of ANP and BNP were significantly elevated in Piezo1 fl/fl + HFD group, while these effects were attenuated by Piezo1 knockout, indicating cardiac injury was partially repaired (Fig. K, L). Myocardial disarray was markedly evident in the Piezo1 fl/fl + HFD group compared to control mice, yet this abnormality was restored upon Piezo1 deletion (Fig. M). Furthermore, WGA staining revealed significantly smaller cross-sectional area of cardiomyocytes in Piezo1 ΔMyh6 + HFD mice relative to those in the Piezo1 fl/fl + HFD group (Fig. N, O). Collectively, these results indicate that Piezo1 deletion ameliorates cardiac dysfunction. Alleviation of cardiac fibrosis with Piezo1 deficiency Given that cardiac fibrosis is a prominent feature of DCM, we detected the extent of myocardial fibrosis through Masson’s trichrome staining. Increased collagen accumulation within the prevascular and interstitial region was observed in Piezo1 fl/fl + HFD mice compared to Piezo1 ΔMyh6 + HFD counterparts (Fig. A–C). IF staining for collagen I and collagen III also exhibited higher collagen levels in Piezo1 fl/fl + HFD than in the in Piezo1 ΔMyh6 + HFD group (Fig. D–F). These findings indicate that cardiac-specific Piezo1 deficiency alleviated cardiac fibrosis in DCM hearts. Impaired oxidative stress and mitochondrial dysfunction reversed due to Piezo1 deficiency Considering the pivotal role of oxidative stress and mitochondria dysfunction in DCM development, we evaluated ROS levels across all groups using DHE and DCFH-DA probes in cardiac tissues. The results revealed elevated fluorescence intensities in the tissues of Piezo1 fl/fl + HFD mice compared to control mice, which reduced after Piezo1 knockout in cardiac tissues (Fig. A–C). Mitochondria-derived anions are known as the principal intracellular source of ROS in DCM. Moreover, increased mitochondria fragmentation is a key feature of diabetes, suggesting a role for abnormal fission in ROS production and mitochondrial dysfunction . Therefore, TEM analysis was conducted to examine the mitochondrial morphology and function. Findings showed abnormal density, disordered arrangements and fragmentation of mitochondria in the Piezo1 fl/fl + HFD group, with Piezo1 deficiency ameliorating these alterations (Fig. D). Additionally, Piezo1 knockout reversed mitochondrial length and morphology compared with Piezo1 fl/fl + HFD mice (Fig. E). Collectively, these results indicate that cardiac-specific Piezo1 knockout significantly improves diabetes-induced mitochondrial dysfunction. Enhanced mitochondrial function in vitro with Piezo1 deficiency To mimic hyperglycemic and hyperlipidemia environment in vivo, H9C2 cells and NMCMs were treated with high glucose in combination with palmitate (HG + PA). The results showed that HG + PA treated cells exhibited elevated ROS levels (Fig. A, B and D, E). To further delineate the effect of Piezo1 on MMP, the JC-10 fluorescent probe was applied. The MMP level was reflected by the ratio of green to red fluorescence, with data showing that aggregates probes were markedly reduced but monomers increased following HG + PA treatment (Fig. C, F). Interestingly, the application of GsMTx4, a Piezo1 inhibitor, markedly reversed changes in ROS and MMP levels. To examine the role of Piezo1 in mitochondrial function in more depth, NMCMs were isolated from Piezo1 fl/fl and Piezo1 ΔMyh6 mice, and then subjected to HG + PA treatment. Meanwhile, heightened levels of cell ROS, mitochondrial ROS and monomers were detected in HG + PA treated primary NMCMs, which were reversed by Piezo1 knockout (Fig. G–L). Additionally, the Cell Mitochondrial Stress Test analysis indicated that HG + PA treatment also led to decreased maximal respiration and spare capacity, while GsMTx4 treatment reversed these effect (Fig. M–O). These data support the contention that Piezo1 deficiency preserves mitochondrial function in HG + PA treated cardiomyocytes. Regulation of mitochondrial dynamics proteins by Piezo1 through calpain/ERK1/2 Several reports demonstrate that impaired mitochondrial dynamics are detrimental to cardiac health, including DCM . In diabetic hearts of mice in the Piezo1 fl/fl + HFD group, gene expression related to mitochondrial fission, including Drp1 and Fis1 , was significantly increased compared to the control mice, whereas expression of genes associated with mitochondrial fusion, including MFN1 , MFN2 was reduced (Fig. A–D). Piezo1 knockout significantly reversed their mRNA levels. H9C2 cells stained with Tomm20 and DAPI demonstrated that HG + PA treatment led to mitochondrial fragmented compared to low glucose conditions, with GsMTx4 reversing this effect (Fig. E, F). IF staining highlighted an increase in phosphorylated Drp1 expression while OPA1 levels were downregulated (Fig. G–I), indicating that Piezo1 inhibition protects against HG + PA induced mitochondria dysfunction. Previous study has shown decreased calpain activity following Piezo1 deficiency in macrophage and endothelial cells . Indeed, our results confirmed that calpain activity was significantly higher in DCM hearts but markedly reduced following Piezo1 deficiency (Fig. J). Moreover, elevated calpain activity in HG + PA induced cells was also reversed after GsMTx4 treatment or Piezo1 knockout (Fig. K, L). Collectively, these data demonstrate that Piezo1 regulates calpain activity during the progression of DCM. Furthermore, we validated protein levels associated with mitochondria dynamics using WB analysis. In diabetic hearts, OPA1 was remarkably reduced in Piezo1 fl/fl + HFD compared to controls. In contrast, levels of p-Drp1 at ser616 not at ser637 were significantly increased in diabetic hearts, although the levels of total Drp1 remained unchanged. Particularly, ERK1/2 is known to phosphorylate Drp1 at ser616, which triggers abnormal mitochondrial fission in cardiac injury . Our data revealed that Piezo1 fl/fl + HFD mice exhibited elevated levels of p-ERK1/2group, while total ERK1/2 levels did not change. Piezo1 deficiency led to a significant increase in OPA1 and decreases in p-Drp at ser616 and p-ERK1/2 levels (Fig. A–G). In H9C2 cells and NMCMs, HG + PA treatment also resulted in upregulated p-Drp1 at ser616 and p-ERK1/2 without affecting total protein levels (Fig. H–Q). Interestingly, both Piezo1 inhibitor and deletion reversed this effect. Altogether, these data indicates that Piezo1 regulates mitochondria dynamics via ERK1/2-mediated phosphorylation. Aggravation of cardiac remodeling by Piezo1 activation To further confirm the physiological role of Piezo1 in DCM development and heart failure in vivo, we evaluated the effects of Piezo1 agonist, Yoda1 upon DCM in C57JL/6 mice. For this purpose, we administrated Yoda1 (i.p injection) to mice after 12 weeks for STZ injection (Fig. A). We then examined cardiac function by echocardiography and discovered that STZ induced obvious LV systolic dysfunction, which was aggravated by Yoda1 administration, as identified by decreased LVEF and LVFS, and increased heart mass (Fig. B–D). Likewise, Yoda1 treatment enhanced collagen deposition relative to the STZ-induced DCM heart (Fig. E–G). Increased levels of ANP and BNP were obviously increased after Yoda1 injection (Fig. H, I). IF staining showed a significant increase of collagen I and III in mice administrated with Yoda1 compared to those in the DCM group (Fig. J–L). This striking correlation of Yoda1 and DCM underscores the critical role of Piezo1 in the progression of this disease.
Previous studies have indicated the up-regulation of Piezo1 in cardiomyocytes of mice with cardiac hypertrophy and ischaemia/reperfusion injury . To determine whether Piezo1 expression is increased in DCM hearts compared to normal tissues, we downloaded RNA-seq data from the GEO dataset and compared the expression levels of ion channels genes, including Piezo1. The results revealed a significant up-regulation of Piezo1 in DCM samples relative to normal hearts (Fig. A, B). To further confirm these findings, Piezo1 dtT/dtT mice were applied to conduct T2DM and T1DM model. IF staining of heart sections indicated higher protein levels of Piezo1 in T2DM (Fig. C, D) and T1DM (Fig. E, F) mice. Similarly, H9C2 cells were treated with high glucose (HG, 35 mM), showing increased Piezo1 expression compared to normal glucose (NG, 1 g/L) conditions (Fig. G, H). Meanwhile, the results of western blot also presented higher Piezo1 level in HG-treated cells than NG group (Fig. I, J). These data underscore the notable increase in Piezo1 expression in DCM mice and HG-treated cells.
To investigate the role of Piezo1 in diabetic hearts, we constructed Piezo1 ΔMyh6 mice. The deletion of Piezo1 was confirmed by genotyping (Supplementary file1: Fig. A). After Piezo1 deletion, there were no significant differences in the shape, body weight, or organ weight relative to body weight (heart, kidney, liver, lung, or spleen) between Piezo1 ΔMyh6 and Piezo1 fl/fl mice (Supplementary file 1: Fig. B–D). Moreover, serum levels of TC, TG and glucose did no differ between the two groups (Supplementary file 1: Fig. E–G). Piezo1 deletion also showed no significant effect on cardiac function, including EF and FS (Supplementary file 1: Fig. H–K). RT-PCR and IF staining of cardiac tissue showed Piezo1 expression was reduced in Piezo1 ΔMyh6 mice compared to Piezo1 fl/fl mice (Supplementary file 1: Fig. L–N). Calcium imaging also showed an obvious reduction in calcium influx in NMCRs isolated from Piezo1 ΔMyh6 mice in response to Yoda1 (Supplementary file 1: Fig. O, P). Further, we also validated Piezo1 deletion using western blot, and it showed that the level of Piezo1 was decreased in Piezo1 ΔMyh6 mice (Supplementary file 1: Fig. Q, R). These results demonstrated successful cardiac-specific knockout of Piezo1 in Piezo1 ΔMyh6 mice. To explore the effect of Piezo1 knockout on cardiac function, echocardiographic analysis was applied. Compared to Piezo1 fl/fl control mice, those in the Piezo1 fl/fl + HFD group displayed cardiac dysfunction, as indicated by increased heart weight and decreased LVEF, LVFS, as well as elevated LVID, d, LVID, s and LVPW (Fig. B–H). Obviously, these echocardiographic results were all reversed following Piezo1 deletion. Glucose tolerance testing indicated that mice in DCM group exhibited impaired glucose tolerance (Fig. I, J). However, there was no difference between Piezo1 fl/fl and Piezo1 ΔMyh6 mice. Additionally, serum levels of TC, TG and LDL-C were significantly elevated in Piezo1 fl/fl + HFD group relative to controls, but were normalized following Piezo1 deletion (Supplementary file 2: Fig. A–C). Although serum levels of HDL-C were lower in Piezo1 fl/fl + HFD group, there was no obvious difference compared to Piezo1 ΔMyh6 + HFD (Supplementary file 2: Fig. D). Natriuretic peptides including atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) have been considered as cardioprotective factors. RT-PCR results showed that the levels of ANP and BNP were significantly elevated in Piezo1 fl/fl + HFD group, while these effects were attenuated by Piezo1 knockout, indicating cardiac injury was partially repaired (Fig. K, L). Myocardial disarray was markedly evident in the Piezo1 fl/fl + HFD group compared to control mice, yet this abnormality was restored upon Piezo1 deletion (Fig. M). Furthermore, WGA staining revealed significantly smaller cross-sectional area of cardiomyocytes in Piezo1 ΔMyh6 + HFD mice relative to those in the Piezo1 fl/fl + HFD group (Fig. N, O). Collectively, these results indicate that Piezo1 deletion ameliorates cardiac dysfunction.
Given that cardiac fibrosis is a prominent feature of DCM, we detected the extent of myocardial fibrosis through Masson’s trichrome staining. Increased collagen accumulation within the prevascular and interstitial region was observed in Piezo1 fl/fl + HFD mice compared to Piezo1 ΔMyh6 + HFD counterparts (Fig. A–C). IF staining for collagen I and collagen III also exhibited higher collagen levels in Piezo1 fl/fl + HFD than in the in Piezo1 ΔMyh6 + HFD group (Fig. D–F). These findings indicate that cardiac-specific Piezo1 deficiency alleviated cardiac fibrosis in DCM hearts.
Considering the pivotal role of oxidative stress and mitochondria dysfunction in DCM development, we evaluated ROS levels across all groups using DHE and DCFH-DA probes in cardiac tissues. The results revealed elevated fluorescence intensities in the tissues of Piezo1 fl/fl + HFD mice compared to control mice, which reduced after Piezo1 knockout in cardiac tissues (Fig. A–C). Mitochondria-derived anions are known as the principal intracellular source of ROS in DCM. Moreover, increased mitochondria fragmentation is a key feature of diabetes, suggesting a role for abnormal fission in ROS production and mitochondrial dysfunction . Therefore, TEM analysis was conducted to examine the mitochondrial morphology and function. Findings showed abnormal density, disordered arrangements and fragmentation of mitochondria in the Piezo1 fl/fl + HFD group, with Piezo1 deficiency ameliorating these alterations (Fig. D). Additionally, Piezo1 knockout reversed mitochondrial length and morphology compared with Piezo1 fl/fl + HFD mice (Fig. E). Collectively, these results indicate that cardiac-specific Piezo1 knockout significantly improves diabetes-induced mitochondrial dysfunction.
To mimic hyperglycemic and hyperlipidemia environment in vivo, H9C2 cells and NMCMs were treated with high glucose in combination with palmitate (HG + PA). The results showed that HG + PA treated cells exhibited elevated ROS levels (Fig. A, B and D, E). To further delineate the effect of Piezo1 on MMP, the JC-10 fluorescent probe was applied. The MMP level was reflected by the ratio of green to red fluorescence, with data showing that aggregates probes were markedly reduced but monomers increased following HG + PA treatment (Fig. C, F). Interestingly, the application of GsMTx4, a Piezo1 inhibitor, markedly reversed changes in ROS and MMP levels. To examine the role of Piezo1 in mitochondrial function in more depth, NMCMs were isolated from Piezo1 fl/fl and Piezo1 ΔMyh6 mice, and then subjected to HG + PA treatment. Meanwhile, heightened levels of cell ROS, mitochondrial ROS and monomers were detected in HG + PA treated primary NMCMs, which were reversed by Piezo1 knockout (Fig. G–L). Additionally, the Cell Mitochondrial Stress Test analysis indicated that HG + PA treatment also led to decreased maximal respiration and spare capacity, while GsMTx4 treatment reversed these effect (Fig. M–O). These data support the contention that Piezo1 deficiency preserves mitochondrial function in HG + PA treated cardiomyocytes.
Several reports demonstrate that impaired mitochondrial dynamics are detrimental to cardiac health, including DCM . In diabetic hearts of mice in the Piezo1 fl/fl + HFD group, gene expression related to mitochondrial fission, including Drp1 and Fis1 , was significantly increased compared to the control mice, whereas expression of genes associated with mitochondrial fusion, including MFN1 , MFN2 was reduced (Fig. A–D). Piezo1 knockout significantly reversed their mRNA levels. H9C2 cells stained with Tomm20 and DAPI demonstrated that HG + PA treatment led to mitochondrial fragmented compared to low glucose conditions, with GsMTx4 reversing this effect (Fig. E, F). IF staining highlighted an increase in phosphorylated Drp1 expression while OPA1 levels were downregulated (Fig. G–I), indicating that Piezo1 inhibition protects against HG + PA induced mitochondria dysfunction. Previous study has shown decreased calpain activity following Piezo1 deficiency in macrophage and endothelial cells . Indeed, our results confirmed that calpain activity was significantly higher in DCM hearts but markedly reduced following Piezo1 deficiency (Fig. J). Moreover, elevated calpain activity in HG + PA induced cells was also reversed after GsMTx4 treatment or Piezo1 knockout (Fig. K, L). Collectively, these data demonstrate that Piezo1 regulates calpain activity during the progression of DCM. Furthermore, we validated protein levels associated with mitochondria dynamics using WB analysis. In diabetic hearts, OPA1 was remarkably reduced in Piezo1 fl/fl + HFD compared to controls. In contrast, levels of p-Drp1 at ser616 not at ser637 were significantly increased in diabetic hearts, although the levels of total Drp1 remained unchanged. Particularly, ERK1/2 is known to phosphorylate Drp1 at ser616, which triggers abnormal mitochondrial fission in cardiac injury . Our data revealed that Piezo1 fl/fl + HFD mice exhibited elevated levels of p-ERK1/2group, while total ERK1/2 levels did not change. Piezo1 deficiency led to a significant increase in OPA1 and decreases in p-Drp at ser616 and p-ERK1/2 levels (Fig. A–G). In H9C2 cells and NMCMs, HG + PA treatment also resulted in upregulated p-Drp1 at ser616 and p-ERK1/2 without affecting total protein levels (Fig. H–Q). Interestingly, both Piezo1 inhibitor and deletion reversed this effect. Altogether, these data indicates that Piezo1 regulates mitochondria dynamics via ERK1/2-mediated phosphorylation.
To further confirm the physiological role of Piezo1 in DCM development and heart failure in vivo, we evaluated the effects of Piezo1 agonist, Yoda1 upon DCM in C57JL/6 mice. For this purpose, we administrated Yoda1 (i.p injection) to mice after 12 weeks for STZ injection (Fig. A). We then examined cardiac function by echocardiography and discovered that STZ induced obvious LV systolic dysfunction, which was aggravated by Yoda1 administration, as identified by decreased LVEF and LVFS, and increased heart mass (Fig. B–D). Likewise, Yoda1 treatment enhanced collagen deposition relative to the STZ-induced DCM heart (Fig. E–G). Increased levels of ANP and BNP were obviously increased after Yoda1 injection (Fig. H, I). IF staining showed a significant increase of collagen I and III in mice administrated with Yoda1 compared to those in the DCM group (Fig. J–L). This striking correlation of Yoda1 and DCM underscores the critical role of Piezo1 in the progression of this disease.
Ample epidemiological evidence has documented a strong correlation between diabetes and heart failure . Patients with diabetes often experience myocardial dysfunction, characterized by myocardial fibrosis, cardiac remodeling, diastolic and systolic dysfunction . This condition is termed as DCM and increasing molecular targets for DCM treatment have been found . Emerging studies have focused on the role of Piezo1 in cardiovascular pathophysiology, including myocardial infarction , atherosclerosis and lymphatic development . Our findings provide several interesting insights. First, we observed a significant increase in Piezo1 expression in the hearts of diabetic mice and in HG-treated cardiomyocytes. Second, cardiac-specific knockout of Piezo1 improved cardiac dysfunction and remodeling, thereby mitigating myocardial fibrosis. Third, Piezo1 deletion alleviated cardiac dysfunction by restoring mitochondrial fragmentation and altering MMP, both in vivo and in vitro, via the ERK/Drp1 signaling pathway. Lastly, Piezo1 activation aggravated cardiac damage through increased collagen synthesis. To the best of our knowledge, this study presents the first report demonstrating the important role of Piezo1 in the progression of DCM and the potential underlying mechanisms involved. Mechanically, cardiac hypertrophy develops in response to increased workload. While our present study elucidates the vital roles of Piezo1 in diabetes and heart dysfunction, the specific regulatory mechanisms of Piezo1 in diabetes complications like DCM require further exploration. The pathophysiology of DCM is complex. Importantly, approximately 95% of ATP is generated by cardiac muscle originating from oxidative phosphorylation in mitochondria, suggesting the key role of mitochondrial dysfunction is DCM progression. Mitochondria possess active Ca 2+ transport systems and several enzymes related to energy metabolism are activated by Ca 2+ . ROS overload is considered as a key trigger of oxidative stress which is one obvious characteristic of DCM. The present study supported the role of oxidative stress in controlling DCM progression in vivo and in vitro. ROS levels were increased in diabetic hearts and HG + PA treated cells but reduced after Piezo1 deletion or inhibitor treatment. Moreover, lipid metabolism plays a vital role in diverse physiological process of heart and cardiovascular diseases. Importantly, lipotoxicity could induce endoplasmic reticulum stress, cell death, inflammatory responses and mitochondrial dysfunction . We also found increased serum levels of total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) in the Piezo1 fl/fl + HFD group but reversed after Piezo1 deletion. Additionally, mitochondrial dysfunction is related to several mechanisms in the pathogenesis of DCM, including mitochondrial morphology, integrity, dynamics, mitophagy and biogenesis . Mitochondrial dynamics, including mitochondrial fission and fusion could regulate mitochondrial size, mass and intercellular lipid accumulation . Emerging evidence has shown that the imbalance of mitochondrial fission and fusion plays a vital role in the diabetic heart [ – ]. In diabetic patients and mice, Drp1 was significantly upregulated whereas OPA1 was downregulated, which was consistent with our results . Interestingly, cardiomyocyte-specific knockout of Piezo1 improved mitochondrial function through inhibiting mitochondrial fragmentation and fission, and suppressing oxidative stress. Calpain can be activated by high level of Ca 2+ and widely expressed in eukaryotic cells . We hypothesized that calpain is involved in HFD/STZ induced heart failure via Piezo1 activation induced Ca 2+ entry. Previous data from our team has shown that calpain is acting downstream of Piezo1. Meanwhile, HG-induced upregulation of calpain1 expression has been reported in H9C2 cells, which was consistent with our results . We also found HG + PA treatment increases mitochondrial fission but decreases mitochondrial fusion. Interestingly, inhibition of calpain activity could dephosphorylate Drp1 at ser637 and suppress mitochondrial fission in acute viral myocarditis . These data together indicate that Piezo1 induced calpain activity regulates mitochondrial dynamics. As a key component for mitochondrial fission, post-translational modifications to Drp1, such as SUMOylation, phosphorylation and S-nitrosylation are crucial for fission activity [ – ]. In this study, we demonstrated that ERK1/2-mediated Drp1 ser616 phosphorylation regulated mitochondrial dynamics in the development of diabetic hearts. ERK1/2 is a member of the mitogen active protease (MAPK) family, which promotes cell division and proliferation . A number of reports have indicated that Drp1 is phosphorylated by ERK1/2 at serine 616 site, leading to aberrant mitochondrial fission . Our study showed that Piezo1 inhibitor, GsMTx4 obviously inhibited HG + PA induced oxidative stress and mitochondrial fission via downregulating phosphorylation of ERK1/2 and Drp1 at ser616. In the present study, there are several limitations. First, complicated mechanisms may be involved in DCM including inflammation, impaired insulin sensitivity, altered cardiac metabolic pathway (chronic hyperglycemia, lipotoxicity and dyslipidemia) and mitochondrial mitophagy other than mitochondrial dynamics . In addition, considering the importance of mitochondrial proteins in mitochondrial dynamics, other proteins possibly contributing to DCM progression and in-depth study on association between calpain and p-ERK1/2 deserve further scrutiny. Second, we focus mainly on type 2 diabetes induced DCM, but whether Piezo1 regulates mitochondrial dynamics in type 1 diabetic heart needs further investigation. Finally, although Piezo1 agonist, Yoda1 is used to activate the ion channel in our study, Yoda1 may activate Piezo1 in immune cells, endothelial cells and epithelial cells other than cardiomyocytes. Therefore, to delineate its unique role in DCM, a cardiac-specific Piezo1 overexpression mouse model would be urgently required. In conclusion, Piezo1 expression was increased in DCM and cardiac-specific knockout of Piezo1 attenuated cardiac fibrosis and improved cardiac function. Piezo1 deficiency or channel closing decreased calpain levels and phosphorylated Drp1 induced mitochondrial fragmentation by downregulating ERK1/2 phosphorylation (Graphical Abstract). Thus, inhibition of Piezo1 by drug treatment or cardiac-specific gene provides a promising approach to the clinical application for DCM treatment.
Below is the link to the electronic supplementary material. Supplementary Material 1: Figure S1. Piezo1 knockout not affect normal heart function. ( A ) Representative genotyping results for Piezo1 fl / fl and Piezo1 ∆ Myh6 mice. ( B ) Body weight of Piezo1 fl / fl and Piezo1 ∆ Myh6 mice. ( C ) The body shape of Piezo1 fl / fl and Piezo1 ∆ Myh6 mice. ( D ) Weight of each organ relative to body weight in Piezo1 fl / fl and Piezo1∆ Myh6 mice. ( E – G ) The serum levels of total cholesterol (TC), total triglycerides (TG) and glucose of Piezo1 fl / fl and Piezo1 ∆ Myh6 mice. ( H – J ) Representative M-mode echocardiographic images and quantitative measurement of the left ventricle ejection fraction and fractional shortening in Piezo1 fl / fl and Piezo1Q mice. ( K ) Electrocardiogram analysis of Piezo1fl/fl and Piezo1 ∆ Myh6 mice. ( L ) Relative mRNA level of Piezo1 in Piezo1fl/fl and Piezo1 ∆ Myh6 mice. ( M , N ) Immunofluorescent staining and quantitative measurement of Piezo1 in Piezo1 fl / fl and Piezo1 ∆ Myh6 mice. n = 5 per group. ( O , P ) Traces showing Ca 2+ entry and mean data of relative peak value in cardiomyocytes from Piezo1 fl / fl and Piezo1 ∆ Myh6 mice in response to Yoda1 treatment (n = 3). ( Q , R ) Western blot and quantitative analysis for Piezo1 in cardiac tissues (n = 3). * P < 0.05. Supplementary Material 2: Figure S2. Piezo1 knockout lowers the level of serum lipid in DCM mice. Serum total triglycerides (TG, A ), total cholesterol (TC, B ), low-density lipoprotein cholesterol (LDL-C, C ) and high-density lipoprotein cholesterol (HDL-C, D ) were assessed in four groups of mice (n = 6). * P < 0.05; ns, not significant. Supplementary Material 3
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Local analgesia for the relief of pain in children undergoing venipuncture and intravenous cannulation: a systematic review and network meta-analysis | bc6ecf5e-759e-4e2f-bea6-3fd0c1975693 | 11887248 | Surgical Procedures, Operative[mh] | Needle procedures, such as venipuncture and intravenous cannulation, are the most frequently performed procedures in hospitals and one of the most common painful sources for children . As reported, 71% of the hospitalized children and 57.1% of children visiting the emergency room underwent venipuncture or application of peripheral venous catheter. Procedure-induced pain was rated to be moderate and severe by 19.5-38.3% and 8.5-38.3% of children respectively, in different settings . Needle procedure-induced pain has short-term and long-term effects. In short term, pain can cause anxiety, fear and avoidance in children and distress in parents . In terms of long-time effects, repeated nociceptive procedures in early stage of life may contribute to the alteration of sensation and pain pattern at older ages . In addition, procedure-induced pain may interfere with the procedures. An autonomic response triggered by needle pain and fear may result in vasoconstriction, which, in turn, makes venipuncture and cannulation more difficult or even failed . Repeated procedures increase the suffering of children and may damage the relationship between nurses and parents. Due to the significant consequences of pain, pain has been highlighted as the fifth vital sign and gained more and more attention of nurses. Accordingly, some guidelines have been established to manage pain in children during venipuncture and intravenous cannulation . It is a priority of nurses to manage pain in children through adequate and effective interventions. Pharmacological and non-pharmacological methods have been recommended for effective management of procedural pain in children . In order to relieve pain during venipuncture and intravenous cannulation, there have existed multiple approaches, such as acupressure , distraction and hypnosis , sugar , local analgesia methods (topical anesthetics, vapocoolant spray and Buzzy), and so on. Among the approaches, topical anesthetics play a vital role in reducing pain for children with needle procedures. There are several types of topical anesthetic agents, formulations and drug delivery systems in use. Traditional agents utilized as topical anesthetics include eutectic mixture of lidocaine and prilocaine (EMLA) and various lidocaine or amethocaine formulations. The EMLA contains 2.5% lidocaine and 2.5% prilocaine which is widely used and usually regarded as “golden standard” to relieve pain during venipuncture and intravenous cannulation . The EMLA is available either in the form of cream or patch. The EMLA cream is an oil and water emulsion of lidocaine and prilocaine. The EMLA patch applies a small dressing to enhance the effect of cream. They are usually effective about 60 minutes’ application . Lidocaine cream, including ELA-Max or Maxilene, commonly uses for pain control and recommends a 30-minute onset time . Another agent is amethocaine or Ametop which contains 4% gel of amethocaine and requires application time ranging from 30 min to 45 min . Novel drug-delivery systems include lidocaine iontophoresis, lidocaine/tetracaine heating patch, pressurized lidocaine delivery system. Lidocaine iontophoresis is a transdermal drug delivery system that uses an electric current to carry ionized lidocaine across the intact skin and requires several minutes for anesthetic to take effects . The lidocaine/tetracaine heating patch is a novel drug delivery system that uses controlled heat to enhance the delivery of a eutectic mixture of 70 mg lidocaine and 70 mg tetracaine through the skin . The pressurized lidocaine delivery system is a needle-free lidocaine injection device. It employs compressed gas to generate the pressure that delivers the stream or particles of lidocaine to penetrate into the skin and induces dermal analgesia within seconds . In addition, non-pharmacological methods including vapocoolant spray and Buzzy are widely used for local pain relief in children undergoing venipuncture and intravenous cannulation. Vapocoolant spray is a cold spray which produces rapid cooling of the skin via evaporation, decreases the speed of impulse conduction through sensory nerves, and thereby reduces pain. It is a rapid-acting alternative to traditional topical anesthetics . Vibration and cold device (Buzzy) is a bee-shaped device applying a battery-operated vibration and ice to produce analgesia immediately . With so many methods available, nurses may be confronted with such a situation that they need choose the most effective one from two or more local analgesia measures. Under that situation, information on relative efficacy of these interventions is critical. There have been several meta-analyses comparing the efficacy of two local analgesia methods or one local analgesia with placebo/routine care to provide information for nurses when selecting pain relief methods for children . For instance, Lander et al. compared amethocaine with EMLA cream and found that amethocaine was more effective in preventing pain in children with venipuncture and intravenous cannulation. These meta-analyses synthesizing direct evidence of head-to-head trials provide valuable information to nurses on relative effects of some two local analgesia methods. However, the information is insufficient for nurses facing the selection between local analgesia methods which have not been directly compared in previous studies. Thus, this study aimed to use a network meta-analysis to compare multiple local analgesia methods simultaneously and produce estimates of the relative effects between any pair of them and find the most effective intervention in pain control. Child-reported pain was the primary outcome of the current study considering that pain is a subjective experience and the child-reported pain would be the most valid indicator for pain. In addition, indicators related to the selection of a local analgesia method were included as secondary outcomes, consisting of success rate at the first attempt, pain assessed by others, anxiety, fear, satisfaction, difficulty of procedure and skin adverse effects.
Literature search strategy The following databases were searched for relevant studies: PubMed, Embase, CINAHL, Scopus, Web of Science, and The Cochrane Library. The published date was from January1, 1990 to December 1, 2024 and the language of publication was restricted to English. Initial search terms included “topical anesthetic”, “local anesthetic”, “EMLA”, “lidocaine/prilocaine cream”, “lidocaine, prilocaine drug combination”, “lidocaine”, “liposomal lidocaine”, “ELA-Max”, “Maxilene”, “vapocoolants”, “vapocoolant spray”, “amethocaine”, “Ametop”, “tetracaine”, “lidocaine iontophoresis”, “lidocaine tetracaine patch”, “RaPydan”, “synera”, “s-caine”, “needle free system”, “needleless system”, “J-tip”, “INJEX”, “ALGRX”, “Buzzy”, “catheterization, peripheral”, “phlebotomy”, “blood specimen collection”, “venipuncture”, “intravenous cannula*”, “intravenous puncture”, “intravenous insert*”, “intravenous placement”, “intravenous catheter*”, “intravenous access”, “intravenous injection”, “intravenous infusion”, “blood draw*”, “blood sampling” “venous cannula*”, “venous puncture”, “venous insert*”, “venous placement”, “venous catheter*”, “venous access”, “venous injection”, “venous infusion”, “child”, “child*”, and “adolescent”. For each database, the search strategy was personalized. An example search in the PubMed database was shown in the Supplementary File . After eligible articles were identified, the reference lists of the eligible articles were manually searched. Included articles in conventional pairwise meta-analyses on this topic were screened as well to avoid possible missing of eligible studies. Inclusion and exclusion criteria Studies were included if they met the following criteria: (1) the study compared the analgesic effects of different local analgesia methods, local analgesia methods with placebo, or with routine care; (2) the local analgesia methods were noninvasive and applied on the skin surface; (3) the local analgesia methods were used for procedures of peripheral venipuncture and intravenous cannulation; (4) the study design was a randomized controlled trial; (5) participants were children aged between 2 and 19 years; (6) the language publication is limited to English. Studies were excluded if (1) the local analgesia methods were applied for peripheral central venous catheter(PICC) or Totally implantable venous access port systems(Port) indewlling; (2) the intervention was a compound method, that is, the intervention integrated more than one pain management method (e.g. topical anesthetics plus virtual reality); (3) data or the full text was not available. Study selection and data extraction All records of literature search were imported to the Endnote to eliminate duplicates. Two researchers read the titles and abstracts to screen for potential eligible studies. Then the same researchers independently evaluated the qualification of studies and extracted data. Disagreements between them were resolved by a third researcher. Information extracted from the included studies comprised the author, year of publication, country, participant age, sample size, local analgesia methods (name/ /dose/application duration), comparison intervention, needle gauge, study setting, cause for procedure, venipuncture site (dorsum of hand/antecubital area/others), pain measurement tool, pain measuring timing (during/after), primary outcome (child-reported pain), secondary outcome (success rate at the first attempt/pain assessed by others/anxiety/fear/satisfaction/difficulty of procedure /skin adverse effects). For studies with pain measured multiple times, only the values measured during or immediately after needle procedure were used. Results of a same intervention with different doses in one study were pooled if the analysis showed no difference in analgesic effect between doses. For studies only reporting median, interquartile range, median or full range, mean and standard deviation (SD) were calculated according to the estimating formulae of Wan . If two types of scales were employed in the same objects in one study, the data with more information was used. Quality assessment The Cochrane handbook for systematic reviews of interventions 5.1.0 was used to assess the quality of included studies. Potential sources of bias include random sequence generation, allocation concealment, blinding of participants and staff, blinding of outcome assessors, incomplete outcome data, and selective reporting. The risk of bias from each potential source is evaluated as high, low or unclear. Two researchers independently assessed the risks of bias, and discrepancies were resolved by the third researcher. Data analysis A frequentist network meta-analysis combining direct and indirect comparisons in a random-effects model was conducted using the “network” and “mvmeta” packages in the software Stata SE version15.1 (StataCorp LP. College Station, TX, USA). Effect sizes were standardized mean differences (SMDs) because included studies involved different pain rating scales. By combining both direct and indirect evidence across a network of studies, network meta-analysis can compare multiple interventions simultaneously in a single analysis and produce estimates of the relative effects between any pair of interventions in the network. In addition, it can provide estimation of the ranking of the interventions. To valid a network meta-analysis, a core assumption of transitivity should be fulfilled. Transitivity means that different sets of studies included in a network meta-analysis should be similar in important effect modifiers, which makes the estimates from indirect comparisons plausible and comparable to direct evidence. The statistical manifestation of transitivity is consistency. In the present study, we used both global (the global Wald test) and local approaches (node splitting method) to check the inconsistency. For the global approach, inconsistency is evaluated in the entire network by modifying the network meta-analysis model to account for potential inconsistency, whereas the local approach detects potential inconsistent loops of evidence in the network. If p values were greater than 0.05 in the global Wald test and node splitting analysis, it indicates that there was no significant inconsistency . The comparisons of interventions were illustrated with a network map. Relative effects between two interventions were displayed with a league table or a forest plot. The ranking probabilities for all interventions were estimated using the probability of being best, mean rank, the surface under the cumulative ranking curve (SUCRA) . The SUCRA is a numeric presentation of the overall ranking with a single number for each intervention. SUCRA values range from 0 to 100%. The greater the SUCRA value (closer to 100%), the higher the likelihood that the intervention is in the top rank; on the contrary, the smaller the SUCRA value (closer to 0), the more likely that the intervention is in the bottom rank. A funnel plot and Egger’s test were used to detect the presence of any significant publication bias in the network meta-analysis. Assessment of the certainty of the evidence Confidence of the evidence estimates from the network meta-analysis was assessed based on the CINeMA (Confidence in Network Meta-Analysis) approach. The CINeMA framework is implemented in a freely available, user-friendly web application aiming to facilitate the evaluation of confidence in the results from network meta-analysis. It covers 6 domains: within-study bias (referring to the impact of risk of bias in the included studies), reporting bias (referring to publication and other reporting bias), indirectness, imprecision, heterogeneity and incoherence. Each domain was judged at 3 levels (major concerns, no concerns, some concerns) to each domain. Judgments across domains can be summarised to obtain 4 levels of confidence for each relative treatment effect (very low, low, moderate, or high) .
The following databases were searched for relevant studies: PubMed, Embase, CINAHL, Scopus, Web of Science, and The Cochrane Library. The published date was from January1, 1990 to December 1, 2024 and the language of publication was restricted to English. Initial search terms included “topical anesthetic”, “local anesthetic”, “EMLA”, “lidocaine/prilocaine cream”, “lidocaine, prilocaine drug combination”, “lidocaine”, “liposomal lidocaine”, “ELA-Max”, “Maxilene”, “vapocoolants”, “vapocoolant spray”, “amethocaine”, “Ametop”, “tetracaine”, “lidocaine iontophoresis”, “lidocaine tetracaine patch”, “RaPydan”, “synera”, “s-caine”, “needle free system”, “needleless system”, “J-tip”, “INJEX”, “ALGRX”, “Buzzy”, “catheterization, peripheral”, “phlebotomy”, “blood specimen collection”, “venipuncture”, “intravenous cannula*”, “intravenous puncture”, “intravenous insert*”, “intravenous placement”, “intravenous catheter*”, “intravenous access”, “intravenous injection”, “intravenous infusion”, “blood draw*”, “blood sampling” “venous cannula*”, “venous puncture”, “venous insert*”, “venous placement”, “venous catheter*”, “venous access”, “venous injection”, “venous infusion”, “child”, “child*”, and “adolescent”. For each database, the search strategy was personalized. An example search in the PubMed database was shown in the Supplementary File . After eligible articles were identified, the reference lists of the eligible articles were manually searched. Included articles in conventional pairwise meta-analyses on this topic were screened as well to avoid possible missing of eligible studies.
Studies were included if they met the following criteria: (1) the study compared the analgesic effects of different local analgesia methods, local analgesia methods with placebo, or with routine care; (2) the local analgesia methods were noninvasive and applied on the skin surface; (3) the local analgesia methods were used for procedures of peripheral venipuncture and intravenous cannulation; (4) the study design was a randomized controlled trial; (5) participants were children aged between 2 and 19 years; (6) the language publication is limited to English. Studies were excluded if (1) the local analgesia methods were applied for peripheral central venous catheter(PICC) or Totally implantable venous access port systems(Port) indewlling; (2) the intervention was a compound method, that is, the intervention integrated more than one pain management method (e.g. topical anesthetics plus virtual reality); (3) data or the full text was not available.
All records of literature search were imported to the Endnote to eliminate duplicates. Two researchers read the titles and abstracts to screen for potential eligible studies. Then the same researchers independently evaluated the qualification of studies and extracted data. Disagreements between them were resolved by a third researcher. Information extracted from the included studies comprised the author, year of publication, country, participant age, sample size, local analgesia methods (name/ /dose/application duration), comparison intervention, needle gauge, study setting, cause for procedure, venipuncture site (dorsum of hand/antecubital area/others), pain measurement tool, pain measuring timing (during/after), primary outcome (child-reported pain), secondary outcome (success rate at the first attempt/pain assessed by others/anxiety/fear/satisfaction/difficulty of procedure /skin adverse effects). For studies with pain measured multiple times, only the values measured during or immediately after needle procedure were used. Results of a same intervention with different doses in one study were pooled if the analysis showed no difference in analgesic effect between doses. For studies only reporting median, interquartile range, median or full range, mean and standard deviation (SD) were calculated according to the estimating formulae of Wan . If two types of scales were employed in the same objects in one study, the data with more information was used.
The Cochrane handbook for systematic reviews of interventions 5.1.0 was used to assess the quality of included studies. Potential sources of bias include random sequence generation, allocation concealment, blinding of participants and staff, blinding of outcome assessors, incomplete outcome data, and selective reporting. The risk of bias from each potential source is evaluated as high, low or unclear. Two researchers independently assessed the risks of bias, and discrepancies were resolved by the third researcher.
A frequentist network meta-analysis combining direct and indirect comparisons in a random-effects model was conducted using the “network” and “mvmeta” packages in the software Stata SE version15.1 (StataCorp LP. College Station, TX, USA). Effect sizes were standardized mean differences (SMDs) because included studies involved different pain rating scales. By combining both direct and indirect evidence across a network of studies, network meta-analysis can compare multiple interventions simultaneously in a single analysis and produce estimates of the relative effects between any pair of interventions in the network. In addition, it can provide estimation of the ranking of the interventions. To valid a network meta-analysis, a core assumption of transitivity should be fulfilled. Transitivity means that different sets of studies included in a network meta-analysis should be similar in important effect modifiers, which makes the estimates from indirect comparisons plausible and comparable to direct evidence. The statistical manifestation of transitivity is consistency. In the present study, we used both global (the global Wald test) and local approaches (node splitting method) to check the inconsistency. For the global approach, inconsistency is evaluated in the entire network by modifying the network meta-analysis model to account for potential inconsistency, whereas the local approach detects potential inconsistent loops of evidence in the network. If p values were greater than 0.05 in the global Wald test and node splitting analysis, it indicates that there was no significant inconsistency . The comparisons of interventions were illustrated with a network map. Relative effects between two interventions were displayed with a league table or a forest plot. The ranking probabilities for all interventions were estimated using the probability of being best, mean rank, the surface under the cumulative ranking curve (SUCRA) . The SUCRA is a numeric presentation of the overall ranking with a single number for each intervention. SUCRA values range from 0 to 100%. The greater the SUCRA value (closer to 100%), the higher the likelihood that the intervention is in the top rank; on the contrary, the smaller the SUCRA value (closer to 0), the more likely that the intervention is in the bottom rank. A funnel plot and Egger’s test were used to detect the presence of any significant publication bias in the network meta-analysis.
Confidence of the evidence estimates from the network meta-analysis was assessed based on the CINeMA (Confidence in Network Meta-Analysis) approach. The CINeMA framework is implemented in a freely available, user-friendly web application aiming to facilitate the evaluation of confidence in the results from network meta-analysis. It covers 6 domains: within-study bias (referring to the impact of risk of bias in the included studies), reporting bias (referring to publication and other reporting bias), indirectness, imprecision, heterogeneity and incoherence. Each domain was judged at 3 levels (major concerns, no concerns, some concerns) to each domain. Judgments across domains can be summarised to obtain 4 levels of confidence for each relative treatment effect (very low, low, moderate, or high) .
Identification of relevant studies and characteristics of included studies Overall, 2565 records were identified through database search. After removing duplicates and reading titles and abstracts, 101 studies were left for full text reading. Finally, 40 studies met the inclusion criteria and were included in the meta-analysis. Of the 61 excluded studies, the reasons for exclusion were as follows: 6 studies had no accessible full text, 14 studies did not meet the age criteria, 18 studies did not meet the outcome criteria, 10 studies were not RCTs, 11 studies involved ineligible interventions and 2 studies were not published in English. Detailed screening and selection process are illustrated in Fig. . In total, 4481 participants were included in the network meta-analysis. The mean trial sample size ranges from 22 to 339. The average age of participants reported in the included studies ranged from 5.3 to 14.0 years and male participants accounted for 50.9% of the total population. Two studies were crossover RCTs and the rest were parallel-group RCTs. Two studies were multicentric and the remaining articles were monocentric. There are 37 two-arm trials and 3 three-arm trials. Nine local analgesia methods were included (EMLA cream in 13 studies, Buzzy in 12 studies, lidocaine cream in 7 studies, needle-free lidocaine injection system in 7 studies, vapocoolant spray in 3 studies, lidocaine iontophoresis in 4 studies, amethocaine in 3 studies, lidocaine/tetracaine heating patch in 3 studies and EMLA patch in 2 studies) (see Supplementary File ). Eight pain measurement scales were used including the Visual Analog Scale (23 studies) , the Facial Pain Scale-Revised (9 studies) , the Wong-Baker Faces Scale (9 studies) , the Oucher Scale (2 studies) , the Numeric Rating Scale (2 study) , the Color Analog Scale (1 study) , the Facial Affective Scale (1 study) and the Poker Chip Tool (1 study) . Eight studies used more than one scale for pain measurement . The most commonly used research setting was the emergency department (15 studies). The primary reasons for venipuncture and intravenous cannulation were blood tests (12 studies) and surgical procedures (7 studies), with other reasons including chemotherapy, blood transfusions, and fluid administration. The dorsum of the hand was the most frequently used site for needle procedures (21 studies), followed by the antecubital area (14 studies). Needle sizes ranged from 18G to 24G, with 22G being the most commonly used. Risk of bias assessment Supplementary File presents the risk of bias of the included studies. Twenty-two studies were evaluated as having a low risk of the methods of random sequence generation. More than half of the included studies did not report adequate information on their methods of allocation concealment (22 studies, 55.0%). Due to the different appearance of interventions, blinding for participants and personnel was not possible in some studies. Among them, 13 studies (32.5%) were evaluated as having a high risk of results being biased from non-blinding. The same 13 studies were considered to be high in the risk of bias from non-blinding of outcome assessment as well. The risk of bias from selective outcome reporting and others was low in all included studies. Briefly, the overall risk of bias was rated as high in 13 studies (32.5%), moderate in 4 studies (10.0%), and low in 23 studies (57.5%). Primary outcome (child-reported pain) The network map of available intervention comparisons in this study is shown in Fig. . Nodes in the network represent interventions and the size of the nodes is proportionate to the number of children receiving the intervention. Lines link direct comparisons of interventions and the thickness of the lines represents the number of trials included in each comparison. As shown in Fig. , the network of the studies included in the analysis is well connected. The most frequently compared intervention was EMLA cream, which was directly compared with all other interventions except vapocoolant spray and Buzzy. EMLA patch was the least compared intervention which was only directly compared with EMLA cream. Comparisons including needle-free lidocaine injection system versus placebo, vapocoolant spray versus placebo and Buzzy versus routine cares made large contributions to the network estimation. Neither the global Wald test nor the node splitting analysis (except lidocaine cream versus needle-free lidocaine injection system) was significant indicating that the whole network and loops were consistent and the prerequisite for network meta-analysis was satisfied. When compared with routine care and placebo, all the local analgesia methods except vapocoolant spray produced significant pain reduction (see Figs. and ). The relative effects of two interventions combining direct and indirect evidence are presented in a league table (Fig. ). The analysis revealed that amethocaine, Buzzy and lidocaine iontophoresis were better in relieving pain compared to vapocoolant spray. There were no significant differences in pain relief between the remaining interventions. The probability of being the best, mean rank and the SUCRA are presented in Supplementary File . According to the results, amethocaine ranked the highest with the probability of being the best (57.6%), mean rank (1.9) and SUCRA (90.8%). Followed by Buzzy and lidocaine iontophoresis with the probability of being the best (17.0% and 9.3%), mean rank (2.8 and 3.8) and SUCRA (81.7% and 71.7%), respectively. Vapocoolant spray was the least efficacious intervention with the probability of being the best (0%), mean rank (9.2) and SUCRA (18.4%). Secondary outcomes Success rate at the first attempt Fifteen studies reported success rate at the first attempt. Among them, 11 studies did not find difference in success rate at the first attempt between interventions and controls. Four studies reported higher success rate when using lidocaine/tetracaine heating patch (compared with EMLA cream), vapocoolant spray (compared with placebo), lidocaine cream (compared with placebo) and lidocaine iontophoresis (compared with placebo) (Supplementary File ). Pain assessed by others Pain was assessed by parents in 12 studies, by operators in 5 studies, and by observers in 10 studies. All the comparisons, except one comparing lidocaine/tetracaine heating patch with EMLA cream and one comparing needle-free lidocaine injection system with Buzzy, were local analgesia methods versus placebo or routine care. There was no difference in pain assessed by operators between lidocaine/tetracaine heating patch and EMLA cream. Needle-free lidocaine injection system and Buzzy showed no difference in pain reduction evaluated by parents. All the comparisons with placebo or routine care, except one comparing Buzzy with routine care , reported significant less pain in local analgesia group when assessed by observers (Supplementary File ). Anxiety Anxiety was assessed in 8 studies. Two studies showed significantly lower anxiety in the Buzzy group than the routine care group and three studies did not. Other studies did not find difference in anxiety in comparisons (EMLA cream versus routine care, lidocaine cream versus needle-free lidocaine injection system, and lidocaine cream versus Buzzy) (Supplementary File ). Fear Fear was assessed in 4 studies. Three studies showed less fear with local analgesia (needle-free lidocaine injection system and Buzzy) than routine care. No difference was found when needle-free lidocaine injection system was compared with EMLA cream and Buzzy (Supplementary File ). Satisfaction Satisfaction was assessed in 7 studies. Two studies reported greater satisfaction with lidocaine iontophoresis and vapocoolant spray when compared with placebo. Other studies did not show difference in satisfaction between comparisons (lidocaine iontophoresis versus EMLA cream, needle-free lidocaine injection system versus Placebo, lidocaine/tetracaine heating patch versus Placebo, lidocaine cream versus needle-free lidocaine injection system and Buzzy versus lidocaine cream) (Supplementary File ). Difficulty of procedure Eleven studies evaluated the difficulty of needle procedure (or ease of procedure) using different interventions. Nine studies did not find difference in the difficulty of procedure between interventions and controls. Two studies were in favor of needle-free lidocaine injection system (versus EMLA cream) and vapocoolant spray (versus placebo) (Supplementary File ). Adverse skin reactions Sixteen studies reported side effects of the skin including erythema, pallor, pruritus, discomfort, burning, tingling, and edema. Overall, the occurrence of skin reactions of local analgesia was common (0 to 90%), but the reactions were mild. Among the 16 studies, 13 did not find difference in the side effects of the skin between interventions and controls. Two studies showed that EMLA cream had more blanching than lidocaine cream and placebo. And one study reported more erythema with needle-free lidocaine injection system than placebo (Supplementary File ). Publication bias The funnel plot is displayed in Fig. . No substantial asymmetry was found through visually estimating the funnel plot and Egger’s test ( P = 0.348) indicated that there was no evidence of publication bias. Certainty of the evidence Certainty of evidence for each comparison was assessed using CINeMA. It showed that 89.1% (49) and 5.5% (3) of all the comparisons were judged “low” and “moderate” in confidence rating, respectively. Only 3.6% (2) comparisons (lidocaine iontophoresis versus routine care and amethocaine versus placebo) between two interventions were judged “high” in confidence rating (see Supplementary File ).
Overall, 2565 records were identified through database search. After removing duplicates and reading titles and abstracts, 101 studies were left for full text reading. Finally, 40 studies met the inclusion criteria and were included in the meta-analysis. Of the 61 excluded studies, the reasons for exclusion were as follows: 6 studies had no accessible full text, 14 studies did not meet the age criteria, 18 studies did not meet the outcome criteria, 10 studies were not RCTs, 11 studies involved ineligible interventions and 2 studies were not published in English. Detailed screening and selection process are illustrated in Fig. . In total, 4481 participants were included in the network meta-analysis. The mean trial sample size ranges from 22 to 339. The average age of participants reported in the included studies ranged from 5.3 to 14.0 years and male participants accounted for 50.9% of the total population. Two studies were crossover RCTs and the rest were parallel-group RCTs. Two studies were multicentric and the remaining articles were monocentric. There are 37 two-arm trials and 3 three-arm trials. Nine local analgesia methods were included (EMLA cream in 13 studies, Buzzy in 12 studies, lidocaine cream in 7 studies, needle-free lidocaine injection system in 7 studies, vapocoolant spray in 3 studies, lidocaine iontophoresis in 4 studies, amethocaine in 3 studies, lidocaine/tetracaine heating patch in 3 studies and EMLA patch in 2 studies) (see Supplementary File ). Eight pain measurement scales were used including the Visual Analog Scale (23 studies) , the Facial Pain Scale-Revised (9 studies) , the Wong-Baker Faces Scale (9 studies) , the Oucher Scale (2 studies) , the Numeric Rating Scale (2 study) , the Color Analog Scale (1 study) , the Facial Affective Scale (1 study) and the Poker Chip Tool (1 study) . Eight studies used more than one scale for pain measurement . The most commonly used research setting was the emergency department (15 studies). The primary reasons for venipuncture and intravenous cannulation were blood tests (12 studies) and surgical procedures (7 studies), with other reasons including chemotherapy, blood transfusions, and fluid administration. The dorsum of the hand was the most frequently used site for needle procedures (21 studies), followed by the antecubital area (14 studies). Needle sizes ranged from 18G to 24G, with 22G being the most commonly used.
Supplementary File presents the risk of bias of the included studies. Twenty-two studies were evaluated as having a low risk of the methods of random sequence generation. More than half of the included studies did not report adequate information on their methods of allocation concealment (22 studies, 55.0%). Due to the different appearance of interventions, blinding for participants and personnel was not possible in some studies. Among them, 13 studies (32.5%) were evaluated as having a high risk of results being biased from non-blinding. The same 13 studies were considered to be high in the risk of bias from non-blinding of outcome assessment as well. The risk of bias from selective outcome reporting and others was low in all included studies. Briefly, the overall risk of bias was rated as high in 13 studies (32.5%), moderate in 4 studies (10.0%), and low in 23 studies (57.5%).
The network map of available intervention comparisons in this study is shown in Fig. . Nodes in the network represent interventions and the size of the nodes is proportionate to the number of children receiving the intervention. Lines link direct comparisons of interventions and the thickness of the lines represents the number of trials included in each comparison. As shown in Fig. , the network of the studies included in the analysis is well connected. The most frequently compared intervention was EMLA cream, which was directly compared with all other interventions except vapocoolant spray and Buzzy. EMLA patch was the least compared intervention which was only directly compared with EMLA cream. Comparisons including needle-free lidocaine injection system versus placebo, vapocoolant spray versus placebo and Buzzy versus routine cares made large contributions to the network estimation. Neither the global Wald test nor the node splitting analysis (except lidocaine cream versus needle-free lidocaine injection system) was significant indicating that the whole network and loops were consistent and the prerequisite for network meta-analysis was satisfied. When compared with routine care and placebo, all the local analgesia methods except vapocoolant spray produced significant pain reduction (see Figs. and ). The relative effects of two interventions combining direct and indirect evidence are presented in a league table (Fig. ). The analysis revealed that amethocaine, Buzzy and lidocaine iontophoresis were better in relieving pain compared to vapocoolant spray. There were no significant differences in pain relief between the remaining interventions. The probability of being the best, mean rank and the SUCRA are presented in Supplementary File . According to the results, amethocaine ranked the highest with the probability of being the best (57.6%), mean rank (1.9) and SUCRA (90.8%). Followed by Buzzy and lidocaine iontophoresis with the probability of being the best (17.0% and 9.3%), mean rank (2.8 and 3.8) and SUCRA (81.7% and 71.7%), respectively. Vapocoolant spray was the least efficacious intervention with the probability of being the best (0%), mean rank (9.2) and SUCRA (18.4%).
Success rate at the first attempt Fifteen studies reported success rate at the first attempt. Among them, 11 studies did not find difference in success rate at the first attempt between interventions and controls. Four studies reported higher success rate when using lidocaine/tetracaine heating patch (compared with EMLA cream), vapocoolant spray (compared with placebo), lidocaine cream (compared with placebo) and lidocaine iontophoresis (compared with placebo) (Supplementary File ). Pain assessed by others Pain was assessed by parents in 12 studies, by operators in 5 studies, and by observers in 10 studies. All the comparisons, except one comparing lidocaine/tetracaine heating patch with EMLA cream and one comparing needle-free lidocaine injection system with Buzzy, were local analgesia methods versus placebo or routine care. There was no difference in pain assessed by operators between lidocaine/tetracaine heating patch and EMLA cream. Needle-free lidocaine injection system and Buzzy showed no difference in pain reduction evaluated by parents. All the comparisons with placebo or routine care, except one comparing Buzzy with routine care , reported significant less pain in local analgesia group when assessed by observers (Supplementary File ). Anxiety Anxiety was assessed in 8 studies. Two studies showed significantly lower anxiety in the Buzzy group than the routine care group and three studies did not. Other studies did not find difference in anxiety in comparisons (EMLA cream versus routine care, lidocaine cream versus needle-free lidocaine injection system, and lidocaine cream versus Buzzy) (Supplementary File ). Fear Fear was assessed in 4 studies. Three studies showed less fear with local analgesia (needle-free lidocaine injection system and Buzzy) than routine care. No difference was found when needle-free lidocaine injection system was compared with EMLA cream and Buzzy (Supplementary File ). Satisfaction Satisfaction was assessed in 7 studies. Two studies reported greater satisfaction with lidocaine iontophoresis and vapocoolant spray when compared with placebo. Other studies did not show difference in satisfaction between comparisons (lidocaine iontophoresis versus EMLA cream, needle-free lidocaine injection system versus Placebo, lidocaine/tetracaine heating patch versus Placebo, lidocaine cream versus needle-free lidocaine injection system and Buzzy versus lidocaine cream) (Supplementary File ). Difficulty of procedure Eleven studies evaluated the difficulty of needle procedure (or ease of procedure) using different interventions. Nine studies did not find difference in the difficulty of procedure between interventions and controls. Two studies were in favor of needle-free lidocaine injection system (versus EMLA cream) and vapocoolant spray (versus placebo) (Supplementary File ). Adverse skin reactions Sixteen studies reported side effects of the skin including erythema, pallor, pruritus, discomfort, burning, tingling, and edema. Overall, the occurrence of skin reactions of local analgesia was common (0 to 90%), but the reactions were mild. Among the 16 studies, 13 did not find difference in the side effects of the skin between interventions and controls. Two studies showed that EMLA cream had more blanching than lidocaine cream and placebo. And one study reported more erythema with needle-free lidocaine injection system than placebo (Supplementary File ).
Fifteen studies reported success rate at the first attempt. Among them, 11 studies did not find difference in success rate at the first attempt between interventions and controls. Four studies reported higher success rate when using lidocaine/tetracaine heating patch (compared with EMLA cream), vapocoolant spray (compared with placebo), lidocaine cream (compared with placebo) and lidocaine iontophoresis (compared with placebo) (Supplementary File ).
Pain was assessed by parents in 12 studies, by operators in 5 studies, and by observers in 10 studies. All the comparisons, except one comparing lidocaine/tetracaine heating patch with EMLA cream and one comparing needle-free lidocaine injection system with Buzzy, were local analgesia methods versus placebo or routine care. There was no difference in pain assessed by operators between lidocaine/tetracaine heating patch and EMLA cream. Needle-free lidocaine injection system and Buzzy showed no difference in pain reduction evaluated by parents. All the comparisons with placebo or routine care, except one comparing Buzzy with routine care , reported significant less pain in local analgesia group when assessed by observers (Supplementary File ).
Anxiety was assessed in 8 studies. Two studies showed significantly lower anxiety in the Buzzy group than the routine care group and three studies did not. Other studies did not find difference in anxiety in comparisons (EMLA cream versus routine care, lidocaine cream versus needle-free lidocaine injection system, and lidocaine cream versus Buzzy) (Supplementary File ).
Fear was assessed in 4 studies. Three studies showed less fear with local analgesia (needle-free lidocaine injection system and Buzzy) than routine care. No difference was found when needle-free lidocaine injection system was compared with EMLA cream and Buzzy (Supplementary File ).
Satisfaction was assessed in 7 studies. Two studies reported greater satisfaction with lidocaine iontophoresis and vapocoolant spray when compared with placebo. Other studies did not show difference in satisfaction between comparisons (lidocaine iontophoresis versus EMLA cream, needle-free lidocaine injection system versus Placebo, lidocaine/tetracaine heating patch versus Placebo, lidocaine cream versus needle-free lidocaine injection system and Buzzy versus lidocaine cream) (Supplementary File ).
Eleven studies evaluated the difficulty of needle procedure (or ease of procedure) using different interventions. Nine studies did not find difference in the difficulty of procedure between interventions and controls. Two studies were in favor of needle-free lidocaine injection system (versus EMLA cream) and vapocoolant spray (versus placebo) (Supplementary File ).
Sixteen studies reported side effects of the skin including erythema, pallor, pruritus, discomfort, burning, tingling, and edema. Overall, the occurrence of skin reactions of local analgesia was common (0 to 90%), but the reactions were mild. Among the 16 studies, 13 did not find difference in the side effects of the skin between interventions and controls. Two studies showed that EMLA cream had more blanching than lidocaine cream and placebo. And one study reported more erythema with needle-free lidocaine injection system than placebo (Supplementary File ).
The funnel plot is displayed in Fig. . No substantial asymmetry was found through visually estimating the funnel plot and Egger’s test ( P = 0.348) indicated that there was no evidence of publication bias.
Certainty of evidence for each comparison was assessed using CINeMA. It showed that 89.1% (49) and 5.5% (3) of all the comparisons were judged “low” and “moderate” in confidence rating, respectively. Only 3.6% (2) comparisons (lidocaine iontophoresis versus routine care and amethocaine versus placebo) between two interventions were judged “high” in confidence rating (see Supplementary File ).
The study comprehensively integrated data on 9 local analgesia methods from 40 randomized controlled trials and performed a network meta-analysis to provide information on effectiveness and relative efficacy of these interventions in children undergoing venipuncture and intravenous cannulation. Results showed that amethocaine, Buzzy, lidocaine iontophoresis, lidocaine/tetracaine heating patch, EMLA patch, EMLA cream, lidocaine cream and needle-free lidocaine injection system were effective in relieving pain of needle procedures in children, whereas vapocoolant spray was not better than placebo and routine care. Moreover, amethocaine, Buzzy and lidocaine iontophoresis were of the highest probability to be the most effective interventions. Amethocaine was found to be the most effective intervention in the network meta-analysis. In the network meta-analysis combining direct and indirect evidence, amethocaine was not superior than EMLA cream in pain control. This result is inconsistent with a previous meta-analysis which found amethocaine to be more efficacious than EMLA cream in pain relief . Considering that the meta-analysis in 2006 involved only two studies, the relative efficacy of amethocaine versus EMLA cream is inconclusive. More research is required to confirm the result. Buzzy is the secondly best intervention. The studies comparing Buzzy with routine care were published since the year of 2010 and mainly from Turkey. There were no direct comparisons between Buzzy and other interventions except one study with lidocaine cream and one with needle-free lidocaine injection system. Buzzy was superior than vapocoolant spray and showed equal effectiveness with other interventions. The results just relied on indirect comparisons only. Direct comparisons between each intervention are needed to confirm these findings. One study compared Buzzy combining the application of lidocaine cream with vapocoolant spray combining the use of lidocaine cream and showed that Buzzy was more effective in pain control, which in favor of the result of network analysis to some extent. Lidocaine iontophoresis uses an external current of the same charge as lidocaine to deliver lidocaine into the dermis and provide topical anesthesia of the skin and underlying tissue . Although it ranked 3 in the efficacy of pain relief in children undergoing venipuncture or intravenous cannulation, it has been relatively less used in children for venipuncture and intravenous cannulation compared with other local analgesia methods these years. Reasons for its limited application may include the availability of the delivery system and habits of nurses. In addition, many studies have reported intolerance of participants to the tingling and burning sensations associated with the application of iontophoresis, which may inhibit its use in practice as well . The incidence of tingling and burning was found to be 60% and 10%, respectively . However, compared with EMLA cream, lidocaine iontophoresis takes less time to establish analgesia in skin (13 min versus 60 min) , which is a major advantage for use in the current busy health care system. It is noteworthy that, among the 9 interventions, vapocoolant spray is the only ineffective intervention compared with both placebo and routine care. The result is consistent with previous traditional meta-analysis . The lack of benefit in children has been considered to be due to the cooling and/or burning sensation, caused by vapocoolant spray, which might be perceived by children as painful . The explanation was supported by the evidence that application of vapocoolant spray was evaluated to be more painful than application of placebo, which might offset its anesthetic effect on pain during venipuncture and intravenous cannulation . In this analysis, amethocaine, Buzzy, and lidocaine iontophoresis were more efficacious than vapocoolant spray. But the explanation of this result should be with caution for its effect relied on indirect evidence only. However, lidocaine/tetracaine heating patch, EMLA patch, EMLA cream, lidocaine cream and needle-free lidocaine injection system were not different in pain relief compared with vapocoolant spray. In addition, there were no differences in degree of pain reduction between the remaining interventions. One study showed that EMLA cream is equally effective as vapocoolant spray in reducing immunization pain in school-aged children. A study found that lidocaine cream was not different from vapocoolant spray in relieving puncture pain in children aged from 0 to 18, which supported the result of this study. However, Lunoe et al. revealed that needle-free lidocaine injection system was better than vapocoolant spray in pain relief for children aged from 1 to 6. Bourdier et al. confirmed that EMLA patch was more effective than Buzzy in pain control in children of 18 months to 6 years old. It is worth mentioning that pain assessment in the studies of Lunoe and Bourdier was performed by nurses other than by children themselves. Therefore, interpretation of the results of this network meta-analysis needs caution, and high-quality studies are still needed to verify the relevant results in the future. The findings provided evidence for the efficacy/inefficacy of lidocaine iontophoresis, lidocaine/tetracaine heating patch, EMLA cream, needle-free lidocaine injection system and vapocoolant spray in pain relief compared with placebo, and needle-free lidocaine injection system and Buzzy compared with routine care. Moreover, results of comparison of EMLA cream versus lidocaine cream, EMLA cream versus needle-free lidocaine injection system and EMLA cream versus EMLA patch also proved persuasive. The results of pairwise and network meta-analyses were consistent (see Supplementary File ). As reported, the absolute minimum clinically important difference for pain reduction was 8–40 mm (based on a 100-mm scale) . Since the results of our network meta-analysis are standardized, we used the smallest standard deviation (15.1) and the largest standard deviation (35.1) reported in the included studies for the VAS 0–100 scale to convert the standardized network meta-analysis results in Fig. into absolute values. We found that, compared to vapocoolant spray, amethocaine, Buzzy, and lidocaine iontophoresis reduced pain levels by 15.4–35.8, 12.4–28.8, and 10.5–24.6, respectively. This indicates that using 8 mm as the minimally clinically significant effect size, the reductions in pain levels for amethocaine, Buzzy, and lidocaine iontophoresis are all clinically meaningful. Compared to routine care, all interventions with statistically significant effects in Fig. showed pain reductions exceeding 8 mm after conversion. Similarly, compared to placebo, all statistically significant interventions achieved the minimally clinically significant effect size. However, if 40 mm is used as the threshold, only amethocaine demonstrated a clinically meaningful reduction in pain levels compared to both routine care and placebo. This suggests that selection of local analgesia should consider the child’s sensitivity to pain. For example, in routine settings, where moderate pain relief is sufficient, interventions such as Buzzy and lidocaine iontophoresis can be practical and effective alternatives. For high-stress or high-pain scenarios (e.g., children with needle phobia or previous traumatic experiences), amethocaine is the preferred choice due to its greater effect size. Limitations The main limitation of the study is the inconsistency between direct and indirect estimates of lidocaine cream versus needle-free lidocaine injection system. Although the global test showed no significant inconsistency treating the network as a whole, loop specific approach was performed in order to further evaluate the extent of inconsistency in the network. Loops refer to ‘evidence cycles’ formed by different pairwise comparisons in a network. Results showed that there was inconsistency in 2 out of 17 loops (11.8%) in our network in Fig. . The percentage of inconsistent loops is similar to 14% in previous studies . Both the inconsistent loops identified shared the same comparison (lidocaine cream versus needle-free lidocaine injection system) including only one study . Veroniki and colleagues considered that, in such cases, inconsistency is possibly introduced by this particular study . The only article that directly compared the needle-free lidocaine injection system with lidocaine cream was analyzed. It was not found that age of participants, needle gauge, venipuncture site, and venipuncture reasons included in this study were significantly different from others. However, it was found that some studies involving needle-free lidocaine injection system may rule out the discomfort caused by the application of the system itself, while some studies may not, which may be the source of inconsistency. Thus, future studies are needed to clearly distinguish between discomfort caused by the drug delivery system and venipuncture pain. Interpretation of results related with the comparison should be made with caution, for the presence of inconsistency may make the results more uncertain. The quality of the evidence was typically high risks of bias due to the differences of appearances of the treatment devices which were not available for blinding. In addition, the placebo in this analysis included placebo cream, jet placebo, saline and isopropyl alcohol. We assumed that the effects of the placebos were non-specific and similar across all interventions, but variations may in fact be present and result in uncertainty in the results. When deciding which local analgesia method to be used, not only the effectiveness but also the price of the interventions need to be considered. In addition, other factors such as the length of time to take effects, the clinical availability and the difficulty of procedure are also taken into account. For example, the cost-effectiveness analyses showed that the application of needle-free lidocaine injection system is the best choice during venipuncture in pediatric emergency department, and amethocaine has an advantage in reducing cost and time compared with EMLA cream. Moreover, in practice, factors such as the preferences of children and families, as well as non-pharmacological techniques like distraction, are often integral to the selection and application of local analgesia methods. However, these elements were not incorporated into the current analysis, which therefore constitutes a limitation of this study, as it provides a ‘stand-alone’ analysis that may not fully capture the complexities of real-world clinical environment. In addition, unpublished literature was not included, which may have introduced publication bias. Studies with non-significant or unfavorable results are less likely to be published, potentially skewing the findings towards more favorable outcomes.
The main limitation of the study is the inconsistency between direct and indirect estimates of lidocaine cream versus needle-free lidocaine injection system. Although the global test showed no significant inconsistency treating the network as a whole, loop specific approach was performed in order to further evaluate the extent of inconsistency in the network. Loops refer to ‘evidence cycles’ formed by different pairwise comparisons in a network. Results showed that there was inconsistency in 2 out of 17 loops (11.8%) in our network in Fig. . The percentage of inconsistent loops is similar to 14% in previous studies . Both the inconsistent loops identified shared the same comparison (lidocaine cream versus needle-free lidocaine injection system) including only one study . Veroniki and colleagues considered that, in such cases, inconsistency is possibly introduced by this particular study . The only article that directly compared the needle-free lidocaine injection system with lidocaine cream was analyzed. It was not found that age of participants, needle gauge, venipuncture site, and venipuncture reasons included in this study were significantly different from others. However, it was found that some studies involving needle-free lidocaine injection system may rule out the discomfort caused by the application of the system itself, while some studies may not, which may be the source of inconsistency. Thus, future studies are needed to clearly distinguish between discomfort caused by the drug delivery system and venipuncture pain. Interpretation of results related with the comparison should be made with caution, for the presence of inconsistency may make the results more uncertain. The quality of the evidence was typically high risks of bias due to the differences of appearances of the treatment devices which were not available for blinding. In addition, the placebo in this analysis included placebo cream, jet placebo, saline and isopropyl alcohol. We assumed that the effects of the placebos were non-specific and similar across all interventions, but variations may in fact be present and result in uncertainty in the results. When deciding which local analgesia method to be used, not only the effectiveness but also the price of the interventions need to be considered. In addition, other factors such as the length of time to take effects, the clinical availability and the difficulty of procedure are also taken into account. For example, the cost-effectiveness analyses showed that the application of needle-free lidocaine injection system is the best choice during venipuncture in pediatric emergency department, and amethocaine has an advantage in reducing cost and time compared with EMLA cream. Moreover, in practice, factors such as the preferences of children and families, as well as non-pharmacological techniques like distraction, are often integral to the selection and application of local analgesia methods. However, these elements were not incorporated into the current analysis, which therefore constitutes a limitation of this study, as it provides a ‘stand-alone’ analysis that may not fully capture the complexities of real-world clinical environment. In addition, unpublished literature was not included, which may have introduced publication bias. Studies with non-significant or unfavorable results are less likely to be published, potentially skewing the findings towards more favorable outcomes.
Our research provides comprehensive information on the efficacy of currently used local analgesia methods in children undergoing venipuncture or intravenous cannulation. Results showed that amethocaine, Buzzy, lidocaine iontophoresis, lidocaine/tetracaine heating patch, EMLA patch, EMLA cream, lidocaine cream, and needle-free lidocaine injection system were more effective in relieving pain compared to placebo and routine care. Amethocaine, Buzzy and lidocaine iontophoresis are most likely to be the most effective interventions. However, the evidence body from the results of network meta analysis was judged “low” on a whole. Due to the limited number of direct comparisons, interpretation of some results should be made with caution. This study highlights the need for direct comparisons between interventions, as many findings rely on indirect evidence. Specifically, further research is needed to directly compare lidocaine cream and needle-free lidocaine injection systems, as the results of this comparison introduce significant uncertainty. Future studies should also integrate factors such as patient preferences and non-pharmacological techniques which are commonly used alongside with local analgesia in clinical practice to better reflect the complexity of real-world clinical environment.
Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6 Supplementary Material 7
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Proteogenomic characterization of molecular and cellular targets for treatment-resistant subtypes in locally advanced cervical cancers | cac87abd-9c84-40ee-a345-0912c6b33448 | 11908047 | Biochemistry[mh] | Uterine cervical cancer (UCC) is the fourth most commonly diagnosed cancer and the fourth leading cause of cancer-related deaths in women . Early-stage UCC can be effectively treated with surgery. Accordingly, the mortality has been ascribed mainly to locally advanced UCC (LACC). The incidence of LACC has been high in under-developed countries , and remains still substantial in some high-income countries, such as Korea, Japan, and Taiwan . A standard treatment modality for LACC declared by National Cancer Institute (NCI) has been concurrent cisplatin-based chemoradiotherapy (CCRT) for the past twenty years. However, it has been argued that CCRT should be further customized to reflect clinical characteristics of LACC. For example, combinations of CCRT with immuno-oncology agents, such as PD-1 or PD-L1 inhibitors, have been exploited as promising modalities . However, these trials showed heterogeneous treatment responses and differential benefits depending on the stage, immune checkpoint expression, and/or mutation burden . Therefore, it is necessary to define LACC subtypes and then develop tailored treatments based on characteristics of the individual subtypes. Several genomic and/or transcriptomic analyses, including the Cancer Genome Atlas (TCGA), have identified subtypes of UCC based on genomic alterations, mRNAs, and/or their associated cellular pathways that reflect pathophysiological characteristics of patients . However, these studies have focused on surgically treated early-stage UCC. There has been thus a significant need for a comprehensive molecular characterization of LACC. The previous studies have investigated mainly genomic and mRNA alterations. However, signaling pathways (e.g., PI3K/AKT signaling) have been also shown to play significant roles in UCC pathogenesis, and proteins (e.g., phosphorylated AKT) central in these pathways have been proposed as therapeutic targets . To explore these protein/phosphorylation signatures, the TCGA study profiled the abundances or phosphorylation levels of proteins in UCC, but only for a limited set of 192 proteins using reverse phase protein arrays. Recent proteogenomic studies have demonstrated that mass spectrometry (MS)-based proteomic analysis can provide abundance and phosphorylation levels for larger proteomes, facilitating effective discovery of protein/phosphorylation signatures and their associated cellular and signaling pathways. Here, we present proteogenomic analysis of LACC patients who underwent primary radiotherapy with or without chemotherapy involving whole-exome sequencing (WES), RNA-sequencing, global proteomics, and phosphoproteomics, as well as single-cell RNA-seq (scRNA-seq) analysis. Our results provide 1) proteogenomic subtypes of LACC, 2) genomic, mRNA, and protein signatures defining these subtypes, 3) functional characteristics of the subtypes based on cellular pathways represented by the molecular signatures, and 4) subpopulations of epithelial, immune, and fibroblast cells associated with the subtypes through integration of scRNA-seq data. These results can contribute to subtype-dependent therapeutic stratification of LACC.
Proteogenomic analysis of UCC We collected treatment-naïve tumor tissues from 350 patients with LACC based on the following criteria, along with matched peripheral blood mononuclear cells from 251 of the patients: 1) stage IB2-IIA showing LACC characteristics [large tumor size (> 3 cm in diameter) and/or lymph node metastasis] treated with primary CCRT or radiotherapy according to the NCI guideline (107 patients); 2) stage IIB-IVA according to 2014 international federation of gynecology and obstetrics (FIGO) staging (212 patients); or 3) stage IVB treated by primary CCRT (31 patients) (Supplementary Table ). Our LACC cohort included a larger percentage (70%) of patients at stage IIB or higher (36.2% in TCGA , and 9.1% in Huang et al. ) with the median cellularity of 75.0% (Supplementary Fig. A and S1B). How WES, RNA-seq, global proteomics, phosphoproteomics, and scRNA-seq analyses were performed for individual samples is described in Supplementary Fig. C. Predominant alteration of keratinization-TP53 regulation axis in LACC We performed WES analysis for 251 patients for whom the matched PBMC samples were available. By comparing WES data from tumors of 251 patients and their matched PBMCs, we identified 55,397 somatic mutations affecting protein sequences (Supplementary Fig. D) and 14 significantly (q < 0.1) mutated genes (SMGs) in our cohort using MutSigCV (Fig. A, 2nd panel). To investigate the SMGs predominant in LACC, we compared their mutation frequencies with those in three previous cohorts including more early-stage tumors (TCGA , Ojesina et al. , and Huang et al. ) and found that mutation frequencies of STK11 , CASP8 , TGFBR2 , KRT10 , and DYNAP were significantly ( P < 0.05) higher in our LACC cohort (Fig. B, red-labeled genes). Next, we identified 12 genes frequently (> 1% of patients) altered by genome integration of human papillomavirus (HPV; Fig. A, 3rd panel), and 10 of them ( KRT5/13/14/16 , MUC4 , UBC , S100A9 , TPX2 , and GANAB ) had significantly higher integration frequencies in our LACC cohort than in the three previous cohorts (Fig. C). Finally, we identified 16 genes having frequent copy number alterations (CNAs) (Fig. A, 4th panel) and found that 13 of them ( HRNR , FLG/FLG2 , RPTN , TCHH , CRNN , RUFY2 , DNA2 , SLC25A16/20 , TET1 , PRKAR2A , and ARIH2 ) showed significantly higher CNA frequencies in our LACC cohort than in the TCGA cohort (Fig. D). To explore functional associations of these predominantly altered genes in LACC (PAG-LACC; Fig. B-D) with LACC pathogenesis, we performed gene set enrichment analysis (GSEA) for them using ConsensusPathDB . The PAG-LACC significantly represented keratinization, TP53 regulation, and toll-like receptor (TLR) cascade pathways (Supplementary Fig. E), suggesting that substantial dysregulation of these pathways are associated with development of LACC. In support, the absence of keratinization was reported to be suggestive for a higher tumor grade associated with LACC characteristics (larger tumor size and lymph node metastasis) , and the loss of TP53-dependent tumor suppression and innate immune response to HPV infection contributes to promoting tumor growth. Furthermore, we identified genes/proteins whose expression or phosphorylation levels correlated with alterations of (Fig. E). Interestingly, the alterations of these genes were significantly ( P < 0.01) enriched in SCC (Fig. E, Histology). To examine the functions of the genes/proteins correlated with the alterations of PAG-LACC, we performed GSEA for them (Supplementary Table ). The genes/proteins correlated with either KRT5/10/13/14/16 or DNA2/UBC/TPX2 alterations commonly represented the keratinization and apoptosis/TP53 regulation pathways (Fig. F, black labeled), supporting the importance of these pathways in LACC pathogenesis. On the other hand, the genes/proteins correlated with KRT5/10/13/14/16 alterations uniquely represented the pathways related to hypoxia (Hif-1 and glycolysis), cell cycle (AP-1, DNA replication, and RND1 GTPase cycle), and cell adhesion (Nectin adhesion and adherens junctions) (Fig. F, blue labeled). The genes/proteins correlated with DNA2/UBC/TPX2 alterations predominantly represented the pathways related to reactive oxygen species (ROS; glutathione and fatty acid degradation/pyruvate metabolism), phagocytosis, and actin cytoskeleton-extracellular matrix (ECM) (ECM-receptor interaction and regulation of RAC1 activity and actin cytoskeleton) (Fig. F, green labeled). These results suggest that the two sets of PAG-LACC can have the shared (keratinization and apoptosis/TP53 regulation pathways) and distinctive (blue and green labeled pathways in Fig. F) roles in LACC pathogenesis. Interestingly, the genes/proteins correlated with KRT5/10/13/14/16 or DNA2/UBC/TPX2 alterations represented both keratinization and apoptosis/TP53 regulation pathways, suggesting potential links between these pathways. To explore such links, we built a network model describing interactions among the PAG-LACC and their correlated genes/proteins involved in these pathways. TP53/63 are known to suppress expression of keratins and cornified envelop components whose disruption facilitates HPV release. Consistent with this previous finding, the network model showed that the loss of TP53 functions by DNA2/UBC/TPX2 mutations accompanied upregulation of cornified envelop components to prevent HPV release (Fig. G, top right). However, the loss of keratin functions by KRT5/10/13/14/16 could lead to the failure of such upregulation to increase the cornified envelop integrity, thereby rather promoting HPV release and tumor growth, consistent with upregulation of cell cycle genes/proteins (Fig. G, bottom) and its upstream signaling pathways (PI3K-AKT). These results suggest that the collective loss of keratinization-TP53 regulation axis by PAG-LACC can define the characteristics of LACC during development of SCC. Proteogenomic subtypes of LACC The TCGA study previously identified three subtypes of UCC based on mRNA data: Keratin-high and Keratin-low SCC, and ADC. However, the TCGA cohort included only 36.2% of stage IIB-IVA, and the TCGC subtypes were thus biased toward early-stage tumors. Moreover, how the whole proteome-level information, such as our global proteome and phosphoproteome data, can change the subtypes of the early-stage-enriched tumors remains elusive. Previously, global proteome profiling, not phosphoproteome profiling, has been performed in a few studies using liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis, but only for small cohort sizes (8 to 15) with low proportions of LACC. In this study, we generated global proteomes and phosphoproteomes from 146 LACC tumors with sufficiently large tumor wet weights to meet the required amounts of proteins and phosphopeptides using LC–MS/MS analysis, and also RNA-seq data for all 350 LACC tumors (Supplementary Fig. C). To identify the molecular subtypes of LACC, we performed clustering analysis on 1) 334 LACC tumors (272 SCC and 62 ADC) using mRNA data and 2) 146 LACC tumors (117 SCC and 29 ADC) using global proteome or phosphoproteome data. Because the different nature of SCC and ADC can confound the clustering, we employed a two-stage clustering that first clustered SCC only (1st stage) and then all tumors (2nd stage) based on the clustering results of SCC (Supplementary Fig. A). For mRNA data, the two-stage clustering identified three clusters of SCC (s-RNA1-3) at the 1st stage and four clusters (RNA1–4) of all LACC tumors (SCC + ADC) at the 2nd stage (Supplementary Fig. B; Supplementary Table A). RNA1-4 were characterized by up-regulation of 790 (rna1), 654 (rna2), 520 (rna3), and 914 (rna4) signature genes, respectively (Fig. A; Supplementary Table B). A majority of ADC (42 of 63) were found enriched in RNA2. We then used these mRNA signatures (rna1-4) to classify tumors in the TCGA cohort and found that 78.6% (198 of 252) could be categorized into RNA1-4 (Supplementary Fig. C, TCGA cohort). We further generated a merged cohort of patients reported by Medina-Martinez et al. , Espinosa et al. , and Shin et al. , which were also enriched with early-stage tumors, and found that 83.8% (62 of 74) could be also classified into RNA1-4 (Supplementary Fig. C, Merged cohort). The remaining tumors (21.4% in TCGA and 16.2% in the merged cohort) were not be classified into RNA1-4 (Supplementary Fig. C), which can make molecular subtypes different between early-stage tumors and LACC. For global proteome data, the two-stage clustering identified four clusters of SCC (s-Prot1-4) at the 1st stage and five clusters of all LACC tumors (Prot1–5) at the 2nd stage (Supplementary Fig. D). For phosphoproteome data, it also identified three clusters of SCC (s-Phos1-3) at the 1st stage and four clusters of all LACC tumors (Phos1–4) at the 2nd stage (Supplementary Fig. E). Prot1-5 and Phos1-4 were characterized by up-regulation of the cluster-specific signature proteins (Fig. B, prot1-5) and phosphoproteins (Fig. C, phos1-4), respectively (Supplementary Table B). Finally, we performed an integrative clustering of 146 tumors with both mRNA and protein data and identified six subtypes (Sub1–6) of LACC (Fig. D). Prot1 and Phos1 profiles (Fig. D, green boxes) further divided RNA1 to Sub1 and 2, and Prot2 profiles (Fig. D, orange boxes) divided RNA4 to Sub3 and 4, indicating that the protein data further subdivide the mRNA-based subtypes due to their complementary nature. We next compared survival of LACC patients in Sub1–6. While molecular subtyping would not be problematic because treatment-naïve samples were used, survival analysis can be problematic because distinct treatments can affect survival. We thus excluded 10 patients at stage IVB having distant metastases, and 9 patients who underwent surgery as the primary treatment modality, and used only patients who received primary CCRT for survival analysis. Sub3, 5, and 6 had relatively lower disease (local/regional recurrence or distant metastasis)-free survival (DFS) and local recurrence-free survival (LRFS) rates (Fig. E and Supplementary Fig. F) than Sub1 and 2, indicating their treatment-resistant nature. Interestingly, Sub4 showed better LRFS than the treatment-resistant Sub3, 5, and 6, but comparable DFS, suggesting a high rate of distant metastasis in Sub4 and thus a need for systematic chemotherapy. We next examined whether the SMGs and frequently mutated non-SMGs were significantly enriched in the treatment-resistant subtypes and found the following enrichments: 1) BPTF mutations in Sub3, 5, and 6 (Sub1 + 2 + 4 vs. Sub3 + 5 + 6), 2) CIC and GCN1 mutations in Sub5, and 3) STX11 , LRP1B , MUC3A , ITPR1 , THSD7A , PLXNA1 , LGR6 , ZC3H13 , PKHD1L1 , FAT1 , and MAGEC1 mutations in Sub6 or in ADC of Sub3 and 6 (Fig. F). In SCC, we identified the keratinization-TP53 regulation axis as a potential cause for LACC. To identify a potential cause for LACC in ADC, we then identified the genes/proteins whose expression and phosphorylation levels correlated with the ADC-enriched alterations of the above 11 genes (Fig. G). The GSEA revealed that these genes/proteins represented N/O-linked glycosylation of mucins and apoptosis. The network model further demonstrated that 1) N-glycosylated molecules (e.g., CD44) could suppress TP53 via MDM2 activation ; and 2) O-glycosylation of mucins could produce tumor-associated antigens (Tn) and inhibit TP53 transcription , which could collectively facilitate tumor growth. These data suggest the collective aberration of N/O glycosylation-TP53 regulation axis can define the characteristics of LACC during development of ADC (Fig. H and I). Characteristics of proteogenomic subtypes of LACC To investigate functional characteristics of Sub1-6, we identified cellular pathways represented by mRNA and protein (protein + phosphorylation) signatures of each subtype (Supplementary Fig. A) through GSEA. For SCC Sub1-2 (RNA1 in Fig. D), their mRNA signatures (S1/2-G, rna1) significantly ( P < 0.05) represented the keratinization-TP53 regulation axis (Fig. A, blue-labeled; Supplementary Table ), which was suggested to be associated with PAG-LACC-driven development of LACC (Fig. G), as well as ROS-related pathways (biological oxidation and chemical carcinogenesis) to induce TP53 activation, which were represented by the genes/proteins correlated with DNA2 / UBC / TPX2 alterations (Fig. F). Sub1-2 can be thus considered to be early-stage squamous LACC, consistent with the findings that they had good DFS (Fig. E) and corresponded to the Keratin-high subtype in TCGA with good survival (RNA1 in Fig. a, TCGA cohort). The protein signatures defining Sub1 (S1-P; prot1 and phos1) consistently represented the same keratinization-TP53 regulation axis while those defining Sub2 (S2-P; prot5 and phos4) represented additionally platelet activation/complement cascade pathways (Fig. A, light blue-labeled). Collectively, these data suggest that both Sub1 and 2 are treatment-sensitive early-stage squamous LACC, but Sub2 may be a more advanced LACC with platelet/complement activation than Sub1. For Sub3 with mixed characteristics of SCC and ADC and SCC Sub4 (RNA4 in Fig. D), its mRNA signatures (S3/4-G, rna2) represented innate (leukocyte infiltration, phagocytosis, and antigen presentation) and adaptive (T/B-cell receptor signaling) immune pathways (Fig. A, yellow-labeled). Moreover, they also represented ECM pathways (collagen and proteoglycan; Fig. A, green-labeled). However, the protein signatures defining Sub4 (S4-P; prot5 and phos4) represented more strongly immune pathways while those defining Sub3 (S3-P; prot2 and phos3) represented further strongly ECM pathways, suggesting the different nature of immune responses between Sub3 and 4. To address this issue, we estimated the proportions of tumor, stromal, and immune cells in tumor microenvironment (TME) using the mRNA signatures previously defined for the cell types (Supplementary Fig. B). Confirming high immune activation in both Sub3 and 4 (ESTIMATE, Puleo, and Peng-Immune), this TME analysis further revealed that activated stroma to induce immune activation was found highly elevated in Sub3 compared to in Sub4 (Moffit, Puleo, Maurer, and Peng in Supplementary Fig. B), suggesting that they could be responsible for immune activation in Sub3. This can also explain strong activation of ECM pathways in Sub3, which was reported to be associated with poor survival via MMP2 activation . These data account for the treatment-resistant nature in Sub3 compared to in Sub4 according to the LRFS (Fig. F). The network model for Sub3 supported these findings that activated stroma secreted cytokines (IL33, CCL21, and CXCL9/10/11/12) for immune activation and produced integrins (ITGA2/4/5/7/L/M), collagens (COL1A1-2/2A1/3A1/5A1-2/6A1-3/8A1), and proteases (MMP2 and ADAMS2) for ECM activation (Fig. B). In contrast, the network model for Sub4 showed activation of the aforementioned immune pathways in response to tumor antigen (Supplementary Fig. C). We further performed immunohistochemistry (IHC) analysis for the representative markers MMP2 and ICOS for ECM activation and T-cell activation , respectively. The analysis confirmed upregulation of MMP2 in stromal cells of Sub3 tumors and upregulation of ICOS in the total area of tumor tissues of Sub4 tumors (Fig. C; see Methods for tumor-stromal distribution of these markers). Collectively, these results suggest that Sub3 and 4 are activated stroma-enriched treatment-resistant LACC and typical immunogenic treatment-sensitive squamous LACC, respectively. For SCC Sub5 (RNA3 in Fig. D), both gene (S5-G, rna3) and protein (S5-P, prot3) signatures represented EMT-related 1) signaling (TGFB/EGFR/Integrin/Basigin/HIF signaling) and 2) ECM remodeling (metalloproteinase/urokinase) pathways (Fig. A, red-labeled). The network model for Sub5 confirmed upregulation of these pathways (Fig. D), and IHC analysis further confirmed upregulation of representative markers BSG , VAV2 , EGFR , and FOSL1 for EMT-related signaling pathways in the tumor area of tissues in Sub5 (Fig. E). Sub3-5 (RNA3-4 in Fig. D) corresponded to the Keratin-low subtype with poor survival in TCGA, but such characteristics were much stronger in Sub5 (RNA3) than in Sub3-4 (RNA4) (Fig. A). Moreover, Sub5 had stronger basal-like characteristics (Puleo and Peng in Supplementary Fig. B) and weaker immune activation (ESTIMATE, Puleo, and Peng) than Sub3-4. These EMT-high, keratin-low, basal-like, and immune-cold characteristics collectively contribute to the treatment-resistant nature of Sub5 (Fig. E). For ADC-enriched Sub6, genes (S6-G, rna2) and/or protein (S6-P, prot4 and phos2) signatures represented N/O-glycosylation (Golgi transport-modification) and mucin-related pathways (mucin glycosylation; Fig. A, dark green-labeled). Mucin-type O-glycosylated structures including Tn antigens are linked to metastasis and poor survival , contributing to the treatment-resistant nature of Sub6. In addition, ciliopathy pathway was also found upregulated in Sub6, consistent with a previous finding that the loss or abnormality of cilia structure was frequently observed in glandular cells of ADC . The network model for Sub6 confirmed upregulation of these pathways (Fig. F), and IHC analysis further confirmed upregulation of a representative marker GPC4 for N/O-glycosylation in the tumor area of tissues in Sub6 (Fig. C). These results suggest that Sub5 is treatment-resistant Keratin-low/immune-cold squamous LACC while Sub6 is treatment-resistant ADC-enriched LACC, respectively. EMT-inducing CIC mutations in treatment-resistant LACC Sub5 Deficiency of CIC in the nucleus was shown to promote cell growth and invasion by derepressing expression of ETV4 that can facilitate EMT . We showed that CIC mutations were enriched in the treatment-resistant Sub5 (Fig. G), which mainly occurred on the C-terminal region containing its nuclear localization signal (Supplementary Fig. D) and could contribute to the loss of nuclear CIC. Moreover, the mRNA level of ETV4 was upregulated in Sub5 as an mRNA signature of Sub5 (rna3 in Fig. GA and D). These data collectively propose a hypothesis that CIC mutations can cause the decrease of nuclear CIC, which leads to derepression of ETV4 mRNA expression and then contributes to EMT, a representative feature of Sub5. To test this hypothesis, we generated #6507A tumor cells carrying a frame shift deletion mutation in the C-terminal region of CIC from a treatment-resistant squamous Sub5 tumor and #6595 tumor cells from another treatment-resistant squamous Sub3 tumor as a control. Western blot analysis showed the significant decrease of nuclear CIC and also the substantial increase of cytosolic/nucleus ETV4 in #6507A (Sub5) cells compared to in #6595 (Sub3) cells (Fig. G and H). Moreover, the expression of epithelial cell (EC) markers CDH1 and CTNNA1 was decreased in #6507A cells compared to in #6595 cells while the expression of mesenchymal cell markers CDH2 and VIM was increased (Fig. G-I), indicating activation of EMT in #6507A (Sub5) cells. These data collectively support the hypothesis that CIC mutations can lead to EMT via the decreased nuclear CIC and the increased ETV4. Cellular heterogeneity associated with LACC Sub1-6 We next investigated what cellular subpopulations are associated with LACC Sub1-6. To this end, we newly collected the 16 samples (12 SCC and 4 ADC samples) for scRNA-seq analysis such that at least one sample was collected for each RNA subtype to model the cellular heterogeneity across RNA1-4. RNA-seq was also performed for these samples, and RNA subtypes were predicted based on rna1-4 signatures as described for TCGA and merged cohorts (Supplementary Fig. C). Nonetheless, the sample collection was biased toward some RNA subtypes (e.g., RNA4). To resolve this bias problem and to improve statistical power for characterization of cellular heterogeneity, we further integrated our scRNA-seq data with four previously reported datasets (GSE208653 with 2 SCC and 1 ADC samples; GSE236738 with 3 SCC samples; E-MTAB-12305 with 4 SCC samples; and S-BSST1035 with 3 SCC and 3 ADC samples). Using the quality control criteria in Supplementary Fig. A, we selected a total of 194,703 cells from our and previous data. We performed clustering analysis for these selected cells and identified 14 clusters and their marker genes (Supplementary Fig. B and S4C). For detailed understanding of epithelial cells (ECs), we further performed subclustering of cells in the epithelial cluster. To avoid potential artifacts that can arise by mixing ECs from SCC and ADC, we first performed the subclustering only using ECs from SCC samples and identified 7 EC subclusters (KRT1/13, GADD45B, AKR1C2, PGK1, CXCL10, MUC5AC, and CEACAM5 high ; Fig. A) and their marker genes (Fig. B). The marker genes of KRT1/13, GADD45B, AKR1C2 high subclusters showed 1) the largest overlaps with S1/2-G (rna1) and S1-P (prot1) (Fig. C); 2) the highest signature scores in Sub1 or 2 (Fig. D); and 3) significantly represented keratinization, TP53 signaling, and ROS pathways, the key pathways of Sub1-2 (Fig. A), respectively (Fig. E), indicating their strong association with Sub1-2. The marker genes of PGK1 and CXCL10 high subclusters showed the largest or significant overlaps with S5-G (rna3) and S5-P (prot3) (Fig. C); the highest signature scores in Sub5 (Fig. D); and represented EMT signaling (TGFB/EGFR/Integrin/HIF) and ECM remodeling (metalloproteinase/urokinase) pathways (Fig. E), the key pathways of Sub5 (Fig. A), indicating their associations with Sub5. The marker genes of MUC5AC high subcluster showed the largest overlap with S6-G (rna2) and significant overlaps with protein signatures [S2/3-P (prot5) and S6-P (prot4)] of ADC-associated Sub3 and 6 (Fig. C); the highest signature scores in Sub3 and 6 (Fig. D); and represented the representative pathway of Sub6, O-linked glycosylation of mucin (Fig. E), suggesting its associations with Sub3 and 6. These results suggest that distinct EC subpopulations appear to dominate Sub1-6 (Fig. A, parenthesis). To examine the relationships between ECs in SCC and ADC, we next transferred the labels of the above 7 SCC EC subclusters into ECs in ADC samples (Fig. F). The majority (82.7%) of ADC ECs were labeled with MUC5AC high (66.9%) and CEACAM5 high (15.8%) subclusters (Fig. F) whose marker genes represented O-linked glycosylation of mucin (Fig. E). These results indicate that ADC ECs are present even in SCC samples, but in a relatively smaller proportion [e.g., 6.0% of MUC5AC high in SCC ECs (Fig. A) vs. 66.9% in ADC ECs (Fig. F)], and there appear to be no EC subpopulations unique to ADC, as indicated by a small proportion (5.9%) of ECs with no SCC EC subcluster labels transferred. Of note, however, the marker genes of CEACAM5 high subcluster, unlike the MUC5AC high subcluster, showed low signature scores for Sub6 (Fig. D), due to the significant overlaps with S1/2-G (rna1) and S5-G (rna3), besides S6-P (prot4), which caused to dilute their signature scores for Sub6. To examine what subpopulations of myeloid cells are associated with Sub1-6, we next performed subclustering of macrophage, dendritic cells (DC), and mast cells in Supplementary Fig. B and identified 8 subclusters [mast cell; CD1C/LAMP3/CLEC9A high DC and plasmacytoid DC (pDC); and C1QB/FCGR3B/FCN1 high macrophage] (Fig. G) and their marker genes (Supplementary Fig. D). The marker genes of the mast cell and CD1C/LAMP3/CLEC9A high DC/pDC and C1QB high macrophage subclusters showed 1) the largest overlaps with mRNA [S3/4-G (rna4)] and protein [S2/3-P (prot5) or S4-P (prot2)] signatures of immunogenic Sub3-4 (Fig. H); 2) the highest signature scores in Sub3-4 (Fig. I); and 3) represented innate (phagocytosis and antigen presentation) and adaptive (CD4/8 + T-cell recruitment and activation/inhibition) immune pathways (Fig. J), consistent with their previously reported functions , suggesting their associations with the immunogenic Sub3-4. Of note, although the protein signatures of Sub4 represented more strongly the immune pathways (Fig. A), infiltrated proportions of these immune cells appeared to be comparable between Sub3 and 4, consistent with the findings from the TME analysis (Supplementary Fig. B). The marker genes of the FCGR3B and FCN1 high macrophage subclusters showed the largest overlaps with S5-G (rna3) and/or S5-P (prot3) of Sub5; the highest signature scores in Sub5; and represented IL-17 and oncostatin M signaling pathways, the key immune pathways of Sub5 (Fig. A), as well as neutrophil activation pathways (neutrophil extracellular trap formation, NETosis, which can be induced by Th17-mediated inflammation and suppress T-cell activation), suggesting their associations with the treatment-resistant immune-cold Sub5. Finally, we performed the same subclustering analysis for cancer-associated fibroblasts (CAF) and smooth muscle cell (SMC) clusters in Supplementary Fig. B (Supplementary Fig. E-S4I). Among the subclusters, the marker genes of PDGFD and CXCL1 high subclusters showed the largest overlaps with S3/4-G (rna4) and S2/3-P (prot5) of Sub3; the highest signature score in Sub3; and represented ECM pathways more strongly upregulated in Sub3 than in Sub4, as well as immune pathways (Fig. K-M), suggesting that they mainly constitute activated stroma in the treatment-resistant Sub3. Immune-suppressing pathways in treatment-resistant LACC Sub5 Among the treatment-resistant subtypes of LACC, the immune-cold squamous LACC Sub5 frequently exhibited aggressive local tumor growth even during the course of radiotherapy. To examine the modality of immunotherapy for this immune-cold Sub5, we first examined whether there could be immune checkpoints associated with suppression of T-cell activation in Sub5. Among the immune checkpoints, PVR, which induces immune evasion of tumor cells through its binding with TIGIT on T-cells, showed elevation of both mRNA and protein levels in Sub5 (Fig. A) and also higher expression levels in PGK1 and CXCL10 high ECs upregulated in Sub5 than in the other EC subpopulations (Supplementary Fig. A). The IHC analysis further confirmed upregulation of PVR proteins in Sub5 (Fig. B). We then examined the interactions between PVR and TIGIT using multiplex fluorescence IHC stain and spatial proximity distance analysis and found that co-localization of PVR-expressing tumor cells and TIGIT-expressing cells within 30 μm was most evident in Sub5 compared to in the other subtypes (Fig. C), suggesting the increased PVR-TIGIT interactions in Sub5. These results collectively support the possibility that PVR can serve as a potential target for the treatment-resistant immune-cold Sub5. Several myeloid subpopulations, such as suppressive neutrophils and macrophages, have been also reported to play critical roles in suppression of T-cell activation . Thus, we next investigated whether these cells could contribute to suppression of T-cell activation in Sub5. Both mRNA and protein signatures for Sub5 significantly represented IL-17 signaling pathway (Fig. A), suggesting the presence of Th17 that can recruit these suppressive cells via IL-17 in Sub5. To check the presence of Th17 cells in Sub5, we performed subclustering of T-cell and NK cell clusters in Supplementary Fig. B and identified 8 T/NK cell subclusters and their marker genes (Supplementary Fig. B and S5C). The marker genes of CD4 + T-cell subcluster, including Th17 cells, had a significant overlap with S5-G (rna3); relatively higher signature scores in Sub5 than in Sub1-2; and significantly represented Th17 cell differentiation (Supplementary Fig. D-S5F). Also, this CD4 + T-cell subcluster included a substantial proportion of Th17 cells expressing IL-17 (Supplementary Fig. B, inlet). These data collectively support the presence of Th17 cells in Sub5. Moreover, the marker genes of FCGR3B and FCN1 high macrophage subclusters significantly represented IL-17 signaling, as well as neutrophil activation (Fig. J). These data collectively suggest a hypothesis that these macrophages with neutrophil-like characteristics may serve as the above suppressive cells activated by IL-17 released from Th17 cells in Sub5. To examine this hypothesis, we first checked the presence of these neutrophil-like suppressive cells (NL-SCs) in Sub5 tumors by performing IHC analysis of CD66B, an established marker for NL-SCs , across tumors in Sub1-6. The analysis revealed that Sub5 tumors had the highest density of CD66B + cells, compared to the tumors in the other subtypes, suggesting the presence of NL-SCs (Fig. D). Moreover, we also calculated the signature scores using the Sub5 mRNA/protein signatures for IL-17 signaling across the myeloid subclusters and found that the signature score (i.e., IL-17 signaling activation) was significantly elevated in FCGR3B and FCN1 high macrophages, compared to in the other myeloid subclusters (Fig. E), supporting the above hypothesis. To further test this hypothesis, we next developed a preclinical mouse model with the #6507A (Sub5) cells used in Fig. G and H (Supplementary Fig. G). Of note, after trying various models including orthotopic cervix tumor models using the cells, we were successful only for intratongue implantation models that reflect cancer clinical phenotypes as previously described . Flow cytometry analysis showed higher percentages of IL-17R + NL-SCs in #6507A (Sub5) tumors than in the bone marrow, spleen, and blood (Fig. F and Supplementary Fig. H). NL-SCs mainly comprised cells expressing IL-17 receptors (IL-17R and IL-21R) in the tumors (Fig. G and Supplementary Fig. I). Moreover, chemotaxis/migration assays showed that IL-17 strongly induced the recruitment of NL-SCs in vitro (Fig. H and ). Finally, we examined the immunosuppressive function of NL-SCs by evaluating T-cell proliferation using carboxyfluorescein succinimidyl ester (CFSE) assays in the presence of NL-SCs (Fig. J). #6507A (Sub5) tumors showed higher mean fluorescence intensities (MFI) of CFSE in CD8 + T-cells with NL-SCs than in the control without NL-SCs (Fig. K and ). Moreover, among four major effector cytokines (Granzyme B, Perforin, IFN-γ, and TNF-α), expression of Granzyme B and Perforin was attenuated in CD8 + cytotoxic T cells co-cultured with NL-SCs (Fig. M). These data indicate that T-cell proliferation was disrupted by NL-SCs, supporting that NL-SCs can contribute to suppression of T-cell activation in Sub5 and thus serve as a potential target for the treatment-resistant immune-cold Sub5.
We collected treatment-naïve tumor tissues from 350 patients with LACC based on the following criteria, along with matched peripheral blood mononuclear cells from 251 of the patients: 1) stage IB2-IIA showing LACC characteristics [large tumor size (> 3 cm in diameter) and/or lymph node metastasis] treated with primary CCRT or radiotherapy according to the NCI guideline (107 patients); 2) stage IIB-IVA according to 2014 international federation of gynecology and obstetrics (FIGO) staging (212 patients); or 3) stage IVB treated by primary CCRT (31 patients) (Supplementary Table ). Our LACC cohort included a larger percentage (70%) of patients at stage IIB or higher (36.2% in TCGA , and 9.1% in Huang et al. ) with the median cellularity of 75.0% (Supplementary Fig. A and S1B). How WES, RNA-seq, global proteomics, phosphoproteomics, and scRNA-seq analyses were performed for individual samples is described in Supplementary Fig. C.
We performed WES analysis for 251 patients for whom the matched PBMC samples were available. By comparing WES data from tumors of 251 patients and their matched PBMCs, we identified 55,397 somatic mutations affecting protein sequences (Supplementary Fig. D) and 14 significantly (q < 0.1) mutated genes (SMGs) in our cohort using MutSigCV (Fig. A, 2nd panel). To investigate the SMGs predominant in LACC, we compared their mutation frequencies with those in three previous cohorts including more early-stage tumors (TCGA , Ojesina et al. , and Huang et al. ) and found that mutation frequencies of STK11 , CASP8 , TGFBR2 , KRT10 , and DYNAP were significantly ( P < 0.05) higher in our LACC cohort (Fig. B, red-labeled genes). Next, we identified 12 genes frequently (> 1% of patients) altered by genome integration of human papillomavirus (HPV; Fig. A, 3rd panel), and 10 of them ( KRT5/13/14/16 , MUC4 , UBC , S100A9 , TPX2 , and GANAB ) had significantly higher integration frequencies in our LACC cohort than in the three previous cohorts (Fig. C). Finally, we identified 16 genes having frequent copy number alterations (CNAs) (Fig. A, 4th panel) and found that 13 of them ( HRNR , FLG/FLG2 , RPTN , TCHH , CRNN , RUFY2 , DNA2 , SLC25A16/20 , TET1 , PRKAR2A , and ARIH2 ) showed significantly higher CNA frequencies in our LACC cohort than in the TCGA cohort (Fig. D). To explore functional associations of these predominantly altered genes in LACC (PAG-LACC; Fig. B-D) with LACC pathogenesis, we performed gene set enrichment analysis (GSEA) for them using ConsensusPathDB . The PAG-LACC significantly represented keratinization, TP53 regulation, and toll-like receptor (TLR) cascade pathways (Supplementary Fig. E), suggesting that substantial dysregulation of these pathways are associated with development of LACC. In support, the absence of keratinization was reported to be suggestive for a higher tumor grade associated with LACC characteristics (larger tumor size and lymph node metastasis) , and the loss of TP53-dependent tumor suppression and innate immune response to HPV infection contributes to promoting tumor growth. Furthermore, we identified genes/proteins whose expression or phosphorylation levels correlated with alterations of (Fig. E). Interestingly, the alterations of these genes were significantly ( P < 0.01) enriched in SCC (Fig. E, Histology). To examine the functions of the genes/proteins correlated with the alterations of PAG-LACC, we performed GSEA for them (Supplementary Table ). The genes/proteins correlated with either KRT5/10/13/14/16 or DNA2/UBC/TPX2 alterations commonly represented the keratinization and apoptosis/TP53 regulation pathways (Fig. F, black labeled), supporting the importance of these pathways in LACC pathogenesis. On the other hand, the genes/proteins correlated with KRT5/10/13/14/16 alterations uniquely represented the pathways related to hypoxia (Hif-1 and glycolysis), cell cycle (AP-1, DNA replication, and RND1 GTPase cycle), and cell adhesion (Nectin adhesion and adherens junctions) (Fig. F, blue labeled). The genes/proteins correlated with DNA2/UBC/TPX2 alterations predominantly represented the pathways related to reactive oxygen species (ROS; glutathione and fatty acid degradation/pyruvate metabolism), phagocytosis, and actin cytoskeleton-extracellular matrix (ECM) (ECM-receptor interaction and regulation of RAC1 activity and actin cytoskeleton) (Fig. F, green labeled). These results suggest that the two sets of PAG-LACC can have the shared (keratinization and apoptosis/TP53 regulation pathways) and distinctive (blue and green labeled pathways in Fig. F) roles in LACC pathogenesis. Interestingly, the genes/proteins correlated with KRT5/10/13/14/16 or DNA2/UBC/TPX2 alterations represented both keratinization and apoptosis/TP53 regulation pathways, suggesting potential links between these pathways. To explore such links, we built a network model describing interactions among the PAG-LACC and their correlated genes/proteins involved in these pathways. TP53/63 are known to suppress expression of keratins and cornified envelop components whose disruption facilitates HPV release. Consistent with this previous finding, the network model showed that the loss of TP53 functions by DNA2/UBC/TPX2 mutations accompanied upregulation of cornified envelop components to prevent HPV release (Fig. G, top right). However, the loss of keratin functions by KRT5/10/13/14/16 could lead to the failure of such upregulation to increase the cornified envelop integrity, thereby rather promoting HPV release and tumor growth, consistent with upregulation of cell cycle genes/proteins (Fig. G, bottom) and its upstream signaling pathways (PI3K-AKT). These results suggest that the collective loss of keratinization-TP53 regulation axis by PAG-LACC can define the characteristics of LACC during development of SCC.
The TCGA study previously identified three subtypes of UCC based on mRNA data: Keratin-high and Keratin-low SCC, and ADC. However, the TCGA cohort included only 36.2% of stage IIB-IVA, and the TCGC subtypes were thus biased toward early-stage tumors. Moreover, how the whole proteome-level information, such as our global proteome and phosphoproteome data, can change the subtypes of the early-stage-enriched tumors remains elusive. Previously, global proteome profiling, not phosphoproteome profiling, has been performed in a few studies using liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis, but only for small cohort sizes (8 to 15) with low proportions of LACC. In this study, we generated global proteomes and phosphoproteomes from 146 LACC tumors with sufficiently large tumor wet weights to meet the required amounts of proteins and phosphopeptides using LC–MS/MS analysis, and also RNA-seq data for all 350 LACC tumors (Supplementary Fig. C). To identify the molecular subtypes of LACC, we performed clustering analysis on 1) 334 LACC tumors (272 SCC and 62 ADC) using mRNA data and 2) 146 LACC tumors (117 SCC and 29 ADC) using global proteome or phosphoproteome data. Because the different nature of SCC and ADC can confound the clustering, we employed a two-stage clustering that first clustered SCC only (1st stage) and then all tumors (2nd stage) based on the clustering results of SCC (Supplementary Fig. A). For mRNA data, the two-stage clustering identified three clusters of SCC (s-RNA1-3) at the 1st stage and four clusters (RNA1–4) of all LACC tumors (SCC + ADC) at the 2nd stage (Supplementary Fig. B; Supplementary Table A). RNA1-4 were characterized by up-regulation of 790 (rna1), 654 (rna2), 520 (rna3), and 914 (rna4) signature genes, respectively (Fig. A; Supplementary Table B). A majority of ADC (42 of 63) were found enriched in RNA2. We then used these mRNA signatures (rna1-4) to classify tumors in the TCGA cohort and found that 78.6% (198 of 252) could be categorized into RNA1-4 (Supplementary Fig. C, TCGA cohort). We further generated a merged cohort of patients reported by Medina-Martinez et al. , Espinosa et al. , and Shin et al. , which were also enriched with early-stage tumors, and found that 83.8% (62 of 74) could be also classified into RNA1-4 (Supplementary Fig. C, Merged cohort). The remaining tumors (21.4% in TCGA and 16.2% in the merged cohort) were not be classified into RNA1-4 (Supplementary Fig. C), which can make molecular subtypes different between early-stage tumors and LACC. For global proteome data, the two-stage clustering identified four clusters of SCC (s-Prot1-4) at the 1st stage and five clusters of all LACC tumors (Prot1–5) at the 2nd stage (Supplementary Fig. D). For phosphoproteome data, it also identified three clusters of SCC (s-Phos1-3) at the 1st stage and four clusters of all LACC tumors (Phos1–4) at the 2nd stage (Supplementary Fig. E). Prot1-5 and Phos1-4 were characterized by up-regulation of the cluster-specific signature proteins (Fig. B, prot1-5) and phosphoproteins (Fig. C, phos1-4), respectively (Supplementary Table B). Finally, we performed an integrative clustering of 146 tumors with both mRNA and protein data and identified six subtypes (Sub1–6) of LACC (Fig. D). Prot1 and Phos1 profiles (Fig. D, green boxes) further divided RNA1 to Sub1 and 2, and Prot2 profiles (Fig. D, orange boxes) divided RNA4 to Sub3 and 4, indicating that the protein data further subdivide the mRNA-based subtypes due to their complementary nature. We next compared survival of LACC patients in Sub1–6. While molecular subtyping would not be problematic because treatment-naïve samples were used, survival analysis can be problematic because distinct treatments can affect survival. We thus excluded 10 patients at stage IVB having distant metastases, and 9 patients who underwent surgery as the primary treatment modality, and used only patients who received primary CCRT for survival analysis. Sub3, 5, and 6 had relatively lower disease (local/regional recurrence or distant metastasis)-free survival (DFS) and local recurrence-free survival (LRFS) rates (Fig. E and Supplementary Fig. F) than Sub1 and 2, indicating their treatment-resistant nature. Interestingly, Sub4 showed better LRFS than the treatment-resistant Sub3, 5, and 6, but comparable DFS, suggesting a high rate of distant metastasis in Sub4 and thus a need for systematic chemotherapy. We next examined whether the SMGs and frequently mutated non-SMGs were significantly enriched in the treatment-resistant subtypes and found the following enrichments: 1) BPTF mutations in Sub3, 5, and 6 (Sub1 + 2 + 4 vs. Sub3 + 5 + 6), 2) CIC and GCN1 mutations in Sub5, and 3) STX11 , LRP1B , MUC3A , ITPR1 , THSD7A , PLXNA1 , LGR6 , ZC3H13 , PKHD1L1 , FAT1 , and MAGEC1 mutations in Sub6 or in ADC of Sub3 and 6 (Fig. F). In SCC, we identified the keratinization-TP53 regulation axis as a potential cause for LACC. To identify a potential cause for LACC in ADC, we then identified the genes/proteins whose expression and phosphorylation levels correlated with the ADC-enriched alterations of the above 11 genes (Fig. G). The GSEA revealed that these genes/proteins represented N/O-linked glycosylation of mucins and apoptosis. The network model further demonstrated that 1) N-glycosylated molecules (e.g., CD44) could suppress TP53 via MDM2 activation ; and 2) O-glycosylation of mucins could produce tumor-associated antigens (Tn) and inhibit TP53 transcription , which could collectively facilitate tumor growth. These data suggest the collective aberration of N/O glycosylation-TP53 regulation axis can define the characteristics of LACC during development of ADC (Fig. H and I).
To investigate functional characteristics of Sub1-6, we identified cellular pathways represented by mRNA and protein (protein + phosphorylation) signatures of each subtype (Supplementary Fig. A) through GSEA. For SCC Sub1-2 (RNA1 in Fig. D), their mRNA signatures (S1/2-G, rna1) significantly ( P < 0.05) represented the keratinization-TP53 regulation axis (Fig. A, blue-labeled; Supplementary Table ), which was suggested to be associated with PAG-LACC-driven development of LACC (Fig. G), as well as ROS-related pathways (biological oxidation and chemical carcinogenesis) to induce TP53 activation, which were represented by the genes/proteins correlated with DNA2 / UBC / TPX2 alterations (Fig. F). Sub1-2 can be thus considered to be early-stage squamous LACC, consistent with the findings that they had good DFS (Fig. E) and corresponded to the Keratin-high subtype in TCGA with good survival (RNA1 in Fig. a, TCGA cohort). The protein signatures defining Sub1 (S1-P; prot1 and phos1) consistently represented the same keratinization-TP53 regulation axis while those defining Sub2 (S2-P; prot5 and phos4) represented additionally platelet activation/complement cascade pathways (Fig. A, light blue-labeled). Collectively, these data suggest that both Sub1 and 2 are treatment-sensitive early-stage squamous LACC, but Sub2 may be a more advanced LACC with platelet/complement activation than Sub1. For Sub3 with mixed characteristics of SCC and ADC and SCC Sub4 (RNA4 in Fig. D), its mRNA signatures (S3/4-G, rna2) represented innate (leukocyte infiltration, phagocytosis, and antigen presentation) and adaptive (T/B-cell receptor signaling) immune pathways (Fig. A, yellow-labeled). Moreover, they also represented ECM pathways (collagen and proteoglycan; Fig. A, green-labeled). However, the protein signatures defining Sub4 (S4-P; prot5 and phos4) represented more strongly immune pathways while those defining Sub3 (S3-P; prot2 and phos3) represented further strongly ECM pathways, suggesting the different nature of immune responses between Sub3 and 4. To address this issue, we estimated the proportions of tumor, stromal, and immune cells in tumor microenvironment (TME) using the mRNA signatures previously defined for the cell types (Supplementary Fig. B). Confirming high immune activation in both Sub3 and 4 (ESTIMATE, Puleo, and Peng-Immune), this TME analysis further revealed that activated stroma to induce immune activation was found highly elevated in Sub3 compared to in Sub4 (Moffit, Puleo, Maurer, and Peng in Supplementary Fig. B), suggesting that they could be responsible for immune activation in Sub3. This can also explain strong activation of ECM pathways in Sub3, which was reported to be associated with poor survival via MMP2 activation . These data account for the treatment-resistant nature in Sub3 compared to in Sub4 according to the LRFS (Fig. F). The network model for Sub3 supported these findings that activated stroma secreted cytokines (IL33, CCL21, and CXCL9/10/11/12) for immune activation and produced integrins (ITGA2/4/5/7/L/M), collagens (COL1A1-2/2A1/3A1/5A1-2/6A1-3/8A1), and proteases (MMP2 and ADAMS2) for ECM activation (Fig. B). In contrast, the network model for Sub4 showed activation of the aforementioned immune pathways in response to tumor antigen (Supplementary Fig. C). We further performed immunohistochemistry (IHC) analysis for the representative markers MMP2 and ICOS for ECM activation and T-cell activation , respectively. The analysis confirmed upregulation of MMP2 in stromal cells of Sub3 tumors and upregulation of ICOS in the total area of tumor tissues of Sub4 tumors (Fig. C; see Methods for tumor-stromal distribution of these markers). Collectively, these results suggest that Sub3 and 4 are activated stroma-enriched treatment-resistant LACC and typical immunogenic treatment-sensitive squamous LACC, respectively. For SCC Sub5 (RNA3 in Fig. D), both gene (S5-G, rna3) and protein (S5-P, prot3) signatures represented EMT-related 1) signaling (TGFB/EGFR/Integrin/Basigin/HIF signaling) and 2) ECM remodeling (metalloproteinase/urokinase) pathways (Fig. A, red-labeled). The network model for Sub5 confirmed upregulation of these pathways (Fig. D), and IHC analysis further confirmed upregulation of representative markers BSG , VAV2 , EGFR , and FOSL1 for EMT-related signaling pathways in the tumor area of tissues in Sub5 (Fig. E). Sub3-5 (RNA3-4 in Fig. D) corresponded to the Keratin-low subtype with poor survival in TCGA, but such characteristics were much stronger in Sub5 (RNA3) than in Sub3-4 (RNA4) (Fig. A). Moreover, Sub5 had stronger basal-like characteristics (Puleo and Peng in Supplementary Fig. B) and weaker immune activation (ESTIMATE, Puleo, and Peng) than Sub3-4. These EMT-high, keratin-low, basal-like, and immune-cold characteristics collectively contribute to the treatment-resistant nature of Sub5 (Fig. E). For ADC-enriched Sub6, genes (S6-G, rna2) and/or protein (S6-P, prot4 and phos2) signatures represented N/O-glycosylation (Golgi transport-modification) and mucin-related pathways (mucin glycosylation; Fig. A, dark green-labeled). Mucin-type O-glycosylated structures including Tn antigens are linked to metastasis and poor survival , contributing to the treatment-resistant nature of Sub6. In addition, ciliopathy pathway was also found upregulated in Sub6, consistent with a previous finding that the loss or abnormality of cilia structure was frequently observed in glandular cells of ADC . The network model for Sub6 confirmed upregulation of these pathways (Fig. F), and IHC analysis further confirmed upregulation of a representative marker GPC4 for N/O-glycosylation in the tumor area of tissues in Sub6 (Fig. C). These results suggest that Sub5 is treatment-resistant Keratin-low/immune-cold squamous LACC while Sub6 is treatment-resistant ADC-enriched LACC, respectively.
Deficiency of CIC in the nucleus was shown to promote cell growth and invasion by derepressing expression of ETV4 that can facilitate EMT . We showed that CIC mutations were enriched in the treatment-resistant Sub5 (Fig. G), which mainly occurred on the C-terminal region containing its nuclear localization signal (Supplementary Fig. D) and could contribute to the loss of nuclear CIC. Moreover, the mRNA level of ETV4 was upregulated in Sub5 as an mRNA signature of Sub5 (rna3 in Fig. GA and D). These data collectively propose a hypothesis that CIC mutations can cause the decrease of nuclear CIC, which leads to derepression of ETV4 mRNA expression and then contributes to EMT, a representative feature of Sub5. To test this hypothesis, we generated #6507A tumor cells carrying a frame shift deletion mutation in the C-terminal region of CIC from a treatment-resistant squamous Sub5 tumor and #6595 tumor cells from another treatment-resistant squamous Sub3 tumor as a control. Western blot analysis showed the significant decrease of nuclear CIC and also the substantial increase of cytosolic/nucleus ETV4 in #6507A (Sub5) cells compared to in #6595 (Sub3) cells (Fig. G and H). Moreover, the expression of epithelial cell (EC) markers CDH1 and CTNNA1 was decreased in #6507A cells compared to in #6595 cells while the expression of mesenchymal cell markers CDH2 and VIM was increased (Fig. G-I), indicating activation of EMT in #6507A (Sub5) cells. These data collectively support the hypothesis that CIC mutations can lead to EMT via the decreased nuclear CIC and the increased ETV4.
We next investigated what cellular subpopulations are associated with LACC Sub1-6. To this end, we newly collected the 16 samples (12 SCC and 4 ADC samples) for scRNA-seq analysis such that at least one sample was collected for each RNA subtype to model the cellular heterogeneity across RNA1-4. RNA-seq was also performed for these samples, and RNA subtypes were predicted based on rna1-4 signatures as described for TCGA and merged cohorts (Supplementary Fig. C). Nonetheless, the sample collection was biased toward some RNA subtypes (e.g., RNA4). To resolve this bias problem and to improve statistical power for characterization of cellular heterogeneity, we further integrated our scRNA-seq data with four previously reported datasets (GSE208653 with 2 SCC and 1 ADC samples; GSE236738 with 3 SCC samples; E-MTAB-12305 with 4 SCC samples; and S-BSST1035 with 3 SCC and 3 ADC samples). Using the quality control criteria in Supplementary Fig. A, we selected a total of 194,703 cells from our and previous data. We performed clustering analysis for these selected cells and identified 14 clusters and their marker genes (Supplementary Fig. B and S4C). For detailed understanding of epithelial cells (ECs), we further performed subclustering of cells in the epithelial cluster. To avoid potential artifacts that can arise by mixing ECs from SCC and ADC, we first performed the subclustering only using ECs from SCC samples and identified 7 EC subclusters (KRT1/13, GADD45B, AKR1C2, PGK1, CXCL10, MUC5AC, and CEACAM5 high ; Fig. A) and their marker genes (Fig. B). The marker genes of KRT1/13, GADD45B, AKR1C2 high subclusters showed 1) the largest overlaps with S1/2-G (rna1) and S1-P (prot1) (Fig. C); 2) the highest signature scores in Sub1 or 2 (Fig. D); and 3) significantly represented keratinization, TP53 signaling, and ROS pathways, the key pathways of Sub1-2 (Fig. A), respectively (Fig. E), indicating their strong association with Sub1-2. The marker genes of PGK1 and CXCL10 high subclusters showed the largest or significant overlaps with S5-G (rna3) and S5-P (prot3) (Fig. C); the highest signature scores in Sub5 (Fig. D); and represented EMT signaling (TGFB/EGFR/Integrin/HIF) and ECM remodeling (metalloproteinase/urokinase) pathways (Fig. E), the key pathways of Sub5 (Fig. A), indicating their associations with Sub5. The marker genes of MUC5AC high subcluster showed the largest overlap with S6-G (rna2) and significant overlaps with protein signatures [S2/3-P (prot5) and S6-P (prot4)] of ADC-associated Sub3 and 6 (Fig. C); the highest signature scores in Sub3 and 6 (Fig. D); and represented the representative pathway of Sub6, O-linked glycosylation of mucin (Fig. E), suggesting its associations with Sub3 and 6. These results suggest that distinct EC subpopulations appear to dominate Sub1-6 (Fig. A, parenthesis). To examine the relationships between ECs in SCC and ADC, we next transferred the labels of the above 7 SCC EC subclusters into ECs in ADC samples (Fig. F). The majority (82.7%) of ADC ECs were labeled with MUC5AC high (66.9%) and CEACAM5 high (15.8%) subclusters (Fig. F) whose marker genes represented O-linked glycosylation of mucin (Fig. E). These results indicate that ADC ECs are present even in SCC samples, but in a relatively smaller proportion [e.g., 6.0% of MUC5AC high in SCC ECs (Fig. A) vs. 66.9% in ADC ECs (Fig. F)], and there appear to be no EC subpopulations unique to ADC, as indicated by a small proportion (5.9%) of ECs with no SCC EC subcluster labels transferred. Of note, however, the marker genes of CEACAM5 high subcluster, unlike the MUC5AC high subcluster, showed low signature scores for Sub6 (Fig. D), due to the significant overlaps with S1/2-G (rna1) and S5-G (rna3), besides S6-P (prot4), which caused to dilute their signature scores for Sub6. To examine what subpopulations of myeloid cells are associated with Sub1-6, we next performed subclustering of macrophage, dendritic cells (DC), and mast cells in Supplementary Fig. B and identified 8 subclusters [mast cell; CD1C/LAMP3/CLEC9A high DC and plasmacytoid DC (pDC); and C1QB/FCGR3B/FCN1 high macrophage] (Fig. G) and their marker genes (Supplementary Fig. D). The marker genes of the mast cell and CD1C/LAMP3/CLEC9A high DC/pDC and C1QB high macrophage subclusters showed 1) the largest overlaps with mRNA [S3/4-G (rna4)] and protein [S2/3-P (prot5) or S4-P (prot2)] signatures of immunogenic Sub3-4 (Fig. H); 2) the highest signature scores in Sub3-4 (Fig. I); and 3) represented innate (phagocytosis and antigen presentation) and adaptive (CD4/8 + T-cell recruitment and activation/inhibition) immune pathways (Fig. J), consistent with their previously reported functions , suggesting their associations with the immunogenic Sub3-4. Of note, although the protein signatures of Sub4 represented more strongly the immune pathways (Fig. A), infiltrated proportions of these immune cells appeared to be comparable between Sub3 and 4, consistent with the findings from the TME analysis (Supplementary Fig. B). The marker genes of the FCGR3B and FCN1 high macrophage subclusters showed the largest overlaps with S5-G (rna3) and/or S5-P (prot3) of Sub5; the highest signature scores in Sub5; and represented IL-17 and oncostatin M signaling pathways, the key immune pathways of Sub5 (Fig. A), as well as neutrophil activation pathways (neutrophil extracellular trap formation, NETosis, which can be induced by Th17-mediated inflammation and suppress T-cell activation), suggesting their associations with the treatment-resistant immune-cold Sub5. Finally, we performed the same subclustering analysis for cancer-associated fibroblasts (CAF) and smooth muscle cell (SMC) clusters in Supplementary Fig. B (Supplementary Fig. E-S4I). Among the subclusters, the marker genes of PDGFD and CXCL1 high subclusters showed the largest overlaps with S3/4-G (rna4) and S2/3-P (prot5) of Sub3; the highest signature score in Sub3; and represented ECM pathways more strongly upregulated in Sub3 than in Sub4, as well as immune pathways (Fig. K-M), suggesting that they mainly constitute activated stroma in the treatment-resistant Sub3.
Among the treatment-resistant subtypes of LACC, the immune-cold squamous LACC Sub5 frequently exhibited aggressive local tumor growth even during the course of radiotherapy. To examine the modality of immunotherapy for this immune-cold Sub5, we first examined whether there could be immune checkpoints associated with suppression of T-cell activation in Sub5. Among the immune checkpoints, PVR, which induces immune evasion of tumor cells through its binding with TIGIT on T-cells, showed elevation of both mRNA and protein levels in Sub5 (Fig. A) and also higher expression levels in PGK1 and CXCL10 high ECs upregulated in Sub5 than in the other EC subpopulations (Supplementary Fig. A). The IHC analysis further confirmed upregulation of PVR proteins in Sub5 (Fig. B). We then examined the interactions between PVR and TIGIT using multiplex fluorescence IHC stain and spatial proximity distance analysis and found that co-localization of PVR-expressing tumor cells and TIGIT-expressing cells within 30 μm was most evident in Sub5 compared to in the other subtypes (Fig. C), suggesting the increased PVR-TIGIT interactions in Sub5. These results collectively support the possibility that PVR can serve as a potential target for the treatment-resistant immune-cold Sub5. Several myeloid subpopulations, such as suppressive neutrophils and macrophages, have been also reported to play critical roles in suppression of T-cell activation . Thus, we next investigated whether these cells could contribute to suppression of T-cell activation in Sub5. Both mRNA and protein signatures for Sub5 significantly represented IL-17 signaling pathway (Fig. A), suggesting the presence of Th17 that can recruit these suppressive cells via IL-17 in Sub5. To check the presence of Th17 cells in Sub5, we performed subclustering of T-cell and NK cell clusters in Supplementary Fig. B and identified 8 T/NK cell subclusters and their marker genes (Supplementary Fig. B and S5C). The marker genes of CD4 + T-cell subcluster, including Th17 cells, had a significant overlap with S5-G (rna3); relatively higher signature scores in Sub5 than in Sub1-2; and significantly represented Th17 cell differentiation (Supplementary Fig. D-S5F). Also, this CD4 + T-cell subcluster included a substantial proportion of Th17 cells expressing IL-17 (Supplementary Fig. B, inlet). These data collectively support the presence of Th17 cells in Sub5. Moreover, the marker genes of FCGR3B and FCN1 high macrophage subclusters significantly represented IL-17 signaling, as well as neutrophil activation (Fig. J). These data collectively suggest a hypothesis that these macrophages with neutrophil-like characteristics may serve as the above suppressive cells activated by IL-17 released from Th17 cells in Sub5. To examine this hypothesis, we first checked the presence of these neutrophil-like suppressive cells (NL-SCs) in Sub5 tumors by performing IHC analysis of CD66B, an established marker for NL-SCs , across tumors in Sub1-6. The analysis revealed that Sub5 tumors had the highest density of CD66B + cells, compared to the tumors in the other subtypes, suggesting the presence of NL-SCs (Fig. D). Moreover, we also calculated the signature scores using the Sub5 mRNA/protein signatures for IL-17 signaling across the myeloid subclusters and found that the signature score (i.e., IL-17 signaling activation) was significantly elevated in FCGR3B and FCN1 high macrophages, compared to in the other myeloid subclusters (Fig. E), supporting the above hypothesis. To further test this hypothesis, we next developed a preclinical mouse model with the #6507A (Sub5) cells used in Fig. G and H (Supplementary Fig. G). Of note, after trying various models including orthotopic cervix tumor models using the cells, we were successful only for intratongue implantation models that reflect cancer clinical phenotypes as previously described . Flow cytometry analysis showed higher percentages of IL-17R + NL-SCs in #6507A (Sub5) tumors than in the bone marrow, spleen, and blood (Fig. F and Supplementary Fig. H). NL-SCs mainly comprised cells expressing IL-17 receptors (IL-17R and IL-21R) in the tumors (Fig. G and Supplementary Fig. I). Moreover, chemotaxis/migration assays showed that IL-17 strongly induced the recruitment of NL-SCs in vitro (Fig. H and ). Finally, we examined the immunosuppressive function of NL-SCs by evaluating T-cell proliferation using carboxyfluorescein succinimidyl ester (CFSE) assays in the presence of NL-SCs (Fig. J). #6507A (Sub5) tumors showed higher mean fluorescence intensities (MFI) of CFSE in CD8 + T-cells with NL-SCs than in the control without NL-SCs (Fig. K and ). Moreover, among four major effector cytokines (Granzyme B, Perforin, IFN-γ, and TNF-α), expression of Granzyme B and Perforin was attenuated in CD8 + cytotoxic T cells co-cultured with NL-SCs (Fig. M). These data indicate that T-cell proliferation was disrupted by NL-SCs, supporting that NL-SCs can contribute to suppression of T-cell activation in Sub5 and thus serve as a potential target for the treatment-resistant immune-cold Sub5.
We have performed comprehensive proteogenomic analysis for LACC. First, comparison of genomic alterations between early-stage UCC and LACC revealed potential factors (keratinization-TP53 regulation axis in SCC and O-glycosylation-TP53 regulation axis in ADC) that could develop aggressive phenotypes in LACC. Second, proteogenomic results revealed three treatment-resistant subtypes of LACC (Sub3, 5, and 6) and further identified the molecular and cellular characteristics for the treatment-resistant nature of Sub3 and 5, both of which belonged to the Keratin-low subtype in TCGA: activated stroma and ADC-like ECs for Sub3 and ECs with high EMT potential and CIC mutations/PVR/NL-SCs for Sub5. Therefore, our comprehensive proteogenomic analysis identified the subtypes of LACC and provided the more detailed molecular/cellular characterization of the treatment-resistant LACC subtypes compared to the previous omics analyses of early-stage UCC-enriched cohorts. The proteogenomic characterization of the treatment-resistant LACC subtypes can facilitate therapeutic stratification of these subtypes. First, for the immune-hot Sub3, activated stroma (PDGFD and CXCL1 high CAFs) and MUC5AC high ECs can be targeted simultaneously to inhibit the EC-driven tumor growth and the CAF-driven aggravated ECM activation at the same time. The activated stroma have been shown to cause chemoresistance and radioresistance , which can decrease the efficacy of primary-CCRT in LACC. Targeting these CAFs can thus improve the effectiveness of primary-CCRT using the following agents: 1) PDGFD neutralizing antibody, CR002 and MAB1159 (R&D systems, Catalog #: MAB1159) or inhibitors (crenolanib and imatinib ) of the PDGFD receptor PDGFRB for PDGFD high CAFs; and 2) CXCL1 inhibitor, Reparixin , or CXCL1 neutralizing antibody for CXCL1 high CAFs. Moreover, MUC5AC inhibitors, such as aclidinium and curcumin , can be treated together to simultaneously target MUC5AC high ECs. Second, for the immune-cold squamous Sub5, aggressive ECs (PGK1 and CXCL10 high ECs) can be targeted at the same time to suppress the elevated EMT using the following agents: PGK1 inhibitor, aryl/alkyl bisphosphonates , for PGK1 high ECs and CXCL10 inhibitor, an food drug administration (FDA)-approved atorvastatin , for CXCL10 high ECs. Moreover, the immunotherapy to inhibit PVR and NL-SCs (FCN1 and FCGR3B high macrophages) that suppress anti-tumor T-cell activation can be further used to release such suppression. TIGIT blocking antibody can be employed to reduce the tumor-induced suppression of T-cells in Sub5 tumors. In addition, IL-17 and IL-17R blockers (e.g., FDA-approved secukinumab and brodalumab ) could be used to reduce the recruitment of NL-SCs and thereby T-cell suppression mediated by NL-SCs. Combinations of these inhibitors and blockers should be explored to improve the therapeutic efficacy for Sub5. Finally, for the ADC Sub6, MUC5AC high ECs and aberrant O-glycosylated mucins can be targeted to inhibit aggressive tumor growth at the same time. Together with the aforementioned MUC5AC inhibitors targeting MUC5AC high ECs, Ac5GalNTGc can be employed to inhibit O-linked glycosylation of mucins . All these data strongly suggest that combinatorial therapeutic means targeting multiple modalities (stromal, immune, and tumor cells) should be employed to treat the treatment-resistant LACCs. Of note, Sub4 showed one of treatment-sensitive LACC subtypes with better survival than the above treatment-resistant subtypes, but worse survival than the treatment-sensitive Sub1-2. Integrated analysis of DFS and LRFS revealed that the medium prognosis could be due to a higher rate of distant metastasis in Sub4 than Sub1-2, which suggest that the more potent systematic chemotherapy and/or immuno-oncology agents are needed to improve the effectiveness of primary CCRT. To test the validity of the proposed treatment strategies, the organoid models or co-culture systems can be developed using cells derived from tumor tissues in the treatment-resistant subtypes. To this end, surface markers for 1) ECs for Sub3 and 6 (MUC5AC high ECs) and Sub5 (PGK1 and CXCL10 high ECs), 2) CAFs for Sub3 (PDGFD and CXCL1 high CAFs), and 3) NL-SCs for Sub5 (FCN1 and FCGR3B high macrophages) should be first identified from the marker genes of these subpopulations (scRNA-seq data), and the subpopulations can be then isolated from tumor tissues by FACS using their surface markers and/or the conventional markers for ECs (EPCAM), CAFs (FAP/ACTA2), and macrophages (CD68). After confirming upregulation of the marker genes used for labeling the subpopulations, the organoid models containing the subpopulations (e.g., MUC5AC high ECs + PDGFD/CXCL1 high CAFs + immune cells for Sub3 and PGK1/CXCL10 high ECs + FCN1/FCGR3B high macrophages + CD8 + T-cells for Sub5) can be generated. However, the organoids may be difficult to generate or not represent the subtype characteristics, such as upregulation of the representative pathways (immune and ECM pathways for Sub3 and EMT-related signaling pathways for Sub5). Alternatively, the co-culture systems can be developed for the subpopulation combinations. Using the organoid models or co-culture systems, the efficacy of the proposed treatment strategies can be tested using the aforementioned inhibitors and/or blockers for the subtype-associated cell types (e.g., reparixin or CXCL1 blocker for CXCL1 high CAFs). In this study, we demonstrated that the co-culture system of NL-SCs + CD8 + T-cells isolated from the mouse model could be used to show that NL-SCs suppress activation of CD8 + T-cells, which can be further used to test the efficacy of NL-SC inhibitors (e.g., IL-17 and IL-17R blockers). For the above therapeutic stratification of LACC, determination of the LACC subtypes for patients should proceed. First, genomic screening for the genes having the mutations enriched in the treatment-resistant subtypes (Fig. G) can be developed to predict the treatment-resistant nature. However, our WES data showed that somatic mutations of these genes were detected only in a subpopulation of the patients in the subtypes, thereby leading to false negatives in prediction of the treatment-resistance. To improve the prediction accuracy, we can further utilize the representative molecules for the following 1) key pathways and 2) subpopulations of tumor, stromal, and immune cells enriched in each subtype identified from our proteogenomic and scRNA-seq analyses: 1) keratinization and apoptosis/TP53 regulation pathways for Sub1-2 enriched with KRT1/13, GADD45B, AKR1C2 high ECs and additionally platelet/complement activation pathways for Sub2; 2) immune and ECM pathways for Sub3 enriched with the aforementioned CAFs and ECs; 3) conventional innate/adaptive immune pathways for Sub4 enriched with CD1C/LAMP3/CLEC9A high DC/pDC and C1QB high macrophages; 4) EMT and ECM remodeling pathways for Sub5 enriched with the aforementioned ECs and NL-SCs; and 5) O-line glycosylation of mucins for Sub6 enriched with MUC5AC high ECs. Besides the genomic screening, in practice, a panel of the representative mRNAs for the key pathways can be first developed, and IHC analysis for the representative proteins for both the key pathways and the enriched cell subpopulations can then further augment the genomic screening and mRNA panel-based predictions. Our in vitro experiments using #6507A tumor cells suggested that the levels of ETV4 and EMT markers could be increased in the Sub5 patients with the loss-of-function mutations of CIC. We thus compared both mRNA and protein levels of ETV4 and EMT-related markers (CDH2, VIM, BSG, VAV2, EGFR, and FOSL1) between Sub5 patients with and without CIC mutations. Unexpectedly, however, there were found to be no significant differences in mRNA and protein levels of these molecules. There could be several reasons: 1) there were only three patients who were found to carry the CIC mutations, and no reliable statistical decision could be drawn due to the low statistical power ( n = 3); 2) the sequencing depth of our WES data were around 100x, and the CIC mutations could be failed to be detected even if small subpopulations of tumor cells actually carried the mutations, making the labels of patients with and without the CIC mutations uncertain; 3) although CIC mutations were detected, they could not lead to the loss-of-function of CIC (e.g., missense mutation causing single amino acid variation) because the amount of functional CIC proteins in the nucleus is important, which could not be distinguished from proteogenomic data; and 4) mRNA and protein levels of the molecules were measured from the entire cells in the tumor tissues, and the levels could not truly represent those of these molecules in the tumor cells where CIC mutations affected their levels. Consistent with this finding, the similar insignificant differences were observed in the IHC data of the EMT-related markers (BSG, VAV2, EGFR, and FOSL1), possibly for the same reasons mentioned above. These results suggest that further detailed functional and clinical studies would be needed for the effect of CIC mutations using organoids and in vitro experiments in a large clinical cohort and also its potential clinical application in treating Sub5 patients. In this study, we proposed a hypothesis that Th17 cells release IL-17, which in turn activates NL-SCs and they then suppress activation of cytotoxic T-cells in Sub5 based on the results from our experiments and data analyses. First, T/NK cell subclustering analysis showed that the marker genes of CD4 + T-cell subcluster had a significant overlap with mRNA signature of Sub5, relatively high signature scores in Sub5, and represented Th17 cell differentiation, in addition to the fact that the subcluster included a substantial proportion of Th17 cells expressing IL-17. Based on these results, we hypothesized that Th17 cells could be present in Sub5. Despite these indications, however, the presence of Th17 cells should be validated in Sub5 tumors by IHC analysis using RORC antibodies. Second, based on the previous findings , we hypothesized that Th17 cells can serve as a major source of IL-17. However, other cells also can produce IL-17 in inflammatory conditions, including group3 innate lymphoid cells (ILC3), δγT cells, invariant NKT cells, and activated macrophages . It is thus needed to validate that Th17 cells truly act as a source of IL-17 in Sub5 tumors. To this end, we can isolate and culture Th17 cells from tumor tissues in Sub5 patients and then measure the released IL-17 in the culture media. Third, we showed that IL-17 strongly increased the migration of NL-SCs isolated from tumors in our mouse models. These results demonstrate a crucial role of IL-17 in the recruitment and activation of NL-SCs, consistent with the previous finding . It can be further confirmed that the released IL-17 in the culture media can activate the NL-SCs isolated from Sub5 tumors. Finally, our co-culture experiments of NL-SCs and CD8 + T-cells isolated from our mouse models revealed that NL-SCs could suppress T-cell activation, consistent with the previous finding . Despite the supporting data from our experiments and data analyses, the aforementioned experiments should be still carried out to validate our hypothesis on the regulatory axis of Th17-NL-SC-T-cell in Sub5. Our study has several issues that previous omics studies also had. First, tumor samples can also include non-tumor cells, which dilutes tumor-associated molecular signatures. To reduce this purity issue, we tried to focus on molecular signatures having consistent alteration patterns across all samples in individual clusters. Second, given local heterogeneity, locally sampled tissues for proteogenomic analysis may not represent disease states of the whole tumor which can cause inconsistency with observed phenotypes (clinical subtypes, metastasis, and survival). For example, locally sampled ADC tissues may include squamous cancer cells, especially in tumors with the adenosquamous nature, and the proteogenomic data for these tissues may include the mixed signatures of ADC and SCC. To resolve this issue partly, we performed scRNA-seq and identified EC subpopulations associated with Sub1-6 and tried to focus on consistent cellular pathways in both bulk proteogenomic and scRNA-seq data. Third, for the integrative analysis, we combined RNA-seq data (merged dataset) from multiple cohorts that included patients with heterogeneous clinical parameters and sample collection/storage conditions. To resolve this issue, we attempted to remove batch effects and focus on statistically powerful conserved signatures across different datasets. However, how much all these problems have been corrected is unclear, and the proposed signatures should be thus validated in larger clinical cohorts before clinical applications. Finally, our proteogenomic analyses are limited to providing correlative signatures, not causative associations.
Sample collection UCC tissue and blood samples were collected from patients prior to radiotherapy at the department of radiotherapy, National Cancer Center (NCC) in Korea from July 2004 to March 2020. Most samples were obtained via biopsy, and 68 samples were obtained from the Bio Bank of NCC, Korea. Pathologic diagnosis was made by two gynecological pathologists. UCC tissues obtained from patients who had undergone radiotherapy as the primary treatment were collected at the outpatient clinic before radiotherapy was initiated along with the blood samples. The tissues collected via biopsy were immediately immersed in liquid nitrogen. Surgical samples were carried in liquid nitrogen as soon as the tissues were removed in the operating room and transferred to a -80 °C deep freezer within 30 min. Sample and clinical data collections were approved by the NCC Institutional Review Board (IRB No. NCC 2016–0019) and informed consent was obtained from all patients. Staging workup included bimanual physical examination, chest and abdomino-pelvic computed tomoghraphy (CT), pelvic magnetic resonance imaging (MRI), and positron emission tomography (PET) scans in all patients. Sigmoidoscopy and cystoscopy were performed for all patients. All patients were clinically staged as International Federation of Gynecology and Obstetrics (FIGO) 2014 staging system. Radiotherapy Concomitant chemoradiotherapy (CCRT) consisted of whole pelvic external beam radiotherapy (EBRT) with chemotherapy and high-dose–rate (HDR) brachytherapy. For patients having poor physical performance, however, RT alone was administered with the curative aim. Patients with stage IVB patients were treated in diverse methods including CCRT, RT alone, post-RT combination chemotherapy, and CCRT + combination chemotherapy. Whole pelvic EBRT dose was 45 to 50.4 Gy. HDR brachytherapy consisted of 6 fractions of CT- (between 2004 and 2008) or MRI-based (since 2009) 3-dimensional image-guided intra-cavitary radiotherapy given twice a week with 5 Gy per fraction (total 30 Gy). The total biologically equivalent dose in 2-Gy fractions to Point A ranged from 72.3 to 102.2 Gy, with a median value of 87 Gy. The final primary tumor response was determined by physical examination, cervical cytology or biopsy if needed, and MRI at 3 months after radiotherapy. Local recurrence was defined as the presence of residual disease not resolved at 3 months after radiotherapy, which was confirmed by biopsy, or as the relapse at the cervix, vaginal, and/or parametrium. WES and RNA sequencing analysis Genomic DNA for WES was isolated from frozen biopsy tumor tissues and peripheral blood buffy coat of patients using the QIAamp DNA Mini kit (Qiagen GmbH, Hilden, Germany). Total RNA for RNA sequencing was extracted from the frozen biopsy tumor tissue using TRIzol (Invitrogen®, Carlsbad, CA, USA), followed by cleaning with the RNeasy Mini Kit (Qiagen GmbH®, Hilden, Germany). Using the isolated genomic DNA and RNA, we generated the sequencing libraries and then performed WES and RNA sequencing analyses following the Illumina’s standard protocols, as described in details in Supplementary Methods. The reads resulted from WES and RNA sequencing were aligned to the GRCh38 reference genome using BWA MEM (version 0.7.17) for WES data and STAR (version 2.4.0) for RNA sequencing data. For the WES data, we identified somatic mutations using GATK3.8 and Strelka2 (version 2.9.10) , significantly mutated genes (SMGs) using MutSigCV (version 1.4.1) , and then copy number alterations (CNAs) using CNVkit (version 0.9.9) . For the RNA sequencing data, the fragments per kilobase of transcript per million mapped reads (FPKM) at the gene level were calculated using RSEM (version 1.3.3) . See Supplementary Methods for the details regarding the preprocessing and analysis of WES and RNA sequencing data. HPV integration analysis To search for HPV integration sites, we attempted to identify the RNA-seq reads that contained the human genome component in one side and the viral genome component in the other side (called human-virus fusion reads) using the two previously reported approaches complementary to each other. In the first approach, we applied the Virus-Clip tool to align RNA-seq reads onto viral genome and obtained potential human-virus fusion reads. To remove the false positives, we separated the fusion reads into human and virus parts and first selected the ones with both parts longer than 21 bp (the minimum length for blast). For each selected fusion read, we then aligned both human and virus parts onto human transcriptome sequences (NCBI refseq RNA) using blastn (version 2.15.0) with default parameters. We further selected the fusion reads in which the human part was aligned (E-value < 1) onto human transcriptome while the virus part was not (E-value < 1) within 5 bp of the region (< 2-codon bp) where the human part was aligned. Based on these selected human-virus fusion reads, we next identified HPV integration sites as the ones supported by two fusion reads and more. In the second approach, as previously described in the TCGA study , we first applied the PathSeq tool (GATK version 4.2.2.0) to the RNA-seq data and identified non-human reads that were not aligned onto human genome (NCBI GRCh38). We then applied the CTAT-VIF tool (version 1.5.0) to the non-human reads and identified the human-virus fusion transcripts and their associated HPV sites. Finally, we combined the HPV integration sites identified from both approaches. Estimation of tumor cellularity Tumor cellularity was estimated based on histological images. For each sample, the percentage of tumor cells relative to all cells, including stromal, immune, and tumor cells, was estimated using the representative hematoxylin–eosin (HE)-stained sample slide. At least ten random high-power fields (HPFs) and up to 30 HPFs were microscopically evaluated, and the average tumor cell count of the total cell counts in each HE-stained slide was estimated as histological tumor cellularity. Global proteome and phosphoproteome analyses We cryopulverized each tumor tissue individually into tissue powder, as described previously , transferred the power to a new tube containing lysis buffer, centrifuged the lysate, and then extracted proteins. The resulting protein was digested by trypsin (V5111, Promega) with a slightly modified filter-aided sample preparation method . To generate the universal reference peptides, we pooled 60 μg of peptides from each tumor peptide sample. For each TMT set, the universal reference peptides (300 μg,126 channel) and ten different tumor samples (300 μg each, 127N through 131C channels) were labeled with 11-plex TMT reagent, according to the manufacturer’s instructions. After desalting, immobilized metal affinity chromatography (IMAC) phosphopeptide enrichment was performed on all TMT-labeled peptides. The flow-through non-phosphopeptide samples from the IMAC experiments were fractionated based on mid-pH reverse-phase liquid chromatography fractionation (mRP fractionation), as previously described . The previously developed DO-NCFC-RP/RPLC system was modified to produce up to 24 online NCFC fractions. This system was operated in one-dimensional RPLC mode (for global proteome) or two-dimensional RP/RPLC mode (for phosphoproteome). Both global proteome and phosphoproteome were analyzed using a quadrupole-orbitrap mass spectrometer (Q Exactive HF-X, Thermo Fisher Scientific) with an electric potential of 2.4 kV and desolvation capillary temperature at 250 °C for electrospray ionization. A sample-specific customized database was constructed with a slight modification to a previously reported method . MS/MS data for both global and phosphoproteome were processed using mPE-MMR for accurate precursor ion mass assignment. The refined MS/MS data were then subjected to MSGF + (version 9949) database search. For phosphoproteome datasets, the unidentified MS/MS data from the MSGF + search were further subjected to a spectral library search . Bipartite graph analysis using an in-house program was used to obtain protein groups from the identified peptides using a previously described process . The 11-plex TMT labeling was used to quantify the protein abundances of the universal reference (channel 126) and ten tumor tissues (channels 127N-131C). After correcting the isotope impurity, the intensities of each TMT reporter ion (126-131C) were extracted with a mass tolerance of 0.005 Da from all MS/MS scans and then normalized using quantile normalization. See Supplementary Methods for the details regarding sample preparation, LC–MS/MS analysis, and database search for global proteome and phosphoproteome analyses. Identification of molecules correlated with genetic alterations We used only expressed mRNAs, proteins, and phosphopeptides, respectively, that had FPKM > 1 (mRNAs) or were detected (proteins and phosphopeptides) in more than 50% of patients with protein and phosphorylation data available. For each SMG, we identified differentially expressed molecules between samples with and without alterations. To this end, for each molecule, we calculated a rank-sum statistic value and a log 2 -median-ratio. We then estimated the empirical null distributions of the rank-sum statistic value and log 2 -median-ratio via random permutation of all samples. Using the estimated empirical distributions, for each molecule, we computed adjusted p values for the observed rank-sum statistic value and log 2 -median-ratio, and then combined these p values using Stouffer’s method . Finally, we identified differentially expressed molecules as those with combined p values < 0.01 and absolute log 2 -median-ratios > a cutoff value, the mean of 2.5th and 97.5th percentiles of the empirical distribution for log 2 -median-ratios (e.g., log 2 -median-ratio = 0.45 for KRT5/10/13/14/16 ). Subtype identification We first selected molecules (mRNAs, proteins, or phosphopeptides) with abundance data across all samples clustered to avoid the bias from missing values. For the 1st stage clustering, we selected squamous tumors only and then top 10 (MAD10), 20 (MAD20), or 30% (MAD30) of molecules (mRNAs, proteins, or phosphopeptides) with the largest median absolute deviations (MADs). We performed a 1st orthogonal non-negative matrix factorization (ONMF ;) clustering for the squamous tumors using MAD10, MAD20, or MAD30. Based on cophenetic correlations and consensus heat maps, we determined the number of clusters (hi_k) and cluster memberships, as previously described . Before the 2nd ONMF clustering, we fixed the memberships of squamous tumors in an initial activation matrix, as described at the bottom of Supplementary Fig. A. Briefly, in the initial activation matrix, we set activation values for the squamous tumors to represent the memberships (e.g., [1 0 0 0] for a squamous tumor in s-Prot1). We also added zeros for the remaining activation values when the number of clusters (k) was larger than hi_k. For adenosquamous and adenocarcinoma, we assigned random activation values sampled from the uniform distribution. We performed the 2nd ONMF clustering with the initial activation matrix using the same MAD10, MAD20, or MAD30 molecules from squamous tumors with varying k. Based on cophenetic correlations, we finally determined k and cluster memberships. Identification of molecular signatures defining the subtypes To identify molecular signatures that defined the subtypes during clustering, we first defined ‘core samples’ for each subtype as the ones with positive silhouette width scores. To obtain the signature molecules defining each subtype, for each molecule, we compared log 2 -fold-changes in the core samples of the subtype with those of the other subtypes using the previously reported integrative statistical hypothesis testing method that computed an adjusted p value (p) by combining p values obtained from two sample t-test and the median ratio test. For each comparison, the putative signature molecules were selected as those with p < 0.05. We then further filtered the selected molecules by choosing the ones with 1) a median value of patients in the subtype larger than zero, 2) a median value of the remaining patients less than zero, and 3) a median value of the patients in the subtype larger than that of the remaining patients. Integrated clustering of subtypes identified from individual types of data An integrated clustering was performed using all three types of data (mRNA, global proteome, and phosphoproteome data). Briefly, for each type of data, a cluster identified from the individual data clustering was first converted to an indicator vector that included the ones for the samples in the subtype and zeros for the remaining samples. The indicator matrices for the three types of data were concatenated into the overall indicator matrix, which was then used as an input for k-means clustering. We selected the number of clusters (k, subtypes) as k = 6 (Sub1-6) after trying multiple k values and checking whether the subtypes resulted from the k-means clustering showed sufficient enrichment of clusters identified from the individual data. Cluster memberships of the samples were determined such that each sample was assigned to a subtype with the minimum distance to the subtype mean. Survival analysis Survival data were shown using Kaplan–Meier curves. Survival can be affected by treatment methods. Thus, to avoid biases in survival analysis, we excluded 36 patients who received RT alone, 15 patients who underwent surgery as a primary treatment, 8 patients who received palliative treatment or incomplete treatment, and 5 patients with treatment or survival information unavailable. In addition, we excluded 29 stage IVB patients that were treated with heterogeneous chemotherapeutic regimens during and after RT (Supplementary Table ). Pathway analysis For integrated pathway analysis, we first identified molecular signatures for Sub1-6 identified from the integrated clustering based on the relationships between Sub1-6 and the clusters identified from the three types of data. For example, for Sub1, we identified the genes (S1-G) selected for RNA1 identified from mRNA data and the proteins (S1-P) selected for Prot1 and Phos1 identified from proteome and phosphoproteome data, respectively. To identify the pathways represented by the genes and proteins for Sub1-6, we performed an enrichment analysis of cellular pathways for the genes and proteins selected for each subtype (e.g., S1-G and S1-P for Sub1) using ConsensusPathDB . The cellular pathways represented by the genes and proteins for each subtype were identified as those with p < 0.05, and the number of molecules involved in the pathway ≥ 3. Reconstruction of network models We first obtained protein–protein interactions (PPIs) from ten interactome databases, including BioGRID , HuRI , IntAct , HitPredict , IID , MINT , DIP , HPRD , HTRIdb , and STRING . For the list of molecules selected for network construction (molecules that have correlation with genetic alterations in Fig. G and J and molecular signatures involved in activated stroma-related processes associated with Sub3 in Fig. B, immune-related processes associated with Sub4 in Supplementary Fig. C, EMT-related processes associated with Sub5 in Fig. D, or the processes related to the production of proteoglycan and Tn antigen associated with Sub6 in Fig. F), we then extracted interactors of the selected molecules (i.e., the molecules and their 1st neighbors) as the nodes and the edges between them based on the PPIs. We visualized a network model to describe the extracted nodes and edges in Cytoscape (version 3.3.0) . Among the 1st neighbors in the network model, we left only the key 1st neighbors without which the connection between the nodes for the selected molecules disappeared. We next added the activation and inhibition reactions between the nodes in the network model obtained from the relevant KEGG pathways (e.g., regulation of actin cytoskeleton in Fig. G) . Finally, we arranged the nodes based on their localization obtained from the KEGG pathways. scRNA-seq Cellular suspensions were loaded onto a chromium controller (10 × Genomics) to generate nanoliter-sized gel bead-in-emulsions (GEMs) containing single cells, reagents, and a single gel bead containing barcoded oligonucleotides. Barcoded sequencing libraries were prepared using Chromium Next GEM Single Cell 3’ v3.1 Dual Index (10X Genomics) according to the manufacturer’s protocol. The sequencing libraries were sequenced on NovaSeq 6000 (Illumina) with the following read lengths: 28 base pairs (bp) for Read 1 (16 bp 10 × Barcode + 12 bp UMI), 10 bp for Sample Index (dual), and 90 bp for Read 2. Next, we aligned the resulting reads from the sequencing to the GRCh38 reference genome and performed the unique molecular identifier (UMI) counting using Cell Ranger software (v.7.0.1) . To improve statistical power for characterization of cellular heterogeneity in LACC, we also integrated scRNA-seq dataset generated from patients with SCC and ADC (GSE208653 , GSE236738 , E-MTAB-12305 , and S-BSST1035 ). Quality control, data normalization and integration, and cell clustering were performed using Seurat (v.4.0.4) . See Supplementary Methods for the details regarding the preprocessing and analysis of scRNA-seq data. Identification of marker genes for the individual cell clusters Using the final merged UMI matrix for each cell cluster (or subcluster), we computed the adjusted p -values, log-fold changes, proportion of cells in the cluster expressing the gene (pct.1) using the ‘scanpy.tl.rank_genes_groups’ function from scanpy (v.1.10.1) . Adjusted p -values (Pw) were calculated for HVGs using the Wilcoxon rank-sum test followed by the Benjamini–Hochberg method. Moreover, to focus on the genes predominantly expressed in the cluster compared to in the other clusters, we further computed adjusted p -values (Pt) from the previously reported empirical t-test for HVGs for the comparison of pct.1 values in the cluster vs. those in the other clusters. Finally, we identified marker genes for the cluster as the ones meeting the following criteria: 1) adjusted Pw < 0.01, 2) log-fold changes > 0.4 (~ 1.49-fold), and 3) adjusted Pt < 0.05, and 4) the highest pct.1 in the cluster compared to in the other clusters. To search for the subtype of LACC associated with the subtypes of the aforementioned four cell types, we first evaluated the significance of overlaps between 1) the bulk RNA and protein signatures for Sub1-6 (e.g., S1-G and S1-P for Sub1) and 2) marker genes from individual subclusters of the aforementioned four cell types (e.g., PGK1 high EC subcluster) using the Fisher’s exact test followed by the Benjamini–Hochberg method. Second, we calculated the signature score for each subcluster in individual samples of Sub1-6 as follows: 1) we selected expressed genes with FPKM > 1 in more than half of the samples in Sub1-6, and then applied quantile normalization to log 2 -(FPKM + 1) for these expressed genes; and 2) after auto-scaling the normalized log 2 -FPKM values, for each sample, we calculated a signature score as the averaged auto-scaled value for the marker genes of the subcluster. Finally, we identified the pathways represented by the marker genes for each subcluster by performing the enrichment analysis of cellular pathways for the marker genes using ConsensusPathDB and selecting the cellular pathways with p < 0.05, and the number of molecules involved in the pathways ≥ 3. Tissue microarrays and IHC Tissue samples were composed of four or more pieces obtained by multiple punch biopsies, measuring approximately 3 × 3 mm each. All pieces from each tumor were formalin-fixed and paraffin-embedded into a single block, and 4 µm-thick sections were stained with hematoxylin and eosin (H&E). After evaluation of H&E tissue sections in each case, representative neoplastic areas were marked, and the corresponding paraffin block was retrieved. A tissue core of 2.0 mm in diameter was obtained from each selected block using Quick-Ray manual tissue microarrayer (UNITMA, Seoul, Korea). Tissue microarrays (TMAs) containing 2 normal cervical tissues and 93 patient tumor tissues were generated and used for IHC and multiplex fluorescence IHC (mIHC) stain. For this TMA slide generation, without any selection, we used all 93 tumor tissues having sufficient amounts available to mount on the TMA slides among the 146 tumor tissues after proteogenomic analysis- 17 of 33 tumors in Sub1, 11 of 17 tumors in Sub2, 16 of 27 tumors in Sub3, 20 of 28 tumors in Sub4, 13 of 18 tumors in Sub5, and 16 of 23 tumors in Sub6. IHC stain was carried out using Roche IHC/ISH system (BenchMark ULTRA) and OptiView DAB IHC Detection Kit (Ventana, 760–700). The following antibodies were used as the primary antibodies: anti-BSG (Abcam, Clone: 10E10), anti-EGFR (Ventana, Clone: 3C6), anti-FOSL1 (Santa Crus, Clone: C-12), anti-VAV2 (Atlas, HPA003224), anti-ICOS (Abcam, Clone: EPR20560), anti-MMP2 (Invitrogen, Clone: 101), anti-GPC4 (Atlas, HPA030836). IHC slides were scanned using the Aperio AT2 DX System (Leica Biosystems) at 20 × magnification and the images are displayed at 20 × magnification using the Aperio ImageScope (Leica Biosystems). Quantification of IHC staining was performed using H-score, which was calculated by intensity and percentage of positively stained cells. The intensity was manually assessed in 4-grade (0, 1, 2, and 3) by two different pathologists as follows: If less than 10% of tumor cells were 1 or higher, the tumor was graded as 0 (negative); if more than 10% of tumor cells were 1 or higher but less than 10% of tumor cells were 2, the tumor was graded as 1 (weak positive); if more than 10% of tumor cells were 2 or higher but less than 10% of tumor cells were 3, the tumor was graded as 2 (moderate positive); and if more than 10% of tumor cells were 3, the tumor was graded as 3 (strong positive). The consensus grades between the two pathologists were determined. H-score was then obtained by multiplying the percentage and intensity: 3 × (percentage of 3 + cells) + 2 × (percentage of 2 + cells) + 1 × (percentage of 1 + cells). Of note, for ICOS for which H-score was not reliably estimated, we used the density of the positive cells, instead of H-score: the number of positive cells (1 + , 2 + or 3 +) per mm 2 . This procedure was done for 1) the total area of the core regions mounted on the TMA slides and 2) subregions enriched with tumor cells. In addition, for MMP2 expressed in a significant portion of stromal cells across tumors, we defined subregions enriched with stromal cells in each tumor and estimated grades for these subregions because the percentage of positive cells could not be reliably determined. Of note, when selecting the subregions for tumor- or stroma-enriched subregions from the total image for each tumor, to focus on the representative subregions and avoid the selection bias, we tried to 1) select the subregions where the tumor or stroma contents were close to the average content in the total image, and also to 2) avoid the subregions that could contain the artifacts. In this manner, the number of the selected subregions varied from one to six, depending on the status of the tumor or stromal distribution in the tumor, and grade/H-score was calculated for all the subregions at once. Multispectral imaging and analysis mIHC stain was performed on prismCDX Co.,Ltd (Gyeonggi-do, Korea) with a Leica Bond Rx™ Automated Stainer (Leica Biosystems). Briefly, the TMA slides were dewaxed with Leica Bond Dewax solution (Leica Biosystems, AR9222), followed by antigen retrieval with Bond Epitope Retrieval 2 (Leica Biosystems, AR9640). The staining process was performed four times in sequential rounds, including incubation with blocking buffer, primary antibody, and Mouse/Rabbit HRP secondary antibody (TheraNovis, C0105), and visualization of antigen with Astra-fluorophore (TheraNovis). Bond Epitope Retrieval 1 was treated to remove bound antibodies before proceeding to the next step. Finally, the nuclei were counterstained with DAPI (Thermo Scientific, 62,248). The slides were coverslipped using ProLong Gold antifade reagent (Invitrogen, P36930). The following antibodies were used: anti-PVR (Cell Signaling Technology, Clone: D8A5G), anti-TIGIT (Abcam, Clone: BLR047F), anti-CD66b (Novus, Clone: G10F5), anti-CK (Novus, Clone:AE-1/AE-3). The following fluorophores were used: Astra-570 (TheraNovis, C0110), Astra-690 (TheraNovis, C0114), Astra-620 (TheraNovis, C0113), Astra-780 (TheraNovis, C0116). mIHC slides were scanned using the PhenoImager™ HT (Akoya Biosciences) at 20 × magnification. The representative images for training were selected in Phenochart™ Whole Slide Viewer (1.1.0 version, Akoya Biosciences), and an algorithm was created in the inForm® Tissue Analysis software (2.6 version, Akoya Biosciences). Multispectral images were unmixed using the spectral library in the inForm software. Tissue was segmented based on cytokeratin (CK), an EC marker used to distinguish between parenchyma and stroma, and each single cell was segmented based on DAPI staining. The cells were phenotyped according to the expression compartment and intensity of each stained marker. After designating all tissue cores to be analyzed on the TMA slide, the created algorithm was applied for the batch analysis. The exported data were consolidated and analyzed in R studio (4.2.1 version) using the phenoptr (Akoya Biosciences) and phenoptrReport (Akoya Biosciences) packages. We calculated the distance between two cells located closest to each other using the ‘find_nearest_distance’ function and then determined the number of specified cells (cells expressing TIGIT) interacting with at least one reference cell (tumor cells or NL-SCs expressing PVR) at the proximity distance and the mean number of reference cells within 30 μm radius of one specified cell, as previously described . Primary culture of cells derived from tumor tissues Tumor samples were finely minced with scissors and dispersed into small aggregates by pipetting. Fine neoplastic tissue fragments were seeded into T-25 flasks. Tumor cells were initially cultured in Opti-MEMI (Thermo Fisher Scientific, MA, USA) with 5% fetal bovine serum (FBS). After primary culture, cells were sustained in RPMI 1640 (Thermo Fisher Scientific, MA, USA) with 10% fetal bovine serum and 1% (v/v) penicillin and streptomycin (10,000U/ml). Incubated flasks in humidified incubators at 37 °C in an atmosphere of 5% CO 2 and 95% air . Immunodetection Western blot analysis and immunofluorescence stain were performed using 1) #6507A tumor cells derived from one tissue of a Sub5 patient carrying a frame shift deletion mutation in the C-terminal region of CIC and 2) #6595 tumor cells (control) derived from one tissue of a Sub3 patient as a control without CIC mutation. Each experiment was independently repeated twice. Cytoplasmic, membrane and nuclear protein extracts were prepared with a subcellular protein fraction Kit (Thermo Scientific, 78,840) and used for western blot analysis. Western blotting was carried out according to the standard procedures using the enhanced-chemiluminescence detection (Amersham™, RPN2232). The following antibodies were used: anti-CIC (Invitrogen, PA5-83,721), anti-ETV4 (Proteintech, 10,684–1-AP), anti-CDH1 (Cell Signaling Technology, Clone: 24E10), anti-CTNNA1 (BD Bioscience, Clone: 5), anti-CDH2 (BD Bioscience, Clone: 32), anti-VIM (BD Bioscience, Clone: RV202), anti-β-Actin (Abcam, Clone: AC-15). Immunofluorescence stain was performed with patient-derived tumor cells. The cells were attached onto glass slides for O/N and fixed in 3.7% formaldehyde at 4℃ cold room for 30 min. They were permeabilized with 0.5% Triton X-100 in PBS (2 mM MgCl 2 ) at room temperature for 10 min and treated with 5% BSA in PBS (2 mM MgCl 2 ) for 1 h to block nonspecific reaction. Sequential incubation of primary antibody and Alexa fluorescence-conjugated secondary antibody (Invitrogen, A11037 and A11029) was performed using DAPI (Invitrogen, D1306) as a counterstain. Immunofluorescence stain images were acquired at 40 × magnification using a Zeiss LSM 780 confocal microscope. Intratongue cervical cancer model We cultured #6507A (Sub5) cells derived from human UCC tissues in RPMI-1640 medium (Biowest, L0498) containing 10% fetal bovine serum (FBS). Subconfluent cancer cells were harvested and washed with fresh RPMI-1640, followed by counting the number of cells. For the intratongue cervical cancer model, 2 × 10 6 #6507A cancer cells were suspended in 40 μl of RPMI-1640/Matrigel (Corning 354,262) mixture (1:1). Seven-ten-week-old Female BALB/c-nu mice were anesthetized with ketamine (100 mg/kg) and xylazine (10 mg/kg) via intraperitoneal injection. After anesthetization, mice were injected with #6507A cancer cells submucosally into the tongue using an insulin syringe with a 29-gauge needle (BD, 320,320). Tumor size was measured with a caliper every two days from 6 days after cancer cell inoculation until the end of the study. Tumor volume was calculated using the following formula: tumor volume = (LD × SD 2 )/2, where LD and SD indicate the long and short diameters, respectively. For processing of tumor tissue and blood, spleen, and bone marrow samples, see Supplementary Methods. Flow cytometry The single-cell suspensions (~ 1.5 × 10 6 cells) from tumor, blood, spleen, and bone marrow samples were incubated with LIVE/DEAD™ Fixable Blue Dead Cell Stain Kit for UV excitation (Invitrogen, L23105) for 30 min at 4 °C and then stained with the following fluorescent monoclonal antibodies according to the manufacturer’s protocol: Anti-CD45 (Invitrogen, Clone: 30-F11), anti-CD11b (Biolegend, Clone: M1/70), anti-Ly6C (Invitrogen, Clone: HK1.4), anti-Ly6G (Invitrogen, Clone: 1A8), anti-IL-17RB (Biolegend, Clone: 9B10), and anti-IL-21R (Biolegend, Clone: 4A9). To measure cytokine expression in CD8 + T cells, cells stained with surface monoclonal antibodies were fixed with intracellular fixation buffer (Invitrogen, 00–8222-49) for 25 min at room temperature, and then stained with the following fluorescent monoclonal antibodies according to the manufacturer’s protocol: anti-TNF-α (Biolegend, Clone: MP6-XT22), anti-Granzyme B (Invitrogen, Clone: NGZB), anti-Perforin (Biolegend, Clone: S16009A), anti-IFN-γ (Biolegend, Clone: XMG1.2). The stained samples were then analyzed using BD Symphony or BD LSRFortessa. Flowjo v10 was used for Flow cytometry data analysis. CFSE T-cell proliferation assay NL-SCs were sorted (FACS Aria III) from the spleen of #6507A tumor-bearing BALB/c-nu mice, and CD4 + T/CD8 + T-cells were sorted from the spleens of naïve BALB/c mice. The sorted T-cells were labeled with CFSE Cell Division Tracker Kit (BioLegend, 423,801) following the manufacturer’s protocol. The final concentration of CFSE was 0.5 µM. CFSE-labeled T-cells (1 × 10 5 cells) were co-cultured with NL-SCs (1 × 10 5 cells) for 4 days with or without NL-SCs in a 96-well plate pre-coated with anti-CD3e (1 μg/mL, BioLegend, 145-2C11) and anti-CD28 antibodies (1 μg/mL, BioLegend, 37.51) overnight at 4 °C. CFSE levels in T-cells were analyzed by flow cytometry using BD LSRII. Flowjo v10 was used for Flow cytometry data analysis. Migration assay NL-SCs (1 × 10 5 ) were seeded on a 3 mm pore PET membrane transwell insert (SPL 37124) in the upper chamber. The lower chamber included 10, 20, 50, or 100 ng/ml of recombinant mouse IL-17 (Peprotech 210–17), or triple combination of 20 ng/ml of IL-17, 20 ng/ml of IL-21(Peprotech 210–21), and 20 ng/ml of IL-22 (Peptrotech 210–22). After 6 h at 37 °C, 5% CO 2 , the medium in the upper chamber was removed and the membranes were fixed with 4% paraformaldehyde (PFA) for 20 min at room temperature (RT). After fixation, the membranes were dried for 10 min and stained with hematoxylin solution (Vitro Vivo Biotech) for 10 min at RT. After non-migrated cells were gently removed with a cotton tip, migrated cells were imaged using a bright-field microscope at 200X magnification. Image J was used to control the contrast images for accurate counting of migrated cells. Statistics The measured values are presented as the mean ± SEM. Comparisons between multiple groups (> 2 groups) were made using ANOVA with Tukey’s or Sidak’s post hoc correction. Student’s t-tests were used to compare data between two groups. Statistical significance was defined as p < 0.05.
UCC tissue and blood samples were collected from patients prior to radiotherapy at the department of radiotherapy, National Cancer Center (NCC) in Korea from July 2004 to March 2020. Most samples were obtained via biopsy, and 68 samples were obtained from the Bio Bank of NCC, Korea. Pathologic diagnosis was made by two gynecological pathologists. UCC tissues obtained from patients who had undergone radiotherapy as the primary treatment were collected at the outpatient clinic before radiotherapy was initiated along with the blood samples. The tissues collected via biopsy were immediately immersed in liquid nitrogen. Surgical samples were carried in liquid nitrogen as soon as the tissues were removed in the operating room and transferred to a -80 °C deep freezer within 30 min. Sample and clinical data collections were approved by the NCC Institutional Review Board (IRB No. NCC 2016–0019) and informed consent was obtained from all patients. Staging workup included bimanual physical examination, chest and abdomino-pelvic computed tomoghraphy (CT), pelvic magnetic resonance imaging (MRI), and positron emission tomography (PET) scans in all patients. Sigmoidoscopy and cystoscopy were performed for all patients. All patients were clinically staged as International Federation of Gynecology and Obstetrics (FIGO) 2014 staging system.
Concomitant chemoradiotherapy (CCRT) consisted of whole pelvic external beam radiotherapy (EBRT) with chemotherapy and high-dose–rate (HDR) brachytherapy. For patients having poor physical performance, however, RT alone was administered with the curative aim. Patients with stage IVB patients were treated in diverse methods including CCRT, RT alone, post-RT combination chemotherapy, and CCRT + combination chemotherapy. Whole pelvic EBRT dose was 45 to 50.4 Gy. HDR brachytherapy consisted of 6 fractions of CT- (between 2004 and 2008) or MRI-based (since 2009) 3-dimensional image-guided intra-cavitary radiotherapy given twice a week with 5 Gy per fraction (total 30 Gy). The total biologically equivalent dose in 2-Gy fractions to Point A ranged from 72.3 to 102.2 Gy, with a median value of 87 Gy. The final primary tumor response was determined by physical examination, cervical cytology or biopsy if needed, and MRI at 3 months after radiotherapy. Local recurrence was defined as the presence of residual disease not resolved at 3 months after radiotherapy, which was confirmed by biopsy, or as the relapse at the cervix, vaginal, and/or parametrium.
Genomic DNA for WES was isolated from frozen biopsy tumor tissues and peripheral blood buffy coat of patients using the QIAamp DNA Mini kit (Qiagen GmbH, Hilden, Germany). Total RNA for RNA sequencing was extracted from the frozen biopsy tumor tissue using TRIzol (Invitrogen®, Carlsbad, CA, USA), followed by cleaning with the RNeasy Mini Kit (Qiagen GmbH®, Hilden, Germany). Using the isolated genomic DNA and RNA, we generated the sequencing libraries and then performed WES and RNA sequencing analyses following the Illumina’s standard protocols, as described in details in Supplementary Methods. The reads resulted from WES and RNA sequencing were aligned to the GRCh38 reference genome using BWA MEM (version 0.7.17) for WES data and STAR (version 2.4.0) for RNA sequencing data. For the WES data, we identified somatic mutations using GATK3.8 and Strelka2 (version 2.9.10) , significantly mutated genes (SMGs) using MutSigCV (version 1.4.1) , and then copy number alterations (CNAs) using CNVkit (version 0.9.9) . For the RNA sequencing data, the fragments per kilobase of transcript per million mapped reads (FPKM) at the gene level were calculated using RSEM (version 1.3.3) . See Supplementary Methods for the details regarding the preprocessing and analysis of WES and RNA sequencing data.
To search for HPV integration sites, we attempted to identify the RNA-seq reads that contained the human genome component in one side and the viral genome component in the other side (called human-virus fusion reads) using the two previously reported approaches complementary to each other. In the first approach, we applied the Virus-Clip tool to align RNA-seq reads onto viral genome and obtained potential human-virus fusion reads. To remove the false positives, we separated the fusion reads into human and virus parts and first selected the ones with both parts longer than 21 bp (the minimum length for blast). For each selected fusion read, we then aligned both human and virus parts onto human transcriptome sequences (NCBI refseq RNA) using blastn (version 2.15.0) with default parameters. We further selected the fusion reads in which the human part was aligned (E-value < 1) onto human transcriptome while the virus part was not (E-value < 1) within 5 bp of the region (< 2-codon bp) where the human part was aligned. Based on these selected human-virus fusion reads, we next identified HPV integration sites as the ones supported by two fusion reads and more. In the second approach, as previously described in the TCGA study , we first applied the PathSeq tool (GATK version 4.2.2.0) to the RNA-seq data and identified non-human reads that were not aligned onto human genome (NCBI GRCh38). We then applied the CTAT-VIF tool (version 1.5.0) to the non-human reads and identified the human-virus fusion transcripts and their associated HPV sites. Finally, we combined the HPV integration sites identified from both approaches.
Tumor cellularity was estimated based on histological images. For each sample, the percentage of tumor cells relative to all cells, including stromal, immune, and tumor cells, was estimated using the representative hematoxylin–eosin (HE)-stained sample slide. At least ten random high-power fields (HPFs) and up to 30 HPFs were microscopically evaluated, and the average tumor cell count of the total cell counts in each HE-stained slide was estimated as histological tumor cellularity.
We cryopulverized each tumor tissue individually into tissue powder, as described previously , transferred the power to a new tube containing lysis buffer, centrifuged the lysate, and then extracted proteins. The resulting protein was digested by trypsin (V5111, Promega) with a slightly modified filter-aided sample preparation method . To generate the universal reference peptides, we pooled 60 μg of peptides from each tumor peptide sample. For each TMT set, the universal reference peptides (300 μg,126 channel) and ten different tumor samples (300 μg each, 127N through 131C channels) were labeled with 11-plex TMT reagent, according to the manufacturer’s instructions. After desalting, immobilized metal affinity chromatography (IMAC) phosphopeptide enrichment was performed on all TMT-labeled peptides. The flow-through non-phosphopeptide samples from the IMAC experiments were fractionated based on mid-pH reverse-phase liquid chromatography fractionation (mRP fractionation), as previously described . The previously developed DO-NCFC-RP/RPLC system was modified to produce up to 24 online NCFC fractions. This system was operated in one-dimensional RPLC mode (for global proteome) or two-dimensional RP/RPLC mode (for phosphoproteome). Both global proteome and phosphoproteome were analyzed using a quadrupole-orbitrap mass spectrometer (Q Exactive HF-X, Thermo Fisher Scientific) with an electric potential of 2.4 kV and desolvation capillary temperature at 250 °C for electrospray ionization. A sample-specific customized database was constructed with a slight modification to a previously reported method . MS/MS data for both global and phosphoproteome were processed using mPE-MMR for accurate precursor ion mass assignment. The refined MS/MS data were then subjected to MSGF + (version 9949) database search. For phosphoproteome datasets, the unidentified MS/MS data from the MSGF + search were further subjected to a spectral library search . Bipartite graph analysis using an in-house program was used to obtain protein groups from the identified peptides using a previously described process . The 11-plex TMT labeling was used to quantify the protein abundances of the universal reference (channel 126) and ten tumor tissues (channels 127N-131C). After correcting the isotope impurity, the intensities of each TMT reporter ion (126-131C) were extracted with a mass tolerance of 0.005 Da from all MS/MS scans and then normalized using quantile normalization. See Supplementary Methods for the details regarding sample preparation, LC–MS/MS analysis, and database search for global proteome and phosphoproteome analyses.
We used only expressed mRNAs, proteins, and phosphopeptides, respectively, that had FPKM > 1 (mRNAs) or were detected (proteins and phosphopeptides) in more than 50% of patients with protein and phosphorylation data available. For each SMG, we identified differentially expressed molecules between samples with and without alterations. To this end, for each molecule, we calculated a rank-sum statistic value and a log 2 -median-ratio. We then estimated the empirical null distributions of the rank-sum statistic value and log 2 -median-ratio via random permutation of all samples. Using the estimated empirical distributions, for each molecule, we computed adjusted p values for the observed rank-sum statistic value and log 2 -median-ratio, and then combined these p values using Stouffer’s method . Finally, we identified differentially expressed molecules as those with combined p values < 0.01 and absolute log 2 -median-ratios > a cutoff value, the mean of 2.5th and 97.5th percentiles of the empirical distribution for log 2 -median-ratios (e.g., log 2 -median-ratio = 0.45 for KRT5/10/13/14/16 ).
We first selected molecules (mRNAs, proteins, or phosphopeptides) with abundance data across all samples clustered to avoid the bias from missing values. For the 1st stage clustering, we selected squamous tumors only and then top 10 (MAD10), 20 (MAD20), or 30% (MAD30) of molecules (mRNAs, proteins, or phosphopeptides) with the largest median absolute deviations (MADs). We performed a 1st orthogonal non-negative matrix factorization (ONMF ;) clustering for the squamous tumors using MAD10, MAD20, or MAD30. Based on cophenetic correlations and consensus heat maps, we determined the number of clusters (hi_k) and cluster memberships, as previously described . Before the 2nd ONMF clustering, we fixed the memberships of squamous tumors in an initial activation matrix, as described at the bottom of Supplementary Fig. A. Briefly, in the initial activation matrix, we set activation values for the squamous tumors to represent the memberships (e.g., [1 0 0 0] for a squamous tumor in s-Prot1). We also added zeros for the remaining activation values when the number of clusters (k) was larger than hi_k. For adenosquamous and adenocarcinoma, we assigned random activation values sampled from the uniform distribution. We performed the 2nd ONMF clustering with the initial activation matrix using the same MAD10, MAD20, or MAD30 molecules from squamous tumors with varying k. Based on cophenetic correlations, we finally determined k and cluster memberships.
To identify molecular signatures that defined the subtypes during clustering, we first defined ‘core samples’ for each subtype as the ones with positive silhouette width scores. To obtain the signature molecules defining each subtype, for each molecule, we compared log 2 -fold-changes in the core samples of the subtype with those of the other subtypes using the previously reported integrative statistical hypothesis testing method that computed an adjusted p value (p) by combining p values obtained from two sample t-test and the median ratio test. For each comparison, the putative signature molecules were selected as those with p < 0.05. We then further filtered the selected molecules by choosing the ones with 1) a median value of patients in the subtype larger than zero, 2) a median value of the remaining patients less than zero, and 3) a median value of the patients in the subtype larger than that of the remaining patients.
An integrated clustering was performed using all three types of data (mRNA, global proteome, and phosphoproteome data). Briefly, for each type of data, a cluster identified from the individual data clustering was first converted to an indicator vector that included the ones for the samples in the subtype and zeros for the remaining samples. The indicator matrices for the three types of data were concatenated into the overall indicator matrix, which was then used as an input for k-means clustering. We selected the number of clusters (k, subtypes) as k = 6 (Sub1-6) after trying multiple k values and checking whether the subtypes resulted from the k-means clustering showed sufficient enrichment of clusters identified from the individual data. Cluster memberships of the samples were determined such that each sample was assigned to a subtype with the minimum distance to the subtype mean.
Survival data were shown using Kaplan–Meier curves. Survival can be affected by treatment methods. Thus, to avoid biases in survival analysis, we excluded 36 patients who received RT alone, 15 patients who underwent surgery as a primary treatment, 8 patients who received palliative treatment or incomplete treatment, and 5 patients with treatment or survival information unavailable. In addition, we excluded 29 stage IVB patients that were treated with heterogeneous chemotherapeutic regimens during and after RT (Supplementary Table ).
For integrated pathway analysis, we first identified molecular signatures for Sub1-6 identified from the integrated clustering based on the relationships between Sub1-6 and the clusters identified from the three types of data. For example, for Sub1, we identified the genes (S1-G) selected for RNA1 identified from mRNA data and the proteins (S1-P) selected for Prot1 and Phos1 identified from proteome and phosphoproteome data, respectively. To identify the pathways represented by the genes and proteins for Sub1-6, we performed an enrichment analysis of cellular pathways for the genes and proteins selected for each subtype (e.g., S1-G and S1-P for Sub1) using ConsensusPathDB . The cellular pathways represented by the genes and proteins for each subtype were identified as those with p < 0.05, and the number of molecules involved in the pathway ≥ 3.
We first obtained protein–protein interactions (PPIs) from ten interactome databases, including BioGRID , HuRI , IntAct , HitPredict , IID , MINT , DIP , HPRD , HTRIdb , and STRING . For the list of molecules selected for network construction (molecules that have correlation with genetic alterations in Fig. G and J and molecular signatures involved in activated stroma-related processes associated with Sub3 in Fig. B, immune-related processes associated with Sub4 in Supplementary Fig. C, EMT-related processes associated with Sub5 in Fig. D, or the processes related to the production of proteoglycan and Tn antigen associated with Sub6 in Fig. F), we then extracted interactors of the selected molecules (i.e., the molecules and their 1st neighbors) as the nodes and the edges between them based on the PPIs. We visualized a network model to describe the extracted nodes and edges in Cytoscape (version 3.3.0) . Among the 1st neighbors in the network model, we left only the key 1st neighbors without which the connection between the nodes for the selected molecules disappeared. We next added the activation and inhibition reactions between the nodes in the network model obtained from the relevant KEGG pathways (e.g., regulation of actin cytoskeleton in Fig. G) . Finally, we arranged the nodes based on their localization obtained from the KEGG pathways.
Cellular suspensions were loaded onto a chromium controller (10 × Genomics) to generate nanoliter-sized gel bead-in-emulsions (GEMs) containing single cells, reagents, and a single gel bead containing barcoded oligonucleotides. Barcoded sequencing libraries were prepared using Chromium Next GEM Single Cell 3’ v3.1 Dual Index (10X Genomics) according to the manufacturer’s protocol. The sequencing libraries were sequenced on NovaSeq 6000 (Illumina) with the following read lengths: 28 base pairs (bp) for Read 1 (16 bp 10 × Barcode + 12 bp UMI), 10 bp for Sample Index (dual), and 90 bp for Read 2. Next, we aligned the resulting reads from the sequencing to the GRCh38 reference genome and performed the unique molecular identifier (UMI) counting using Cell Ranger software (v.7.0.1) . To improve statistical power for characterization of cellular heterogeneity in LACC, we also integrated scRNA-seq dataset generated from patients with SCC and ADC (GSE208653 , GSE236738 , E-MTAB-12305 , and S-BSST1035 ). Quality control, data normalization and integration, and cell clustering were performed using Seurat (v.4.0.4) . See Supplementary Methods for the details regarding the preprocessing and analysis of scRNA-seq data.
Using the final merged UMI matrix for each cell cluster (or subcluster), we computed the adjusted p -values, log-fold changes, proportion of cells in the cluster expressing the gene (pct.1) using the ‘scanpy.tl.rank_genes_groups’ function from scanpy (v.1.10.1) . Adjusted p -values (Pw) were calculated for HVGs using the Wilcoxon rank-sum test followed by the Benjamini–Hochberg method. Moreover, to focus on the genes predominantly expressed in the cluster compared to in the other clusters, we further computed adjusted p -values (Pt) from the previously reported empirical t-test for HVGs for the comparison of pct.1 values in the cluster vs. those in the other clusters. Finally, we identified marker genes for the cluster as the ones meeting the following criteria: 1) adjusted Pw < 0.01, 2) log-fold changes > 0.4 (~ 1.49-fold), and 3) adjusted Pt < 0.05, and 4) the highest pct.1 in the cluster compared to in the other clusters. To search for the subtype of LACC associated with the subtypes of the aforementioned four cell types, we first evaluated the significance of overlaps between 1) the bulk RNA and protein signatures for Sub1-6 (e.g., S1-G and S1-P for Sub1) and 2) marker genes from individual subclusters of the aforementioned four cell types (e.g., PGK1 high EC subcluster) using the Fisher’s exact test followed by the Benjamini–Hochberg method. Second, we calculated the signature score for each subcluster in individual samples of Sub1-6 as follows: 1) we selected expressed genes with FPKM > 1 in more than half of the samples in Sub1-6, and then applied quantile normalization to log 2 -(FPKM + 1) for these expressed genes; and 2) after auto-scaling the normalized log 2 -FPKM values, for each sample, we calculated a signature score as the averaged auto-scaled value for the marker genes of the subcluster. Finally, we identified the pathways represented by the marker genes for each subcluster by performing the enrichment analysis of cellular pathways for the marker genes using ConsensusPathDB and selecting the cellular pathways with p < 0.05, and the number of molecules involved in the pathways ≥ 3.
Tissue samples were composed of four or more pieces obtained by multiple punch biopsies, measuring approximately 3 × 3 mm each. All pieces from each tumor were formalin-fixed and paraffin-embedded into a single block, and 4 µm-thick sections were stained with hematoxylin and eosin (H&E). After evaluation of H&E tissue sections in each case, representative neoplastic areas were marked, and the corresponding paraffin block was retrieved. A tissue core of 2.0 mm in diameter was obtained from each selected block using Quick-Ray manual tissue microarrayer (UNITMA, Seoul, Korea). Tissue microarrays (TMAs) containing 2 normal cervical tissues and 93 patient tumor tissues were generated and used for IHC and multiplex fluorescence IHC (mIHC) stain. For this TMA slide generation, without any selection, we used all 93 tumor tissues having sufficient amounts available to mount on the TMA slides among the 146 tumor tissues after proteogenomic analysis- 17 of 33 tumors in Sub1, 11 of 17 tumors in Sub2, 16 of 27 tumors in Sub3, 20 of 28 tumors in Sub4, 13 of 18 tumors in Sub5, and 16 of 23 tumors in Sub6. IHC stain was carried out using Roche IHC/ISH system (BenchMark ULTRA) and OptiView DAB IHC Detection Kit (Ventana, 760–700). The following antibodies were used as the primary antibodies: anti-BSG (Abcam, Clone: 10E10), anti-EGFR (Ventana, Clone: 3C6), anti-FOSL1 (Santa Crus, Clone: C-12), anti-VAV2 (Atlas, HPA003224), anti-ICOS (Abcam, Clone: EPR20560), anti-MMP2 (Invitrogen, Clone: 101), anti-GPC4 (Atlas, HPA030836). IHC slides were scanned using the Aperio AT2 DX System (Leica Biosystems) at 20 × magnification and the images are displayed at 20 × magnification using the Aperio ImageScope (Leica Biosystems). Quantification of IHC staining was performed using H-score, which was calculated by intensity and percentage of positively stained cells. The intensity was manually assessed in 4-grade (0, 1, 2, and 3) by two different pathologists as follows: If less than 10% of tumor cells were 1 or higher, the tumor was graded as 0 (negative); if more than 10% of tumor cells were 1 or higher but less than 10% of tumor cells were 2, the tumor was graded as 1 (weak positive); if more than 10% of tumor cells were 2 or higher but less than 10% of tumor cells were 3, the tumor was graded as 2 (moderate positive); and if more than 10% of tumor cells were 3, the tumor was graded as 3 (strong positive). The consensus grades between the two pathologists were determined. H-score was then obtained by multiplying the percentage and intensity: 3 × (percentage of 3 + cells) + 2 × (percentage of 2 + cells) + 1 × (percentage of 1 + cells). Of note, for ICOS for which H-score was not reliably estimated, we used the density of the positive cells, instead of H-score: the number of positive cells (1 + , 2 + or 3 +) per mm 2 . This procedure was done for 1) the total area of the core regions mounted on the TMA slides and 2) subregions enriched with tumor cells. In addition, for MMP2 expressed in a significant portion of stromal cells across tumors, we defined subregions enriched with stromal cells in each tumor and estimated grades for these subregions because the percentage of positive cells could not be reliably determined. Of note, when selecting the subregions for tumor- or stroma-enriched subregions from the total image for each tumor, to focus on the representative subregions and avoid the selection bias, we tried to 1) select the subregions where the tumor or stroma contents were close to the average content in the total image, and also to 2) avoid the subregions that could contain the artifacts. In this manner, the number of the selected subregions varied from one to six, depending on the status of the tumor or stromal distribution in the tumor, and grade/H-score was calculated for all the subregions at once.
mIHC stain was performed on prismCDX Co.,Ltd (Gyeonggi-do, Korea) with a Leica Bond Rx™ Automated Stainer (Leica Biosystems). Briefly, the TMA slides were dewaxed with Leica Bond Dewax solution (Leica Biosystems, AR9222), followed by antigen retrieval with Bond Epitope Retrieval 2 (Leica Biosystems, AR9640). The staining process was performed four times in sequential rounds, including incubation with blocking buffer, primary antibody, and Mouse/Rabbit HRP secondary antibody (TheraNovis, C0105), and visualization of antigen with Astra-fluorophore (TheraNovis). Bond Epitope Retrieval 1 was treated to remove bound antibodies before proceeding to the next step. Finally, the nuclei were counterstained with DAPI (Thermo Scientific, 62,248). The slides were coverslipped using ProLong Gold antifade reagent (Invitrogen, P36930). The following antibodies were used: anti-PVR (Cell Signaling Technology, Clone: D8A5G), anti-TIGIT (Abcam, Clone: BLR047F), anti-CD66b (Novus, Clone: G10F5), anti-CK (Novus, Clone:AE-1/AE-3). The following fluorophores were used: Astra-570 (TheraNovis, C0110), Astra-690 (TheraNovis, C0114), Astra-620 (TheraNovis, C0113), Astra-780 (TheraNovis, C0116). mIHC slides were scanned using the PhenoImager™ HT (Akoya Biosciences) at 20 × magnification. The representative images for training were selected in Phenochart™ Whole Slide Viewer (1.1.0 version, Akoya Biosciences), and an algorithm was created in the inForm® Tissue Analysis software (2.6 version, Akoya Biosciences). Multispectral images were unmixed using the spectral library in the inForm software. Tissue was segmented based on cytokeratin (CK), an EC marker used to distinguish between parenchyma and stroma, and each single cell was segmented based on DAPI staining. The cells were phenotyped according to the expression compartment and intensity of each stained marker. After designating all tissue cores to be analyzed on the TMA slide, the created algorithm was applied for the batch analysis. The exported data were consolidated and analyzed in R studio (4.2.1 version) using the phenoptr (Akoya Biosciences) and phenoptrReport (Akoya Biosciences) packages. We calculated the distance between two cells located closest to each other using the ‘find_nearest_distance’ function and then determined the number of specified cells (cells expressing TIGIT) interacting with at least one reference cell (tumor cells or NL-SCs expressing PVR) at the proximity distance and the mean number of reference cells within 30 μm radius of one specified cell, as previously described .
Tumor samples were finely minced with scissors and dispersed into small aggregates by pipetting. Fine neoplastic tissue fragments were seeded into T-25 flasks. Tumor cells were initially cultured in Opti-MEMI (Thermo Fisher Scientific, MA, USA) with 5% fetal bovine serum (FBS). After primary culture, cells were sustained in RPMI 1640 (Thermo Fisher Scientific, MA, USA) with 10% fetal bovine serum and 1% (v/v) penicillin and streptomycin (10,000U/ml). Incubated flasks in humidified incubators at 37 °C in an atmosphere of 5% CO 2 and 95% air .
Western blot analysis and immunofluorescence stain were performed using 1) #6507A tumor cells derived from one tissue of a Sub5 patient carrying a frame shift deletion mutation in the C-terminal region of CIC and 2) #6595 tumor cells (control) derived from one tissue of a Sub3 patient as a control without CIC mutation. Each experiment was independently repeated twice. Cytoplasmic, membrane and nuclear protein extracts were prepared with a subcellular protein fraction Kit (Thermo Scientific, 78,840) and used for western blot analysis. Western blotting was carried out according to the standard procedures using the enhanced-chemiluminescence detection (Amersham™, RPN2232). The following antibodies were used: anti-CIC (Invitrogen, PA5-83,721), anti-ETV4 (Proteintech, 10,684–1-AP), anti-CDH1 (Cell Signaling Technology, Clone: 24E10), anti-CTNNA1 (BD Bioscience, Clone: 5), anti-CDH2 (BD Bioscience, Clone: 32), anti-VIM (BD Bioscience, Clone: RV202), anti-β-Actin (Abcam, Clone: AC-15). Immunofluorescence stain was performed with patient-derived tumor cells. The cells were attached onto glass slides for O/N and fixed in 3.7% formaldehyde at 4℃ cold room for 30 min. They were permeabilized with 0.5% Triton X-100 in PBS (2 mM MgCl 2 ) at room temperature for 10 min and treated with 5% BSA in PBS (2 mM MgCl 2 ) for 1 h to block nonspecific reaction. Sequential incubation of primary antibody and Alexa fluorescence-conjugated secondary antibody (Invitrogen, A11037 and A11029) was performed using DAPI (Invitrogen, D1306) as a counterstain. Immunofluorescence stain images were acquired at 40 × magnification using a Zeiss LSM 780 confocal microscope.
We cultured #6507A (Sub5) cells derived from human UCC tissues in RPMI-1640 medium (Biowest, L0498) containing 10% fetal bovine serum (FBS). Subconfluent cancer cells were harvested and washed with fresh RPMI-1640, followed by counting the number of cells. For the intratongue cervical cancer model, 2 × 10 6 #6507A cancer cells were suspended in 40 μl of RPMI-1640/Matrigel (Corning 354,262) mixture (1:1). Seven-ten-week-old Female BALB/c-nu mice were anesthetized with ketamine (100 mg/kg) and xylazine (10 mg/kg) via intraperitoneal injection. After anesthetization, mice were injected with #6507A cancer cells submucosally into the tongue using an insulin syringe with a 29-gauge needle (BD, 320,320). Tumor size was measured with a caliper every two days from 6 days after cancer cell inoculation until the end of the study. Tumor volume was calculated using the following formula: tumor volume = (LD × SD 2 )/2, where LD and SD indicate the long and short diameters, respectively. For processing of tumor tissue and blood, spleen, and bone marrow samples, see Supplementary Methods.
The single-cell suspensions (~ 1.5 × 10 6 cells) from tumor, blood, spleen, and bone marrow samples were incubated with LIVE/DEAD™ Fixable Blue Dead Cell Stain Kit for UV excitation (Invitrogen, L23105) for 30 min at 4 °C and then stained with the following fluorescent monoclonal antibodies according to the manufacturer’s protocol: Anti-CD45 (Invitrogen, Clone: 30-F11), anti-CD11b (Biolegend, Clone: M1/70), anti-Ly6C (Invitrogen, Clone: HK1.4), anti-Ly6G (Invitrogen, Clone: 1A8), anti-IL-17RB (Biolegend, Clone: 9B10), and anti-IL-21R (Biolegend, Clone: 4A9). To measure cytokine expression in CD8 + T cells, cells stained with surface monoclonal antibodies were fixed with intracellular fixation buffer (Invitrogen, 00–8222-49) for 25 min at room temperature, and then stained with the following fluorescent monoclonal antibodies according to the manufacturer’s protocol: anti-TNF-α (Biolegend, Clone: MP6-XT22), anti-Granzyme B (Invitrogen, Clone: NGZB), anti-Perforin (Biolegend, Clone: S16009A), anti-IFN-γ (Biolegend, Clone: XMG1.2). The stained samples were then analyzed using BD Symphony or BD LSRFortessa. Flowjo v10 was used for Flow cytometry data analysis.
NL-SCs were sorted (FACS Aria III) from the spleen of #6507A tumor-bearing BALB/c-nu mice, and CD4 + T/CD8 + T-cells were sorted from the spleens of naïve BALB/c mice. The sorted T-cells were labeled with CFSE Cell Division Tracker Kit (BioLegend, 423,801) following the manufacturer’s protocol. The final concentration of CFSE was 0.5 µM. CFSE-labeled T-cells (1 × 10 5 cells) were co-cultured with NL-SCs (1 × 10 5 cells) for 4 days with or without NL-SCs in a 96-well plate pre-coated with anti-CD3e (1 μg/mL, BioLegend, 145-2C11) and anti-CD28 antibodies (1 μg/mL, BioLegend, 37.51) overnight at 4 °C. CFSE levels in T-cells were analyzed by flow cytometry using BD LSRII. Flowjo v10 was used for Flow cytometry data analysis.
NL-SCs (1 × 10 5 ) were seeded on a 3 mm pore PET membrane transwell insert (SPL 37124) in the upper chamber. The lower chamber included 10, 20, 50, or 100 ng/ml of recombinant mouse IL-17 (Peprotech 210–17), or triple combination of 20 ng/ml of IL-17, 20 ng/ml of IL-21(Peprotech 210–21), and 20 ng/ml of IL-22 (Peptrotech 210–22). After 6 h at 37 °C, 5% CO 2 , the medium in the upper chamber was removed and the membranes were fixed with 4% paraformaldehyde (PFA) for 20 min at room temperature (RT). After fixation, the membranes were dried for 10 min and stained with hematoxylin solution (Vitro Vivo Biotech) for 10 min at RT. After non-migrated cells were gently removed with a cotton tip, migrated cells were imaged using a bright-field microscope at 200X magnification. Image J was used to control the contrast images for accurate counting of migrated cells.
The measured values are presented as the mean ± SEM. Comparisons between multiple groups (> 2 groups) were made using ANOVA with Tukey’s or Sidak’s post hoc correction. Student’s t-tests were used to compare data between two groups. Statistical significance was defined as p < 0.05.
Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6
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Digital-assisted diagnosis and orthodontic management of an impacted mandibular lateral incisor: a case report | c779c691-a4e6-4ac8-bdb7-da0b7b32dba4 | 11479465 | Dentistry[mh] | The failure of an impacted tooth to erupt in its normal position during tooth eruption for various reasons (e.g., impaction by alveolar bone, fibrous tissue, or other teeth) is known as impaction, which can occur in any tooth with a high prevalence of 2.0–14.4% (excluding the third molar) . Incisors play a crucial role in the stomatognathic system and are a significant factor in facial aesthetics and harmony. However, local or systemic factors may also cause impaction of incisors, resulting in craniomandibular aesthetics and dysfunction. According to previous studies, the rate of mesial incisor occlusion in the upper jaw is between 0.06% and 0.2% , whereas mandibular incisor occlusion is even less common. Altered incisor eruption can cause significant concern for patients. A correct diagnosis of incisor impaction and a clear understanding of its prognostic implications are necessary to design an appropriate treatment plan. The aetiology of incisor impaction includes increased resistance to eruption due to factors such as trauma to the deciduous teeth, abnormal local mucosal density, and neighbouring ectopic teeth. Furthermore, tooth impaction may also be caused by pathological systemic diseases, supernumerary teeth, cysts and tumours . Among these morphological abnormalities, root dilaceration is the most common. This condition not only increases the complexity of treatment but also poses risks of complications such as root resorption and root exposure following orthodontic traction. Particularly during treatment, when the root apex comes into contact with the labial cortical bone, controlling torque becomes more challenging, further complicating the treatment process . The most common treatments for incisor impaction are guided forced eruption, extraction of the impaction, and orthodontic space closure. Given that impaction typically occurs in younger patients, any postextraction restorative measures are generally provisional and must be followed by permanent restoration once the patient reaches maturity. During this interim period, significant alveolar bone loss at the extraction site may occur, which not only complicates subsequent restorative procedures but also potentially hinders the effectiveness of orthodontic space closure . Therefore, clinicians generally prefer the former approach, which considers the preservation of tooth structure, alveolar bone width achieved through force-induced bone regeneration, overall periodontal health, and aesthetic benefits. Patients often desire to retain impacted teeth and restore them to their original position . This clinical case illustrates the complex decision-making process and therapeutic strategies involved in managing a rare case of mandibular lateral incisor impaction with associated class II malocclusion and facial proclination. Preoperative digital simulation plays a crucial role in determining the feasibility of guided eruption, ultimately leading to successful treatment outcomes. This case highlights the effectiveness of a combined approach involving guided eruption surgery and orthodontic treatment, resulting not only in successful repositioning of the impacted tooth but also in significant improvements in the patient's facial aesthetics and overall oral health.
Diagnosis and aetiology A 12-year-old male patient sought orthodontic treatment due to concerns about insufficient lip closure and a protrusive mouth. The patient had a history of childhood chin and dental trauma, although the details were unclear and reported a habit of mouth breathing. The intraoral examination revealed disturbed tooth eruption with tooth 32 absent, a 5 mm deep overbite, an 8 mm overjet, a 2 mm space in the mandibular dentition, a bilateral Class II canine relationship, a left Class III molar relationship, and a right Class I molar distal relationship (Fig. ). Facial analysis revealed that the patient had a symmetrical facial profile with a convex facial contour, prominent upper lip, a receding chin, and incomplete lip closure. Panoramic radiographs and CBCT confirmed the vertical impaction of tooth 32; digital reconstruction with Mimics and Geomagic revealed that the crown of tooth 32 was positioned distally, with the apical third of the root also curving distally at nearly a 90° angle from the long axis and a hypodense area around the crown indicating a follicular cyst. No significant root resorption was noted on tooth 31, and the root of tooth 33 was incompletely formed. In the upper jaw, tooth 25 was located palatally and twisted 55.3° away from its normal position in the upper jaw (Figs. and ). Cephalometric analysis revealed a depression of the lower margins of the second and third cervical vertebrae and a transformation of the third and fourth cervical vertebrae from a horizontal trapezoid to a horizontal rectangle, indicating the CS3 to CS4 stage of cervical maturation and suggesting that the patient was at the peak of their growth spurt with significant growth potential. The upper anterior teeth were inclined anteriorly, with a combined saddle angle, joint angle, and mandibular angle of 395.21° and a normal S-Go/N-Me ratio, indicating an average growth pattern, whereas the OP-FH angle was reduced, and the occlusal plane angle was low (Fig. and Table ). Treatment objectives Levelling and aligning the dental arches while correcting individual tooth rotations. Managing the impacted mandibular incisor to establish an optimal occlusal relationship. Leveraging the patient's growth potential to promote mandibular advancement and improve the soft-tissue profile. Maintaining the upper midline and adjusting the lower midline as needed. Achieving a stable and functional occlusion. Treatment alternatives For the mandible: The key to the mandibular treatment plan lies in whether to retain or extract tooth 32. Therefore, the patient and his parents were given the following options on the basis of the treatment objectives. The first option was as follows: Space expansion and an attempt to induce eruption of the impacted tooth: Preserving the width of the alveolar bone surrounding the impacted tooth is crucial . Facilitating the natural eruption of the impacted tooth aligns best with the physiological principles of tooth movement. However, this approach poses certain challenges, including a prolonged treatment duration, the necessity for interdisciplinary collaboration, and potential issues related to crown and gingival aesthetics. Selection of the surgical exposure technique and the direction of orthodontic traction must be approached with great care . To evaluate the feasibility of guided eruption for tooth 32, a digital simulation of tooth arrangement and a comprehensive space analysis were conducted: DICOM data obtained from the patient’s preoperative CBCT scan were directly imported into Mimics software for modelling. Surface models of the left mandibular lateral incisor and the mandibular segment were extracted and subsequently imported into Geomagic Studio, a specialized reverse engineering software, for smoothing and refinement, resulting in a detailed three-dimensional representation of the morphology and spatial orientation of tooth 32. The root of tooth 32 exhibited a 90° curvature, indicating vertical impaction, with no significant contact between the root and adjacent teeth. The literature suggests that the greater the crown‒root curvature angle, the greater is the treatment difficulty. Curvatures near the cervical region present substantial challenges, whereas those near the root are considered less problematic. Overall, the difficulty of inducing eruption for this impacted tooth is moderate, but there is a potential risk of root resorption during the eruption process. By measuring the width of tooth 32 in the 3D model and calculating the space required for its alignment within the dental arch, we utilized the Invisalign alignment tool to simulate the space needed for alignment and levelling, which fell within our estimated growth potential (Figs. and and Table ). 2) Surgical extraction of the impacted lateral incisor with subsequent orthodontic space closure or restorative treatment: This treatment approach offers a shorter duration; however, direct space closure fails to address the Bolton discrepancy of the anterior teeth. Posttreatment, there may be a misalignment of the upper and lower dental midlines, and the vertical proclination of the lower anterior teeth may exacerbate the deep overbite, all of which are disadvantageous for the patient. Restorative treatment would need to be delayed until the patient reaches maturity, and the prolonged absence of the tooth could lead to alveolar bone resorption, potentially resulting in further aesthetic challenges in the future. 2. For the Maxilla: Maxillary expansion: The patient had a deep overbite, deep overjet, and incomplete lip closure, which required retraction of the upper anterior teeth. To prevent further deepening of the overjet, the upper anterior teeth should be tilted and intruded appropriately. The GALL line was used as a reference, and the upper anterior teeth were retracted by 1 mm while being intruded by 3°, requiring approximately 4 mm of space. With mild crowding in the upper dental arch and a rounded canine arch shape, expanding the width between the upper canines could provide approximately 3 mm of space for the anterior teeth. The patient had 0.9 mm of space due to the unshed left second deciduous molar, resulting in a total of approximately 4 mm of space. In such cases, enamel stripping may be necessary. In summary, after considering the above options, the patient and his parents elected to pursue guided eruption of tooth 32 combined with maxillary expansion. Treatment progress The patient was treated with 0.020 × 0.025-inch brackets, and the arch was sequentially replaced with nickel‒titanium (NiTi) wires (0.012 − 0.018-inch NiTi, 0.016 × 0.022 − 0.019 × 0.025-inch NiTi) for alignment and levelling. The arch was stabilized with 0.019 × 0.025 stainless steel wires. A spring was added to widen the space between teeth 24 and 26. After eruption of tooth 25, brackets were attached to the buccal side, and an elastic rubber chain was used to suspend the wire. Lingual side brackets were bonded to teeth 24 and 25, and an elastic rubber chain was used to connect the lingual side clasps. An ‘8’ ligature was used for the teeth 23 and 24 brackets to provide traction to correct the twist in tooth 25. After replacement with a 0.019 × 0.025 stainless steel wire, Class III plastic traction (5/16, 4.5 oz) was added between teeth 16 and 43 and between teeth 26 and 33, pulling teeth 33 and 43 towards the distal centre. To achieve the desired space, a push spring was inserted and maintained between teeth 31 − 33. Apical radiographs of tooth 32 were taken every 3–6 months to monitor for signs of eruption. After approximately 1 year of space expansion, tooth 32 reached the subgingival position with an encapsulated low-density shadow around the crown (Fig. ). This phenomenon indicated an incomplete resorption of the capsule, resulting in a lack of eruptive force. To facilitate eruption, the cystic sac was cleaned, and the crown of tooth 32 was exposed on the labial side, with a lingual clasp bonded to the tooth. Approximately 60–90 g of elastic traction was added to the affected tooth while maintaining the position of the push spring. Continuous light traction was applied to the crown of the impacted lateral incisor, resulting in eruption at approximately crown 4/5. The buccal tubes were bonded to teeth 17, 27, 37, and 47, and a nickel‒titanium round wire was used for alignment. When gingival recession was observed on tooth 32, the bracket on tooth 32 was counterbonded, and the axial inclination of the root was adjusted (Fig. ). In the mandible, a 0.016 × 0.022-inch stainless steel square wire was used in combination with a portal auxiliary arch to correct the torque of the affected teeth (Fig. ). Fine adjustments were made by closing small openings in the premolar region via triangular traction at teeth 34, 35, 44, and 45. The patient achieved a Class I relationship between the canines and molars on both sides, with the upper and lower midlines essentially in the centre. The maxillary and mandibular clear retainers were left in place after the fixed orthodontic appliances were removed. A postoperative impression was obtained, and medical advice was provided. Treatment results Following treatment, the deep overbite and overjet were resolved, resulting in bilateral canine and molar neutral relationships with the upper and lower midlines centred. Tooth 32 was correctly positioned, showing gingival recession up to the cervical third, a probing depth (PD) of 3 mm, and partial exposure of alveolar bone. The teeth remained intact without significant tenderness, percussion pain, or mobility. These features prompted a referral to periodontics for consultation. The soft tissue profile was deemed favourable. Additionally, the treatment improved the width of the anterior and middle segments of the upper dental arch without significantly altering the posterior segment, which transitioned the arch form from pointed to ovoid, providing the necessary space. The distal movement of the lower canines resulted in an increased width of anterior segment 4 of the lower dental arch. As a result of growth potential, the middle and posterior segments widened posttreatment, ensuring that the upper and lower arch widths were harmonized. Panoramic radiography and postoperative CBCT revealed that the roots were parallel. Tooth 32 had a blunted root, a large apical foramen, and root resorption up to the apical third, but there were no signs of inflammation or discontinuities in the periodontal ligament. Postoperative CBCT revealed symmetrical temporomandibular joint spaces, with no significant narrowing or widening observed. The condylar morphology appeared normal, with no evidence of bony destruction or abnormal proliferation (Fig.S.1). The superimposed cephalometric images demonstrated forward and downward mandibular growth, which improved the mandibular retrusion and soft tissue profile, indicating successful treatment outcomes (Figs. , and ).
A 12-year-old male patient sought orthodontic treatment due to concerns about insufficient lip closure and a protrusive mouth. The patient had a history of childhood chin and dental trauma, although the details were unclear and reported a habit of mouth breathing. The intraoral examination revealed disturbed tooth eruption with tooth 32 absent, a 5 mm deep overbite, an 8 mm overjet, a 2 mm space in the mandibular dentition, a bilateral Class II canine relationship, a left Class III molar relationship, and a right Class I molar distal relationship (Fig. ). Facial analysis revealed that the patient had a symmetrical facial profile with a convex facial contour, prominent upper lip, a receding chin, and incomplete lip closure. Panoramic radiographs and CBCT confirmed the vertical impaction of tooth 32; digital reconstruction with Mimics and Geomagic revealed that the crown of tooth 32 was positioned distally, with the apical third of the root also curving distally at nearly a 90° angle from the long axis and a hypodense area around the crown indicating a follicular cyst. No significant root resorption was noted on tooth 31, and the root of tooth 33 was incompletely formed. In the upper jaw, tooth 25 was located palatally and twisted 55.3° away from its normal position in the upper jaw (Figs. and ). Cephalometric analysis revealed a depression of the lower margins of the second and third cervical vertebrae and a transformation of the third and fourth cervical vertebrae from a horizontal trapezoid to a horizontal rectangle, indicating the CS3 to CS4 stage of cervical maturation and suggesting that the patient was at the peak of their growth spurt with significant growth potential. The upper anterior teeth were inclined anteriorly, with a combined saddle angle, joint angle, and mandibular angle of 395.21° and a normal S-Go/N-Me ratio, indicating an average growth pattern, whereas the OP-FH angle was reduced, and the occlusal plane angle was low (Fig. and Table ).
Levelling and aligning the dental arches while correcting individual tooth rotations. Managing the impacted mandibular incisor to establish an optimal occlusal relationship. Leveraging the patient's growth potential to promote mandibular advancement and improve the soft-tissue profile. Maintaining the upper midline and adjusting the lower midline as needed. Achieving a stable and functional occlusion.
For the mandible: The key to the mandibular treatment plan lies in whether to retain or extract tooth 32. Therefore, the patient and his parents were given the following options on the basis of the treatment objectives. The first option was as follows: Space expansion and an attempt to induce eruption of the impacted tooth: Preserving the width of the alveolar bone surrounding the impacted tooth is crucial . Facilitating the natural eruption of the impacted tooth aligns best with the physiological principles of tooth movement. However, this approach poses certain challenges, including a prolonged treatment duration, the necessity for interdisciplinary collaboration, and potential issues related to crown and gingival aesthetics. Selection of the surgical exposure technique and the direction of orthodontic traction must be approached with great care . To evaluate the feasibility of guided eruption for tooth 32, a digital simulation of tooth arrangement and a comprehensive space analysis were conducted: DICOM data obtained from the patient’s preoperative CBCT scan were directly imported into Mimics software for modelling. Surface models of the left mandibular lateral incisor and the mandibular segment were extracted and subsequently imported into Geomagic Studio, a specialized reverse engineering software, for smoothing and refinement, resulting in a detailed three-dimensional representation of the morphology and spatial orientation of tooth 32. The root of tooth 32 exhibited a 90° curvature, indicating vertical impaction, with no significant contact between the root and adjacent teeth. The literature suggests that the greater the crown‒root curvature angle, the greater is the treatment difficulty. Curvatures near the cervical region present substantial challenges, whereas those near the root are considered less problematic. Overall, the difficulty of inducing eruption for this impacted tooth is moderate, but there is a potential risk of root resorption during the eruption process. By measuring the width of tooth 32 in the 3D model and calculating the space required for its alignment within the dental arch, we utilized the Invisalign alignment tool to simulate the space needed for alignment and levelling, which fell within our estimated growth potential (Figs. and and Table ). 2) Surgical extraction of the impacted lateral incisor with subsequent orthodontic space closure or restorative treatment: This treatment approach offers a shorter duration; however, direct space closure fails to address the Bolton discrepancy of the anterior teeth. Posttreatment, there may be a misalignment of the upper and lower dental midlines, and the vertical proclination of the lower anterior teeth may exacerbate the deep overbite, all of which are disadvantageous for the patient. Restorative treatment would need to be delayed until the patient reaches maturity, and the prolonged absence of the tooth could lead to alveolar bone resorption, potentially resulting in further aesthetic challenges in the future. 2. For the Maxilla: Maxillary expansion: The patient had a deep overbite, deep overjet, and incomplete lip closure, which required retraction of the upper anterior teeth. To prevent further deepening of the overjet, the upper anterior teeth should be tilted and intruded appropriately. The GALL line was used as a reference, and the upper anterior teeth were retracted by 1 mm while being intruded by 3°, requiring approximately 4 mm of space. With mild crowding in the upper dental arch and a rounded canine arch shape, expanding the width between the upper canines could provide approximately 3 mm of space for the anterior teeth. The patient had 0.9 mm of space due to the unshed left second deciduous molar, resulting in a total of approximately 4 mm of space. In such cases, enamel stripping may be necessary. In summary, after considering the above options, the patient and his parents elected to pursue guided eruption of tooth 32 combined with maxillary expansion.
The patient was treated with 0.020 × 0.025-inch brackets, and the arch was sequentially replaced with nickel‒titanium (NiTi) wires (0.012 − 0.018-inch NiTi, 0.016 × 0.022 − 0.019 × 0.025-inch NiTi) for alignment and levelling. The arch was stabilized with 0.019 × 0.025 stainless steel wires. A spring was added to widen the space between teeth 24 and 26. After eruption of tooth 25, brackets were attached to the buccal side, and an elastic rubber chain was used to suspend the wire. Lingual side brackets were bonded to teeth 24 and 25, and an elastic rubber chain was used to connect the lingual side clasps. An ‘8’ ligature was used for the teeth 23 and 24 brackets to provide traction to correct the twist in tooth 25. After replacement with a 0.019 × 0.025 stainless steel wire, Class III plastic traction (5/16, 4.5 oz) was added between teeth 16 and 43 and between teeth 26 and 33, pulling teeth 33 and 43 towards the distal centre. To achieve the desired space, a push spring was inserted and maintained between teeth 31 − 33. Apical radiographs of tooth 32 were taken every 3–6 months to monitor for signs of eruption. After approximately 1 year of space expansion, tooth 32 reached the subgingival position with an encapsulated low-density shadow around the crown (Fig. ). This phenomenon indicated an incomplete resorption of the capsule, resulting in a lack of eruptive force. To facilitate eruption, the cystic sac was cleaned, and the crown of tooth 32 was exposed on the labial side, with a lingual clasp bonded to the tooth. Approximately 60–90 g of elastic traction was added to the affected tooth while maintaining the position of the push spring. Continuous light traction was applied to the crown of the impacted lateral incisor, resulting in eruption at approximately crown 4/5. The buccal tubes were bonded to teeth 17, 27, 37, and 47, and a nickel‒titanium round wire was used for alignment. When gingival recession was observed on tooth 32, the bracket on tooth 32 was counterbonded, and the axial inclination of the root was adjusted (Fig. ). In the mandible, a 0.016 × 0.022-inch stainless steel square wire was used in combination with a portal auxiliary arch to correct the torque of the affected teeth (Fig. ). Fine adjustments were made by closing small openings in the premolar region via triangular traction at teeth 34, 35, 44, and 45. The patient achieved a Class I relationship between the canines and molars on both sides, with the upper and lower midlines essentially in the centre. The maxillary and mandibular clear retainers were left in place after the fixed orthodontic appliances were removed. A postoperative impression was obtained, and medical advice was provided.
Following treatment, the deep overbite and overjet were resolved, resulting in bilateral canine and molar neutral relationships with the upper and lower midlines centred. Tooth 32 was correctly positioned, showing gingival recession up to the cervical third, a probing depth (PD) of 3 mm, and partial exposure of alveolar bone. The teeth remained intact without significant tenderness, percussion pain, or mobility. These features prompted a referral to periodontics for consultation. The soft tissue profile was deemed favourable. Additionally, the treatment improved the width of the anterior and middle segments of the upper dental arch without significantly altering the posterior segment, which transitioned the arch form from pointed to ovoid, providing the necessary space. The distal movement of the lower canines resulted in an increased width of anterior segment 4 of the lower dental arch. As a result of growth potential, the middle and posterior segments widened posttreatment, ensuring that the upper and lower arch widths were harmonized. Panoramic radiography and postoperative CBCT revealed that the roots were parallel. Tooth 32 had a blunted root, a large apical foramen, and root resorption up to the apical third, but there were no signs of inflammation or discontinuities in the periodontal ligament. Postoperative CBCT revealed symmetrical temporomandibular joint spaces, with no significant narrowing or widening observed. The condylar morphology appeared normal, with no evidence of bony destruction or abnormal proliferation (Fig.S.1). The superimposed cephalometric images demonstrated forward and downward mandibular growth, which improved the mandibular retrusion and soft tissue profile, indicating successful treatment outcomes (Figs. , and ).
Possible aetiology of lateral incisor impaction Since the patient was in the mixed dentition period at the time of consultation, information about the deciduous dentition could only be obtained by direct inquiry from the patient. Therefore, we could only analyse the possible aetiology of the patient's lateral incisor impaction. The patient denied any history of systemic underlying disease or medication. Imaging findings did not reveal any abnormally dense bone or low-density mass interfering with eruption. The clinical examination also did not reveal a nonpathologic source of soft tissue thickening interference. Typically, after birth, the permanent tooth germ is positioned within a bony depression beneath the root of the deciduous tooth, encased by the dental sac tissue. The tooth germ remains in this location until approximately three-fourths of the root development is completed, at which point it breaks through the dental sac and begins to erupt, usually around the time the child reaches school age . During this process, any inflammation of the root caused by caries or the impaction of deciduous teeth can exert abnormal pressure on the permanent tooth germ, leading to alterations in the anatomical morphology of the developing permanent dentition . Notably, the patient reported a history of chin and dental trauma in childhood, although the details were unclear, and minor changes in the dental arch may not have been noticed by the patient or their parents. However, abnormal impact forces could have displaced the tooth germ to an abnormal position or angle, obstructing its normal eruption path and potentially leading to impaction. The panoramic radiograph revealed a curved root of the impacted lateral incisor in this patient. When the developing tooth germ is subjected to sustained mechanical forces beyond its tolerance, it can result in an abnormal tooth morphology. The rigid crown structure may deviate from the normal eruption axis, causing deformation of the elastic dental apical complex tissues, which histologically include Hertwig's epithelial root sheath, the apical papilla, and the surrounding dental follicle, ultimately leading to partial root curvature . 2. Treatment strategy: space expansion and growth patterns The primary consideration for this patient was the source of the space. Since the patient's scattered mandibular pretreatment spaces did not match the width of the blocked teeth, proper spaces had to be obtained through molar distalization or mandibular arch expansion. According to growth and development studies , development of the cuspal interdental width of the mandibular dental arch stops at approximately 11 years of age, but the available space in the posterior segment of the dental arch increases by 1.45 mm per year in boys younger than 17 years of age. The development of the cuspal interdental width of the mandibular teeth in this patient was almost complete, and the posterior segment of the mandibular dental arch still had more available space. When performing space analysis, it is important to consider vertical dimensions in addition to sagittal and horizontal space expansion. Considering that this was a normodivergent case, the total Jarabak angle was within the normal range, and the direction of mandibular growth was normal. Control of the vertical orientation can be slightly relaxed. According to Sato et al. , in the growing facial skeleton, the vertical height of the maxillary teeth determines the position of the occlusion plane, whereas the growth of the maxillary alveolar bone determines the inclination of the occlusion plane, and a gently sloping posterior occlusal plane of the maxilla facilitates the development of the mandible in a counterclockwise direction. In this case, we used elastic Class III traction to distally move the cuspids to gain clearance while elongating the upper molars to guide the maxillary posterior occlusal plane to flatten, which helped the mandible grow in the correct direction and lift the deep overlay of the occlusion; the side effect force of proximo-central movement of the 26 teeth generated by elastic traction was offset by the push springs between teeth 24 and 26. During the alignment phase, we corrected the axial inclination of the upper anterior teeth, and with further development of the mandible, the patient's mouth and lips were able to close, and the side effect of lip inclination of the anterior teeth produced by elastic traction was counteracted by the strong functional orthodontic forces generated by the lip and buccal muscles. Scattered spaces were present in the lower anterior teeth, and the push springs did not cause lip tilt in the lower anterior teeth; during the space creation phase, we added a small amount of the rocking chair type to the upper and lower archwires to depress the anterior teeth and maintain the anterior torque (Fig. ). By leveraging digital technology, we can accurately assess the available space in the patient’s mandibular arch and precisely measure the width of the impacted tooth and the required space through three-dimensional simulation. This process allows us to predict whether future growth will provide adequate space. Additionally, the 3D simulation provides a clear visualization of the morphology of tooth 32 and its relationship with adjacent teeth, helping to identify the path of least resistance and to optimize the direction of traction. When formulating the treatment plan, the 3D model and digital simulation also enable patients and their families to better understand the proposed treatment, aiding those without a medical background in comprehending the treatment process and the rationale behind decision-making. 3. Treatment strategy: timing of treatment The success of treatment for an impacted tooth depends on the position of the tooth, the degree of root curvature, the timing of treatment, the available space in the dental arch, and the activity of the Hertwig epithelial root sheath . According to the literature , even when the root of an impacted tooth is fully developed and the resistance from the crown is reduced, there is still a tendency for the impacted tooth to erupt upwards, and the earlier the intervention on the impacted tooth, the more likely it is to erupt naturally. According to Baccetti T-modified cervical spine analysis , this patient was at the peak of growth and development in the CS3-CS4 stage, with high growth potential, and because the impacted tooth was curved in the proximal apical 1/3 and vertically impacted, it was a moderately difficult curved tooth . Therefore, there is a certain possibility of inducing natural eruption of the impacted tooth, but resorption is likely to occur when the curved root is extruded by the alveolar bone. During the induction process, forceful intervention on the impacted tooth should be as little as possible to increase the likelihood of natural eruption and to promote the formation of normal keratinized gingiva . If there is no significant change in the position of the blocked tooth within six months of the induction intervention, excessive resistance to eruption should be considered, and traction treatment should be used instead. Although the preinduction intervention in this case brought the blocked tooth to the subgingival level, there was still no significant change at six months, and it was hypothesized that the capsule was encircling the crown of the blocked tooth, resulting in the inability to continue erupting; therefore, we surgically exposed the blocked tooth, bonded a small traction device, and increased traction to assist in eruption. 4. Treatment strategies: biomechanics and complications During traction, the blocked teeth were subjected to upward and forward forces due to the buccal position of the orthodontic archwires. Although we used light force traction, unavoidable root resorption and gingival recession occurred postoperatively (Fig. ). The process of orthodontic tooth movement is accompanied by continuous remodelling of the root-surface cementum, and when the orthodontic force or resistance is too high, the cementum resorption is greater than the restoration, and irreversible defects appear on the root surface of the tooth . Sameshima concluded that a malformed root morphology increases the risk of root resorption during the treatment process . The recommended force to move an impacted tooth is between 60–100 g . We used a force of 60–90 g for pulling, but the force exerted on the affected tooth was a continuous traction force, and the anatomical morphology of the affected tooth itself may have been the trigger for root resorption. Nevertheless, the treated impeded tooth had an acceptable crown-to-root ratio, although the root apex was rounded, and it still exhibited good retention with no associated endodontic symptoms. The uneven thickness of the bone wall around the root may cause the gingiva of the affected tooth to be inconsistent with the height of the healthy tooth, as it is impossible to ensure that the direction of traction of the impacted tooth exactly matches the position of the impaction during traction of the tooth out of the alveolar bone . In the present case, the upward-forward traction resulted in loss of the buccal bone wall of the affected tooth and gingival recession of the affected tooth. To solve this problem, we counterbonded the brackets on the affected teeth and used aussie wire to fabricate a torque ring to assist in applying lingual torque force and alleviate the problem of gingival recession on the impacted teeth. Although there was still some degree of gingival recession after surgery, postoperative CT revealed that the buccolingual bone plate of the blocked tooth was within the acceptable range. We recommended that the patient undergo gingival soft tissue surgery, which the patient declined. Long-term follow-up observation of this affected tooth is necessary. 5. Treatment strategy: treatment risks to consider for impacted teeth If guided eruption of the impacted tooth fails, surgical transplantation is an option. While transplantation can occur before or after full root development, studies indicate that fully developed roots may require endodontic treatment but do not worsen the prognosis . However, male patients might have lower success rates because of greater occlusal forces . Transplanting a tooth with a curved root complicates root canal treatment and often requires multidisciplinary care, leading to uncertain outcomes. Alternatively, extraction followed by space expansion and later implant or restorative treatment is feasible, although implants generally have lower survival rates and higher risks of peri-implant mucositis in comparison to natural teeth . Long-term implant use may cause loosening of adjacent teeth, periodontal disease, and aesthetic issues while also being less effective in maintaining the alveolar bone volume. In this case, removing the impacted tooth and closing the space via posterior tooth movement would likely result in significant Bolton ratio discrepancies. Additionally, some of the upper anterior dental tissues might need to be sacrificed to improve the occlusal relationship and the soft-tissue profile, thereby introducing further disadvantages for the patient.
A successful treatment plan was developed using digital simulation of the mandibular lateral incisor. Posttreatment imaging confirmed that the impacted tooth was in a satisfactory final position, the arch space was effectively utilized, and biomechanical forces were managed strategically to facilitate eruption of the tooth and maintain the stability of adjacent teeth.
Supplementary Material 1.
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Trends Over Time in Use of Nonrecommended Tests and Treatments Since Publication of the American Academy of Pediatrics Bronchiolitis Guideline | afca9c85-1d64-43af-88fe-b16727c64b54 | 7885040 | Pediatrics[mh] | Bronchiolitis is a common pediatric illness with a robust evidence base suggesting that no specific test or treatment is associated with a change in the clinical disease course. Despite this, the delivery of low-value care to children with bronchiolitis persists. , This is associated with increased risk for adverse outcomes from unnecessary care and increased health care costs. , Consequently, bronchiolitis is the target of many international guidelines aiming to standardize care. In the United States, the American Academy of Pediatrics (AAP) published a clinical practice guideline in 2006 and updated it in 2014. The most substantive change to the 2014 guideline was a recommendation against beta-agonist use among children with bronchiolitis, replacing support in the 2006 guideline for a monitored trial. Several studies have assessed clinical care outcomes following publication of the 2006 AAP bronchiolitis guideline using different methods and databases. Comparing care delivered in the post-2006 guideline period (ie, 2006-2012) with the preguideline period, Parikh et al found reduced use of bronchodilators, corticosteroids, complete blood counts (CBCs), respiratory syncytial virus testing, and chest radiographs (CRs) among patients admitted to the hospital. Employing a similar before and after study design to assess emergency department (ED) care, Johnson et al found a reduction in CR use only, with no other changes in the period after guideline publication (ie, 2006-2009). Assessing changes in compliance with guideline recommendations in the postguideline period, Florin et al found decreasing rates of corticosteroid and CR use from 2007 to 2012 among patients admitted to the hospital, whereas Burstein et al found no change in rates of CR use and Papenburg et al found no change in rates of antibiotic use in the ED from 2007 to 2015. Thus, current evidence on provider compliance with AAP bronchiolitis guideline recommendations may be incomplete. Questions remain surrounding the amount of change associated with guideline publication and the degree to which any improvements associated with guideline publication may be sustained over time. Furthermore, none of the existing literature, to our knowledge, addresses a significant time period following the 2014 update, leaving important knowledge gaps surrounding the utility of guideline updates. In this study, we aimed to evaluate trends over time in use of nonrecommended tests and treatments for bronchiolitis from the time of the 2006 AAP guideline publication to the present among a sample of patients in US children’s hospitals.
The Dartmouth-Hitchcock Medical Center Institutional Review Board approved this cohort study upon determination that it did not constitute human subjects research. The study was conducted in accordance with Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline. Study Design and Data Source This was a retrospective, observational hospital cohort study using the Pediatric Health Information Systems (PHIS) database (Children’s Hospital Association). The PHIS database contains deidentified administrative data from a large sample of tertiary care children’s hospitals. The database accounts for approximately 20% of pediatric hospitalizations in the United States. Data quality is ensured through a joint effort between the Children’s Hospital Association and participating hospitals. Patient Population We included encounters by children ages 28 days to 2 years discharged from November 1, 2006, to December 31, 2019, with a primary discharge diagnosis of acute bronchiolitis ( International Classification of Diseases, Ninth Revision code 466.11 or 466.19 or International Classification of Diseases, Tenth Revision code J21.X). We created 2 patient groups for analysis in this study: the ED group and the inpatient group. ED Group In PHIS, an encounter is defined as ED if the patient was ultimately discharged from the ED and not admitted to the hospital. Therefore, our ED group included only children discharged from the ED; all measured outcomes were reflective of care administered in the ED setting. Inpatient Group For children admitted to a hospital, PHIS combines billing for care delivered during the associated ED encounter with billing data for that hospitalization. Therefore, our inpatient group included usage from the associated ED visit as well as inpatient charges (except in the case of a transfer from an outside ED). Inpatient encounters were included only if the encounter also received the All Patient Refined Diagnosis Related Groups (version 36) for bronchiolitis and respiratory syncytial virus pneumonia (code 138) for specificity. Observation encounters were included in the inpatient group. Only hospitals contributing data for the full study period were included. This was determined by setting, such that hospitals must have contributed ED data for the full study period for their data to be included in the ED group and inpatient data for the full study period for their data to be included in the inpatient group. We excluded encounters by patients with complex chronic conditions, those with a billing charge for mechanical ventilation, and those with an inpatient length of stay (LOS) of greater than 10 days as these encounters represent clinical scenarios that fall outside those for which current clinical guidelines offer recommendations. All encounters meeting inclusion criteria were analyzed individually. We did not exclude hospital readmissions or repeat ED visits within the same episode of illness; these were treated as distinct clinical encounters. Encounters were grouped into 2 periods based on discharge date. Guideline period 1 spanned from November 2006, 1 month after the publication of the 2006 AAP guideline, to November 2014, the month of the 2014 guideline publication. Guideline period 2 spanned from December 2014, 1 month after the publication of the 2014 guideline, to December 2019. Measures The primary outcomes were rates of diagnostic testing and treatment as determined from billing data. We included tests (ie, CBC, CR, and viral testing) and treatments (ie, bronchodilators, corticosteroids, and antibiotics) that the AAP guidelines specifically recommend against in the evaluation and management of routine bronchiolitis. Bronchodilators included any form of epinephrine, albuterol, or levalbuterol. We analyzed LOS for inpatient and observation encounters and hospital admission rates from the ED between the 2 guideline periods as balancing measures. Statistical Analysis Demographic characteristics were summarized with frequencies and percentages, with values from guideline period 1 compared with those from guideline period 2 using χ 2 tests to identify candidate variables for adjustment. Segmented regression analysis with an interrupted time series (ITS) was conducted with the publication of the 2014 guideline as the event point. This analysis measured rates of change in outcomes over the 2 study periods, defined as the slope associated with use of tests and treatments over each period, and level change, defined as the change in use of tests and treatments between time periods divided by a single event point. Monthly rates of resource use were included in the segmented regression analysis. The model adjusted for the hospital providing service with random intercepts to control for clustering, as well as fixed effects for age, race/ethnicity, and payer. The ITS output is presented as a point estimate with 95% CIs for monthly slopes, change in slope between time periods, and level change between time periods. All statistical analyses were performed using SAS version 9.4 (SAS Institute) from June through December 2020. Changes were considered statistically significant if the 95% CI did not include 0.
This was a retrospective, observational hospital cohort study using the Pediatric Health Information Systems (PHIS) database (Children’s Hospital Association). The PHIS database contains deidentified administrative data from a large sample of tertiary care children’s hospitals. The database accounts for approximately 20% of pediatric hospitalizations in the United States. Data quality is ensured through a joint effort between the Children’s Hospital Association and participating hospitals.
We included encounters by children ages 28 days to 2 years discharged from November 1, 2006, to December 31, 2019, with a primary discharge diagnosis of acute bronchiolitis ( International Classification of Diseases, Ninth Revision code 466.11 or 466.19 or International Classification of Diseases, Tenth Revision code J21.X). We created 2 patient groups for analysis in this study: the ED group and the inpatient group. ED Group In PHIS, an encounter is defined as ED if the patient was ultimately discharged from the ED and not admitted to the hospital. Therefore, our ED group included only children discharged from the ED; all measured outcomes were reflective of care administered in the ED setting. Inpatient Group For children admitted to a hospital, PHIS combines billing for care delivered during the associated ED encounter with billing data for that hospitalization. Therefore, our inpatient group included usage from the associated ED visit as well as inpatient charges (except in the case of a transfer from an outside ED). Inpatient encounters were included only if the encounter also received the All Patient Refined Diagnosis Related Groups (version 36) for bronchiolitis and respiratory syncytial virus pneumonia (code 138) for specificity. Observation encounters were included in the inpatient group. Only hospitals contributing data for the full study period were included. This was determined by setting, such that hospitals must have contributed ED data for the full study period for their data to be included in the ED group and inpatient data for the full study period for their data to be included in the inpatient group. We excluded encounters by patients with complex chronic conditions, those with a billing charge for mechanical ventilation, and those with an inpatient length of stay (LOS) of greater than 10 days as these encounters represent clinical scenarios that fall outside those for which current clinical guidelines offer recommendations. All encounters meeting inclusion criteria were analyzed individually. We did not exclude hospital readmissions or repeat ED visits within the same episode of illness; these were treated as distinct clinical encounters. Encounters were grouped into 2 periods based on discharge date. Guideline period 1 spanned from November 2006, 1 month after the publication of the 2006 AAP guideline, to November 2014, the month of the 2014 guideline publication. Guideline period 2 spanned from December 2014, 1 month after the publication of the 2014 guideline, to December 2019.
In PHIS, an encounter is defined as ED if the patient was ultimately discharged from the ED and not admitted to the hospital. Therefore, our ED group included only children discharged from the ED; all measured outcomes were reflective of care administered in the ED setting.
For children admitted to a hospital, PHIS combines billing for care delivered during the associated ED encounter with billing data for that hospitalization. Therefore, our inpatient group included usage from the associated ED visit as well as inpatient charges (except in the case of a transfer from an outside ED). Inpatient encounters were included only if the encounter also received the All Patient Refined Diagnosis Related Groups (version 36) for bronchiolitis and respiratory syncytial virus pneumonia (code 138) for specificity. Observation encounters were included in the inpatient group. Only hospitals contributing data for the full study period were included. This was determined by setting, such that hospitals must have contributed ED data for the full study period for their data to be included in the ED group and inpatient data for the full study period for their data to be included in the inpatient group. We excluded encounters by patients with complex chronic conditions, those with a billing charge for mechanical ventilation, and those with an inpatient length of stay (LOS) of greater than 10 days as these encounters represent clinical scenarios that fall outside those for which current clinical guidelines offer recommendations. All encounters meeting inclusion criteria were analyzed individually. We did not exclude hospital readmissions or repeat ED visits within the same episode of illness; these were treated as distinct clinical encounters. Encounters were grouped into 2 periods based on discharge date. Guideline period 1 spanned from November 2006, 1 month after the publication of the 2006 AAP guideline, to November 2014, the month of the 2014 guideline publication. Guideline period 2 spanned from December 2014, 1 month after the publication of the 2014 guideline, to December 2019.
The primary outcomes were rates of diagnostic testing and treatment as determined from billing data. We included tests (ie, CBC, CR, and viral testing) and treatments (ie, bronchodilators, corticosteroids, and antibiotics) that the AAP guidelines specifically recommend against in the evaluation and management of routine bronchiolitis. Bronchodilators included any form of epinephrine, albuterol, or levalbuterol. We analyzed LOS for inpatient and observation encounters and hospital admission rates from the ED between the 2 guideline periods as balancing measures.
Demographic characteristics were summarized with frequencies and percentages, with values from guideline period 1 compared with those from guideline period 2 using χ 2 tests to identify candidate variables for adjustment. Segmented regression analysis with an interrupted time series (ITS) was conducted with the publication of the 2014 guideline as the event point. This analysis measured rates of change in outcomes over the 2 study periods, defined as the slope associated with use of tests and treatments over each period, and level change, defined as the change in use of tests and treatments between time periods divided by a single event point. Monthly rates of resource use were included in the segmented regression analysis. The model adjusted for the hospital providing service with random intercepts to control for clustering, as well as fixed effects for age, race/ethnicity, and payer. The ITS output is presented as a point estimate with 95% CIs for monthly slopes, change in slope between time periods, and level change between time periods. All statistical analyses were performed using SAS version 9.4 (SAS Institute) from June through December 2020. Changes were considered statistically significant if the 95% CI did not include 0.
Patient Population Over the 2006 to 2019 study period, 25 hospitals contributed complete data for the ED group and 35 hospitals contributed complete data for the inpatient group. There were 602 375 encounters among children discharged with a primary diagnosis of bronchiolitis; 404 203 encounters (67.1%) were in the ED group and 198 172 encounters (32.9%) were in the inpatient group. In both groups and guideline periods, 468 226 encounters (77.7%) involved children 12 months of age or younger, 356 796 encounters (59.2%) involved boys, and 223 098 encounters (37.0%) involved non-Hispanic White patients. Race/ethnicity differences were greatest in the inpatient setting, where 80 234 encounters (40.5%) involved non-Hispanic White patients, compared with 142 864 encounters (35.3%) in the ED setting . Trends in Testing Over guideline period 1 (ie, November 2006 to November 2014), the ITS model found a decrease in use for all testing measures in both groups, with the exception of viral testing in the ED group . In the ED group, the percent of encounters with CBC use changed by a mean of −0.03% monthly (95% CI, −0.04% to −0.02%) and the percent of encounters with CR use changed by a mean of −0.19% monthly (95% CI, −0.21% to −0.18%). In the inpatient group, the percent of encounters with CBC use changed by a mean of −0.13% monthly (95% CI, −0.16% to −0.11%), the percent with CR use changed by a mean of −0.23% monthly (95% CI, −0.26 to −0.21), and the percent with viral testing changed by a mean of −0.13% monthly (95% CI, −0.16% to −0.11%). Using the 2014 guideline publication as the event point for the ITS analysis, there were decreases in use of CR and viral testing between guideline periods. In the ED group, the percent of encounters with CR use changed by −4.1 percentage points (95% CI, −5.9 percentage points to −2.4 percentage points) between the 2 periods, and the percent with viral testing changed by −3.7 percentage points (95% CI, −5.9 percentage points to −1.5 percentage points). In the inpatient group, the percent with CR use changed by −6.3 percentage points (95% CI, −8.1 percentage points to −4.4 percentage points) and the percent with viral testing changed by −7.3 percentage points (95% CI, −9.6 percentage points to −5.0 percentage points) between periods . Use of all testing measures continued to decrease over guideline period 2, although the decrease slowed for CR in the ED group and CBC in the inpatient group . Over the full study period, in the ED group, adjusted use decreased from 6.4% of encounters (95% CI, 5.1%-7.7%) to 2.3% (95% CI, 1.0%-3.6%) for CBC, 48.4% (95% CI, 44.0%-52.9%) to 14.2% (95% CI, 9.8%-18.7%) for CR, and 23.5% (95% CI, 16.2%-30.8%) to 18.3% (95% CI, 11.0% to 25.6%) for viral testing. In the inpatient group, adjusted use decreased from 44.6% of encounters (95% CI, 39.8%-49.3%) to 23.6% (95% CI, 18.8%-28.3%) for CBC, 78.8% (95% CI, 75.6%-82.1%) to 37.3% (95% CI, 34.0%-40.6%) for CR, and 60.9% (95% CI, 55.3%-66.6%) to 33.5% (95% CI, 27.8%-39.2%) for viral testing. Trends in testing measures over time are shown in . Trends in Treatments Over guideline period 1, the ITS model found decreasing use for all treatments in both group . In the ED group, the percent of encounters with bronchodilator use changed by a mean of −0.11% monthly (95% CI, −0.13% to −0.09%), the percent with steroid use changed by a mean of −0.05% monthly (95% CI, −0.06 to −0.04%), and the percent with antibiotic use changed by a mean of −0.01% monthly (95% CI, −0.01% to −0.001%). In the inpatient group, the percent with bronchodilator use changed by a mean of −0.08% monthly (95% CI, −0.10% to −0.05%), the percent with steroid use changed by a mean of −0.09% monthly (95% CI, −0.12% to −0.07%), and the percent with antibiotic use changed by a mean of −0.16% monthly (95% CI, −0.19% to −0.14%). Using the 2014 guideline publication as the event point for the ITS analysis, there were decreases in all treatment measures between guideline periods. In the ED group, the percent of encounters with bronchodilator use changed by −13.5 percentage points (95% CI, −15.2 percentage points to −11.8 percentage points), the percent with steroid use changed by −2.0 percentage points (95% CI, −3.1 percentage points to −0.9 percentage points), and the percent with antibiotic use changed by −0.5 percentage points (95% CI, −1.0 percentage points to −0.01 percentage points) between periods. In the inpatient group, the percent of encounters with bronchodilator use changed by −11.3 percentage points (95% CI, −13.1 percentage points to −9.4 percentage points) and the percent with steroid use changed by −6.2 percentage points (95% CI, −8.5 percentage points to −3.9 percentage points) between periods . Over guideline period 2, the decrease in bronchodilator use found in guideline period 1 steepened significantly . In the ED group, the negative slope steepened by −0.15% (95% CI, −0.20 to −0.11), to a new mean monthly slope of −0.26% (95% CI, −0.30 to −0.23). In the inpatient group, the negative slope steepened by −0.18% (95% CI, −0.23 to −0.13), to a new mean monthly slope of −0.26% (95% CI, −0.30 to −0.22). Use of all treatment measures continued to decrease significantly across guideline period 2, except for antibiotics in the ED group; there was also a slowing of the declining trajectory in antibiotic use in the inpatient group over this period. Over the full study in period, in the ED group, adjusted use decreased from 56.3% (95% CI, 51.1% to 61.5%) to 26.0% (95% CI, 20.8% to 31.2%) for bronchodilators, 15.7% (95% CI, 13.0% to 18.2%) to 6.1% (95% CI, 3.4% to 8.7%) for steroids, and 4.2% (95% CI 3.3% to 5.0%) to 2.7% (95% CI, 1.8% to 3.6%) for antibiotics. In the inpatient group, adjusted use decreased from 73.0% (95% CI, 68.0% to 78.0%) to 50.1% (95% CI, 45.1% to 55.1%) for bronchodilators, 38.6% (95% CI, 35.3% to 42.0%) to 17.9% (95% CI, 14.6% to 21.2%) for steroids, and 49.1% (95% CI, 46.9% to 51.2%) to 23.8% (95% CI, 21.6% to 25.9%) for antibiotics. Trends in treatment measures over time are shown in . Balancing Measures Over the full study period, LOS decreased from 2.0 days (95% CI, 1.9 days-2.1 days) to 1.7 days (95% CI, 1.7 days-1.8 days), with a negative slope over both guideline periods. An increase of 0.03 days (95% CI 0.02 days-0.08 days) was found at the event point; there was no change in slope between periods . Hospital admission rate decreased over the full study period, from 18.0% (95% CI, 13.8%-22.2%) to 17.8% (95% CI, 13.6%-22.1%). There was a positive change in slope of 0.02% (95% CI, 0.01%-0.03%) over guideline period 2; no change in hospital admission rate was found at the event point .
Over the 2006 to 2019 study period, 25 hospitals contributed complete data for the ED group and 35 hospitals contributed complete data for the inpatient group. There were 602 375 encounters among children discharged with a primary diagnosis of bronchiolitis; 404 203 encounters (67.1%) were in the ED group and 198 172 encounters (32.9%) were in the inpatient group. In both groups and guideline periods, 468 226 encounters (77.7%) involved children 12 months of age or younger, 356 796 encounters (59.2%) involved boys, and 223 098 encounters (37.0%) involved non-Hispanic White patients. Race/ethnicity differences were greatest in the inpatient setting, where 80 234 encounters (40.5%) involved non-Hispanic White patients, compared with 142 864 encounters (35.3%) in the ED setting .
Over guideline period 1 (ie, November 2006 to November 2014), the ITS model found a decrease in use for all testing measures in both groups, with the exception of viral testing in the ED group . In the ED group, the percent of encounters with CBC use changed by a mean of −0.03% monthly (95% CI, −0.04% to −0.02%) and the percent of encounters with CR use changed by a mean of −0.19% monthly (95% CI, −0.21% to −0.18%). In the inpatient group, the percent of encounters with CBC use changed by a mean of −0.13% monthly (95% CI, −0.16% to −0.11%), the percent with CR use changed by a mean of −0.23% monthly (95% CI, −0.26 to −0.21), and the percent with viral testing changed by a mean of −0.13% monthly (95% CI, −0.16% to −0.11%). Using the 2014 guideline publication as the event point for the ITS analysis, there were decreases in use of CR and viral testing between guideline periods. In the ED group, the percent of encounters with CR use changed by −4.1 percentage points (95% CI, −5.9 percentage points to −2.4 percentage points) between the 2 periods, and the percent with viral testing changed by −3.7 percentage points (95% CI, −5.9 percentage points to −1.5 percentage points). In the inpatient group, the percent with CR use changed by −6.3 percentage points (95% CI, −8.1 percentage points to −4.4 percentage points) and the percent with viral testing changed by −7.3 percentage points (95% CI, −9.6 percentage points to −5.0 percentage points) between periods . Use of all testing measures continued to decrease over guideline period 2, although the decrease slowed for CR in the ED group and CBC in the inpatient group . Over the full study period, in the ED group, adjusted use decreased from 6.4% of encounters (95% CI, 5.1%-7.7%) to 2.3% (95% CI, 1.0%-3.6%) for CBC, 48.4% (95% CI, 44.0%-52.9%) to 14.2% (95% CI, 9.8%-18.7%) for CR, and 23.5% (95% CI, 16.2%-30.8%) to 18.3% (95% CI, 11.0% to 25.6%) for viral testing. In the inpatient group, adjusted use decreased from 44.6% of encounters (95% CI, 39.8%-49.3%) to 23.6% (95% CI, 18.8%-28.3%) for CBC, 78.8% (95% CI, 75.6%-82.1%) to 37.3% (95% CI, 34.0%-40.6%) for CR, and 60.9% (95% CI, 55.3%-66.6%) to 33.5% (95% CI, 27.8%-39.2%) for viral testing. Trends in testing measures over time are shown in .
Over guideline period 1, the ITS model found decreasing use for all treatments in both group . In the ED group, the percent of encounters with bronchodilator use changed by a mean of −0.11% monthly (95% CI, −0.13% to −0.09%), the percent with steroid use changed by a mean of −0.05% monthly (95% CI, −0.06 to −0.04%), and the percent with antibiotic use changed by a mean of −0.01% monthly (95% CI, −0.01% to −0.001%). In the inpatient group, the percent with bronchodilator use changed by a mean of −0.08% monthly (95% CI, −0.10% to −0.05%), the percent with steroid use changed by a mean of −0.09% monthly (95% CI, −0.12% to −0.07%), and the percent with antibiotic use changed by a mean of −0.16% monthly (95% CI, −0.19% to −0.14%). Using the 2014 guideline publication as the event point for the ITS analysis, there were decreases in all treatment measures between guideline periods. In the ED group, the percent of encounters with bronchodilator use changed by −13.5 percentage points (95% CI, −15.2 percentage points to −11.8 percentage points), the percent with steroid use changed by −2.0 percentage points (95% CI, −3.1 percentage points to −0.9 percentage points), and the percent with antibiotic use changed by −0.5 percentage points (95% CI, −1.0 percentage points to −0.01 percentage points) between periods. In the inpatient group, the percent of encounters with bronchodilator use changed by −11.3 percentage points (95% CI, −13.1 percentage points to −9.4 percentage points) and the percent with steroid use changed by −6.2 percentage points (95% CI, −8.5 percentage points to −3.9 percentage points) between periods . Over guideline period 2, the decrease in bronchodilator use found in guideline period 1 steepened significantly . In the ED group, the negative slope steepened by −0.15% (95% CI, −0.20 to −0.11), to a new mean monthly slope of −0.26% (95% CI, −0.30 to −0.23). In the inpatient group, the negative slope steepened by −0.18% (95% CI, −0.23 to −0.13), to a new mean monthly slope of −0.26% (95% CI, −0.30 to −0.22). Use of all treatment measures continued to decrease significantly across guideline period 2, except for antibiotics in the ED group; there was also a slowing of the declining trajectory in antibiotic use in the inpatient group over this period. Over the full study in period, in the ED group, adjusted use decreased from 56.3% (95% CI, 51.1% to 61.5%) to 26.0% (95% CI, 20.8% to 31.2%) for bronchodilators, 15.7% (95% CI, 13.0% to 18.2%) to 6.1% (95% CI, 3.4% to 8.7%) for steroids, and 4.2% (95% CI 3.3% to 5.0%) to 2.7% (95% CI, 1.8% to 3.6%) for antibiotics. In the inpatient group, adjusted use decreased from 73.0% (95% CI, 68.0% to 78.0%) to 50.1% (95% CI, 45.1% to 55.1%) for bronchodilators, 38.6% (95% CI, 35.3% to 42.0%) to 17.9% (95% CI, 14.6% to 21.2%) for steroids, and 49.1% (95% CI, 46.9% to 51.2%) to 23.8% (95% CI, 21.6% to 25.9%) for antibiotics. Trends in treatment measures over time are shown in .
Over the full study period, LOS decreased from 2.0 days (95% CI, 1.9 days-2.1 days) to 1.7 days (95% CI, 1.7 days-1.8 days), with a negative slope over both guideline periods. An increase of 0.03 days (95% CI 0.02 days-0.08 days) was found at the event point; there was no change in slope between periods . Hospital admission rate decreased over the full study period, from 18.0% (95% CI, 13.8%-22.2%) to 17.8% (95% CI, 13.6%-22.1%). There was a positive change in slope of 0.02% (95% CI, 0.01%-0.03%) over guideline period 2; no change in hospital admission rate was found at the event point .
This cohort study found that in the 13 years since publication of the 2006 AAP bronchiolitis guideline, there has been a consistently declining trajectory in most overuse measures in a sample of US children’s hospitals. After the 2014 guideline publication, there were further decreases in the ED and inpatient groups in use of CR, viral testing, bronchodilators, and steroids. There was also a significant trajectory change in bronchodilator use after the 2014 update, with rates of decrease more than 2-fold those observed before the update in both groups. These findings occurred in the context of small changes in LOS and hospital admission rates over the study period that are unlikely to represent a clinically relevant change in outcomes. Given that the largest changes over time were found for the bronchodilator measure, these changes warrant further discussion. The 2014 guideline update states that bronchodilators should not be administered to patients with bronchiolitis, replacing statements in the 2006 guideline that allowed for a monitored bronchodilator trial among these patients. The albuterol recommendation was the most substantive change between the 2 publications; thus, it may not be surprising that bronchodilator use is the measure for which the greatest change was observed following the 2014 update. While ITS analysis separates change into an incremental component and a slope component, we recognize that our large data set with a longer time period may create the appearance of a sudden change, which in reality was more gradual. However, the significant change in the trajectory of bronchodilator use after the 2014 guideline update further supports our choice of event point. Significant knowledge gaps remain surrounding how practice guidelines translate into clinical improvements. There is evidence to suggest that characteristics of guideline recommendations may be associated with the success of guideline uptake. The 2006 and 2014 bronchiolitis guidelines focused on reducing tests and treatments for which there is no supportive evidence. This process, also referred to as deimplementation, is associated with particular challenges for clinicians due to structural and psychological barriers associated with discontinuation of existing practices. , Whereas providers may adopt practices based on relatively weak early evidence for benefit, there is often resistance to reversal of practices until strong evidence for inefficacy is found. Our study results support the idea that a nationally promulgated clinical practice guideline may help overcome some barriers to deimplementation. One mechanism through which clinical practice guidelines may facilitate deimplementation at the patient level is by supporting active quality improvement (QI) interventions. A 2014 systematic review of 14 published QI initiatives in inpatient bronchiolitis care found that these interventions were associated with reductions in bronchodilator, steroid, antibiotic, and CR use. The QI efforts included in this review or published after the review have been associated with reduced use of nonrecommended services by implementing local clinical pathways citing AAP recommendations , , , , , , , , , , ; international studies using other national guidelines as the basis for local improvements have been associated with similar improvements. , , , Such QI efforts constitute 1 factor potentially associated with the decline in nonrecommended services found across our study period. While we suggest that our study provides evidence supporting the association of clinical guidelines with improved bronchiolitis care, there are many additional factors that were likely associated with changes in care patterns over our study period. Awareness of health care overuse as a widespread problem has increased over this time period, and other published recommendations focused on reducing low-value practices have followed. One such example is the Choosing Wisely campaign, an initiative founded by the American Board of Internal Medicine in 2012 to promote evidence-based, necessary care. In 2013, several recommendations for bronchiolitis were added to the Choosing Wisely initiative, including those recommending against the use of steroids, bronchodilators, CRs, and antibiotics. , Discriminating the outcomes associated with such important initiatives from those associated with clinical guidelines is challenging. The AAP guidelines are cited as support for these Choosing Wisely measures, and it seems likely that guidance from varying sources are associated with synergistic outcomes. , Our study found important improvements in bronchiolitis care in the ED and inpatient settings. However, usage rates observed at the end of our study period also suggest a need for continued deimplementation efforts. Higher rates of use observed in the inpatient group compared with the ED group may be associated with increased intervention for patients with more acute presentations, and this may or may not be warranted. Increased focus on developing and adjusting realistic improvement targets, such as achievable benchmarks of care, may play an important role in future deimplementation efforts. Appropriate usage rates for the measures evaluated in this study are not always zero; notably, however, rates at the end of our study period remain well above achievable benchmarks of care previously established using PHIS data, particularly in the inpatient group. , , Limitations This study has several limitations. We used administrative data to determine our study population and use patterns. Administrative data do not provide detailed clinical information for each encounter, and therefore we cannot determine which clinical scenarios or levels of acuity may be associated with use of measured services. Our population included only patients cared for in US children’s hospitals, which deliver a minority of bronchiolitis care. Therefore, our findings may not be generalizable to other care settings. For the inpatient group, we were unable to differentiate care provided in the ED prior to hospitalization from care delivered in the inpatient setting. There are 2 issues associated with seasonality that relate to our analysis. First, bronchiolitis severity fluctuates from year to year, and we did not adjust for severity of illness at the patient level; however, we included a long time series in which year to year variation in disease severity should balance out over time. Second, we did not adjust for the known variation in use of these tests and treatments associated with variability in patient volume over the course of any given year , ; however, we included monthly use rates in our regression model and a similar number and distribution of months in the 2 guideline periods to minimize the association of seasonality factors with our results. We cannot establish a direct causal relationship between guideline publication and the trends observed in this study. The use of segmented regression analysis supported a temporal association; however, we did not evaluate other secular trends that may have been associated with changes in bronchiolitis care over this time period. As noted, dichotomizing the long inclusion period may overestimate the magnitude of the level change associated with the event point.
This study has several limitations. We used administrative data to determine our study population and use patterns. Administrative data do not provide detailed clinical information for each encounter, and therefore we cannot determine which clinical scenarios or levels of acuity may be associated with use of measured services. Our population included only patients cared for in US children’s hospitals, which deliver a minority of bronchiolitis care. Therefore, our findings may not be generalizable to other care settings. For the inpatient group, we were unable to differentiate care provided in the ED prior to hospitalization from care delivered in the inpatient setting. There are 2 issues associated with seasonality that relate to our analysis. First, bronchiolitis severity fluctuates from year to year, and we did not adjust for severity of illness at the patient level; however, we included a long time series in which year to year variation in disease severity should balance out over time. Second, we did not adjust for the known variation in use of these tests and treatments associated with variability in patient volume over the course of any given year , ; however, we included monthly use rates in our regression model and a similar number and distribution of months in the 2 guideline periods to minimize the association of seasonality factors with our results. We cannot establish a direct causal relationship between guideline publication and the trends observed in this study. The use of segmented regression analysis supported a temporal association; however, we did not evaluate other secular trends that may have been associated with changes in bronchiolitis care over this time period. As noted, dichotomizing the long inclusion period may overestimate the magnitude of the level change associated with the event point.
This cohort study found that use of nonevidence-based tests and therapies for bronchiolitis has decreased since 2006 in a sample of encounters at US children’s hospitals. Publication of the 2014 AAP bronchiolitis guideline update was temporally associated with further decreases in use of some nonrecommended services, with the greatest decrease observed for bronchodilator use.
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Balancing between being the most valuable player (MVP) and passing the ball: a qualitative study of support when living with chronic pain in Sweden | ec8561bb-cc29-43b4-b163-3d427bd30b9c | 10831426 | Patient-Centered Care[mh] | Pain is defined as ‘an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage’. Chronic pain persists or recurs for over 3 months and is classified as a disease on its own, not just a symptom. The prevalence of chronic pain differs between studies, contexts and types of measurement. In a large European study comprising 16 countries, the prevalence of chronic pain was estimated to be 19%. A US study showed a prevalence rate of 20.4%. Persons with chronic pain often have comorbidities (eg, depression, anxiety, cardiovascular disease and cancer), side effects from medication and poor health-related quality of life. Chronic pain can adversely affect sleep, daily activities, relationships and the ability to work. Pain is often perceived as invisible to others, which can contribute to feeling unjustly treated in society. From a societal and health economic perspective, chronic pain presents challenges because it is a common reason for sick leave and healthcare-seeking behaviour. In Sweden, the cost (indirect and direct) of chronic pain-related diagnoses was estimated at €32 billion per year in 2012, of which 59% were due to sick leave and early retirement. A meta-synthesis showed that support from family and friends is important in pain management. Social support can include sharing advice, expressions of empathy and contributing to positive feelings. In contrast, lacking support can lead to feelings of loneliness and not being needed. Peer support interventions have been shown to decrease pain severity and interference. However, there is conflicting evidence of the positive effects of support. A peer support intervention for veterans with musculoskeletal pain found no statistically significant impact on pain. Studies investigating spouses’ participation in educational interventions suggest no additional benefits of including a partner and that participating with a partner could make participants more prone to fatigue and lower self-efficacy compared with not participating with a partner. Collaborative relationships with healthcare professionals constitute support that facilitates self-management of pain. The biopsychosocial model and the multimodal approach have been shown to improve pain management. However, it has also been reported that persons with chronic pain feel that healthcare professionals rarely take their condition seriously and that they desire better support from health professionals. Due to conflicting evidence and the complexity of support for persons with chronic pain, there is a need to understand the meaning of support, both within and outside the healthcare system. A deeper understanding of the phenomenon would facilitate the comprehension of the need for support and could aid in bringing clarity on what kind of support persons with chronic pain want and need. Therefore, this study aims to elucidate the meaning of lived experience of support from social networks and the healthcare sector in persons with chronic pain.
Design The present study applied a qualitative method with a phenomenological hermeneutic approach inspired by Lindseth and Norberg. Phenomenological hermeneutics is suitable for interpreting the essential meaning of a lived phenomenon through text narratives. This study follows the Standards for Reporting Qualitative Research guidelines. Participants and setting Participants were recruited from four Swedish patient organisations by a Facebook post or an email sent from the organisations. These organisations are well established, with members having different diagnoses and many having chronic pain in common. Persons willing to participate in the study contacted the first author (VL) by email. Inclusion criteria were ≥18 years of age, living in Sweden and having chronic musculoskeletal pain (defined as ‘chronic pain arising from musculoskeletal structures’ ). Persons who primarily seemed to struggle with other conditions and congenital diseases, such as concurrent cancer diagnosis, were excluded. Participants who mainly wanted to share their narratives about musculoskeletal pain but had congenital diseases, undergone cancer treatment or had another pain-related diagnosis were not excluded. Some 177 persons (1 non-binary, 4 men, 172 women) expressed interest in participating. A purposive sampling strategy was employed to include participants from different parts of Sweden, regardless of treatment or current contact with healthcare. Five participants mentioned receiving support from the healthcare sector and social networks by starting to share their narratives in the email expressing interest in participating. They were purposefully selected as they were willing to share their vast experience of the phenomenon under study, allowing the collection of rich data. Maximum variation sampling allowed the discovery of common meanings across demographic differences. Therefore, a diversity of experiences of support, age, geographical location, sick leave rate and background diagnosis was sought even though most potential participants were women. Eight participants were initially included, and their narratives were deemed sufficient to answer the study’s research question. Another two participants were interviewed to achieve greater variation in education level. None of the participants declined to participate. The material was considered rich enough to find meanings of support. After discussions in the research group, inclusion was halted at 10 participants. The author who conducted the interviews (VL) has a nursing and public health background. Before the study, the interviewer’s preunderstanding was written (see ) and reflected on in the analysis. VL was a novice in phenomenological hermeneutics; however, the research group’s extensive experience complemented her lack of practice in this field. A patient representative was also part of the research group and contributed with experience of living with chronic pain. 10.1136/bmjopen-2023-079229.supp1 Supplementary data Data collection A semistructured interview guide ( ), derived from Brinkmann and Kvale, was developed by VL with input from SW, ML and IE. The guide included three domains of support: the healthcare sector, social networks and how support from social networks could be integrated into care. The three domains were chosen based on their previously described importance. The interview guide contained open-ended questions with suggestions for additional probing questions. It was piloted in the first two interviews and revised by changing from the question ‘Which persons outside of the healthcare sector have you gotten support/help from?’ to ‘Which persons outside of the healthcare sector have been important to you regarding your pain?’ The final version of the question better facilitated narratives about social networks. The narratives from the two pilot interviews were deemed relevant, as they answered the research question and were thus included in the data analysis. Seven interviews were conducted digitally through Zoom, one by phone, and two face-to-face between February 2021 and August 2022. The interviews were recorded and transcribed verbatim by VL. Participants chose the interview date, place and format. Video and telephone interviews are trustworthy alternatives to face-to-face interviews in qualitative research. 10.1136/bmjopen-2023-079229.supp2 Supplementary data Patient and public involvement Four patient organisations contributed to recruiting study participants and will contribute to disseminating the findings. One of the coauthors (V-AS) is a patient representative. V-AS actively participated in data analysis and manuscript preparation. Data analysis Data were analysed with phenomenological hermeneutics. The method, influenced by Ricoeur’s theory of interpretation and developed by Lindseth and Norberg, involves three intertwined phases: naïve understanding, structural analysis and interpretation of the whole. Through the hermeneutic spiral, the phases are constantly overlapping, revisited and compared with each other to move between explanation and understanding by interpretation of the whole and the parts. Naïve understanding Each interview was read several times. VL formulated a naïve understanding for each interview before constructing a merged naïve understanding of all interviews. Structural analyses The structural analyses (see ) were performed with the software NVivo V.12 by VL with input from the other authors. The text of each interview was divided into meaning units and condensed. All text was considered, but only text associated with the study’s aim was included in the structural analyses. The condensed meaning units were continuously compared with the naïve understanding. The interviews were read through again, and the naïve understanding was revised and compared with the structural analyses. This process was repeated several times. Eventually, tentative themes and subthemes were formulated and compared with the condensed meaning units and the naïve understanding. VL and IE continuously discussed and reformulated the tentative findings before consulting the other authors. Interpretation of the whole In interpreting the whole VL and IE compared the preunderstanding, the naïve understanding and the structural analyses several times to identify inconsistencies. The analysis was revised until all parts were consistent. The underlying meaning in the data was reflected on and compared with the existing literature, such as previous studies, the work of the philosopher Ricoeur and the underpinnings of person-centred care, yielding a new understanding. ML read all the interviews and the findings to ensure the interpretations were reasonable before giving feedback on the naïve understanding, structural analyses and interpretation of the whole. The understanding of the meaning of the findings was discussed among all authors several times to connect their perspectives, knowledge and understandings. The interpreted metaphor was developed through discussions among all authors based on the link to the naïve understanding and structural analyses. When consensus on the meaning of the findings and the metaphor was reached, the interpretation of the whole was formulated.
The present study applied a qualitative method with a phenomenological hermeneutic approach inspired by Lindseth and Norberg. Phenomenological hermeneutics is suitable for interpreting the essential meaning of a lived phenomenon through text narratives. This study follows the Standards for Reporting Qualitative Research guidelines.
Participants were recruited from four Swedish patient organisations by a Facebook post or an email sent from the organisations. These organisations are well established, with members having different diagnoses and many having chronic pain in common. Persons willing to participate in the study contacted the first author (VL) by email. Inclusion criteria were ≥18 years of age, living in Sweden and having chronic musculoskeletal pain (defined as ‘chronic pain arising from musculoskeletal structures’ ). Persons who primarily seemed to struggle with other conditions and congenital diseases, such as concurrent cancer diagnosis, were excluded. Participants who mainly wanted to share their narratives about musculoskeletal pain but had congenital diseases, undergone cancer treatment or had another pain-related diagnosis were not excluded. Some 177 persons (1 non-binary, 4 men, 172 women) expressed interest in participating. A purposive sampling strategy was employed to include participants from different parts of Sweden, regardless of treatment or current contact with healthcare. Five participants mentioned receiving support from the healthcare sector and social networks by starting to share their narratives in the email expressing interest in participating. They were purposefully selected as they were willing to share their vast experience of the phenomenon under study, allowing the collection of rich data. Maximum variation sampling allowed the discovery of common meanings across demographic differences. Therefore, a diversity of experiences of support, age, geographical location, sick leave rate and background diagnosis was sought even though most potential participants were women. Eight participants were initially included, and their narratives were deemed sufficient to answer the study’s research question. Another two participants were interviewed to achieve greater variation in education level. None of the participants declined to participate. The material was considered rich enough to find meanings of support. After discussions in the research group, inclusion was halted at 10 participants. The author who conducted the interviews (VL) has a nursing and public health background. Before the study, the interviewer’s preunderstanding was written (see ) and reflected on in the analysis. VL was a novice in phenomenological hermeneutics; however, the research group’s extensive experience complemented her lack of practice in this field. A patient representative was also part of the research group and contributed with experience of living with chronic pain. 10.1136/bmjopen-2023-079229.supp1 Supplementary data
A semistructured interview guide ( ), derived from Brinkmann and Kvale, was developed by VL with input from SW, ML and IE. The guide included three domains of support: the healthcare sector, social networks and how support from social networks could be integrated into care. The three domains were chosen based on their previously described importance. The interview guide contained open-ended questions with suggestions for additional probing questions. It was piloted in the first two interviews and revised by changing from the question ‘Which persons outside of the healthcare sector have you gotten support/help from?’ to ‘Which persons outside of the healthcare sector have been important to you regarding your pain?’ The final version of the question better facilitated narratives about social networks. The narratives from the two pilot interviews were deemed relevant, as they answered the research question and were thus included in the data analysis. Seven interviews were conducted digitally through Zoom, one by phone, and two face-to-face between February 2021 and August 2022. The interviews were recorded and transcribed verbatim by VL. Participants chose the interview date, place and format. Video and telephone interviews are trustworthy alternatives to face-to-face interviews in qualitative research. 10.1136/bmjopen-2023-079229.supp2 Supplementary data
Four patient organisations contributed to recruiting study participants and will contribute to disseminating the findings. One of the coauthors (V-AS) is a patient representative. V-AS actively participated in data analysis and manuscript preparation.
Data were analysed with phenomenological hermeneutics. The method, influenced by Ricoeur’s theory of interpretation and developed by Lindseth and Norberg, involves three intertwined phases: naïve understanding, structural analysis and interpretation of the whole. Through the hermeneutic spiral, the phases are constantly overlapping, revisited and compared with each other to move between explanation and understanding by interpretation of the whole and the parts. Naïve understanding Each interview was read several times. VL formulated a naïve understanding for each interview before constructing a merged naïve understanding of all interviews. Structural analyses The structural analyses (see ) were performed with the software NVivo V.12 by VL with input from the other authors. The text of each interview was divided into meaning units and condensed. All text was considered, but only text associated with the study’s aim was included in the structural analyses. The condensed meaning units were continuously compared with the naïve understanding. The interviews were read through again, and the naïve understanding was revised and compared with the structural analyses. This process was repeated several times. Eventually, tentative themes and subthemes were formulated and compared with the condensed meaning units and the naïve understanding. VL and IE continuously discussed and reformulated the tentative findings before consulting the other authors. Interpretation of the whole In interpreting the whole VL and IE compared the preunderstanding, the naïve understanding and the structural analyses several times to identify inconsistencies. The analysis was revised until all parts were consistent. The underlying meaning in the data was reflected on and compared with the existing literature, such as previous studies, the work of the philosopher Ricoeur and the underpinnings of person-centred care, yielding a new understanding. ML read all the interviews and the findings to ensure the interpretations were reasonable before giving feedback on the naïve understanding, structural analyses and interpretation of the whole. The understanding of the meaning of the findings was discussed among all authors several times to connect their perspectives, knowledge and understandings. The interpreted metaphor was developed through discussions among all authors based on the link to the naïve understanding and structural analyses. When consensus on the meaning of the findings and the metaphor was reached, the interpretation of the whole was formulated.
Each interview was read several times. VL formulated a naïve understanding for each interview before constructing a merged naïve understanding of all interviews.
The structural analyses (see ) were performed with the software NVivo V.12 by VL with input from the other authors. The text of each interview was divided into meaning units and condensed. All text was considered, but only text associated with the study’s aim was included in the structural analyses. The condensed meaning units were continuously compared with the naïve understanding. The interviews were read through again, and the naïve understanding was revised and compared with the structural analyses. This process was repeated several times. Eventually, tentative themes and subthemes were formulated and compared with the condensed meaning units and the naïve understanding. VL and IE continuously discussed and reformulated the tentative findings before consulting the other authors.
In interpreting the whole VL and IE compared the preunderstanding, the naïve understanding and the structural analyses several times to identify inconsistencies. The analysis was revised until all parts were consistent. The underlying meaning in the data was reflected on and compared with the existing literature, such as previous studies, the work of the philosopher Ricoeur and the underpinnings of person-centred care, yielding a new understanding. ML read all the interviews and the findings to ensure the interpretations were reasonable before giving feedback on the naïve understanding, structural analyses and interpretation of the whole. The understanding of the meaning of the findings was discussed among all authors several times to connect their perspectives, knowledge and understandings. The interpreted metaphor was developed through discussions among all authors based on the link to the naïve understanding and structural analyses. When consensus on the meaning of the findings and the metaphor was reached, the interpretation of the whole was formulated.
Ten participants were included in the study (two men, one non-binary and seven women). All eligible participants of other genders than female were included. The demographic characteristics of participants are described in . The interviews lasted between 39 and 101 min (mean 77 min). Findings from the analyses are presented in the following order: the naïve understanding, the structural analyses and the interpretation of the whole. Naïve understanding The naïve understanding of the meaning of support is that it reinforces participants’ ability to manage their pain and everyday life. Participants seek to address their pain and life situation independently but need support to achieve these goals. They feel lonely in and diminished by the healthcare sector, often seen as unavailable or hostile. Support from the right healthcare professional, someone who listens and will go the extra mile to establish a diagnosis and provide help, makes a big difference in participants’ perception of their own capability. Experiences of support from outside the healthcare sector vary considerably. Although participants are eager to manage independently, social networks that believe in them, show compassion and fight together with them are essential. Structural analyses The main theme, themes and subthemes are described below and in . The metaphor of a football match is used throughout the designation of the main theme, themes and subthemes to elucidate the meaning of support. The metaphor is related to participants’ narratives and elaborated on under each heading. Balancing between being the most valuable player and passing the ball in the match against pain Chronic pain can be a constant battle, and just like a football match, it can vary in intensity. In this match, pain is the opponent, the person with chronic pain is the most valuable player (MVP), and the teammates are individuals within the MVP’s social networks and healthcare sector. The social networks could include family, partners, friends, employers, colleagues, peers with chronic pain, personal trainers, personal coaches, persons performing complementary therapies, neighbours and pets. The ball (designated as pain management) in this football match is passed around to members of the MVP’s team to win the match against pain. The attempt to win the match does not mean being pain-free but living the life the person with chronic pain wants to live despite the pain. The meaning of lived experiences of support is the constant balancing act between managing alone (being the MVP) and accepting help from others (passing the ball), which is further explained through the themes and sub-themes. Being the MVP Participants wanted to contribute to society like everyone else and manage independently by taking the lead in their care and daily life. They also desired to be who they were without pain dominating their lives. Contemplating the metaphor, this can be interpreted as they aspired to be the MVP in all aspects of their lives. Being believed and listened to were important aspects of being trusted to dribble the ball, which is essential when seeking to be the MVP. Being a valuable player and not just the injured one Participants sought to be recognised as the persons they were, with unique personalities and experiences, which could often be difficult to achieve. When perceived as a product of their pain, they felt excluded and viewed as someone who could not accomplish much. When the social networks provided support by accepting the pain as part of the participants but still recognising them for who they were and their capabilities, it facilitated their acceptance of themselves and the pain. They used to ask me,’ Why are you limping?’ I said,’ I played football last weekend,’ and I have never played football. So he [participant’s partner] told me, ‘Now you’re going to stop to tell them that you’ve played football.’ After that, I felt fine. There was no problem. I even have a colleague who says, ‘You’re limping. Maybe you should sit down.’ I don’t have to be perfect all the time. Participant 4 Pets could also contribute to this support, providing unconditional affection and companionship. Participants also wanted healthcare professionals to recognise them as the persons they were. They felt supported when healthcare professionals aimed at strengthening their resources by not only focusing on their limitations but also on their abilities. Participants felt an enhanced power by accessing self-help devices (eg, orthoses). It is about being an important part of society, to contribute… instead of being the one others should take care of. Self-help devices help to achieve that. Participant 10 The social networks provided support by requesting the participants’ help and advice. This support affirmed the participants’ view of themselves as unique, capable, meaningful and contributors rather than just someone with pain. Providing peer support to others with pain within a patient organisation exemplifies how participants contributed. I find good support in supporting others. You get a reflection of yourself that way. So, maybe that is my best support, to support others. […] It was perfect to have somebody who needed me. Participant 3 Being recognised as a person rather than someone struggling with pain could be interpreted as being considered a valuable player in football. Valuable football players are still useful to the team when injured, as everyone appreciates their efforts and knows their potential. They are not regarded as ‘that injured player.’ They are still valuable, and everyone is eager to see them return to the field. Being trusted to dribble To participants, a diagnosis was important to have their pain experiences taken seriously, understanding their pain and being believed, but it was often perceived as a challenging process. A diagnosis meant validating their condition and was also experienced as facilitating being believed, trusted and understood by the social networks. Being believed, trusted and understood by others was a support, and it also encouraged that expectations from others did not clash with the participants’ abilities. When participants were trusted with tasks they could perform, their view of themselves as capable persons was reinforced. I have to put on a mask in front of people and pretend to be happy. But my friend says, ’I don’t mind that you’re low and in pain. You don’t need to be happy and energised. We can still have coffee.’ It's like getting rid of a 20 kg backpack. He understands. Participant 7 Participants sometimes felt they received better support within complementary therapies compared with traditional care. They felt listened to and perceived as capable. This complimentary support, however, was not always affordable because of the participants’ often strained economy. My massage therapist sees me. I think that is a need that everyone has, to be seen and listened to. Participant 2 Being believed and listened to when sharing experiences of pain could be viewed as a football player being trusted by other teammates. The teammates show that the player and their abilities are trusted by passing them the ball and encouraging them to dribble, meaning taking responsibility for the next move. Passing the ball Living with pain was challenging, and occasionally, participants felt their abilities were inadequate. They needed a team to help them regain trust in themselves and fight to improve their situation. In football, the MVP must have a team to pass the ball to because they cannot win the game alone. Being part of a team Participants often felt alone, struggling with pain. Navigating the healthcare system and the social insurance agency’s policies was difficult. Fighting different systems alone evoked feelings of being diminished, vulnerable and powerless. When they found regular contact with a healthcare professional willing to help and possibly involve other professionals, or when their networks helped them fight the system, they did not feel as lonely. Regular contact enhanced the participants’ sense of capability. Having support from others, they felt more confident and could accomplish more. My personal trainer said, ‘I have a plan. Let’s focus on this so you can continue fighting.’ Thanks to her, I am stronger and I feel like things are moving forward. Participant 1 I want to take responsibility for my pain and situation myself, but to be able to have someone to ask for help when I can’t bear to deal with it. Like a backup, a support that stands on the side but does not overtake the main responsibility. It is very easy to end up in a subordinate position when you have a chronic condition, that you’re in the hands of others. I want to be in charge but still have that support system around me as a backup for when I’m worse. When I do not have that, I have to push myself beyond my limits, and my health deteriorates. Participant 8 Reducing loneliness by accepting support from others could be analogous to being part of a football team. The individual is stronger with teammates and has a better chance of beating the other team (ie, living the desired life despite pain). Being part of a team also means being included and not alone. Having teammates when you have been tackled Participants felt hopeless when told by healthcare professionals there was nothing left to be done after undergoing several medical treatments or when test results failed to reveal the cause of their pain. The hope of feeling capable was restored when they were provided support (eg, tailored training programmes or self-help devices). When social networks provided support by facilitating daily tasks, tailored work schedules, ideas for pain management or contacts with trusted healthcare professionals, participants felt hope that their circumstances would improve, and they could live the desired life. I was advised to change my diet. It helped me so much. It somewhat improved my state because I could affect my situation a little bit myself. Participant 5 Regaining hope could mean having a teammate take the ball when the football player has been tackled and cannot dribble on their own (when the pain is unbearable, and they do not know how to move on). By having a teammate take the ball (pain management), the hope remains that the team can control the ball instead of losing it to the opposing team (the pain). There is hope that there is something else to try, even though all options for pain management are exhausted and someone is fighting with you when you feel like your abilities are not enough to fight the pain on your own. When I get this lumbago, I believe it will never pass, and I have to live my whole life like this. And then I talk to him [participant’s partner], and he reminds me it will pass, and I’ll be alright. It is good to be reminded. Otherwise, I’ll go into that tunnel, thinking everything will go bad. Participant 4 Worrying about being a benchwarmer Participants found it challenging to determine what they could share about their situation with their networks (particularly family and friends) without appearing as a burden. Not wanting to strain their networks or cause worry discouraged participants from including them in their care. I don’t know how much is okay to… share. What is oversharing? And how much can I share so it becomes enough, so they understand, but it does not become too much? It is a balancing act, and I find it difficult to know where the boundaries are. I dare not take that leap to tell them about my situation. Participant 6 Some healthcare professionals blamed participants for their situation, whereas others went beyond their regular duties to support participants by working during their free time (eg, lunch break). Such support made a huge difference, as participants needed their help. At the same time, the feeling of being a burden was enhanced because the healthcare professionals had to sacrifice their spare time to offer that support. Fear of being a burden due to pain could be seen as fear of losing the title of MVP and becoming a benchwarmer, that is, always on the bench without the opportunity to participate and contribute. You are sort of like a ball being kicked around within the system. And even if you try to tell them ’No, this is the field, this is the playing field’, it becomes a bit like whatever. […] But I have been so lucky that these people are helping me out of pure, goodhearted will, even though they do not have time for it. Because their bosses tell them, ‘You should only do this or that because these are our resources.’ And I mean, they even helped me during lunch and such things. I must be careful when asking them for help because they are so kind-hearted. Participant 9 Interpretation of the whole As the main theme suggests, the meaning of the participants’ lived experiences of support from the healthcare sector and social networks is to balance being a capable person and accepting help from others to continue being that capable person. Being capable means being recognised for who you are as a person and your qualities, to contribute, to be trusted and listened to. Accepting support means to not be alone, having someone fighting with you in order to enhance one’s capability, but also to worry about being a burden. In football terms, being capable corresponds to being the MVP and accepting support corresponds to passing the ball. Developing the interpreted football metaphor; the MVP and the team compete against pain (see ). Many football players dream of being the MVP, whose actions ultimately determine the match’s outcome. Our interpretation of the findings is that persons with chronic pain are no different, that is, they aspire to be important. However, not even the MVP can win a match without team support. They need the team to believe in their capability and support them to reach their full potential. In accordance with how the MVP takes the lead, we would argue that persons with chronic pain take the lead in their daily lives and care by dribbling the ball (pain management). However, there must be a balance, as no team will win a match through only having the MVP dribbling, that is, it is also necessary to pass the ball. Passing the ball does not mean losing the title as MVP; instead, it means boosting the chances of winning the match through the help of teammates. Living with chronic pain often leads to accepting a life with pain. Aspiring to win the match against pain is not about being pain-free but about living a meaningful life and being capable despite the pain. When social networks and healthcare professionals do not listen to persons with chronic pain, believe them, see their capabilities or claim they can no longer be helped, they go to the opposing team. The person with chronic pain might also end up on the opposing team by, for instance, engaging in negative thoughts and behaviours. The field must be just and equitable to ensure the teammates and the MVP are on the same team fighting against the same opponent. For example, healthcare professionals must have fair conditions to stay on the right team and support the MVP instead of considering them a benchwarmer. The composition of the MVP’s team (social networks and healthcare professionals) and the optimal balance between being the MVP and passing the ball (being capable and accepting support to be capable) varies from person to person and over time. Persons with chronic pain feel valued and supported when the healthcare sector and social networks strengthen their capability by encouraging them to be the MVP and pass the ball. The balancing act between the two is the meaning of lived experiences of support.
The naïve understanding of the meaning of support is that it reinforces participants’ ability to manage their pain and everyday life. Participants seek to address their pain and life situation independently but need support to achieve these goals. They feel lonely in and diminished by the healthcare sector, often seen as unavailable or hostile. Support from the right healthcare professional, someone who listens and will go the extra mile to establish a diagnosis and provide help, makes a big difference in participants’ perception of their own capability. Experiences of support from outside the healthcare sector vary considerably. Although participants are eager to manage independently, social networks that believe in them, show compassion and fight together with them are essential.
The main theme, themes and subthemes are described below and in . The metaphor of a football match is used throughout the designation of the main theme, themes and subthemes to elucidate the meaning of support. The metaphor is related to participants’ narratives and elaborated on under each heading. Balancing between being the most valuable player and passing the ball in the match against pain Chronic pain can be a constant battle, and just like a football match, it can vary in intensity. In this match, pain is the opponent, the person with chronic pain is the most valuable player (MVP), and the teammates are individuals within the MVP’s social networks and healthcare sector. The social networks could include family, partners, friends, employers, colleagues, peers with chronic pain, personal trainers, personal coaches, persons performing complementary therapies, neighbours and pets. The ball (designated as pain management) in this football match is passed around to members of the MVP’s team to win the match against pain. The attempt to win the match does not mean being pain-free but living the life the person with chronic pain wants to live despite the pain. The meaning of lived experiences of support is the constant balancing act between managing alone (being the MVP) and accepting help from others (passing the ball), which is further explained through the themes and sub-themes. Being the MVP Participants wanted to contribute to society like everyone else and manage independently by taking the lead in their care and daily life. They also desired to be who they were without pain dominating their lives. Contemplating the metaphor, this can be interpreted as they aspired to be the MVP in all aspects of their lives. Being believed and listened to were important aspects of being trusted to dribble the ball, which is essential when seeking to be the MVP. Being a valuable player and not just the injured one Participants sought to be recognised as the persons they were, with unique personalities and experiences, which could often be difficult to achieve. When perceived as a product of their pain, they felt excluded and viewed as someone who could not accomplish much. When the social networks provided support by accepting the pain as part of the participants but still recognising them for who they were and their capabilities, it facilitated their acceptance of themselves and the pain. They used to ask me,’ Why are you limping?’ I said,’ I played football last weekend,’ and I have never played football. So he [participant’s partner] told me, ‘Now you’re going to stop to tell them that you’ve played football.’ After that, I felt fine. There was no problem. I even have a colleague who says, ‘You’re limping. Maybe you should sit down.’ I don’t have to be perfect all the time. Participant 4 Pets could also contribute to this support, providing unconditional affection and companionship. Participants also wanted healthcare professionals to recognise them as the persons they were. They felt supported when healthcare professionals aimed at strengthening their resources by not only focusing on their limitations but also on their abilities. Participants felt an enhanced power by accessing self-help devices (eg, orthoses). It is about being an important part of society, to contribute… instead of being the one others should take care of. Self-help devices help to achieve that. Participant 10 The social networks provided support by requesting the participants’ help and advice. This support affirmed the participants’ view of themselves as unique, capable, meaningful and contributors rather than just someone with pain. Providing peer support to others with pain within a patient organisation exemplifies how participants contributed. I find good support in supporting others. You get a reflection of yourself that way. So, maybe that is my best support, to support others. […] It was perfect to have somebody who needed me. Participant 3 Being recognised as a person rather than someone struggling with pain could be interpreted as being considered a valuable player in football. Valuable football players are still useful to the team when injured, as everyone appreciates their efforts and knows their potential. They are not regarded as ‘that injured player.’ They are still valuable, and everyone is eager to see them return to the field. Being trusted to dribble To participants, a diagnosis was important to have their pain experiences taken seriously, understanding their pain and being believed, but it was often perceived as a challenging process. A diagnosis meant validating their condition and was also experienced as facilitating being believed, trusted and understood by the social networks. Being believed, trusted and understood by others was a support, and it also encouraged that expectations from others did not clash with the participants’ abilities. When participants were trusted with tasks they could perform, their view of themselves as capable persons was reinforced. I have to put on a mask in front of people and pretend to be happy. But my friend says, ’I don’t mind that you’re low and in pain. You don’t need to be happy and energised. We can still have coffee.’ It's like getting rid of a 20 kg backpack. He understands. Participant 7 Participants sometimes felt they received better support within complementary therapies compared with traditional care. They felt listened to and perceived as capable. This complimentary support, however, was not always affordable because of the participants’ often strained economy. My massage therapist sees me. I think that is a need that everyone has, to be seen and listened to. Participant 2 Being believed and listened to when sharing experiences of pain could be viewed as a football player being trusted by other teammates. The teammates show that the player and their abilities are trusted by passing them the ball and encouraging them to dribble, meaning taking responsibility for the next move. Passing the ball Living with pain was challenging, and occasionally, participants felt their abilities were inadequate. They needed a team to help them regain trust in themselves and fight to improve their situation. In football, the MVP must have a team to pass the ball to because they cannot win the game alone. Being part of a team Participants often felt alone, struggling with pain. Navigating the healthcare system and the social insurance agency’s policies was difficult. Fighting different systems alone evoked feelings of being diminished, vulnerable and powerless. When they found regular contact with a healthcare professional willing to help and possibly involve other professionals, or when their networks helped them fight the system, they did not feel as lonely. Regular contact enhanced the participants’ sense of capability. Having support from others, they felt more confident and could accomplish more. My personal trainer said, ‘I have a plan. Let’s focus on this so you can continue fighting.’ Thanks to her, I am stronger and I feel like things are moving forward. Participant 1 I want to take responsibility for my pain and situation myself, but to be able to have someone to ask for help when I can’t bear to deal with it. Like a backup, a support that stands on the side but does not overtake the main responsibility. It is very easy to end up in a subordinate position when you have a chronic condition, that you’re in the hands of others. I want to be in charge but still have that support system around me as a backup for when I’m worse. When I do not have that, I have to push myself beyond my limits, and my health deteriorates. Participant 8 Reducing loneliness by accepting support from others could be analogous to being part of a football team. The individual is stronger with teammates and has a better chance of beating the other team (ie, living the desired life despite pain). Being part of a team also means being included and not alone. Having teammates when you have been tackled Participants felt hopeless when told by healthcare professionals there was nothing left to be done after undergoing several medical treatments or when test results failed to reveal the cause of their pain. The hope of feeling capable was restored when they were provided support (eg, tailored training programmes or self-help devices). When social networks provided support by facilitating daily tasks, tailored work schedules, ideas for pain management or contacts with trusted healthcare professionals, participants felt hope that their circumstances would improve, and they could live the desired life. I was advised to change my diet. It helped me so much. It somewhat improved my state because I could affect my situation a little bit myself. Participant 5 Regaining hope could mean having a teammate take the ball when the football player has been tackled and cannot dribble on their own (when the pain is unbearable, and they do not know how to move on). By having a teammate take the ball (pain management), the hope remains that the team can control the ball instead of losing it to the opposing team (the pain). There is hope that there is something else to try, even though all options for pain management are exhausted and someone is fighting with you when you feel like your abilities are not enough to fight the pain on your own. When I get this lumbago, I believe it will never pass, and I have to live my whole life like this. And then I talk to him [participant’s partner], and he reminds me it will pass, and I’ll be alright. It is good to be reminded. Otherwise, I’ll go into that tunnel, thinking everything will go bad. Participant 4 Worrying about being a benchwarmer Participants found it challenging to determine what they could share about their situation with their networks (particularly family and friends) without appearing as a burden. Not wanting to strain their networks or cause worry discouraged participants from including them in their care. I don’t know how much is okay to… share. What is oversharing? And how much can I share so it becomes enough, so they understand, but it does not become too much? It is a balancing act, and I find it difficult to know where the boundaries are. I dare not take that leap to tell them about my situation. Participant 6 Some healthcare professionals blamed participants for their situation, whereas others went beyond their regular duties to support participants by working during their free time (eg, lunch break). Such support made a huge difference, as participants needed their help. At the same time, the feeling of being a burden was enhanced because the healthcare professionals had to sacrifice their spare time to offer that support. Fear of being a burden due to pain could be seen as fear of losing the title of MVP and becoming a benchwarmer, that is, always on the bench without the opportunity to participate and contribute. You are sort of like a ball being kicked around within the system. And even if you try to tell them ’No, this is the field, this is the playing field’, it becomes a bit like whatever. […] But I have been so lucky that these people are helping me out of pure, goodhearted will, even though they do not have time for it. Because their bosses tell them, ‘You should only do this or that because these are our resources.’ And I mean, they even helped me during lunch and such things. I must be careful when asking them for help because they are so kind-hearted. Participant 9
Chronic pain can be a constant battle, and just like a football match, it can vary in intensity. In this match, pain is the opponent, the person with chronic pain is the most valuable player (MVP), and the teammates are individuals within the MVP’s social networks and healthcare sector. The social networks could include family, partners, friends, employers, colleagues, peers with chronic pain, personal trainers, personal coaches, persons performing complementary therapies, neighbours and pets. The ball (designated as pain management) in this football match is passed around to members of the MVP’s team to win the match against pain. The attempt to win the match does not mean being pain-free but living the life the person with chronic pain wants to live despite the pain. The meaning of lived experiences of support is the constant balancing act between managing alone (being the MVP) and accepting help from others (passing the ball), which is further explained through the themes and sub-themes. Being the MVP Participants wanted to contribute to society like everyone else and manage independently by taking the lead in their care and daily life. They also desired to be who they were without pain dominating their lives. Contemplating the metaphor, this can be interpreted as they aspired to be the MVP in all aspects of their lives. Being believed and listened to were important aspects of being trusted to dribble the ball, which is essential when seeking to be the MVP. Being a valuable player and not just the injured one Participants sought to be recognised as the persons they were, with unique personalities and experiences, which could often be difficult to achieve. When perceived as a product of their pain, they felt excluded and viewed as someone who could not accomplish much. When the social networks provided support by accepting the pain as part of the participants but still recognising them for who they were and their capabilities, it facilitated their acceptance of themselves and the pain. They used to ask me,’ Why are you limping?’ I said,’ I played football last weekend,’ and I have never played football. So he [participant’s partner] told me, ‘Now you’re going to stop to tell them that you’ve played football.’ After that, I felt fine. There was no problem. I even have a colleague who says, ‘You’re limping. Maybe you should sit down.’ I don’t have to be perfect all the time. Participant 4 Pets could also contribute to this support, providing unconditional affection and companionship. Participants also wanted healthcare professionals to recognise them as the persons they were. They felt supported when healthcare professionals aimed at strengthening their resources by not only focusing on their limitations but also on their abilities. Participants felt an enhanced power by accessing self-help devices (eg, orthoses). It is about being an important part of society, to contribute… instead of being the one others should take care of. Self-help devices help to achieve that. Participant 10 The social networks provided support by requesting the participants’ help and advice. This support affirmed the participants’ view of themselves as unique, capable, meaningful and contributors rather than just someone with pain. Providing peer support to others with pain within a patient organisation exemplifies how participants contributed. I find good support in supporting others. You get a reflection of yourself that way. So, maybe that is my best support, to support others. […] It was perfect to have somebody who needed me. Participant 3 Being recognised as a person rather than someone struggling with pain could be interpreted as being considered a valuable player in football. Valuable football players are still useful to the team when injured, as everyone appreciates their efforts and knows their potential. They are not regarded as ‘that injured player.’ They are still valuable, and everyone is eager to see them return to the field. Being trusted to dribble To participants, a diagnosis was important to have their pain experiences taken seriously, understanding their pain and being believed, but it was often perceived as a challenging process. A diagnosis meant validating their condition and was also experienced as facilitating being believed, trusted and understood by the social networks. Being believed, trusted and understood by others was a support, and it also encouraged that expectations from others did not clash with the participants’ abilities. When participants were trusted with tasks they could perform, their view of themselves as capable persons was reinforced. I have to put on a mask in front of people and pretend to be happy. But my friend says, ’I don’t mind that you’re low and in pain. You don’t need to be happy and energised. We can still have coffee.’ It's like getting rid of a 20 kg backpack. He understands. Participant 7 Participants sometimes felt they received better support within complementary therapies compared with traditional care. They felt listened to and perceived as capable. This complimentary support, however, was not always affordable because of the participants’ often strained economy. My massage therapist sees me. I think that is a need that everyone has, to be seen and listened to. Participant 2 Being believed and listened to when sharing experiences of pain could be viewed as a football player being trusted by other teammates. The teammates show that the player and their abilities are trusted by passing them the ball and encouraging them to dribble, meaning taking responsibility for the next move. Passing the ball Living with pain was challenging, and occasionally, participants felt their abilities were inadequate. They needed a team to help them regain trust in themselves and fight to improve their situation. In football, the MVP must have a team to pass the ball to because they cannot win the game alone. Being part of a team Participants often felt alone, struggling with pain. Navigating the healthcare system and the social insurance agency’s policies was difficult. Fighting different systems alone evoked feelings of being diminished, vulnerable and powerless. When they found regular contact with a healthcare professional willing to help and possibly involve other professionals, or when their networks helped them fight the system, they did not feel as lonely. Regular contact enhanced the participants’ sense of capability. Having support from others, they felt more confident and could accomplish more. My personal trainer said, ‘I have a plan. Let’s focus on this so you can continue fighting.’ Thanks to her, I am stronger and I feel like things are moving forward. Participant 1 I want to take responsibility for my pain and situation myself, but to be able to have someone to ask for help when I can’t bear to deal with it. Like a backup, a support that stands on the side but does not overtake the main responsibility. It is very easy to end up in a subordinate position when you have a chronic condition, that you’re in the hands of others. I want to be in charge but still have that support system around me as a backup for when I’m worse. When I do not have that, I have to push myself beyond my limits, and my health deteriorates. Participant 8 Reducing loneliness by accepting support from others could be analogous to being part of a football team. The individual is stronger with teammates and has a better chance of beating the other team (ie, living the desired life despite pain). Being part of a team also means being included and not alone. Having teammates when you have been tackled Participants felt hopeless when told by healthcare professionals there was nothing left to be done after undergoing several medical treatments or when test results failed to reveal the cause of their pain. The hope of feeling capable was restored when they were provided support (eg, tailored training programmes or self-help devices). When social networks provided support by facilitating daily tasks, tailored work schedules, ideas for pain management or contacts with trusted healthcare professionals, participants felt hope that their circumstances would improve, and they could live the desired life. I was advised to change my diet. It helped me so much. It somewhat improved my state because I could affect my situation a little bit myself. Participant 5 Regaining hope could mean having a teammate take the ball when the football player has been tackled and cannot dribble on their own (when the pain is unbearable, and they do not know how to move on). By having a teammate take the ball (pain management), the hope remains that the team can control the ball instead of losing it to the opposing team (the pain). There is hope that there is something else to try, even though all options for pain management are exhausted and someone is fighting with you when you feel like your abilities are not enough to fight the pain on your own. When I get this lumbago, I believe it will never pass, and I have to live my whole life like this. And then I talk to him [participant’s partner], and he reminds me it will pass, and I’ll be alright. It is good to be reminded. Otherwise, I’ll go into that tunnel, thinking everything will go bad. Participant 4 Worrying about being a benchwarmer Participants found it challenging to determine what they could share about their situation with their networks (particularly family and friends) without appearing as a burden. Not wanting to strain their networks or cause worry discouraged participants from including them in their care. I don’t know how much is okay to… share. What is oversharing? And how much can I share so it becomes enough, so they understand, but it does not become too much? It is a balancing act, and I find it difficult to know where the boundaries are. I dare not take that leap to tell them about my situation. Participant 6 Some healthcare professionals blamed participants for their situation, whereas others went beyond their regular duties to support participants by working during their free time (eg, lunch break). Such support made a huge difference, as participants needed their help. At the same time, the feeling of being a burden was enhanced because the healthcare professionals had to sacrifice their spare time to offer that support. Fear of being a burden due to pain could be seen as fear of losing the title of MVP and becoming a benchwarmer, that is, always on the bench without the opportunity to participate and contribute. You are sort of like a ball being kicked around within the system. And even if you try to tell them ’No, this is the field, this is the playing field’, it becomes a bit like whatever. […] But I have been so lucky that these people are helping me out of pure, goodhearted will, even though they do not have time for it. Because their bosses tell them, ‘You should only do this or that because these are our resources.’ And I mean, they even helped me during lunch and such things. I must be careful when asking them for help because they are so kind-hearted. Participant 9
Participants wanted to contribute to society like everyone else and manage independently by taking the lead in their care and daily life. They also desired to be who they were without pain dominating their lives. Contemplating the metaphor, this can be interpreted as they aspired to be the MVP in all aspects of their lives. Being believed and listened to were important aspects of being trusted to dribble the ball, which is essential when seeking to be the MVP. Being a valuable player and not just the injured one Participants sought to be recognised as the persons they were, with unique personalities and experiences, which could often be difficult to achieve. When perceived as a product of their pain, they felt excluded and viewed as someone who could not accomplish much. When the social networks provided support by accepting the pain as part of the participants but still recognising them for who they were and their capabilities, it facilitated their acceptance of themselves and the pain. They used to ask me,’ Why are you limping?’ I said,’ I played football last weekend,’ and I have never played football. So he [participant’s partner] told me, ‘Now you’re going to stop to tell them that you’ve played football.’ After that, I felt fine. There was no problem. I even have a colleague who says, ‘You’re limping. Maybe you should sit down.’ I don’t have to be perfect all the time. Participant 4 Pets could also contribute to this support, providing unconditional affection and companionship. Participants also wanted healthcare professionals to recognise them as the persons they were. They felt supported when healthcare professionals aimed at strengthening their resources by not only focusing on their limitations but also on their abilities. Participants felt an enhanced power by accessing self-help devices (eg, orthoses). It is about being an important part of society, to contribute… instead of being the one others should take care of. Self-help devices help to achieve that. Participant 10 The social networks provided support by requesting the participants’ help and advice. This support affirmed the participants’ view of themselves as unique, capable, meaningful and contributors rather than just someone with pain. Providing peer support to others with pain within a patient organisation exemplifies how participants contributed. I find good support in supporting others. You get a reflection of yourself that way. So, maybe that is my best support, to support others. […] It was perfect to have somebody who needed me. Participant 3 Being recognised as a person rather than someone struggling with pain could be interpreted as being considered a valuable player in football. Valuable football players are still useful to the team when injured, as everyone appreciates their efforts and knows their potential. They are not regarded as ‘that injured player.’ They are still valuable, and everyone is eager to see them return to the field. Being trusted to dribble To participants, a diagnosis was important to have their pain experiences taken seriously, understanding their pain and being believed, but it was often perceived as a challenging process. A diagnosis meant validating their condition and was also experienced as facilitating being believed, trusted and understood by the social networks. Being believed, trusted and understood by others was a support, and it also encouraged that expectations from others did not clash with the participants’ abilities. When participants were trusted with tasks they could perform, their view of themselves as capable persons was reinforced. I have to put on a mask in front of people and pretend to be happy. But my friend says, ’I don’t mind that you’re low and in pain. You don’t need to be happy and energised. We can still have coffee.’ It's like getting rid of a 20 kg backpack. He understands. Participant 7 Participants sometimes felt they received better support within complementary therapies compared with traditional care. They felt listened to and perceived as capable. This complimentary support, however, was not always affordable because of the participants’ often strained economy. My massage therapist sees me. I think that is a need that everyone has, to be seen and listened to. Participant 2 Being believed and listened to when sharing experiences of pain could be viewed as a football player being trusted by other teammates. The teammates show that the player and their abilities are trusted by passing them the ball and encouraging them to dribble, meaning taking responsibility for the next move.
Participants sought to be recognised as the persons they were, with unique personalities and experiences, which could often be difficult to achieve. When perceived as a product of their pain, they felt excluded and viewed as someone who could not accomplish much. When the social networks provided support by accepting the pain as part of the participants but still recognising them for who they were and their capabilities, it facilitated their acceptance of themselves and the pain. They used to ask me,’ Why are you limping?’ I said,’ I played football last weekend,’ and I have never played football. So he [participant’s partner] told me, ‘Now you’re going to stop to tell them that you’ve played football.’ After that, I felt fine. There was no problem. I even have a colleague who says, ‘You’re limping. Maybe you should sit down.’ I don’t have to be perfect all the time. Participant 4 Pets could also contribute to this support, providing unconditional affection and companionship. Participants also wanted healthcare professionals to recognise them as the persons they were. They felt supported when healthcare professionals aimed at strengthening their resources by not only focusing on their limitations but also on their abilities. Participants felt an enhanced power by accessing self-help devices (eg, orthoses). It is about being an important part of society, to contribute… instead of being the one others should take care of. Self-help devices help to achieve that. Participant 10 The social networks provided support by requesting the participants’ help and advice. This support affirmed the participants’ view of themselves as unique, capable, meaningful and contributors rather than just someone with pain. Providing peer support to others with pain within a patient organisation exemplifies how participants contributed. I find good support in supporting others. You get a reflection of yourself that way. So, maybe that is my best support, to support others. […] It was perfect to have somebody who needed me. Participant 3 Being recognised as a person rather than someone struggling with pain could be interpreted as being considered a valuable player in football. Valuable football players are still useful to the team when injured, as everyone appreciates their efforts and knows their potential. They are not regarded as ‘that injured player.’ They are still valuable, and everyone is eager to see them return to the field.
To participants, a diagnosis was important to have their pain experiences taken seriously, understanding their pain and being believed, but it was often perceived as a challenging process. A diagnosis meant validating their condition and was also experienced as facilitating being believed, trusted and understood by the social networks. Being believed, trusted and understood by others was a support, and it also encouraged that expectations from others did not clash with the participants’ abilities. When participants were trusted with tasks they could perform, their view of themselves as capable persons was reinforced. I have to put on a mask in front of people and pretend to be happy. But my friend says, ’I don’t mind that you’re low and in pain. You don’t need to be happy and energised. We can still have coffee.’ It's like getting rid of a 20 kg backpack. He understands. Participant 7 Participants sometimes felt they received better support within complementary therapies compared with traditional care. They felt listened to and perceived as capable. This complimentary support, however, was not always affordable because of the participants’ often strained economy. My massage therapist sees me. I think that is a need that everyone has, to be seen and listened to. Participant 2 Being believed and listened to when sharing experiences of pain could be viewed as a football player being trusted by other teammates. The teammates show that the player and their abilities are trusted by passing them the ball and encouraging them to dribble, meaning taking responsibility for the next move.
Living with pain was challenging, and occasionally, participants felt their abilities were inadequate. They needed a team to help them regain trust in themselves and fight to improve their situation. In football, the MVP must have a team to pass the ball to because they cannot win the game alone. Being part of a team Participants often felt alone, struggling with pain. Navigating the healthcare system and the social insurance agency’s policies was difficult. Fighting different systems alone evoked feelings of being diminished, vulnerable and powerless. When they found regular contact with a healthcare professional willing to help and possibly involve other professionals, or when their networks helped them fight the system, they did not feel as lonely. Regular contact enhanced the participants’ sense of capability. Having support from others, they felt more confident and could accomplish more. My personal trainer said, ‘I have a plan. Let’s focus on this so you can continue fighting.’ Thanks to her, I am stronger and I feel like things are moving forward. Participant 1 I want to take responsibility for my pain and situation myself, but to be able to have someone to ask for help when I can’t bear to deal with it. Like a backup, a support that stands on the side but does not overtake the main responsibility. It is very easy to end up in a subordinate position when you have a chronic condition, that you’re in the hands of others. I want to be in charge but still have that support system around me as a backup for when I’m worse. When I do not have that, I have to push myself beyond my limits, and my health deteriorates. Participant 8 Reducing loneliness by accepting support from others could be analogous to being part of a football team. The individual is stronger with teammates and has a better chance of beating the other team (ie, living the desired life despite pain). Being part of a team also means being included and not alone.
Participants often felt alone, struggling with pain. Navigating the healthcare system and the social insurance agency’s policies was difficult. Fighting different systems alone evoked feelings of being diminished, vulnerable and powerless. When they found regular contact with a healthcare professional willing to help and possibly involve other professionals, or when their networks helped them fight the system, they did not feel as lonely. Regular contact enhanced the participants’ sense of capability. Having support from others, they felt more confident and could accomplish more. My personal trainer said, ‘I have a plan. Let’s focus on this so you can continue fighting.’ Thanks to her, I am stronger and I feel like things are moving forward. Participant 1 I want to take responsibility for my pain and situation myself, but to be able to have someone to ask for help when I can’t bear to deal with it. Like a backup, a support that stands on the side but does not overtake the main responsibility. It is very easy to end up in a subordinate position when you have a chronic condition, that you’re in the hands of others. I want to be in charge but still have that support system around me as a backup for when I’m worse. When I do not have that, I have to push myself beyond my limits, and my health deteriorates. Participant 8 Reducing loneliness by accepting support from others could be analogous to being part of a football team. The individual is stronger with teammates and has a better chance of beating the other team (ie, living the desired life despite pain). Being part of a team also means being included and not alone.
Participants felt hopeless when told by healthcare professionals there was nothing left to be done after undergoing several medical treatments or when test results failed to reveal the cause of their pain. The hope of feeling capable was restored when they were provided support (eg, tailored training programmes or self-help devices). When social networks provided support by facilitating daily tasks, tailored work schedules, ideas for pain management or contacts with trusted healthcare professionals, participants felt hope that their circumstances would improve, and they could live the desired life. I was advised to change my diet. It helped me so much. It somewhat improved my state because I could affect my situation a little bit myself. Participant 5 Regaining hope could mean having a teammate take the ball when the football player has been tackled and cannot dribble on their own (when the pain is unbearable, and they do not know how to move on). By having a teammate take the ball (pain management), the hope remains that the team can control the ball instead of losing it to the opposing team (the pain). There is hope that there is something else to try, even though all options for pain management are exhausted and someone is fighting with you when you feel like your abilities are not enough to fight the pain on your own. When I get this lumbago, I believe it will never pass, and I have to live my whole life like this. And then I talk to him [participant’s partner], and he reminds me it will pass, and I’ll be alright. It is good to be reminded. Otherwise, I’ll go into that tunnel, thinking everything will go bad. Participant 4 Worrying about being a benchwarmer Participants found it challenging to determine what they could share about their situation with their networks (particularly family and friends) without appearing as a burden. Not wanting to strain their networks or cause worry discouraged participants from including them in their care. I don’t know how much is okay to… share. What is oversharing? And how much can I share so it becomes enough, so they understand, but it does not become too much? It is a balancing act, and I find it difficult to know where the boundaries are. I dare not take that leap to tell them about my situation. Participant 6 Some healthcare professionals blamed participants for their situation, whereas others went beyond their regular duties to support participants by working during their free time (eg, lunch break). Such support made a huge difference, as participants needed their help. At the same time, the feeling of being a burden was enhanced because the healthcare professionals had to sacrifice their spare time to offer that support. Fear of being a burden due to pain could be seen as fear of losing the title of MVP and becoming a benchwarmer, that is, always on the bench without the opportunity to participate and contribute. You are sort of like a ball being kicked around within the system. And even if you try to tell them ’No, this is the field, this is the playing field’, it becomes a bit like whatever. […] But I have been so lucky that these people are helping me out of pure, goodhearted will, even though they do not have time for it. Because their bosses tell them, ‘You should only do this or that because these are our resources.’ And I mean, they even helped me during lunch and such things. I must be careful when asking them for help because they are so kind-hearted. Participant 9
Participants found it challenging to determine what they could share about their situation with their networks (particularly family and friends) without appearing as a burden. Not wanting to strain their networks or cause worry discouraged participants from including them in their care. I don’t know how much is okay to… share. What is oversharing? And how much can I share so it becomes enough, so they understand, but it does not become too much? It is a balancing act, and I find it difficult to know where the boundaries are. I dare not take that leap to tell them about my situation. Participant 6 Some healthcare professionals blamed participants for their situation, whereas others went beyond their regular duties to support participants by working during their free time (eg, lunch break). Such support made a huge difference, as participants needed their help. At the same time, the feeling of being a burden was enhanced because the healthcare professionals had to sacrifice their spare time to offer that support. Fear of being a burden due to pain could be seen as fear of losing the title of MVP and becoming a benchwarmer, that is, always on the bench without the opportunity to participate and contribute. You are sort of like a ball being kicked around within the system. And even if you try to tell them ’No, this is the field, this is the playing field’, it becomes a bit like whatever. […] But I have been so lucky that these people are helping me out of pure, goodhearted will, even though they do not have time for it. Because their bosses tell them, ‘You should only do this or that because these are our resources.’ And I mean, they even helped me during lunch and such things. I must be careful when asking them for help because they are so kind-hearted. Participant 9
As the main theme suggests, the meaning of the participants’ lived experiences of support from the healthcare sector and social networks is to balance being a capable person and accepting help from others to continue being that capable person. Being capable means being recognised for who you are as a person and your qualities, to contribute, to be trusted and listened to. Accepting support means to not be alone, having someone fighting with you in order to enhance one’s capability, but also to worry about being a burden. In football terms, being capable corresponds to being the MVP and accepting support corresponds to passing the ball. Developing the interpreted football metaphor; the MVP and the team compete against pain (see ). Many football players dream of being the MVP, whose actions ultimately determine the match’s outcome. Our interpretation of the findings is that persons with chronic pain are no different, that is, they aspire to be important. However, not even the MVP can win a match without team support. They need the team to believe in their capability and support them to reach their full potential. In accordance with how the MVP takes the lead, we would argue that persons with chronic pain take the lead in their daily lives and care by dribbling the ball (pain management). However, there must be a balance, as no team will win a match through only having the MVP dribbling, that is, it is also necessary to pass the ball. Passing the ball does not mean losing the title as MVP; instead, it means boosting the chances of winning the match through the help of teammates. Living with chronic pain often leads to accepting a life with pain. Aspiring to win the match against pain is not about being pain-free but about living a meaningful life and being capable despite the pain. When social networks and healthcare professionals do not listen to persons with chronic pain, believe them, see their capabilities or claim they can no longer be helped, they go to the opposing team. The person with chronic pain might also end up on the opposing team by, for instance, engaging in negative thoughts and behaviours. The field must be just and equitable to ensure the teammates and the MVP are on the same team fighting against the same opponent. For example, healthcare professionals must have fair conditions to stay on the right team and support the MVP instead of considering them a benchwarmer. The composition of the MVP’s team (social networks and healthcare professionals) and the optimal balance between being the MVP and passing the ball (being capable and accepting support to be capable) varies from person to person and over time. Persons with chronic pain feel valued and supported when the healthcare sector and social networks strengthen their capability by encouraging them to be the MVP and pass the ball. The balancing act between the two is the meaning of lived experiences of support.
This study applied an interpretative approach in explaining the meaning of support from the healthcare sector and social networks of persons with chronic pain. The findings indicate that, regardless of who is providing the support, the meaning of support when living with chronic pain is to strengthen the individuals’ capability and, when the abilities do not seem enough, feel that someone is fighting together with the individual to regain their capability. Previous studies have mainly performed descriptive analyses, focusing on pain management rather than on the meaning of support. Holtrop et al found three primary purposes of important relationships in pain management: providing instrumental support, offering inspiration and motivation, and assisting in decision-making. Our results are similar but show that support strengthens the participants’ capability. In line with the present study Holtrop et al found that persons with chronic pain wanted to be recognised as persons rather than their condition and that their lives should be seen as no different from others. Meanwhile, they wanted their limitations due to pain to be accepted. Our study also shows that pets could provide this support, which aligns with Bair et al , who demonstrated that pets can be powerful motivators in pain management. The Bair et al participants relied on support from care managers. Similarly, our results show that support means having someone fight for individuals with chronic pain when their abilities are inadequate. Acknowledging the patient as an expert and capable person is fundamental to person-centred care. The present study clarifies that persons with chronic pain want to be active and recognised as capable, productive partners in care. Accepting support can strengthen their capability, which is also emphasised in person-centred care. The capabilities approach focuses on human development and social justice, recognising that people’s capabilities are shaped and formed by environmental and social circumstances. A systematic review investigating empirical evidence underpinning the conceptualisations of person-centred care for serious illness found that person-centred care empowers patients and their families by providing information and including them in decision-making actions on their daily lives and care. Considering these results, person-centred care may be valuable in enhancing capability. It would be worthwhile to explore whether this is the case among persons with chronic pain and their close others. Methodological considerations Lindseth and Norberg suggest that phenomenological hermeneutics seeks not to encapsulate the whole truth but to present meanings of a lived phenomenon vis-à-vis interpreting the narrative text. Findings are valid if they represent meaning derived from narrated experiences and illuminate something we want to understand. One-sided opinions can, however, emerge and conscious validation of the interpretation and analysis become important. The hermeneutic spiral, in which pending between understanding (naïve understanding) and explanation (structural analysis), constitutes a reliable approach to validate the findings. Discussions between the authors ensured the interpretations were plausible while not being the only possible options. Additionally, to ensure that the interpretations were reasonable one author (ML) read all the interviews before participating in the analysis. Qualitative samples should be large enough to understand the studied phenomenon but small enough not to hinder qualitative analysis. In phenomenology saturation is not used to determine the number of participants ; fewer participants are needed if the data are rich. The research group decided the collected data sufficed to answer the research question and was not too extensive to capture the meaning of the phenomenon. Most participants in the current study had post high school education, were female and were born in Sweden, which could affect the universality of the findings. Universality is described as an intersubjective understanding of the meaning of lived experiences, meaning that persons can understand the phenomenon better through the findings, even though their situation might not perfectly align with the findings. Because all participants had lived with pain for many years, they had broad experiences of support and provided rich narratives. Follow-up questions were used to ensure that the interviewer understood them correctly. Measures were taken to make participants comfortable (confirming they knew they could ask questions, take breaks, etc) and to encourage sharing their narratives. However, Bruce et al described the chronic ‘pain journey to acceptance’ and that different coping mechanisms are useful depending on where the person is in the journey, which might also translate to support. Some participants grew up with pain, which might have affected our findings. However, participants narrated their lived experiences of support as adults while comparing them to their experiences as children rather than merging them. The need to use Zoom due to the COVID-19 pandemic might have affected the content of the interviews. Still, video interviews are cost-effective and inclusive. Metaphors were employed in the interpretation process. Ricoeur contends that the metaphor enriches the meaning of a phenomenon through the creative tension of similarities and differences, creating a new understanding. The metaphors demonstrate how language can extend to its limits and affect how we understand the world.
Lindseth and Norberg suggest that phenomenological hermeneutics seeks not to encapsulate the whole truth but to present meanings of a lived phenomenon vis-à-vis interpreting the narrative text. Findings are valid if they represent meaning derived from narrated experiences and illuminate something we want to understand. One-sided opinions can, however, emerge and conscious validation of the interpretation and analysis become important. The hermeneutic spiral, in which pending between understanding (naïve understanding) and explanation (structural analysis), constitutes a reliable approach to validate the findings. Discussions between the authors ensured the interpretations were plausible while not being the only possible options. Additionally, to ensure that the interpretations were reasonable one author (ML) read all the interviews before participating in the analysis. Qualitative samples should be large enough to understand the studied phenomenon but small enough not to hinder qualitative analysis. In phenomenology saturation is not used to determine the number of participants ; fewer participants are needed if the data are rich. The research group decided the collected data sufficed to answer the research question and was not too extensive to capture the meaning of the phenomenon. Most participants in the current study had post high school education, were female and were born in Sweden, which could affect the universality of the findings. Universality is described as an intersubjective understanding of the meaning of lived experiences, meaning that persons can understand the phenomenon better through the findings, even though their situation might not perfectly align with the findings. Because all participants had lived with pain for many years, they had broad experiences of support and provided rich narratives. Follow-up questions were used to ensure that the interviewer understood them correctly. Measures were taken to make participants comfortable (confirming they knew they could ask questions, take breaks, etc) and to encourage sharing their narratives. However, Bruce et al described the chronic ‘pain journey to acceptance’ and that different coping mechanisms are useful depending on where the person is in the journey, which might also translate to support. Some participants grew up with pain, which might have affected our findings. However, participants narrated their lived experiences of support as adults while comparing them to their experiences as children rather than merging them. The need to use Zoom due to the COVID-19 pandemic might have affected the content of the interviews. Still, video interviews are cost-effective and inclusive. Metaphors were employed in the interpretation process. Ricoeur contends that the metaphor enriches the meaning of a phenomenon through the creative tension of similarities and differences, creating a new understanding. The metaphors demonstrate how language can extend to its limits and affect how we understand the world.
For participants, who lived with chronic pain, support means balancing between being capable (the MVP) and willing to accept support (passing the ball), which aligns with the concept of person-centred care. Our findings may be useful for policy-makers, managers and clinical professionals when planning and performing care for persons with chronic pain. Future research should focus on how the healthcare sector can create support to enable persons with chronic pain to be the MVP while being able to pass the ball to their social networks and the healthcare sector.
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L’examen génital et gynécologique qui tient compte des traumatismes subis | 07b694f3-c752-441d-b372-7955cb51cf7e | 8443284 | Gynaecology[mh] | Au Canada, plus de la moitié des personnes transgenres, 1 femme sur 3 et 1 homme sur 8, déclarent avoir fait l’objet de violence sexuelle . Les examens ravivent le souvenir des traumatismes et exacerbent les symptômes d’anxiété chez environ 50 % des victimes d’agressions sexuelles , . Étant donné cette forte prévalence, les soins qui tiennent compte des traumatismes subis devraient reposer sur la prémisse d’une telle possibilité et les professionnels de la santé devraient toujours interroger la patientèle à ce sujet lors de l’anamnèse. L’objectif est un soutien optimal et l’évitement de ce qui pourrait raviver ou exacerber les symptômes du traumatisme . Les professionnels de la santé devraient utiliser une formulation neutre dans leurs propos; se montrer sensibles aux enjeux culturels, historiques et sexospécifiques; et expliquer à la personne à quoi s’attendre avant et durant l’examen. La personne pourrait préférer choisir le moment de son examen (p. ex., lors de la consultation en cours ou d’une consultation future); elle pourrait vouloir être accompagnée pendant l’examen ou procéder elle-même aux prélèvements requis ou à l’insertion de l’instrument servant à l’examen. Les professionnels de la santé devraient quitter la salle d’examen lorsque la personne se dévêt ou se vêt. Cela valide sa dignité et lui laisse le temps de formuler des questions. Durant l’examen, il faut couvrir son corps et ne laisser à découvert que les zones à examiner, et ce, pendant le minimum de temps requis. Les résultats de l’examen ne devraient lui être transmis que lorsqu’elle est entièrement vêtue . Des études sur l’autoexamen pour le virus du papillome humain et les maladies transmises sexuellement ont montré des taux élevés de participation, la facilité de l’autoprélèvement des spécimens et l’efficacité des interventions . Les autoprélèvements cervicaux et vaginaux pour le dépistage de Chlamydia trachomatis et Neisseria gonorrhoeae ont généré une sensibilité de 94 %–99 % et une spécificité de 97 %–99 %; Les autoprélèvements vaginaux de spécimens pour le dépistage de Candida albicans , dubliniensis , parapsilosis et tropicalis ont montré une sensibilité de 90 %–94 % et une spécificité de 90 %–93 % . Les résultats des spécimens autoprélevés ont été semblables à ceux des spécimens recueillis par le médecin. Les tests urinaires sont sensibles à 98 % et spécifiques à 99 % pour C. trachomatis et N. gonorrhoeae et pourraient être utilisés plutôt que le prélèvement cervical chez les patientes qui ne souhaitent pas recueillir de spécimens vaginaux . On peut se procurer des trousses gratuitement dans les laboratoires locaux au Canada. |
Development and validation of a new multiplex for upgrading Y-STRs population databases from 12 to 23 markers and its forensic casework application | 718e6067-73a3-437f-a2bd-3232d1009d43 | 9758231 | Forensic Medicine[mh] | Y chromosome polymorphisms have become a valuable tool in forensic, anthropological, evolutionary, and genealogical studies , . Due to its paternal inheritance, they elude recombination to a great extent, being able to discriminate between male lineages, preserving a simple record of their history and being useful tools for understanding the geographical distribution of current populations . Y-STRs, with mutation rates in the order of 1 × 10 –3 per locus per generation, have strong power of discrimination among paternal unrelated lineages and play a key role in the field of forensic genetics , – . Although Y-STRs do not allow individualization as autosomal markers do, they may be useful in certain situations. For instance, for male donor analysis in male–female DNA mixtures, such as in cases of sexual assault, paternity testing with male offspring – and disaster victims or missing person investigations, involving males . Furthermore, Y-STR information has proven to be helpful in rapidly determining the number of male contributors in mixtures. Being hemizygous, Y-STR profiles have mostly one allele in their loci, so the presence of multiple alleles at single-copy loci is a clear clue of the number of male contributors , , . Y-STR analysis can also aid in reconstructing paternal relationship and even sometimes be used to infer the geographic region of paternal ancestry of a male DNA donor, useful in the case of missing persons , , . Over the past decades, thousands of Y-STRs have been identified and several commercially available Y-STR kits have been developed . Currently, most studies related to the analysis of Y-STRs aim to search for new markers to develop multiplex panels that offer greater discriminatory power, as it has been observed that a low number of Y-STRs may be insufficient for differentiating male lineages . This is the reason why more markers are needed than those included initially in the 9 Y-STRs of the Minimal Haplotype, the 12 Y-STRs included in the PPY (PowerPlex ® Y, Promega Corporation, Madison, WI, USA), or the 17 Y-STRs of the Yfiler® kit (Yfiler, Life Technologies, Foster, City, CA) . Indeed, the development of new kits with a larger set of markers has been shown to provide higher genetic resolution by increasing both haplotype diversity and discriminatory power compared to other panels in numerous populations – . Despite the foregoing, where more markers analysed usually means greater discriminatory power, to date numerous Y-STR population data available in the Y-STR Haplotype Reference Database ( http://www.yhrd.org ) are still based on the 12 Y-STRs of the PPY. In fact, currently the YHRD (Release R67) still presents 1398 population samples including 9 Y-STRs (Minimal Haplotype), 1177 with 12 Y-STRs (PPY) and 1089 containing 17 Y-STRs (Yfiler). However, only 402 samples report the 23 Y-STRs of the PPY23 (PowerPlex ® Y23 System, Promega Corporation, WI, USA) and 314 the 27 Y-STRs of the YfilerPlus . The ideal scenario would be for the same samples to be regenotyped as new markers appear. This would allow the databases to be updated continuously, which would be of great advantage in the forensic field. However, re-analysing all populations with the new Y-STR kits that are becoming commercially available is a labour-intensive, time-consuming and expensive task. Here, we present the development and validation of a novel 11 plus DYS385a/b Y-STR multiplex panel, an extension of the one previously developed by Nuñez et al. (2017) . The extended panel includes the eleven markers, DYS448, DYS456, DYS458, DYS635, Y-GATA H4, DYS576, DYS481, DYS549, DYS533, DYS570 and DYS643, which are contained in the PPY23 but absent in the PPY, as well as DYS385a/b for traceability purposes (Fig. ). All loci here included and their mutation rates have been previously studied , , . DYS385a/b has been selected as an overlapping marker since it is a multicopy Y-STR and reaches the highest genetic diversity among the markers present in PPY23 . The number of markers has been extended to 23 because, as previously mentioned, among the kits with a high number of markers, PPY23 is the one with the largest proportion of samples analysed. The aim of this new panel is offer a more cost-effective option to update populations that are currently typed with PPY. In addition, this would allow us to perform comparative analyses of the updated populations with a greater number of individuals with a genetic profile of 23 Y-STRs. The primer design was based on a miniSTR strategy in order to increase the performance success of this multiplex in degraded DNA. The developmental validation was performed following the guidelines of the SWGDAM . The new multiplex was applied in a population that was previously analyzed for the 12 Y-STRs of PPY with the aim to increase the current genetic data as well as to evaluate the capability of the multiplex.
Selection of markers and primer design The new multiplex panel includes the eleven markers DYS448, DYS456, DYS458, DYS635, Y-GATA H4, DYS576, DYS481, DYS549, DYS533, DYS570 and DYS643, which are contained in the PPY23 but absent in the PPY. Additionally, the loci DYS385a/b was included in the multiplex reaction as a traceability marker, as it is present in the aforementioned commercial kits. Since the 11 plus DYS385a/b Y-STR multiplex panel is an extension of the earlier one developed by Nuñez et al. (2017), for the eight markers that were already contained in that panel (DYS456, DYS576, DYS481, DYS549, DYS533, DYS570, DYS643 and DYS385a/b) the same primers described were used . For the remaining four Y-STR loci analyzed (DYS448, DYS458, DYS635 and Y-GATA H4), the primer design was performed using PerlPrimer v1.1.21 . Potential primer cross-reactions were examined via this software, and the Y-chromosome specifity was evaluated using BLASTN aligment tool ( https://blast.ncbi.nlm.nih.gov/Blast.cgi ). Forward primers were labeled with a fluorescent dye at the 5′ end (Supplementary Table ). Singleplex PCR reaction Each primer pair was initially tested in a singleplex PCR reaction using the 2800 M control DNA (Promega Corporation, Madison, WI). The singleplex reaction consisted of 12.5 μl of QIAGEN Multiplex PCR kit (Qiagen, Valencia, CA), 1 μl of primer (forward and reverse with an initial concentration of 10 μM), 1 ng of genomic DNA and 10.5 μl of Milli-Q water for a final reaction volume of 25 μl. PCR was performed in a GeneAmp 9800 (AB/LT/TFS) under the following cycle conditions: initial denaturation at 95ºC for 15 min was followed by 30 cycles of 94 °C for 30 s, 65 °C for 90 s, and 72 °C for 90 s, and a final extension at 72 °C for 10 min. Evaluation of amplification performance was conducted by electrophoresis on 1.50% agarose gels and visualized with GelRed (3.00% μL/ml) (Biotium Inc.,Hayward, USA) and UV light (UVItec Cambridge, USA or UK). PCR products were purified using 2 μl EXOSAP (Takara Bio Inc., Japan) to 5 μl of PCR product and sequencing was performed to confirm the specific amplification of each Y-STR. Sequencing was performed using the BigDye ® TerminatorTM v1.1 Cycle Sequencing Kit (AB/LT/TFS: Applied Biosystems™, Life Technologies, ThermoFisher Scientific, Waltham, MA, USA). Sequencing products were purified with BigDye ® XTerminatorTM Purification Kit (AB/LT/TFS) and capillary electrophoresis was done on a 3130 Genetic Analyzer (AB/LT/TFS). Sequencing results were analyzed with the Sequencing Analysis software v5.2 (AB/LT/TFS). Multiplex PCR reaction and capillary electrophoresis The 12 Y-STR loci under study were typed using multiplex reactions containing 5 μl of QIAGEN Multiplex PCR kit (Qiagen, Valencia, CA), 0.8 μl of primermix (primer concentrations in the mix are described in Supplementary Table ),1 ng of genomic DNA and Milli-Q water for a final reaction volumen of 10 μl. PCR was performed in a GeneAmp 9800 (AB/LT/TFS) using the same foregoing cycle conditions. PCR products separation and detection were performed by capillary electrophoresis with an ABI3130 Genetic Analyzer (AB/LT/TFS) using the GeneScan 500 LIZ (AB/LT/TFS) as an internal size standard and fragment lengths were assessed with GeneMapper v4.0 (AB/LT/TFS). The analytical threshold was set at 50 RFUs for peak height minimum. Allelic nomenclature follows the recommendations of the International Society for Forensic Genetics (ISFG) ( https://www.isfg.org ). The allelic ladder for this multiplex was constructed (Supplementary Fig. ). For each Y-STR locus, DNA samples showing different allelic variations were simultaneously amplified using the corresponding primer pair. Amplification product for each allele was mixed at appropriate ratios to produce the multiplex allelic ladder. Concordance study To compare allele designation concordance of the new assay, a set of 100 male DNA samples from the resident population living in the Basque Country previously analyzed with PPY23 in our laboratory, was examined with the novel multiplex panel. These two assays have in common the 12 Y-STR markers included in the new multiplex. Sensivity and stability studies In order to evaluate the minimum amount of DNA required to obtain a complete Y-STR profile, 2800 M DNA control (Promega, Madison, WI) was used for amplification in triplicates in ascending quantities: 25 pg/μl, 50 pg/μl, 100 pg/μl, 200 pg/μl, 400 pg/μl, 1 ng/μl, 1.6 ng/μl, and 10 ng/μl. Stability studies were conducted by including different concentrations of two common inhibitors, haematin (Sigma-Aldrich Corporation, St. Louis, MO, USA) and humic acid (Sigma-Aldrich Corporation, St. Louis, MO, USA) to the amplification reaction mix containing 1 ng of 2800 M DNA. This study was performed in duplicate using ascending concentrations of the PCR inhibitors: 100 μM, 150 μM, 300 μM, 500 μM, 750 μM, 1000 μM, 1500 μM, 3000 μM, and 5000 μM of haematin and 25 ng/μl, 50 ng/μl, 100 ng/μl, 200 ng/μl, 250 ng/μl, 300 ng/μl, 500 ng/μl, 1000 ng/μl, 2000 ng/μl, and 3000 ng/μl of humic acid. Artificially degraded DNA samples were prepared to evaluate stability of the Y-STR panel. 1 μg of a DNA in-house control sample was digested with 1 μL of DNAse Reaction Buffer, 0.5 μL of DNAse I and Milli-Q water for a final reaction volumen of 10 μl (DNase I, RNase-free, ThermoFisher Scientific, Waltham, MA, USA) for 15 min, 30 min, 1 h, 2 h, 4 h and 16 h at 37 °C. To inactivate DNAse I, 1 μL of 50 mM EDTA was added and then incubated at 65 °C for 10 min. These samples were amplified in duplicate. Species specifity To analyze the species specificity, DNA samples from bull, goat, sheep, pig, cock, rabbit, dog, cat and mouse were tested. All samples were provided by the Bank of DNA of the BIOMICs Group at the University of the Basque Country (UPV/EHU). Of each animal species, 1 ng of DNA was used for each amplification reaction. Repeatability and reproducibility The parameter of repeatability was evaluated by analysing whether the peaks of different replicas were always located in the position where the allele of the corresponding STRs should appear. Reproducibility was checked by performing the entire analysis by three different operators and by running amplification PCRs on three different thermal cyclers: GeneAmp PCR System 9700 Gold (AB/LT/TFS), GeneAmp 9800 PCR System (AB/LT/TFS) and C1000 thermal cycler (Bio-Rad, Hercules, CA, USA). Afterwards, the electropherograms resulting from these diverse analyses were compared to test the reproducibility of the results. Mixture detection The capacity of our panel to detect an admixed contribution was tested with a male:male and male:female mixtures. Male:male DNA mixtures were prepared using 2800 M DNA control and DNA in-house control sample with the following ratios of 19:1, 9:1, 3:1, 1:1, 1:3, 1:9 and 1:19. To perform the multiplex amplification reaction the total amount of mixed DNA input was mantained at 1 ng. Male:female DNA mixtures were established using a constant amount of 30 ng K562 DNA control (Promega) with a decreasing template of 2800 M DNA control (1 ng, 400 pg, 200 pg, 100 pg, 50 pg and 25 pg). Each mixture analysis was repeated for two times. Sizing accuracy and stutter calculation Sizing accuracy was tested by evaluating the standard deviation of allele size observed after 20 injections of the allelic ladder (Supplementary Fig. ) on a 3130 Genetic Analyzer (AB/LT/TFS). Peaks that differed from the true allele by one repetition (± 0.5 bases) were considered stutter peaks. The percentage of observed stutter at each locus was examined by dividing the stutter peak height (in RFUs) by the corresponding allele peak height. To evaluate the effect of stutter peaks, a subset of 100 samples were randomly selected from the total collection analyzed in this study. Analysis of casework-type samples To test the effectiveness of this panel with forensic-type samples, two samples from skeletal remains (bones) with degraded DNA and three casework samples from intercomparison exercises organized by the Spanish and Portuguese-Speaking Group (GHEP) of the International Society for Forensic Genetics (ISFG), were analyzed. Samples from skeletal remains (coded in this study as BADN1304 and BADN2049) belong to Spanish Civil War (1936–1939). These samples were selected as examples of forensic samples routinely analysed in our laboratory. The samples from GHEP were items M4 and M8 from exercise 2018 (coded in this study as M4-GHEP18 and M8-GHEP18) and item M4 from exercise 2020 (coded in this study as M4-GHEP20). Population study and forensic parameters A sample of 84 unrelated males from Ibiza (Balearic Islands, Spain), previously genotyped with the 12 Y-STR PPY was combined with the new Y-STRs in order to assess the forensic parameters of the resulting 23 Y-STR haplotypes. The study was approved by the General Directorate of Research + Development + Innovation of the Government of the Balearic Islands, Spain (Ref. AAEE procedure 12099/2003). All donors gave their informed consent before inclusion in the study, following the principles and ethical guidelines of the Declaration of Helsinki for the protection of human subjects. The individuals from this study also gave their informed consent for the samples to be used in the population-based follow-up studies. Samples were collected in 2003. According to current Spanish legislation, samples collected before 2007 can continue to be used for research purposes, for which they must be anonymized. Blood samples used in this work were collected before 2007 and anonymized in accordance with the Law 14/2007 on Biomedical Research. DNA was extracted by using QIAamp spin columns (Qiagen, Hilden, Germany) following the manufacturer’s recommendations. Allele frequencies, single-marker genetic diversity (GD), haplotype diversity (HD), as well as different, unique and population specific haplotypes, were assessed using the software Arlequin v3.5.2.2 . For these calculations, the DYS385a/b alleles were treated as haplotypes. The global discrimination capacity (DC) was calculated by dividing the number of different haplotypes by the total number of individuals in the population sample. Ethic declarations The study was approved by the General Directorate of Research + Development + Innovation of the Government of the Balearic Islands, Spain (Ref. AAEE procedure 12099/2003). All donors gave their informed consent before inclusion in the study, following the principles and ethical guidelines of the Declaration of Helsinki for the protection of human subjects. The individuals from this study also gave their informed consent for the samples to be used in the population-based follow-up studies. Samples were collected in 2003. According to current Spanish legislation, samples collected before 2007 can continue to be used for research purposes, for which they must be anonymized. Blood samples used in this work were collected before 2007 and anonymized in accordance with the Law 14/2007 on Biomedical Research.
The new multiplex panel includes the eleven markers DYS448, DYS456, DYS458, DYS635, Y-GATA H4, DYS576, DYS481, DYS549, DYS533, DYS570 and DYS643, which are contained in the PPY23 but absent in the PPY. Additionally, the loci DYS385a/b was included in the multiplex reaction as a traceability marker, as it is present in the aforementioned commercial kits. Since the 11 plus DYS385a/b Y-STR multiplex panel is an extension of the earlier one developed by Nuñez et al. (2017), for the eight markers that were already contained in that panel (DYS456, DYS576, DYS481, DYS549, DYS533, DYS570, DYS643 and DYS385a/b) the same primers described were used . For the remaining four Y-STR loci analyzed (DYS448, DYS458, DYS635 and Y-GATA H4), the primer design was performed using PerlPrimer v1.1.21 . Potential primer cross-reactions were examined via this software, and the Y-chromosome specifity was evaluated using BLASTN aligment tool ( https://blast.ncbi.nlm.nih.gov/Blast.cgi ). Forward primers were labeled with a fluorescent dye at the 5′ end (Supplementary Table ).
Each primer pair was initially tested in a singleplex PCR reaction using the 2800 M control DNA (Promega Corporation, Madison, WI). The singleplex reaction consisted of 12.5 μl of QIAGEN Multiplex PCR kit (Qiagen, Valencia, CA), 1 μl of primer (forward and reverse with an initial concentration of 10 μM), 1 ng of genomic DNA and 10.5 μl of Milli-Q water for a final reaction volume of 25 μl. PCR was performed in a GeneAmp 9800 (AB/LT/TFS) under the following cycle conditions: initial denaturation at 95ºC for 15 min was followed by 30 cycles of 94 °C for 30 s, 65 °C for 90 s, and 72 °C for 90 s, and a final extension at 72 °C for 10 min. Evaluation of amplification performance was conducted by electrophoresis on 1.50% agarose gels and visualized with GelRed (3.00% μL/ml) (Biotium Inc.,Hayward, USA) and UV light (UVItec Cambridge, USA or UK). PCR products were purified using 2 μl EXOSAP (Takara Bio Inc., Japan) to 5 μl of PCR product and sequencing was performed to confirm the specific amplification of each Y-STR. Sequencing was performed using the BigDye ® TerminatorTM v1.1 Cycle Sequencing Kit (AB/LT/TFS: Applied Biosystems™, Life Technologies, ThermoFisher Scientific, Waltham, MA, USA). Sequencing products were purified with BigDye ® XTerminatorTM Purification Kit (AB/LT/TFS) and capillary electrophoresis was done on a 3130 Genetic Analyzer (AB/LT/TFS). Sequencing results were analyzed with the Sequencing Analysis software v5.2 (AB/LT/TFS).
The 12 Y-STR loci under study were typed using multiplex reactions containing 5 μl of QIAGEN Multiplex PCR kit (Qiagen, Valencia, CA), 0.8 μl of primermix (primer concentrations in the mix are described in Supplementary Table ),1 ng of genomic DNA and Milli-Q water for a final reaction volumen of 10 μl. PCR was performed in a GeneAmp 9800 (AB/LT/TFS) using the same foregoing cycle conditions. PCR products separation and detection were performed by capillary electrophoresis with an ABI3130 Genetic Analyzer (AB/LT/TFS) using the GeneScan 500 LIZ (AB/LT/TFS) as an internal size standard and fragment lengths were assessed with GeneMapper v4.0 (AB/LT/TFS). The analytical threshold was set at 50 RFUs for peak height minimum. Allelic nomenclature follows the recommendations of the International Society for Forensic Genetics (ISFG) ( https://www.isfg.org ). The allelic ladder for this multiplex was constructed (Supplementary Fig. ). For each Y-STR locus, DNA samples showing different allelic variations were simultaneously amplified using the corresponding primer pair. Amplification product for each allele was mixed at appropriate ratios to produce the multiplex allelic ladder.
To compare allele designation concordance of the new assay, a set of 100 male DNA samples from the resident population living in the Basque Country previously analyzed with PPY23 in our laboratory, was examined with the novel multiplex panel. These two assays have in common the 12 Y-STR markers included in the new multiplex.
In order to evaluate the minimum amount of DNA required to obtain a complete Y-STR profile, 2800 M DNA control (Promega, Madison, WI) was used for amplification in triplicates in ascending quantities: 25 pg/μl, 50 pg/μl, 100 pg/μl, 200 pg/μl, 400 pg/μl, 1 ng/μl, 1.6 ng/μl, and 10 ng/μl. Stability studies were conducted by including different concentrations of two common inhibitors, haematin (Sigma-Aldrich Corporation, St. Louis, MO, USA) and humic acid (Sigma-Aldrich Corporation, St. Louis, MO, USA) to the amplification reaction mix containing 1 ng of 2800 M DNA. This study was performed in duplicate using ascending concentrations of the PCR inhibitors: 100 μM, 150 μM, 300 μM, 500 μM, 750 μM, 1000 μM, 1500 μM, 3000 μM, and 5000 μM of haematin and 25 ng/μl, 50 ng/μl, 100 ng/μl, 200 ng/μl, 250 ng/μl, 300 ng/μl, 500 ng/μl, 1000 ng/μl, 2000 ng/μl, and 3000 ng/μl of humic acid. Artificially degraded DNA samples were prepared to evaluate stability of the Y-STR panel. 1 μg of a DNA in-house control sample was digested with 1 μL of DNAse Reaction Buffer, 0.5 μL of DNAse I and Milli-Q water for a final reaction volumen of 10 μl (DNase I, RNase-free, ThermoFisher Scientific, Waltham, MA, USA) for 15 min, 30 min, 1 h, 2 h, 4 h and 16 h at 37 °C. To inactivate DNAse I, 1 μL of 50 mM EDTA was added and then incubated at 65 °C for 10 min. These samples were amplified in duplicate.
To analyze the species specificity, DNA samples from bull, goat, sheep, pig, cock, rabbit, dog, cat and mouse were tested. All samples were provided by the Bank of DNA of the BIOMICs Group at the University of the Basque Country (UPV/EHU). Of each animal species, 1 ng of DNA was used for each amplification reaction.
The parameter of repeatability was evaluated by analysing whether the peaks of different replicas were always located in the position where the allele of the corresponding STRs should appear. Reproducibility was checked by performing the entire analysis by three different operators and by running amplification PCRs on three different thermal cyclers: GeneAmp PCR System 9700 Gold (AB/LT/TFS), GeneAmp 9800 PCR System (AB/LT/TFS) and C1000 thermal cycler (Bio-Rad, Hercules, CA, USA). Afterwards, the electropherograms resulting from these diverse analyses were compared to test the reproducibility of the results.
The capacity of our panel to detect an admixed contribution was tested with a male:male and male:female mixtures. Male:male DNA mixtures were prepared using 2800 M DNA control and DNA in-house control sample with the following ratios of 19:1, 9:1, 3:1, 1:1, 1:3, 1:9 and 1:19. To perform the multiplex amplification reaction the total amount of mixed DNA input was mantained at 1 ng. Male:female DNA mixtures were established using a constant amount of 30 ng K562 DNA control (Promega) with a decreasing template of 2800 M DNA control (1 ng, 400 pg, 200 pg, 100 pg, 50 pg and 25 pg). Each mixture analysis was repeated for two times.
Sizing accuracy was tested by evaluating the standard deviation of allele size observed after 20 injections of the allelic ladder (Supplementary Fig. ) on a 3130 Genetic Analyzer (AB/LT/TFS). Peaks that differed from the true allele by one repetition (± 0.5 bases) were considered stutter peaks. The percentage of observed stutter at each locus was examined by dividing the stutter peak height (in RFUs) by the corresponding allele peak height. To evaluate the effect of stutter peaks, a subset of 100 samples were randomly selected from the total collection analyzed in this study.
To test the effectiveness of this panel with forensic-type samples, two samples from skeletal remains (bones) with degraded DNA and three casework samples from intercomparison exercises organized by the Spanish and Portuguese-Speaking Group (GHEP) of the International Society for Forensic Genetics (ISFG), were analyzed. Samples from skeletal remains (coded in this study as BADN1304 and BADN2049) belong to Spanish Civil War (1936–1939). These samples were selected as examples of forensic samples routinely analysed in our laboratory. The samples from GHEP were items M4 and M8 from exercise 2018 (coded in this study as M4-GHEP18 and M8-GHEP18) and item M4 from exercise 2020 (coded in this study as M4-GHEP20).
A sample of 84 unrelated males from Ibiza (Balearic Islands, Spain), previously genotyped with the 12 Y-STR PPY was combined with the new Y-STRs in order to assess the forensic parameters of the resulting 23 Y-STR haplotypes. The study was approved by the General Directorate of Research + Development + Innovation of the Government of the Balearic Islands, Spain (Ref. AAEE procedure 12099/2003). All donors gave their informed consent before inclusion in the study, following the principles and ethical guidelines of the Declaration of Helsinki for the protection of human subjects. The individuals from this study also gave their informed consent for the samples to be used in the population-based follow-up studies. Samples were collected in 2003. According to current Spanish legislation, samples collected before 2007 can continue to be used for research purposes, for which they must be anonymized. Blood samples used in this work were collected before 2007 and anonymized in accordance with the Law 14/2007 on Biomedical Research. DNA was extracted by using QIAamp spin columns (Qiagen, Hilden, Germany) following the manufacturer’s recommendations. Allele frequencies, single-marker genetic diversity (GD), haplotype diversity (HD), as well as different, unique and population specific haplotypes, were assessed using the software Arlequin v3.5.2.2 . For these calculations, the DYS385a/b alleles were treated as haplotypes. The global discrimination capacity (DC) was calculated by dividing the number of different haplotypes by the total number of individuals in the population sample.
The study was approved by the General Directorate of Research + Development + Innovation of the Government of the Balearic Islands, Spain (Ref. AAEE procedure 12099/2003). All donors gave their informed consent before inclusion in the study, following the principles and ethical guidelines of the Declaration of Helsinki for the protection of human subjects. The individuals from this study also gave their informed consent for the samples to be used in the population-based follow-up studies. Samples were collected in 2003. According to current Spanish legislation, samples collected before 2007 can continue to be used for research purposes, for which they must be anonymized. Blood samples used in this work were collected before 2007 and anonymized in accordance with the Law 14/2007 on Biomedical Research.
Primer set and PCR optimization The 11 plus DYS385a/b Y-STR multiplex panel allows the analysis of the markers DYS448, DYS456, DYS458, DYS635, Y-GATA H4, DYS576, DYS481, DYS549, DYS533, DYS570, DYS643 and DYS385a/b. Primer design was carried out following a miniSTR approach by locating primers as close to the Y-STR repetition units as possible. The final 12 primer pairs generate PCR fragments 105 to 316 bp long (Fig. and Supplementary Table ). This design has the advantage of reducing the amplicon size for markers DYS533, DYS549, DYS481, DYS643 and Y-GATA H4 with regard to the PPY23 system (Supplementary Fig. ). Concordance study A total of 100 samples from the resident population living in the Basque Country were compared with haplotypes obtained in previous analyses performed in our laboratory employing the PPY23 kit. The results showed that the profiles of the same 12 Y-STR markers were completely identical. Sensivity and stability studies Sensitivity was evaluated through the analysis of positive control 2800 M at different concentrations. The results indicated that the minimum quantity of DNA necessary to obtain complete genetic profiles, with peak heights above 50 RFUs, in triplicate reactions was 100 pg/μl. Lower amounts experienced allele dropouts of the larger amplicons (Supplementary Table and Supplementary Figs. and ). However, given the results for 50 pg/μl and 25 pg/μl, by increasing certain conditions within the genotyping step, such as the amount of DNA or the injection time, complete profiles might be obtained. Taken together, these results suggest that 11 plus DYS385a/b Y-STR multiplex panel under study could be applied to forensic remains with high limitation in their DNA content. Stability studies consisted of PCR reactions that included inhibitors such as haematin or humic acid. Complete genetic profiles were obtained with concentrations of ≤ 100 μM of haematin and ≤ 50 ng/μl of humic acid for all replicas (Supplementary Table and Supplementary Figs. and ). Additionally, to determine the efficiency of amplification with degraded samples, artificially degraded DNA was prepared by digestion with DNAse I at different times. Complete genetic profiles were obtained with incubation times < 1 h for all replicas. After 1 h incubation, due to the shortage of target DNA, the results start to randomise. For instance, the 1 h incubation time resulted in 83.33% and 50.00% partial profiles, for each replica respectively. Another example occurs after 4 h incubation, where 50.00% and 16.67% of partial profiles were obtained for each replicate respectively (Supplementary Figs. and ). All stability test results are indicative of the robustness of the novel panel at moderate DNA degradation levels. Species specifity Evidence collected at the crime scene may be exposed to non-human biological sources, such as those of animal origin, and cross-contamination with DNA from other species may occur. In this regard, it is important to assess the species specificity of the assay, ensuring that primers designed to amplify the Y-STRs in this 11 plus DYS385a/b Y-STR multiplex panel are human-specific and do not amplify animal DNA. Here, we have analysed some common livestock and domestic animal species, assuming that these might be the most frequently found at a crime scene. The results showed the absence of DNA amplification results for all non-human samples tested (Supplementary Fig. ). Therefore, our panel produces no cross-reaction in the tested animal samples, which shows its specificity in terms of species that are common in the human habitat. Repeatability and reproducibility Analysis of different replicas proved the repeatability of the panel. No profile experienced a change of allele in any of the replicates, and the position in which the peaks corresponding to each marker appeared did not suffer displacements in the different electropherograms. Since samples are analysed in different capillaries and different runs, the background noise may differ between replicas, resulting in electropherograms with slightly different RFUs. Moreover, in order to check the reproducibility of the technique when using different thermocyclers, the procedure was performed in a GeneAmp PCR System 9700 (AB/LT/TFS), in a GeneAmp PCR System 9800 (AB/LT/TFS) and in a C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA). No differences were observed in the results, demonstrating the reproducibility of the technique when different thermocyclers were used. Additionally, no further differences were detected when the technique was performed by three different operators. In all cases, identical electropherograms were obtained, resulting in complete profiles of 12 Y-STRs. Mixture detection Mixtures of multiple male samples or female and male are frequently encountered in forensic crime scenes. Here, the ability of the panel to reveal the presence of mixed DNA samples was tested by two types of mixtures containing male:male and male:female. For male:male DNA mixtures, as the ratios increased, the proportion of minor alleles that could be identified decreased. The minor component at 3:1 and 1:3 ratios was completely identified. At 9:1 the minor component resulted also on complete profiles. However, the minor component at 1:9 resulted in a 95.83% partial profile on average. At ratios of 19:1 and 1:19, the minor component resulted in 29.17% and 54.17% partial profiles on average, respectively (Fig. a, Supplementary Table and Supplementary Fig. a). For male:female DNA mixtures, 11 plus DYS385a/b Y-STR multiplex panel was tested in the presence of large amounts of female DNA. The results showed that complete profiles were obtained when the male DNA amount was varied from 1 ng to 400 pg. When the male template DNA amount was reduced to 200 pg, 100 pg, 50 pg and 25 pg the average loci detection rates declined due to allele dropout (Fig. b, Supplementary Table and Supplementary Fig. b). A higher percentage of alleles recovered in 100 pg compared to 200 pg, as well as in 25 pg compared to 50 pg, is due to the fact that primer annealing during PCR is a random process. In cases where there is a small amount of DNA, this randomness can lead to such results. Furthermore, obtaining complete profiles with a higher amount of DNA than in the sensitivity test is explained by the fact that sensitivity might be affected in mixtures. When the target sequence represents only a small fraction of the total DNA, as in this case where 30 ng of female DNA control is present, the annealing frequency between the primers and the target sites in the first cycles can be reduced, leading to a decrease in sensitivity . Identifying the number of contributors in the mixtures and defining the minor and major contributor genotyping, as well as obtaining the Y-STR profile of male contributor in sexual assault cases are some of the challenges of forensic investigation. The 12Y-STR multiplex panel has proven to overcome these difficulties successfully. Sizing accuracy and stutter calculation To test the sizing accuracy of amplified alleles, size differences between the alleles from 20 injections of the allelic ladder on a 3130 Genetic Analyzer (AB/LT/TFS) were compared. The standard deviation in the size values was calculated for each allele in each locus (Supplementary Table ). It ranged from 0.0355 (DYS481) to 0.1856 (DYS385ab), suggesting high accuracy of the detection system and demonstrating that the size precision level is sufficient for sizing and discrimination of microvariants and off-ladder peaks. Stutter peaks are common artifacts observed during the PCR amplification process. Since these artifacts can complicate interpretation, it is important to evaluate the expected percentage of stuttering at each locus to avoid incorrect allele sizing . Stutter parameters are shown in Supplementary Table . DYS643 was the locus with the lowest stutter ratio percentage (4.72%) while the higher average percentage was showed by DYS481 (21.32%). Except for the loci of DYS456 (17.26%) and DYS481 (21.32%), the mean stutter ratios of other loci were lower than 15%. Analysis of casework-type samples The effectiveness of this panel for analyzing forensic-type samples was tested over two skeletal remains with degraded DNA, as well as over three items from intercomparison exercises organized by the GHEP-ISFG. The analysis of skeletal samples from Spanish Civil War (1936–1939), BADN1304 and BADN2049 resulted on complete profiles (12 Y-STRs). These results were compared with the ones obtained with the PPY23, and in both cases the same Y-STR profiles were obtained. The analysis of samples M4-GHEP18 and M8-GHEP18 resulted in complete profiles. These results were checked with the consensus results obtained in the intercomparison exercises of GHEP-ISFG, confirming the Y-STR profile of these samples and reaffirming the reliability of this panel. M4-GHEP20 is a mixture of blood and semen from two males being possible to observe both complete profiles in its analysis. Overall, these results show that the electropherograms obtained with this panel can be informative enough for forensic-type samples, even if they contained degraded DNA. Population study and forensic parameters The 11 plus DYS385a/b Y-STR multiplex panel was applied to expand the current data available for the population of Ibiza, previously analyzed with the PPY. Forensic parameters were compared for the 12 loci previously analyzed (PPY) and the resulting 17 Y-STRs (contained in Y-Filer) and 23 Y-STRs (contained in PPY23), both using PPY data extended with the novel 11 plus DYS385a/b Y-STR multiplex panel. Allelic frequencies and haplotypes Allele frequencies and gene diversity (GD) of the 23 Y-STRs (12 Y-STRs previously analyzed and the new 11 Y-STRs here genotyped) for Ibiza are summarized in the Supplementary Table . Supplementary Table provides the 23-loci haplotypes of the 84 individuals from this population. Forensic and population genetic parameters At the single-locus level, DYS456, DYS458 and DYS576 loci were the most discriminative of the eleven incorporated Y-STRs included in the multiplex, generating the highest GD values (0.8181 for DYS576, 0.7533 for DYS458 and 0.7372 for DYS456) (Supplementary Table ). The lowest GD value in this case was 0.4079 for DYS533. These results are maintained if DYS385a/b loci is included in the computation. At the haplotype level, the forensic and population genetics parameters of the Ibiza population based on 12-loci contained in PPY (12 loci previously analyzed with PPY), 17-loci contained in Y-Filer (12 loci previously analyzed with PPY and new 5 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) and 23-loci contained in PPY23 (12 loci previously analyzed with PPY and new 11 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) haplotypes are compiled in Table . As expected the values for number of haplotypes, unique haplotypes, haplotype diversity and discrimination capacity augmented as the number of loci increased. When 23-loci haplotypes were considered, Ibiza exhibit high levels of haplotype diversity, with value of 0.9977, and the discrimination value was 0.9048.
The 11 plus DYS385a/b Y-STR multiplex panel allows the analysis of the markers DYS448, DYS456, DYS458, DYS635, Y-GATA H4, DYS576, DYS481, DYS549, DYS533, DYS570, DYS643 and DYS385a/b. Primer design was carried out following a miniSTR approach by locating primers as close to the Y-STR repetition units as possible. The final 12 primer pairs generate PCR fragments 105 to 316 bp long (Fig. and Supplementary Table ). This design has the advantage of reducing the amplicon size for markers DYS533, DYS549, DYS481, DYS643 and Y-GATA H4 with regard to the PPY23 system (Supplementary Fig. ).
A total of 100 samples from the resident population living in the Basque Country were compared with haplotypes obtained in previous analyses performed in our laboratory employing the PPY23 kit. The results showed that the profiles of the same 12 Y-STR markers were completely identical.
Sensitivity was evaluated through the analysis of positive control 2800 M at different concentrations. The results indicated that the minimum quantity of DNA necessary to obtain complete genetic profiles, with peak heights above 50 RFUs, in triplicate reactions was 100 pg/μl. Lower amounts experienced allele dropouts of the larger amplicons (Supplementary Table and Supplementary Figs. and ). However, given the results for 50 pg/μl and 25 pg/μl, by increasing certain conditions within the genotyping step, such as the amount of DNA or the injection time, complete profiles might be obtained. Taken together, these results suggest that 11 plus DYS385a/b Y-STR multiplex panel under study could be applied to forensic remains with high limitation in their DNA content. Stability studies consisted of PCR reactions that included inhibitors such as haematin or humic acid. Complete genetic profiles were obtained with concentrations of ≤ 100 μM of haematin and ≤ 50 ng/μl of humic acid for all replicas (Supplementary Table and Supplementary Figs. and ). Additionally, to determine the efficiency of amplification with degraded samples, artificially degraded DNA was prepared by digestion with DNAse I at different times. Complete genetic profiles were obtained with incubation times < 1 h for all replicas. After 1 h incubation, due to the shortage of target DNA, the results start to randomise. For instance, the 1 h incubation time resulted in 83.33% and 50.00% partial profiles, for each replica respectively. Another example occurs after 4 h incubation, where 50.00% and 16.67% of partial profiles were obtained for each replicate respectively (Supplementary Figs. and ). All stability test results are indicative of the robustness of the novel panel at moderate DNA degradation levels.
Evidence collected at the crime scene may be exposed to non-human biological sources, such as those of animal origin, and cross-contamination with DNA from other species may occur. In this regard, it is important to assess the species specificity of the assay, ensuring that primers designed to amplify the Y-STRs in this 11 plus DYS385a/b Y-STR multiplex panel are human-specific and do not amplify animal DNA. Here, we have analysed some common livestock and domestic animal species, assuming that these might be the most frequently found at a crime scene. The results showed the absence of DNA amplification results for all non-human samples tested (Supplementary Fig. ). Therefore, our panel produces no cross-reaction in the tested animal samples, which shows its specificity in terms of species that are common in the human habitat.
Analysis of different replicas proved the repeatability of the panel. No profile experienced a change of allele in any of the replicates, and the position in which the peaks corresponding to each marker appeared did not suffer displacements in the different electropherograms. Since samples are analysed in different capillaries and different runs, the background noise may differ between replicas, resulting in electropherograms with slightly different RFUs. Moreover, in order to check the reproducibility of the technique when using different thermocyclers, the procedure was performed in a GeneAmp PCR System 9700 (AB/LT/TFS), in a GeneAmp PCR System 9800 (AB/LT/TFS) and in a C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA). No differences were observed in the results, demonstrating the reproducibility of the technique when different thermocyclers were used. Additionally, no further differences were detected when the technique was performed by three different operators. In all cases, identical electropherograms were obtained, resulting in complete profiles of 12 Y-STRs.
Mixtures of multiple male samples or female and male are frequently encountered in forensic crime scenes. Here, the ability of the panel to reveal the presence of mixed DNA samples was tested by two types of mixtures containing male:male and male:female. For male:male DNA mixtures, as the ratios increased, the proportion of minor alleles that could be identified decreased. The minor component at 3:1 and 1:3 ratios was completely identified. At 9:1 the minor component resulted also on complete profiles. However, the minor component at 1:9 resulted in a 95.83% partial profile on average. At ratios of 19:1 and 1:19, the minor component resulted in 29.17% and 54.17% partial profiles on average, respectively (Fig. a, Supplementary Table and Supplementary Fig. a). For male:female DNA mixtures, 11 plus DYS385a/b Y-STR multiplex panel was tested in the presence of large amounts of female DNA. The results showed that complete profiles were obtained when the male DNA amount was varied from 1 ng to 400 pg. When the male template DNA amount was reduced to 200 pg, 100 pg, 50 pg and 25 pg the average loci detection rates declined due to allele dropout (Fig. b, Supplementary Table and Supplementary Fig. b). A higher percentage of alleles recovered in 100 pg compared to 200 pg, as well as in 25 pg compared to 50 pg, is due to the fact that primer annealing during PCR is a random process. In cases where there is a small amount of DNA, this randomness can lead to such results. Furthermore, obtaining complete profiles with a higher amount of DNA than in the sensitivity test is explained by the fact that sensitivity might be affected in mixtures. When the target sequence represents only a small fraction of the total DNA, as in this case where 30 ng of female DNA control is present, the annealing frequency between the primers and the target sites in the first cycles can be reduced, leading to a decrease in sensitivity . Identifying the number of contributors in the mixtures and defining the minor and major contributor genotyping, as well as obtaining the Y-STR profile of male contributor in sexual assault cases are some of the challenges of forensic investigation. The 12Y-STR multiplex panel has proven to overcome these difficulties successfully.
To test the sizing accuracy of amplified alleles, size differences between the alleles from 20 injections of the allelic ladder on a 3130 Genetic Analyzer (AB/LT/TFS) were compared. The standard deviation in the size values was calculated for each allele in each locus (Supplementary Table ). It ranged from 0.0355 (DYS481) to 0.1856 (DYS385ab), suggesting high accuracy of the detection system and demonstrating that the size precision level is sufficient for sizing and discrimination of microvariants and off-ladder peaks. Stutter peaks are common artifacts observed during the PCR amplification process. Since these artifacts can complicate interpretation, it is important to evaluate the expected percentage of stuttering at each locus to avoid incorrect allele sizing . Stutter parameters are shown in Supplementary Table . DYS643 was the locus with the lowest stutter ratio percentage (4.72%) while the higher average percentage was showed by DYS481 (21.32%). Except for the loci of DYS456 (17.26%) and DYS481 (21.32%), the mean stutter ratios of other loci were lower than 15%.
The effectiveness of this panel for analyzing forensic-type samples was tested over two skeletal remains with degraded DNA, as well as over three items from intercomparison exercises organized by the GHEP-ISFG. The analysis of skeletal samples from Spanish Civil War (1936–1939), BADN1304 and BADN2049 resulted on complete profiles (12 Y-STRs). These results were compared with the ones obtained with the PPY23, and in both cases the same Y-STR profiles were obtained. The analysis of samples M4-GHEP18 and M8-GHEP18 resulted in complete profiles. These results were checked with the consensus results obtained in the intercomparison exercises of GHEP-ISFG, confirming the Y-STR profile of these samples and reaffirming the reliability of this panel. M4-GHEP20 is a mixture of blood and semen from two males being possible to observe both complete profiles in its analysis. Overall, these results show that the electropherograms obtained with this panel can be informative enough for forensic-type samples, even if they contained degraded DNA.
The 11 plus DYS385a/b Y-STR multiplex panel was applied to expand the current data available for the population of Ibiza, previously analyzed with the PPY. Forensic parameters were compared for the 12 loci previously analyzed (PPY) and the resulting 17 Y-STRs (contained in Y-Filer) and 23 Y-STRs (contained in PPY23), both using PPY data extended with the novel 11 plus DYS385a/b Y-STR multiplex panel. Allelic frequencies and haplotypes Allele frequencies and gene diversity (GD) of the 23 Y-STRs (12 Y-STRs previously analyzed and the new 11 Y-STRs here genotyped) for Ibiza are summarized in the Supplementary Table . Supplementary Table provides the 23-loci haplotypes of the 84 individuals from this population. Forensic and population genetic parameters At the single-locus level, DYS456, DYS458 and DYS576 loci were the most discriminative of the eleven incorporated Y-STRs included in the multiplex, generating the highest GD values (0.8181 for DYS576, 0.7533 for DYS458 and 0.7372 for DYS456) (Supplementary Table ). The lowest GD value in this case was 0.4079 for DYS533. These results are maintained if DYS385a/b loci is included in the computation. At the haplotype level, the forensic and population genetics parameters of the Ibiza population based on 12-loci contained in PPY (12 loci previously analyzed with PPY), 17-loci contained in Y-Filer (12 loci previously analyzed with PPY and new 5 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) and 23-loci contained in PPY23 (12 loci previously analyzed with PPY and new 11 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) haplotypes are compiled in Table . As expected the values for number of haplotypes, unique haplotypes, haplotype diversity and discrimination capacity augmented as the number of loci increased. When 23-loci haplotypes were considered, Ibiza exhibit high levels of haplotype diversity, with value of 0.9977, and the discrimination value was 0.9048.
Allele frequencies and gene diversity (GD) of the 23 Y-STRs (12 Y-STRs previously analyzed and the new 11 Y-STRs here genotyped) for Ibiza are summarized in the Supplementary Table . Supplementary Table provides the 23-loci haplotypes of the 84 individuals from this population.
At the single-locus level, DYS456, DYS458 and DYS576 loci were the most discriminative of the eleven incorporated Y-STRs included in the multiplex, generating the highest GD values (0.8181 for DYS576, 0.7533 for DYS458 and 0.7372 for DYS456) (Supplementary Table ). The lowest GD value in this case was 0.4079 for DYS533. These results are maintained if DYS385a/b loci is included in the computation. At the haplotype level, the forensic and population genetics parameters of the Ibiza population based on 12-loci contained in PPY (12 loci previously analyzed with PPY), 17-loci contained in Y-Filer (12 loci previously analyzed with PPY and new 5 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) and 23-loci contained in PPY23 (12 loci previously analyzed with PPY and new 11 loci here analyzed with the 11 plus DYS385a/b Y-STR multiplex panel) haplotypes are compiled in Table . As expected the values for number of haplotypes, unique haplotypes, haplotype diversity and discrimination capacity augmented as the number of loci increased. When 23-loci haplotypes were considered, Ibiza exhibit high levels of haplotype diversity, with value of 0.9977, and the discrimination value was 0.9048.
In the present study, a novel 11 plus DYS385a/b Y-STR multiplex panel has been developed and validated to expand to 23-loci Y-STR haplotypes population samples already analyzed with the 12-Y-STRs (PPY). Indeed, the application of this new panel has allowed to update the current Y-STR database of the Ibiza population previously based on 12 loci genotyped by using the PPY, increasing the resulting haplotype diversity and discriminatory capacity, and consequently providing evidence of the suitability of these Y-STR markers for forensic purposes. Furthermore, the validation studies have also shown that the new panel is valuable for forensic applications as it overcomes the typical difficulties found at a crime scene. In conclusion, the new panel here described represents an efficient and affordable alternative to expand to 23 Y-STRs the studied markers in numerous populations that nowadays are analyzed only with the PPY, being of great interest in population genetics and forensic use.
Supplementary Figures. Supplementary Tables.
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Colon mucosal proteomics of ankylosing spondylitis versus gut inflammation | d5cb2418-8521-4aa5-9e1b-5adac0807874 | 11642932 | Biochemistry[mh] | Ankylosing spondylitis (AS) is a chronic and progressive inflammatory disease which mainly invades the fibrous and synovial joints of the sacroiliac and spinal joints . Peripheral involvement includes enthesitis, dactylitis and arthritis. The most common extra-articular manifestations are uveitis, psoriasis and inflammatory bowel disease . The etiology and pathogenesis of AS remain unclear but are thought to be related to factors such as genetics, oxidative stress, mineral metabolism disorders, smoking, infections, and gut microbiota . The gut microbiota is a complex microbial ecosystem that plays a crucial role in the development of various autoimmune diseases, including multiple sclerosis, rheumatoid arthritis, type 1 diabetes and systemic lupus erythematosus . It is reported that up to 70% of AS patients have subclinical intestinal inflammation, and 5–10% suffer from more severe intestinal inflammation, even inflammatory bowel disease (IBD) . In addition, it has been found that gut inflammation is often closely associated with high disease activity of AS and more severe sacroiliac joint bone marrow edema . Our research group’s previous clinical observation found that the intervention of intestinal symptoms in patients with AS accompanied by gut inflammation can not only improve abdominal pain and diarrhea, but also better alleviate the pain symptoms, reduce disease activity and even reverse imaging findings. Therefore, we boldly speculate that there is some mysterious correlation between AS and gut inflammation. Proteomics researchers uses different approaches to look for target proteins, quantify signal proteins, and analyze protein interactions in efforts to investigate the nature of diseases. Most proteomics studies on AS have focused on serological markers , and no studies have investigated the relationship between AS and gut inflammation at the level of colon mucosal proteomics. In this study, we performed colon mucosal proteomics to investigate the relationship between AS and gut inflammation and to identify any differentially expressed proteins (DEPs) unique to AS combined with gut inflammation. We also investigated the effect of differentially expressed proteins on inflammatory cytokines through in vitro experiments to explore its potential role in the pathogenesis of AS and gut inflammation. shows our experimental workflow.
2.1 Materials We collected tissue samples from outpatients and inpatients treated at the Department of Rheumatology and Immunology or the Digestive Endoscopy Center, Jiangsu Provincial Hospital of Traditional Chinese Medicine, between July 2020 and December 2020. AS patients diagnosed according to the modified New York Criteria for Ankylosing Spondylitis (American College of Rheumatology, 1984) were included in the AS group. Patients were included in the gut inflammation group when they underwent colonoscopy and found acute or chronic lesions in the biopsy specimen . Patients who met the inclusion criteria of both AS and gut inflammation were included in the AS combined with gut inflammation group. Individuals without AS and gut inflammation were included in the healthy group. Subjects with the diagnosis of other intestinal diseases (such as inflammatory bowel disease), autoimmune diseases, infectious diseases (such as tuberculosis or cytomegalovirus, etc.), and a history of neurological cognitive disease were excluded from the four groups. In order not to affect the results of the study, patients who have used biological agents within one year are not allowed to join the group. Finally, 10 men aged 23 to 88 (mean: 44) and 10 women aged 31 to 69 (mean: 53.5) were included in this study. 2.2 Main instruments Nano Elute chromatography system and timsTOF Pro mass spectrometer (Bruker, Germany); low-temperature high-speed centrifuge (5430R;Eppendorf, Germany); Agilent 1260 Infinity II HPLC system (Agilent, USA); electrophoresis apparatus (Bio-Rad, USA); ultrasonic disintegrator (JY96-IIN; Ningbo Xinzhi Biological Technology Co. Ltd., China); vacuum centrifugal concentrator (LNG-T98; Jiangsu Taicang Huamei Technology Co. Ltd., China); MP Fastprep-24 homogenizer (Fastprep-24 5G; MP, USA); thermostatic incubator (GNP-9080; Shanghai Jinghong Chemical Co. Ltd., China); electronic balance (AX324Z; OHAUS, USA); compact thermostatic mixer (HCM-100 pro; Beijing Dalong Technology Co. Ltd., China); vortex shaker (GENIE Vortex-2; Scientific Industries, USA); NanoDrop 2000 spectrophotometer and Multiscan FC microplate reader (Thermo Fisher Scientific, USA).
We collected tissue samples from outpatients and inpatients treated at the Department of Rheumatology and Immunology or the Digestive Endoscopy Center, Jiangsu Provincial Hospital of Traditional Chinese Medicine, between July 2020 and December 2020. AS patients diagnosed according to the modified New York Criteria for Ankylosing Spondylitis (American College of Rheumatology, 1984) were included in the AS group. Patients were included in the gut inflammation group when they underwent colonoscopy and found acute or chronic lesions in the biopsy specimen . Patients who met the inclusion criteria of both AS and gut inflammation were included in the AS combined with gut inflammation group. Individuals without AS and gut inflammation were included in the healthy group. Subjects with the diagnosis of other intestinal diseases (such as inflammatory bowel disease), autoimmune diseases, infectious diseases (such as tuberculosis or cytomegalovirus, etc.), and a history of neurological cognitive disease were excluded from the four groups. In order not to affect the results of the study, patients who have used biological agents within one year are not allowed to join the group. Finally, 10 men aged 23 to 88 (mean: 44) and 10 women aged 31 to 69 (mean: 53.5) were included in this study.
Nano Elute chromatography system and timsTOF Pro mass spectrometer (Bruker, Germany); low-temperature high-speed centrifuge (5430R;Eppendorf, Germany); Agilent 1260 Infinity II HPLC system (Agilent, USA); electrophoresis apparatus (Bio-Rad, USA); ultrasonic disintegrator (JY96-IIN; Ningbo Xinzhi Biological Technology Co. Ltd., China); vacuum centrifugal concentrator (LNG-T98; Jiangsu Taicang Huamei Technology Co. Ltd., China); MP Fastprep-24 homogenizer (Fastprep-24 5G; MP, USA); thermostatic incubator (GNP-9080; Shanghai Jinghong Chemical Co. Ltd., China); electronic balance (AX324Z; OHAUS, USA); compact thermostatic mixer (HCM-100 pro; Beijing Dalong Technology Co. Ltd., China); vortex shaker (GENIE Vortex-2; Scientific Industries, USA); NanoDrop 2000 spectrophotometer and Multiscan FC microplate reader (Thermo Fisher Scientific, USA).
3.1 Sample collection A total of 20 samples were collected for colonic mucosa study, including five from the healthy group (group A; A1, A2, A3, A4, A5), five from the gut inflammation group (group B; B1, B2, B3, B4, B5), five from the AS group (group C; C1, C2, C3, C4, C5), and five from the AS combined with gut inflammation group (group D; D1, D2, D3, D4, D5). Colonoscopy was performed to randomly collect a piece of colon mucosal tissue (approximately 200–500 mg) from every included patient. Any nontarget tissues such as connective tissue and adipose tissue were immediately removed. The samples were washed in phosphate-buffered saline to remove blood and debris, put in liquid nitrogen, and then stored at -80°C within 2 hours. This study was approved by the Ethics Committee of the Affiliated Hospital of Nanjing University of Traditional Chinese Medicine(Ethics No. 2020NL-062-03). All participants signed informed consent forms. 3.2 Proteomic analysis of colonic mucosa 3.2.1 Protein extraction A certain amount of SDT lysis solution (4% SDS, 100 mM Tris-HCl, pH 7.6) was added to each sample, followed by homogenization in a Lysing Matrix A tube (24×2, 6.0 M/S, 60 s), boiling in a water bath for 10 minutes, and centrifugation at 14,000 g for 15 minutes. The supernatant was filtered with a 0.22-μm centrifuge tube, and the filtrate was collected. The protein concentration was measured with the bicinchoninic acid method, and then the samples were aliquoted and stored at -80°C. 3.2.2 Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) Loading buffer (6×) was added to each protein sample (20 μg), which was boiled in a water bath for 5 minutes and then separated by 12% SDS-PAGE (250 V, 40 minutes) and stained with Coomassie blue. 3.2.3 Filter-aided sample preparation (FASP) In a centrifuge tube, a protein sample (80 μg) and the dithiothreitol stock solution were added and mixed to a final concentration of 100 mM, followed by boiling in a water bath for 5 minutes. Once the sample had cooled to room temperature, 200 μL of UA buffer (8M Urea, 150mM Tris-HCl, pH 8.5) was added and mixed, and then the sample was transferred to a 30-kD ultrafiltration centrifuge tube and centrifuged at 12,500 g for 15 minutes. The filtrate was discarded, and the above procedure was repeated once. One hundred microliters of IAA buffer (100 mM IAA in UA) was added, and the sample was placed on a shaker at 600 rpm for 1 minute, followed by 30-minute reaction in the dark at room temperature and then centrifugation at 12,500 g for 15 minutes. Next, 100 μL of UA buffer was added, and the sample was centrifuged at 12,500 g for 15 minutes. The above procedure was repeated twice. Then 100 μL of 40 mM NH 4 HCO3 solution was added, and the sample was centrifuged at 12 500 g for 15 minutes. The procedure was repeated twice. Next, 40 μL of trypsin buffer (4 μg of trypsin in 40 μL of 40 mM NH 4 HCO3 solution) was added, and the sample was placed on a shaker at 600 rpm for 1 minute and then 16–18 hours at 37°C. The sample was transferred to a collection tube and centrifuged at 12,500 g for 15 minutes. Twenty microliters of 40 mM NH 4 HCO 3 solution was added, and the sample was centrifuged at 12,500 g for 15 minutes. The filtrate was collected, desalted with a C 18 cartridge, lyophilized, and suspended in 40 μL of 0.1% formic acid solution, followed by peptide quantification at 280 nm. 3.2.4 Mass spectrometry (MS) The mixed peptides were separated with the NanoElute system with a nanoliter flow rate (solution A: 0.1% formic acid aqueous solution; solution B: 0.1% formic acid acetonitrile aqueous solution [100% acetonitrile]). The column was balanced with 100% solution A, and the samples were loaded with an autosampler to the column (IonOpticks, Australia, 25 cm × 75 μm, C18 column, 1.6 μm) for separation over a 2-hour gradient at 300 nL/min. The gradient included 3% solution B for minutes 0–5; 3–28% solution B for minutes 5–95; 28–38% solution B for minutes 95–110; 38–100% solution B for minutes 110–115; and 100% solution B for minutes 115–120. The PASEF mode of the timsTOF Pro mass spectrometer (Bruker, Germany) was used for MS analysis. The parameters were as follows: analysis time: 120 minutes; detection method: positive ion; precursor ion scan range: 100–1700 m / z ; ion mobility 1/K0: 0.6–1.6 V⋅s/cm 2 ; ion accumulation or release time: 100 ms; ion utilization rate: 100%; capillary voltage: 1500 V; drying gas rate: 3 L/min; and drying temperature: 180°C. The settings of PASEF were 10 MS/MS scans (total cycle time: 1.16 s), charge range 0–5, dynamic rejection time 0.4 minutes, ion target intensity 20,000, ion intensity threshold 2500, and collision-induced dissociation fragmentation energy 42 eV. 3.3 Cellular experiments to investigate the effects of NMRAL1 on inflammatory factors 3.3.1 Cell culture RAW264.7 macrophages were obtained from the Cell Bank of the Chinese Academy of Sciences. The cells were cultured in DMEM medium supplemented with 10% fetal bovine serum (FBS), 50μM β-mercaptoethanol, 20 mM HEPES, 10 mM sodium pyruvate, 100μg/ml streptomycin, and 100 U/ml penicillin. The cells were maintained in a 5% CO2 incubator. 3.3.2 NMRAL1 siRNA transfection in RAW264.7 macrophages P3 generation cells were plated in 6-well plates, with 1×10^4 cells seeded in 2 mL of medium per well. The cells were divided into three groups: blank control group (NC), model group (Mod), and model+ transfection group (Mod+Trans). On the day of transfection, the cells reached 50–60% confluence. For the model +transfection group, EndofectinTM RNAi transfection reagent (GeneCopoeia, USA) and NMRAL1 siRNA (Cas9X, Suzhou, China) were diluted in optiMEM (Gibco, USA). A total of 250 μL of the transfection mixture was gently added dropwise to the RAW264.7 macrophages, and the cells were incubated at 37°C in a 5% CO2 incubator for 24 hours. After 24 hours of transfection, 1μg/mL LPS (Sigma, USA) was added to both the model group and the model + transfection group, and the cells were incubated at 37°C in a 5% CO2 incubator for an additional 12 hours. After this incubation, the supernatants and RNA were collected for further analysis. Although RAW264.7 macrophages produce TNF-α, IL-1β, and IL-23 in response to LPS stimulation, they secrete relatively low levels of IL-17. Therefore, to enhance the detection of IL-17, a co-culture system was employed. After LPS stimulation, the supernatant from the RAW264.7 macrophages was collected and co-cultured with Jurkat human T lymphocyte leukemia cells (iCell Bioscience Inc, Shanghai, China). Following incubation, the supernatant from the co-culture was collected and used for subsequent ELISA analysis to detect IL-17 expression levels. 3.3.3 Quantitative Real-Time PCR (RT-qPCR) analysis of NMRAL1 mRNA expression Total RNA was isolated using an RNA extraction kit (Accurate Biology, Nanjing, China), and reverse transcription was performed using a reverse transcription kit (Vazyme, Nanjing, China). The amplification was conducted in a total volume of 20μL (Vazyme, Nanjing, China) containing 0.4μL (10μM) forward and reverse primers for NMRAL1, 10μL of 2× ChamQ Blue Universal SYBR, 1μL of reverse-transcribed cDNA, and 8.2μL of ddH2O. The PCR conditions were as follows: initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 5 seconds, and annealing/extension at 60°C for 30 seconds. The relative expression levels of NMRAL1 mRNA were normalized to β-actin and calculated using the 2- ΔΔCt method. The primers used in the present study are listed as follows (5’-3’). NMRAL1 FORWARD: TGC GGC TGC CTT GCT ATT T ; NMRAL1 REVERSE: TCA GGA GTT GTC TTG GCA TGA ; Actb FORWARD: GGC TGT ATT CCC CTC CAT CG ; Actb REVERSE: CCA GTT GGT AAC AAT GCC ATG T . 3.3.4 ELISA for detection of inflammatory cytokines in supernatants Supernatants from RAW264.7 macrophage cultures were collected to measure the levels of TNF-α, IL-1β, and IL-23 using commercial ELISA kits (Jinyibai, Nanjing, China). After co-culture, supernatants were harvested to detect IL-17 levels by ELISA. All measurements were performed according to the manufacturer’s instructions, and each sample was analyzed in triplicate. 3.4 Data analysis 3.4.1 MS file processing MaxQuant was used for quantitative calculation of label-free quantitative proteomic data. 3.4.2 Database selection The database Uniprot_HomoSapiens_20367_20200226 ( http://www.UniProt.org ) was used to identify proteins. 3.4.3 Parameters for qualitative and quantitative protein analysis The label-free quantitation algorithm was used for quantitative analysis, and MaxQuant was used for qualitative matching. The parameters of the database are as follows: Maximum missed cleavages are 2. Fixed modifications are carbamidomethyl(C). Variable modifications are oxidation(m), acetyl(protein N-term). Database is Uniprot_HomoSapiens_20367_20200226 and database pattern is target-reverse true. Include contaminants are target-reverse. A global FDR control strategy was applied to adjust p-values for multiple testing and the cutoff of global false discovery rate (FDR) for peptide and protein identification is set to less than or equal to 0.01. This approach ensures that the likelihood of type I errors due to multiple comparisons is adequately controlled, maintaining the integrity of our findings. 3.5 Statistical analyses Graphpad7.0 was used for statistical analysis. Quantitative variables were presented as mean ± standard deviation (SD) and the data between multiple groups were analyzed using one-way ANOVA. A P value < 0.05 was accepted as significant.
A total of 20 samples were collected for colonic mucosa study, including five from the healthy group (group A; A1, A2, A3, A4, A5), five from the gut inflammation group (group B; B1, B2, B3, B4, B5), five from the AS group (group C; C1, C2, C3, C4, C5), and five from the AS combined with gut inflammation group (group D; D1, D2, D3, D4, D5). Colonoscopy was performed to randomly collect a piece of colon mucosal tissue (approximately 200–500 mg) from every included patient. Any nontarget tissues such as connective tissue and adipose tissue were immediately removed. The samples were washed in phosphate-buffered saline to remove blood and debris, put in liquid nitrogen, and then stored at -80°C within 2 hours. This study was approved by the Ethics Committee of the Affiliated Hospital of Nanjing University of Traditional Chinese Medicine(Ethics No. 2020NL-062-03). All participants signed informed consent forms.
3.2.1 Protein extraction A certain amount of SDT lysis solution (4% SDS, 100 mM Tris-HCl, pH 7.6) was added to each sample, followed by homogenization in a Lysing Matrix A tube (24×2, 6.0 M/S, 60 s), boiling in a water bath for 10 minutes, and centrifugation at 14,000 g for 15 minutes. The supernatant was filtered with a 0.22-μm centrifuge tube, and the filtrate was collected. The protein concentration was measured with the bicinchoninic acid method, and then the samples were aliquoted and stored at -80°C. 3.2.2 Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) Loading buffer (6×) was added to each protein sample (20 μg), which was boiled in a water bath for 5 minutes and then separated by 12% SDS-PAGE (250 V, 40 minutes) and stained with Coomassie blue. 3.2.3 Filter-aided sample preparation (FASP) In a centrifuge tube, a protein sample (80 μg) and the dithiothreitol stock solution were added and mixed to a final concentration of 100 mM, followed by boiling in a water bath for 5 minutes. Once the sample had cooled to room temperature, 200 μL of UA buffer (8M Urea, 150mM Tris-HCl, pH 8.5) was added and mixed, and then the sample was transferred to a 30-kD ultrafiltration centrifuge tube and centrifuged at 12,500 g for 15 minutes. The filtrate was discarded, and the above procedure was repeated once. One hundred microliters of IAA buffer (100 mM IAA in UA) was added, and the sample was placed on a shaker at 600 rpm for 1 minute, followed by 30-minute reaction in the dark at room temperature and then centrifugation at 12,500 g for 15 minutes. Next, 100 μL of UA buffer was added, and the sample was centrifuged at 12,500 g for 15 minutes. The above procedure was repeated twice. Then 100 μL of 40 mM NH 4 HCO3 solution was added, and the sample was centrifuged at 12 500 g for 15 minutes. The procedure was repeated twice. Next, 40 μL of trypsin buffer (4 μg of trypsin in 40 μL of 40 mM NH 4 HCO3 solution) was added, and the sample was placed on a shaker at 600 rpm for 1 minute and then 16–18 hours at 37°C. The sample was transferred to a collection tube and centrifuged at 12,500 g for 15 minutes. Twenty microliters of 40 mM NH 4 HCO 3 solution was added, and the sample was centrifuged at 12,500 g for 15 minutes. The filtrate was collected, desalted with a C 18 cartridge, lyophilized, and suspended in 40 μL of 0.1% formic acid solution, followed by peptide quantification at 280 nm. 3.2.4 Mass spectrometry (MS) The mixed peptides were separated with the NanoElute system with a nanoliter flow rate (solution A: 0.1% formic acid aqueous solution; solution B: 0.1% formic acid acetonitrile aqueous solution [100% acetonitrile]). The column was balanced with 100% solution A, and the samples were loaded with an autosampler to the column (IonOpticks, Australia, 25 cm × 75 μm, C18 column, 1.6 μm) for separation over a 2-hour gradient at 300 nL/min. The gradient included 3% solution B for minutes 0–5; 3–28% solution B for minutes 5–95; 28–38% solution B for minutes 95–110; 38–100% solution B for minutes 110–115; and 100% solution B for minutes 115–120. The PASEF mode of the timsTOF Pro mass spectrometer (Bruker, Germany) was used for MS analysis. The parameters were as follows: analysis time: 120 minutes; detection method: positive ion; precursor ion scan range: 100–1700 m / z ; ion mobility 1/K0: 0.6–1.6 V⋅s/cm 2 ; ion accumulation or release time: 100 ms; ion utilization rate: 100%; capillary voltage: 1500 V; drying gas rate: 3 L/min; and drying temperature: 180°C. The settings of PASEF were 10 MS/MS scans (total cycle time: 1.16 s), charge range 0–5, dynamic rejection time 0.4 minutes, ion target intensity 20,000, ion intensity threshold 2500, and collision-induced dissociation fragmentation energy 42 eV.
A certain amount of SDT lysis solution (4% SDS, 100 mM Tris-HCl, pH 7.6) was added to each sample, followed by homogenization in a Lysing Matrix A tube (24×2, 6.0 M/S, 60 s), boiling in a water bath for 10 minutes, and centrifugation at 14,000 g for 15 minutes. The supernatant was filtered with a 0.22-μm centrifuge tube, and the filtrate was collected. The protein concentration was measured with the bicinchoninic acid method, and then the samples were aliquoted and stored at -80°C.
Loading buffer (6×) was added to each protein sample (20 μg), which was boiled in a water bath for 5 minutes and then separated by 12% SDS-PAGE (250 V, 40 minutes) and stained with Coomassie blue.
In a centrifuge tube, a protein sample (80 μg) and the dithiothreitol stock solution were added and mixed to a final concentration of 100 mM, followed by boiling in a water bath for 5 minutes. Once the sample had cooled to room temperature, 200 μL of UA buffer (8M Urea, 150mM Tris-HCl, pH 8.5) was added and mixed, and then the sample was transferred to a 30-kD ultrafiltration centrifuge tube and centrifuged at 12,500 g for 15 minutes. The filtrate was discarded, and the above procedure was repeated once. One hundred microliters of IAA buffer (100 mM IAA in UA) was added, and the sample was placed on a shaker at 600 rpm for 1 minute, followed by 30-minute reaction in the dark at room temperature and then centrifugation at 12,500 g for 15 minutes. Next, 100 μL of UA buffer was added, and the sample was centrifuged at 12,500 g for 15 minutes. The above procedure was repeated twice. Then 100 μL of 40 mM NH 4 HCO3 solution was added, and the sample was centrifuged at 12 500 g for 15 minutes. The procedure was repeated twice. Next, 40 μL of trypsin buffer (4 μg of trypsin in 40 μL of 40 mM NH 4 HCO3 solution) was added, and the sample was placed on a shaker at 600 rpm for 1 minute and then 16–18 hours at 37°C. The sample was transferred to a collection tube and centrifuged at 12,500 g for 15 minutes. Twenty microliters of 40 mM NH 4 HCO 3 solution was added, and the sample was centrifuged at 12,500 g for 15 minutes. The filtrate was collected, desalted with a C 18 cartridge, lyophilized, and suspended in 40 μL of 0.1% formic acid solution, followed by peptide quantification at 280 nm.
The mixed peptides were separated with the NanoElute system with a nanoliter flow rate (solution A: 0.1% formic acid aqueous solution; solution B: 0.1% formic acid acetonitrile aqueous solution [100% acetonitrile]). The column was balanced with 100% solution A, and the samples were loaded with an autosampler to the column (IonOpticks, Australia, 25 cm × 75 μm, C18 column, 1.6 μm) for separation over a 2-hour gradient at 300 nL/min. The gradient included 3% solution B for minutes 0–5; 3–28% solution B for minutes 5–95; 28–38% solution B for minutes 95–110; 38–100% solution B for minutes 110–115; and 100% solution B for minutes 115–120. The PASEF mode of the timsTOF Pro mass spectrometer (Bruker, Germany) was used for MS analysis. The parameters were as follows: analysis time: 120 minutes; detection method: positive ion; precursor ion scan range: 100–1700 m / z ; ion mobility 1/K0: 0.6–1.6 V⋅s/cm 2 ; ion accumulation or release time: 100 ms; ion utilization rate: 100%; capillary voltage: 1500 V; drying gas rate: 3 L/min; and drying temperature: 180°C. The settings of PASEF were 10 MS/MS scans (total cycle time: 1.16 s), charge range 0–5, dynamic rejection time 0.4 minutes, ion target intensity 20,000, ion intensity threshold 2500, and collision-induced dissociation fragmentation energy 42 eV.
3.3.1 Cell culture RAW264.7 macrophages were obtained from the Cell Bank of the Chinese Academy of Sciences. The cells were cultured in DMEM medium supplemented with 10% fetal bovine serum (FBS), 50μM β-mercaptoethanol, 20 mM HEPES, 10 mM sodium pyruvate, 100μg/ml streptomycin, and 100 U/ml penicillin. The cells were maintained in a 5% CO2 incubator. 3.3.2 NMRAL1 siRNA transfection in RAW264.7 macrophages P3 generation cells were plated in 6-well plates, with 1×10^4 cells seeded in 2 mL of medium per well. The cells were divided into three groups: blank control group (NC), model group (Mod), and model+ transfection group (Mod+Trans). On the day of transfection, the cells reached 50–60% confluence. For the model +transfection group, EndofectinTM RNAi transfection reagent (GeneCopoeia, USA) and NMRAL1 siRNA (Cas9X, Suzhou, China) were diluted in optiMEM (Gibco, USA). A total of 250 μL of the transfection mixture was gently added dropwise to the RAW264.7 macrophages, and the cells were incubated at 37°C in a 5% CO2 incubator for 24 hours. After 24 hours of transfection, 1μg/mL LPS (Sigma, USA) was added to both the model group and the model + transfection group, and the cells were incubated at 37°C in a 5% CO2 incubator for an additional 12 hours. After this incubation, the supernatants and RNA were collected for further analysis. Although RAW264.7 macrophages produce TNF-α, IL-1β, and IL-23 in response to LPS stimulation, they secrete relatively low levels of IL-17. Therefore, to enhance the detection of IL-17, a co-culture system was employed. After LPS stimulation, the supernatant from the RAW264.7 macrophages was collected and co-cultured with Jurkat human T lymphocyte leukemia cells (iCell Bioscience Inc, Shanghai, China). Following incubation, the supernatant from the co-culture was collected and used for subsequent ELISA analysis to detect IL-17 expression levels. 3.3.3 Quantitative Real-Time PCR (RT-qPCR) analysis of NMRAL1 mRNA expression Total RNA was isolated using an RNA extraction kit (Accurate Biology, Nanjing, China), and reverse transcription was performed using a reverse transcription kit (Vazyme, Nanjing, China). The amplification was conducted in a total volume of 20μL (Vazyme, Nanjing, China) containing 0.4μL (10μM) forward and reverse primers for NMRAL1, 10μL of 2× ChamQ Blue Universal SYBR, 1μL of reverse-transcribed cDNA, and 8.2μL of ddH2O. The PCR conditions were as follows: initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 5 seconds, and annealing/extension at 60°C for 30 seconds. The relative expression levels of NMRAL1 mRNA were normalized to β-actin and calculated using the 2- ΔΔCt method. The primers used in the present study are listed as follows (5’-3’). NMRAL1 FORWARD: TGC GGC TGC CTT GCT ATT T ; NMRAL1 REVERSE: TCA GGA GTT GTC TTG GCA TGA ; Actb FORWARD: GGC TGT ATT CCC CTC CAT CG ; Actb REVERSE: CCA GTT GGT AAC AAT GCC ATG T . 3.3.4 ELISA for detection of inflammatory cytokines in supernatants Supernatants from RAW264.7 macrophage cultures were collected to measure the levels of TNF-α, IL-1β, and IL-23 using commercial ELISA kits (Jinyibai, Nanjing, China). After co-culture, supernatants were harvested to detect IL-17 levels by ELISA. All measurements were performed according to the manufacturer’s instructions, and each sample was analyzed in triplicate.
RAW264.7 macrophages were obtained from the Cell Bank of the Chinese Academy of Sciences. The cells were cultured in DMEM medium supplemented with 10% fetal bovine serum (FBS), 50μM β-mercaptoethanol, 20 mM HEPES, 10 mM sodium pyruvate, 100μg/ml streptomycin, and 100 U/ml penicillin. The cells were maintained in a 5% CO2 incubator.
P3 generation cells were plated in 6-well plates, with 1×10^4 cells seeded in 2 mL of medium per well. The cells were divided into three groups: blank control group (NC), model group (Mod), and model+ transfection group (Mod+Trans). On the day of transfection, the cells reached 50–60% confluence. For the model +transfection group, EndofectinTM RNAi transfection reagent (GeneCopoeia, USA) and NMRAL1 siRNA (Cas9X, Suzhou, China) were diluted in optiMEM (Gibco, USA). A total of 250 μL of the transfection mixture was gently added dropwise to the RAW264.7 macrophages, and the cells were incubated at 37°C in a 5% CO2 incubator for 24 hours. After 24 hours of transfection, 1μg/mL LPS (Sigma, USA) was added to both the model group and the model + transfection group, and the cells were incubated at 37°C in a 5% CO2 incubator for an additional 12 hours. After this incubation, the supernatants and RNA were collected for further analysis. Although RAW264.7 macrophages produce TNF-α, IL-1β, and IL-23 in response to LPS stimulation, they secrete relatively low levels of IL-17. Therefore, to enhance the detection of IL-17, a co-culture system was employed. After LPS stimulation, the supernatant from the RAW264.7 macrophages was collected and co-cultured with Jurkat human T lymphocyte leukemia cells (iCell Bioscience Inc, Shanghai, China). Following incubation, the supernatant from the co-culture was collected and used for subsequent ELISA analysis to detect IL-17 expression levels.
Total RNA was isolated using an RNA extraction kit (Accurate Biology, Nanjing, China), and reverse transcription was performed using a reverse transcription kit (Vazyme, Nanjing, China). The amplification was conducted in a total volume of 20μL (Vazyme, Nanjing, China) containing 0.4μL (10μM) forward and reverse primers for NMRAL1, 10μL of 2× ChamQ Blue Universal SYBR, 1μL of reverse-transcribed cDNA, and 8.2μL of ddH2O. The PCR conditions were as follows: initial denaturation at 95°C for 30 seconds, followed by 40 cycles of denaturation at 95°C for 5 seconds, and annealing/extension at 60°C for 30 seconds. The relative expression levels of NMRAL1 mRNA were normalized to β-actin and calculated using the 2- ΔΔCt method. The primers used in the present study are listed as follows (5’-3’). NMRAL1 FORWARD: TGC GGC TGC CTT GCT ATT T ; NMRAL1 REVERSE: TCA GGA GTT GTC TTG GCA TGA ; Actb FORWARD: GGC TGT ATT CCC CTC CAT CG ; Actb REVERSE: CCA GTT GGT AAC AAT GCC ATG T .
Supernatants from RAW264.7 macrophage cultures were collected to measure the levels of TNF-α, IL-1β, and IL-23 using commercial ELISA kits (Jinyibai, Nanjing, China). After co-culture, supernatants were harvested to detect IL-17 levels by ELISA. All measurements were performed according to the manufacturer’s instructions, and each sample was analyzed in triplicate.
3.4.1 MS file processing MaxQuant was used for quantitative calculation of label-free quantitative proteomic data. 3.4.2 Database selection The database Uniprot_HomoSapiens_20367_20200226 ( http://www.UniProt.org ) was used to identify proteins. 3.4.3 Parameters for qualitative and quantitative protein analysis The label-free quantitation algorithm was used for quantitative analysis, and MaxQuant was used for qualitative matching. The parameters of the database are as follows: Maximum missed cleavages are 2. Fixed modifications are carbamidomethyl(C). Variable modifications are oxidation(m), acetyl(protein N-term). Database is Uniprot_HomoSapiens_20367_20200226 and database pattern is target-reverse true. Include contaminants are target-reverse. A global FDR control strategy was applied to adjust p-values for multiple testing and the cutoff of global false discovery rate (FDR) for peptide and protein identification is set to less than or equal to 0.01. This approach ensures that the likelihood of type I errors due to multiple comparisons is adequately controlled, maintaining the integrity of our findings.
MaxQuant was used for quantitative calculation of label-free quantitative proteomic data.
The database Uniprot_HomoSapiens_20367_20200226 ( http://www.UniProt.org ) was used to identify proteins.
The label-free quantitation algorithm was used for quantitative analysis, and MaxQuant was used for qualitative matching. The parameters of the database are as follows: Maximum missed cleavages are 2. Fixed modifications are carbamidomethyl(C). Variable modifications are oxidation(m), acetyl(protein N-term). Database is Uniprot_HomoSapiens_20367_20200226 and database pattern is target-reverse true. Include contaminants are target-reverse. A global FDR control strategy was applied to adjust p-values for multiple testing and the cutoff of global false discovery rate (FDR) for peptide and protein identification is set to less than or equal to 0.01. This approach ensures that the likelihood of type I errors due to multiple comparisons is adequately controlled, maintaining the integrity of our findings.
Graphpad7.0 was used for statistical analysis. Quantitative variables were presented as mean ± standard deviation (SD) and the data between multiple groups were analyzed using one-way ANOVA. A P value < 0.05 was accepted as significant.
4.1 Basic characteristics of the participants A total of 5 healthy individuals, 5 gut inflammation patients, 5 AS patients and 5 AS with gut inflammation patients were enrolled into the colon mucosal tissue study. The CRP level was (6.62±4.08) mg/L in gut inflammation group. The CRP level was (16.28±6.72) mg/L in AS group. And the CRP level was (18.63±7.84) mg/L in AS with gut inflammation group . 4.2 Qualitative and quantitative analysis A total of 7039 proteins and 81141 peptides were identified in the database. provides detailed information on the proteins identified in our study, including Protein ID, Gene Name, Number of Peptides, and Molecular Weight. provides detailed information on the peptides identified in our study, encompassing Sequence, Length, Mass, and Score. For the Quantitative results, we screened duplicate data to select data with at least 50% nonempty values. A DEP was defined as one that was up or downregulated by at least 2-fold ( P <0.05) between two groups. The number of significant DEPs is shown in . Principal Component Analysis (PCA) revealed clear distinctions between the different study groups, demonstrating that the proteomic profiles of colonic mucosal tissues vary significantly among patients with AS, gut inflammation, AS combined with gut inflammation and healthy individuals . summarizes the proteins identified as upregulated or downregulated, with upregulation marked in yellow and downregulation in green. The table also lists the fold change values for these differentially expressed proteins in each group. 4.3 Bioinformatics analysis 4.3.1 Volcano plot We used the fold change in protein expression and the p-value between the two groups to generate a volcano plot, highlighting the significant differences in protein expression between the sample groups. DEPs were identified between groups B and A, groups D and C, groups D and B, and groups C and A . Among the highly differentially expressed proteins identified, SPATS2L, PCSK1, and FAM98A showed significant upregulation in group B compared to group A. COL5A1 was notably upregulated in group D compared to group C, while APCS and ALPL were significantly different between groups D and B. Additionally, CARHSP1 was identified as highly differentially expressed between groups C and A. These proteins are marked in the volcano plots . 4.3.2 Cluster analysis Cluster analysis revealed that the differentially expressed proteins (DEPs) exhibited high intergroup heterogeneity, indicating low similarity in protein expression profiles between the different groups (B/A, D/C, D/B, and C/A). Conversely, there was high intragroup homogeneity, meaning that the protein expression profiles within each group were highly similar, thereby reinforcing the distinctiveness of the DEPs associated with each group comparison . 4.3.3 Gene Ontology (GO) annotation and enrichment analysis GO is a standardized functional classification system, and its top-level annotations include biological processes, molecular functions, and cellular components. We compared the GO annotations for the B/A, D/C, D/B, and C/A DEPs . The InterPro database was used to analyze the enrichment of the functional domains of the DEPs. GO enrichment analysis showed that the DEPs of group B versus group A mainly had the biological functions of phosphatidylcholine-sterol O -acyltransferase activator activity, positive regulation of cholesterol esterification, platelet alpha granule lumen, lipoprotein metabolic process, negative regulation of cytokine secretion involved in immune response, and embryonic skeletal system development. GO enrichment analysis showed that the DEPs of group D versus group C mainly had biological functions related to very-low-density lipoprotein particles, chloride channel activity, lipoprotein metabolic processes, histone demethylase activity (H3-K4 specific), apoptotic DNA fragmentation, and cellular oxidant detoxification. In the group D versus group B comparison, the main biological functions of the DEPs were zinc ion binding, myoblast differentiation, transcription regulatory region DNA binding, cell growth, epithelial-to-mesenchymal transition, regulation of MDA-5 signaling pathway, and regulation of RIG-I signaling pathway. Between group C and group A, the DEPs had the main biological functions of skeletal muscle fiber adaptation, smooth muscle contractile fiber, mitochondrial respiratory chain complex I assembly, vascular smooth muscle contraction, mitochondrial outer membrane permeabilization involved in programmed cell death, l -phenylalanine metabolic processes, sarcomere organization, negative regulation of B cell proliferation, and negative regulation of interleukin-5 production. 4.3.4 Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis The DEPs were analyzed for their enrichment in KEGG pathways. KEGG analysis showed that the DEPs of group B versus group A were enriched in the pathways of cholesterol metabolism, complement and coagulation cascades, proteoglycans in cancer, PPAR signaling pathway, and fat digestion and absorption. The DEPs of group D versus group C were enriched in PPAR signaling, arachidonic acid metabolism, cholesterol metabolism, and proximal tubule bicarbonate reclamation. The DEPs of group D versus group B were enriched in RNA transport. The DEPs of group C versus group A were enriched in thermogenesis, retrograde endocannabinoid signaling, apoptosis-fly, and asthma . 4.3.5 Screening of DEPs The DEPs of group B (gut inflammation) versus group A (healthy individuals) and of group D (AS combined with gut inflammation) versus group C (AS) were aligned to identify their common DEPs. These were NMRAL1, ORM1, and APOA2. The only DEP shared in common by the group D (AS combined with gut inflammation) versus group B (gut inflammation) comparison and the group C (AS) versus group A (healthy individuals) comparison was NMRAL1). Finally, aligning these two sets with each other revealed that NMRAL1 was the DEP that identified group D. The Venn diagram below vividly demonstrates the process of screening DEPs . 4.4 Changes in inflammatory cytokine expression in NMRAL1 siRNA-transfected macrophages To explore the inflammation-related function of NMRAL1 protein, we utilized the murine monocyte/macrophage cell line RAW264.7, an established model for inflammation studies. RT-qPCR results showed that, compared to the blank control group, the relative expression of NMRAL1 mRNA was significantly decreased in the model group treated with LPS ( P <0.001). The reduction in NMRAL1 mRNA expression was even more pronounced in the NMRAL1 siRNA-transfected macrophages ( P <0.0001), indicating successful transfection of NMRAL1 siRNA . ELISA results demonstrated that the expression levels of TNF-α, IL-1β and IL-23 were significantly increased in the model group compared to the blank control group ( P < 0.0001, P <0.001). Notably, IL-17 levels were measured following co-culture of LPS-stimulated RAW264.7 macrophage supernatants with Jurkat cells to enhance IL-17 detection. After NMRAL1 siRNA transfection, the expression levels of all these inflammatory cytokines, including IL-17, were significantly decreased in the model + transfection group ( P <0.0001, P <0.01, P <0.05) .
A total of 5 healthy individuals, 5 gut inflammation patients, 5 AS patients and 5 AS with gut inflammation patients were enrolled into the colon mucosal tissue study. The CRP level was (6.62±4.08) mg/L in gut inflammation group. The CRP level was (16.28±6.72) mg/L in AS group. And the CRP level was (18.63±7.84) mg/L in AS with gut inflammation group .
A total of 7039 proteins and 81141 peptides were identified in the database. provides detailed information on the proteins identified in our study, including Protein ID, Gene Name, Number of Peptides, and Molecular Weight. provides detailed information on the peptides identified in our study, encompassing Sequence, Length, Mass, and Score. For the Quantitative results, we screened duplicate data to select data with at least 50% nonempty values. A DEP was defined as one that was up or downregulated by at least 2-fold ( P <0.05) between two groups. The number of significant DEPs is shown in . Principal Component Analysis (PCA) revealed clear distinctions between the different study groups, demonstrating that the proteomic profiles of colonic mucosal tissues vary significantly among patients with AS, gut inflammation, AS combined with gut inflammation and healthy individuals . summarizes the proteins identified as upregulated or downregulated, with upregulation marked in yellow and downregulation in green. The table also lists the fold change values for these differentially expressed proteins in each group.
4.3.1 Volcano plot We used the fold change in protein expression and the p-value between the two groups to generate a volcano plot, highlighting the significant differences in protein expression between the sample groups. DEPs were identified between groups B and A, groups D and C, groups D and B, and groups C and A . Among the highly differentially expressed proteins identified, SPATS2L, PCSK1, and FAM98A showed significant upregulation in group B compared to group A. COL5A1 was notably upregulated in group D compared to group C, while APCS and ALPL were significantly different between groups D and B. Additionally, CARHSP1 was identified as highly differentially expressed between groups C and A. These proteins are marked in the volcano plots . 4.3.2 Cluster analysis Cluster analysis revealed that the differentially expressed proteins (DEPs) exhibited high intergroup heterogeneity, indicating low similarity in protein expression profiles between the different groups (B/A, D/C, D/B, and C/A). Conversely, there was high intragroup homogeneity, meaning that the protein expression profiles within each group were highly similar, thereby reinforcing the distinctiveness of the DEPs associated with each group comparison . 4.3.3 Gene Ontology (GO) annotation and enrichment analysis GO is a standardized functional classification system, and its top-level annotations include biological processes, molecular functions, and cellular components. We compared the GO annotations for the B/A, D/C, D/B, and C/A DEPs . The InterPro database was used to analyze the enrichment of the functional domains of the DEPs. GO enrichment analysis showed that the DEPs of group B versus group A mainly had the biological functions of phosphatidylcholine-sterol O -acyltransferase activator activity, positive regulation of cholesterol esterification, platelet alpha granule lumen, lipoprotein metabolic process, negative regulation of cytokine secretion involved in immune response, and embryonic skeletal system development. GO enrichment analysis showed that the DEPs of group D versus group C mainly had biological functions related to very-low-density lipoprotein particles, chloride channel activity, lipoprotein metabolic processes, histone demethylase activity (H3-K4 specific), apoptotic DNA fragmentation, and cellular oxidant detoxification. In the group D versus group B comparison, the main biological functions of the DEPs were zinc ion binding, myoblast differentiation, transcription regulatory region DNA binding, cell growth, epithelial-to-mesenchymal transition, regulation of MDA-5 signaling pathway, and regulation of RIG-I signaling pathway. Between group C and group A, the DEPs had the main biological functions of skeletal muscle fiber adaptation, smooth muscle contractile fiber, mitochondrial respiratory chain complex I assembly, vascular smooth muscle contraction, mitochondrial outer membrane permeabilization involved in programmed cell death, l -phenylalanine metabolic processes, sarcomere organization, negative regulation of B cell proliferation, and negative regulation of interleukin-5 production. 4.3.4 Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis The DEPs were analyzed for their enrichment in KEGG pathways. KEGG analysis showed that the DEPs of group B versus group A were enriched in the pathways of cholesterol metabolism, complement and coagulation cascades, proteoglycans in cancer, PPAR signaling pathway, and fat digestion and absorption. The DEPs of group D versus group C were enriched in PPAR signaling, arachidonic acid metabolism, cholesterol metabolism, and proximal tubule bicarbonate reclamation. The DEPs of group D versus group B were enriched in RNA transport. The DEPs of group C versus group A were enriched in thermogenesis, retrograde endocannabinoid signaling, apoptosis-fly, and asthma . 4.3.5 Screening of DEPs The DEPs of group B (gut inflammation) versus group A (healthy individuals) and of group D (AS combined with gut inflammation) versus group C (AS) were aligned to identify their common DEPs. These were NMRAL1, ORM1, and APOA2. The only DEP shared in common by the group D (AS combined with gut inflammation) versus group B (gut inflammation) comparison and the group C (AS) versus group A (healthy individuals) comparison was NMRAL1). Finally, aligning these two sets with each other revealed that NMRAL1 was the DEP that identified group D. The Venn diagram below vividly demonstrates the process of screening DEPs .
We used the fold change in protein expression and the p-value between the two groups to generate a volcano plot, highlighting the significant differences in protein expression between the sample groups. DEPs were identified between groups B and A, groups D and C, groups D and B, and groups C and A . Among the highly differentially expressed proteins identified, SPATS2L, PCSK1, and FAM98A showed significant upregulation in group B compared to group A. COL5A1 was notably upregulated in group D compared to group C, while APCS and ALPL were significantly different between groups D and B. Additionally, CARHSP1 was identified as highly differentially expressed between groups C and A. These proteins are marked in the volcano plots .
Cluster analysis revealed that the differentially expressed proteins (DEPs) exhibited high intergroup heterogeneity, indicating low similarity in protein expression profiles between the different groups (B/A, D/C, D/B, and C/A). Conversely, there was high intragroup homogeneity, meaning that the protein expression profiles within each group were highly similar, thereby reinforcing the distinctiveness of the DEPs associated with each group comparison .
GO is a standardized functional classification system, and its top-level annotations include biological processes, molecular functions, and cellular components. We compared the GO annotations for the B/A, D/C, D/B, and C/A DEPs . The InterPro database was used to analyze the enrichment of the functional domains of the DEPs. GO enrichment analysis showed that the DEPs of group B versus group A mainly had the biological functions of phosphatidylcholine-sterol O -acyltransferase activator activity, positive regulation of cholesterol esterification, platelet alpha granule lumen, lipoprotein metabolic process, negative regulation of cytokine secretion involved in immune response, and embryonic skeletal system development. GO enrichment analysis showed that the DEPs of group D versus group C mainly had biological functions related to very-low-density lipoprotein particles, chloride channel activity, lipoprotein metabolic processes, histone demethylase activity (H3-K4 specific), apoptotic DNA fragmentation, and cellular oxidant detoxification. In the group D versus group B comparison, the main biological functions of the DEPs were zinc ion binding, myoblast differentiation, transcription regulatory region DNA binding, cell growth, epithelial-to-mesenchymal transition, regulation of MDA-5 signaling pathway, and regulation of RIG-I signaling pathway. Between group C and group A, the DEPs had the main biological functions of skeletal muscle fiber adaptation, smooth muscle contractile fiber, mitochondrial respiratory chain complex I assembly, vascular smooth muscle contraction, mitochondrial outer membrane permeabilization involved in programmed cell death, l -phenylalanine metabolic processes, sarcomere organization, negative regulation of B cell proliferation, and negative regulation of interleukin-5 production.
The DEPs were analyzed for their enrichment in KEGG pathways. KEGG analysis showed that the DEPs of group B versus group A were enriched in the pathways of cholesterol metabolism, complement and coagulation cascades, proteoglycans in cancer, PPAR signaling pathway, and fat digestion and absorption. The DEPs of group D versus group C were enriched in PPAR signaling, arachidonic acid metabolism, cholesterol metabolism, and proximal tubule bicarbonate reclamation. The DEPs of group D versus group B were enriched in RNA transport. The DEPs of group C versus group A were enriched in thermogenesis, retrograde endocannabinoid signaling, apoptosis-fly, and asthma .
The DEPs of group B (gut inflammation) versus group A (healthy individuals) and of group D (AS combined with gut inflammation) versus group C (AS) were aligned to identify their common DEPs. These were NMRAL1, ORM1, and APOA2. The only DEP shared in common by the group D (AS combined with gut inflammation) versus group B (gut inflammation) comparison and the group C (AS) versus group A (healthy individuals) comparison was NMRAL1). Finally, aligning these two sets with each other revealed that NMRAL1 was the DEP that identified group D. The Venn diagram below vividly demonstrates the process of screening DEPs .
To explore the inflammation-related function of NMRAL1 protein, we utilized the murine monocyte/macrophage cell line RAW264.7, an established model for inflammation studies. RT-qPCR results showed that, compared to the blank control group, the relative expression of NMRAL1 mRNA was significantly decreased in the model group treated with LPS ( P <0.001). The reduction in NMRAL1 mRNA expression was even more pronounced in the NMRAL1 siRNA-transfected macrophages ( P <0.0001), indicating successful transfection of NMRAL1 siRNA . ELISA results demonstrated that the expression levels of TNF-α, IL-1β and IL-23 were significantly increased in the model group compared to the blank control group ( P < 0.0001, P <0.001). Notably, IL-17 levels were measured following co-culture of LPS-stimulated RAW264.7 macrophage supernatants with Jurkat cells to enhance IL-17 detection. After NMRAL1 siRNA transfection, the expression levels of all these inflammatory cytokines, including IL-17, were significantly decreased in the model + transfection group ( P <0.0001, P <0.01, P <0.05) .
A growing body of evidence suggests a close relationship between intestinal inflammation and ankylosing spondylitis . Campos JF etal. recently discovered that patients with spondyloarthritis (SpA) have a high prevalence of microscopic gut inflammation, and fecal calprotectin levels can effectively identify microscopic inflammation, serving as a biomarker for microscopic intestinal inflammation in SpA patients . Based on the similar pathogenesis between inflammatory bowel disease and SpA, some scholars proposed the intestinal joint axis theory . Previous studies on AS biomarkers have primarily focused on serum proteomics, lipidomics, and metabolomics . The present study is the first to investigate the relationship between AS and gut inflammation through colon mucosal proteomics. In this study, we collected colon mucosal samples to compare the DEPs between AS and gut inflammation. A total of 20 patients were included in this study, with five patients each in the healthy group (group A), the gut inflammation group (group B), the AS group (group C), and the AS combined with gut inflammation group (group D). We identified a total of 81,141 peptides and 7039 proteins. Further analysis demonstrated abnormal protein expression in colon mucosa in groups B, C, and D relative to group A. We identified one DEP that distinguished group D from the other groups, suggesting that the DEPs identified in this study represent intergroup differences. By GO and KEGG analysis, we identified NMRAL1 as the DEP identifying AS combined with gut inflammation. NMRAL1, also called NmrA-like family domain-containing protein 1 or HSCARG, is an nicotinamide adenine dinucleotide phosphate (NADPH) sensor protein . The crystal structure of NMRAL1 consists of an N-terminal NmrA domain containing a Rossmann fold and a smaller C-terminal domain . NADPH is an allosteric regulator of the structure and function of NMRAL1. Under normal redox status, NMRAL1 binds to coenzyme NADPH via its Rossmann fold, which stabilizes NMRAL1 as an asymmetric dimer in the cytoplasm. Decrease in the NADPH/NADP+ ratio results in NMRAL1 existing mainly in its NADPH-free monomeric form . Previous studies have shown that NMRAL1 participates in a variety of biological processes, including redox homeostasis , innate immunity , cellular antiviral response and DNA damage response . For example, NMRAL1 could represses the cellular ROS generation by inhibiting mRNA and protein expression of p47phox (a subunit of NADPH oxidase), suggesting that NMRAL1 is a novel regulator regulating NADPH oxidase activity and ROS balance . In addition, NMRAL1 has a close biological relationship with cancer. Zang W et al. recently demonstrated the up-regulation of HSCARG exacerbates mammary tumorigenesis. They found that compared with wild type or heterozygous PyMT mice, PyMT transgenic mice with NMRAL1 gene knockout show delayed mammary tumor occurrence. Wang J et al. identified NMRAL1 as a potential novel risk gene for schizophrenia, regulated by the rs2270363 variant. This gene may confer susceptibility to schizophrenia by influencing neural development and modulating dendritic spine density. Inflammation serves as a critical pathogenic mechanism in AS, typically characterized by the dysregulated production of various inflammatory cytokines. Among these, TNF-α has been identified as potential serum biomarkers for AS . TNF-α is widely recognized as a central inflammatory cytokine in AS. Researchers have found that high concentrations of TNF-α can induce METTL14-mediated m6A modification of the ELMO1 3′ UTR, enhancing the migration of AS mesenchymal stem cells, thereby promoting the progression of AS through pathological osteogenesis . Liu B et al. recently found that anti-TNF-α therapy attenuate arthritis progression and alter the gut microbiota in proteoglycan-induced ankylosing spondylitis in mice. A mendelian randomization study found that IL-1β, a pro-inflammatory cytokine, plays a key role in the pathogenesis of AS . Recent studies have shown that AS patients present with significantly higher mean plasma levels of IL-1β when compared to healthy controls. Moreover, the IL-1β rs2853550 AG genotype has been identified as a genetic variant that heightens the risk of developing AS within the Chinese population . The IL-23/IL-17 axis plays an important role in both AS and gut inflammation. This axis mainly includes IL-23, the IL-23 receptor (IL-23R), signal transducer and activator of transcription 3 (STAT3), Janus kinase 2 (JAK2), and IL-17, among others . Several studies have found that serum levels of IL-17 and IL-23 are significantly elevated in AS patients, and the increase in IL-23 levels is more pronounced in patients with active disease . Qaiyum et al. observed that in the context of subclinical intestinal inflammation, activated Paneth cells are prone to producing IL-23, which further stimulates the production of IL-17 by immune cells such as Th17 cells, type 3 innate lymphoid cells (ILC3), and mucosa-associated invariant T (MAIT) cells, which are pivotal in the pathogenesis of spondyloarthritis. Our experimental results demonstrate that NMRAL1 protein plays a significant upstream regulatory role in the expression of key inflammatory cytokines associated with AS. Specifically, the downregulation of NMRAL1, either through LPS treatment or siRNA transfection, led to a notable increase in the levels of TNF-α, IL-1β, IL-17, and IL-23. Conversely, knocking down NMRAL1 resulted in a significant reduction in these cytokines, highlighting its potential as a critical modulator in AS-related inflammation and suggesting its value as a potential therapeutic target in managing the disease. Our study has certain limitations. Firstly, the number of cases included in our research is relatively small. A larger sample size would enhance the generalizability of our findings and reduce the potential impact of random variation. Future studies with larger sample sizes are needed to validate these results. Secondly, disease activity and duration may also have a relationship with the expression of NMRAL1 protein. Further analyzing the relationship between the NMRAL1 protein and the activity of AS and gut inflammation is needed. Additionally, we did not include serum samples from patients with other inflammatory or autoimmune diseases, which would have further validated the specificity of NMRAL1 as a biomarker for AS combined with gut inflammation. In conclusion, we used proteomic technology to identify DEPs in the colonic mucosa of patients with AS only, patients with gut inflammation only, patients with AS combined with gut inflammation, and healthy individuals. Among these, we identified NMRAL1 as a specific protein present in the intestinal mucosa of patients with AS complicated by gut inflammation, suggesting it could serve as a potential marker for this condition. Our functional studies using a murine macrophage cell model further demonstrated that NMRAL1 plays a role in regulating key inflammatory cytokines, highlighting its potential significance in the pathogenesis of AS. Moving forward, we plan to expand our sample size and conduct more in-depth investigations into the functional role of NMRAL1, with the goal of providing novel insights and potential therapeutic strategies for the diagnosis and treatment of AS.
S1 Fig Principal component analysis. This Principal Component Analysis (PCA) plot represents the proteomic profiles of colonic mucosal tissues across four groups: healthy individuals (Group A), patients with gut inflammation only (Group B), patients with AS only (Group C), and patients with AS combined with gut inflammation (Group D). PC1 and PC2 explain 0.28 and 0.12 of the total variance, respectively. The clear separation between the groups along the principal components indicates significant differences in proteomic profiles. (PDF) S1 Table Protein identification results. This table provides detailed information on the proteins identified in the study. (XLSX) S2 Table Peptides identification results. This table provides detailed information on the peptides identified in the study. (XLSX) S3 Table Protein differential analysis list. This Table summarizes the proteins identified as upregulated or downregulated, with upregulation marked in yellow and downregulation in green. The table also lists the fold change values for these differentially expressed proteins in each group. (XLSX)
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Impact of untreated preoperative asymptomatic bacteriuria in patients undergoing holmium laser enucleation of prostate | 502c692a-8b38-4f47-9fb9-49479efd689c | 11785438 | Surgical Procedures, Operative[mh] | Asymptomatic bacteriuria (ASB) has led to debate between clinicians within urology. Although some advocate treating ASB before any urological interventions, others are questioning this routine practice, calling for closer investigations and a more robust evidence base. The term ASB refers to the isolation of bacterial species in significant counts (≥10 5 cfu/ml) from a clean catch urine specimen of a patient without any urinary symptoms or acute signs. Since the discovery of ASB, its clinical significance and management has been uncertain. Published medical literature and guidelines (European Association of Urology [EAU] 2022) focus on positive interventions especially before endourological procedures such as prostate surgery. , However, most of the evidence used to support the guidelines dates to the 1980s, before the routine use of antibiotics on induction. No guidelines clearly define the timing or duration of treatment for ASB. Some studies suggested starting treatment 72h before the intervention although treating ASB does not prevent patients from being recolonised. , Such early treatment may, therefore, seem excessive and allow the opportunity for further infection to develop before the procedure with increased antimicrobial resistance. ASB is common in the general population among adults. Prevalence of ASB varies with age, gender and sexual activity. In elderly men, the prevalence of ASB is reported to be between 4% and 7%. Major contributing factors include prostatic enlargement leading to bladder outlet obstruction, resulting in incomplete bladder emptying and urinary stasis. Many patients with bladder outlet obstruction are managed with an indwelling catheter for adequate bladder drainage while awaiting their surgical intervention. Inevitably patients with long-term indwelling catheters will have ASB, secondary to colonisation of the catheter. Multiple studies have emphasised that the longer the duration of catheterisation, the higher the risk of developing catheter-associated bacteriuria. The incidence of bacteriuria in patients with an indwelling catheter is 3–7% per day. After chronic catheterisation (defined as 28 days or more), almost 100% (98.4%) of patients will have bacteriuria and 77% would have polymicrobial bacteriuria. The EAU guidelines (2022) on urological infections suggest that before endourological interventions on the urinary tract, especially where there is breach of the mucosa, a urine culture should be taken, and in the case of ASB preoperative treatment is advised. Several randomised controlled trials have compared the effect of antibiotic treatment with no treatment in urological procedures such as transurethral resection of the prostate (TURP) and of bladder tumour (TURBT). Patients given antibiotics before surgery had reduced postoperative complications, such as fever, symptomatic urinary tract infection (UTI) and septicaemia. However, the studies quoted in the guidelines were all performed in the 1980s and compare patients who did not receive any antibiotics at all perioperatively. – Contemporary practice is to administer periprocedural antibiotic prophylaxis in major urological surgeries because it has been shown to reduce postoperative infectious complications. , However, very little research has been conducted regarding whether periprocedural prophylactic antibiotics are effective in reducing postinfective complications in patients who did not receive preoperative treatment for ASB. This raises the question – should patients with ASB undergoing endourological procedures receive treatment preoperatively, or is perioperative antimicrobial prophylaxis adequate? It is our practice not to treat ASB preoperatively with antibiotics. This retrospective study was therefore designed to determine if patients with untreated ASB before undergoing holmium laser enucleation of prostate (HoLEP) had a higher risk of developing postoperative infective complications compared with patients with no bacterial growth in the urine before surgery.
A retrospective study was conducted between 2015 and 2020 at Southend University Hospital (now part of Mid and South Essex NHS Trust), UK. This was approved as an audit by the hospital governance committee. Some 447 consecutive patients undergoing HoLEP were selected. Four patients with ASB who received antimicrobial therapy before surgery were excluded. Data collection was performed by using the hospital database. Full clinical records were reviewed. The information was categorised into indication of the procedure including lower urinary tract symptoms (LUTs) or urinary retention (patients with indwelling catheters), preoperative urine cultures indicating ASB or no bacterial growth and infective postoperative complications. Complications were further subcategorised into patients being admitted with urosepsis or those requiring only oral antibiotics for UTI without fever, epididymo-orchitis, haematuria and prostatitis. By using an integrated system with the primary care records available, patients who developed postinfective complications treated with oral antibiotics in the community were also identified. All patients received intravenous antibiotics at induction of anaesthesia guided by urine culture sensitivities or as per the local trust protocols. Local trust protocol was gentamicin (2mg/kg); co-amoxiclav was added for those patients with an indwelling catheter at the time of surgery. Postoperative oral antibiotics (3 days of trimethoprim, or co-amoxiclav if trimethoprim contraindicated) were prescribed as per the operating surgeon’s discretion to a small number within both groups of patients.
In total 447 patients undergoing HoLEP were identified, out of whom four were excluded because they were prescribed oral antibiotics preoperatively by other clinicians. Indications for HoLEP are outlined in . A total of 443 patients were studied . There was no significant difference in spread of relevant comorbidities (e.g. diabetes) between the two groups. Some 125 patients were found to have ASB before surgery. Those with an indwelling urethral catheter (urinary retention) had a higher percentage of ASB at 84% (105 of 125) compared with those without a catheter (LUTS) at 16% (20 of 125) . In patients with an indwelling urethral catheter and ASB, 61 grew a single organism and 44 had mixed growth. In the LUTS group (patients with no catheter and ASB), 16 had a single organism in their urine specimen and 4 had a mixed growth. No urosepsis occurred in the ASB group compared with 2 in the remaining 318 patients (0.6%) with no growth on preoperative urine culture. Of the two patients who developed urosepsis, one had an indwelling urethral catheter for urinary retention before surgery. Both patients were admitted and treated with parenteral antimicrobial therapy with good recovery . A total of 29 (7%) patients of the whole cohort were treated with oral antibiotics for symptomatic postoperative complications: 8 (6.4%) in those with ASB and 21 (7%) in patients with no bacterial growth on urine culture preoperatively. The most common condition, for which 24 of the 29 patients were given oral antibiotics, was suspected UTI. However, only 11 of 24 (37.9% of the 29 patients treated with oral antibiotics) patients had a positive urine culture and the 2 patients admitted with visible haematuria and suspected UTI had no growth on their subsequent urine cultures. Three (10.3%) patients had clinically diagnosed epididymo-orchitis and one patient was treated for prostatitis. All patients were treated with oral antibiotics with no further complications. Patients with ASB requiring postoperative antibiotics did not grow similar bacteria on the postoperative urine culture . In the 125 patients with ASB, 7 in 105 (7%) in the catheterised group required oral antibiotics for symptomatic infections after surgery compared with 1 in 20 (5%) patients in the LUTS category. For patients with no preoperative bacterial growth on urine culture, 8 (9%) with urinary retention and 13 (6%) with LUTS developed infective complications. As shown by the results, ASB did not predict for postoperative infective complications (urosepsis odds ratio [OR]: 0.50 p =0.66; oral antibiotics OR: 0.97 p =0.93).
In this retrospective study, preoperative ASB was not associated with higher rates of postoperative urosepsis or positive urine culture results among symptomatic patients undergoing HoLEP. A similar percentage of patients in both cohorts developed infective complications, such as UTI. These data therefore seem to suggest that there is no benefit in reducing postoperative infective complications in treating ASB before HoLEP. The EAU 2022 guidelines on urological infections advise treatment of ASB preoperatively, highlighting four studies as the evidence base. gives a summary of the studies quoted. – This study is the first to question the recommendations of treating patients with ASB before HoLEP and highlight that, in our cohort, ASB did not affect postoperative infection rates. In this study, all patients undergoing HoLEP received intravenous perioperative antibiotics at induction of anaesthesia. As stated by the EAU and American Urological Association guidelines for urological infections, there is a high level of evidence that single-dose prophylactic antibiotics reduce the rate of infectious postoperative complications in patients undergoing TURP. , As demonstrated in this study, perioperative prophylaxis with single-dose antibiotics is just as effective for patients with ASB in reducing postoperative complications. Therefore, pretreating patients with ASB before HoLEP surgery does not seem to be of benefit from an infective outcomes perspective. The further burden placed on health services with having to treat ASB patients and re-culture urine is also a significant factor to consider. Screening patients for bacteriuria before diagnostic and therapeutic procedures would, however, still be important because it would guide antimicrobial coverage in conjunction with the procedure. The choice of antibiotics would obviously depend on local pathogen prevalence and type of procedure, but a urine culture would help identify multiresistant organisms. This study has raised an important point in the management of ASB in patients undergoing HoLEP. Identifying other surgical procedures whereby the postoperative outcome is unchanged by not treating ASB will not only improve cost-effectiveness, but also result in more judicious use of antimicrobials, meeting the goals of antimicrobial stewardship. As highlighted by the ‘Choosing Wisely’ campaign, not treating ASB in most circumstances is recommended, given concerns about the harms of antimicrobial use, such as emergence of antimicrobial resistance, adverse drug events and increases in Clostridium difficile infection because treating ASB is without any demonstrated value. Moreover, there could be a reduction in on-the-day cancellations from patients found to have ASB. The EAU guidelines (2022) reference research performed before the existence of HoLEP as a surgical option and focus mainly on TURP, whereas now a multitude of surgical options are available for treating bladder outlet obstruction. The studies highlighted in these guidelines do have a number of limitations. Three of the studies have poor sample sizes, with fewer than 192 participants (112–192) across both randomisation arms. Cafferkey et al do have a larger sample size (565), but 206 of these patients had sterile urine preoperatively and therefore part of these data cannot be reliably applied to the ASB cohort and may have skewed the presented results. Whether the procedure performed transurethrally leads to a difference in infective outcome rate is an area not fully researched and limited robust evidence exists regarding this. Although, given that some bladder outlet obstruction surgeries are now becoming more ‘minimally invasive’, it could be inferred that these provide lower risk of introducing infective pathogens due to limited breaching of the mucosal barrier. To our knowledge, this is the first study conducted to assess the impact of untreated preoperative ASB in patients undergoing HoLEP. Although not a randomised prospective study, a large cohort size has been evaluated, reflecting clinical practice over a 5-year period. Study limitations We acknowledge a few limitations with our work. Factors suggested to have an impact on postoperative complication rate include patient comorbidities, laser time for the HoLEP and duration of catheterisation after surgery. These data are not accurately recorded for our cohort and so formal analysis of the impact of this could be an area for further prospective research. Some patients received a short (5-day) course of antibiotics after the procedure, no standardised criteria were followed as to which patients received antibiotics after the procedure because this was based on clinician preference. Only patients undergoing HoLEP were included in this study. Further prospective studies should be conducted to assess whether similar findings will be found in patients undergoing other bladder outlet obstruction procedures such as TURP. Our findings raise important issues regarding antimicrobial use and stewardship, and highlight a gap in current, up-to-date knowledge and evidence for clinical practice.
We acknowledge a few limitations with our work. Factors suggested to have an impact on postoperative complication rate include patient comorbidities, laser time for the HoLEP and duration of catheterisation after surgery. These data are not accurately recorded for our cohort and so formal analysis of the impact of this could be an area for further prospective research. Some patients received a short (5-day) course of antibiotics after the procedure, no standardised criteria were followed as to which patients received antibiotics after the procedure because this was based on clinician preference. Only patients undergoing HoLEP were included in this study. Further prospective studies should be conducted to assess whether similar findings will be found in patients undergoing other bladder outlet obstruction procedures such as TURP. Our findings raise important issues regarding antimicrobial use and stewardship, and highlight a gap in current, up-to-date knowledge and evidence for clinical practice.
The presence of ASB in patients undergoing HoLEP does not require preoperative antibiotics. However, it is important that clinicians give adequate perioperative antibiotics guided by local policy and urine culture sensitivities. Judicious use of antibiotics is advised, especially considering increasing prevalence of antimicrobial resistance. Although current guidelines advocate treatment of ASB before urological procedures, further research is required to establish whether this is necessary in the current era.
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Current Practices and Evidence of Aspirin Usage in Microvascular Surgery: A Systematic Review and Meta‐Analysis | 1ff97ef5-e5bb-4319-a125-6ea4adb20a5f | 11772259 | Microsurgery[mh] | Introduction Microvascular surgery is a broad field of plastic surgery that includes various disciplines related to a multitude of anatomical regions (Kagel ). In recent years, there have been significant advancements to surgical acumen in this realm, as new technologies and techniques have been developed to optimize patient outcomes. To do so, the avoidance of complications is paramount. A common concern, in the postoperative time period, is the formation of clots at the site of microvascular anastomose which can result in the necrosis of the entire flap. The incidence of microvascular thrombosis depends on a variety of elements, such as patient factors, wound‐related factors, the presence of active cancer, the degree of vessel damage, and so forth. A study conducted on thrombosis formation in microsurgical breast reconstruction noted that thrombotic events occurred in 1.5%–6.2% of breast reconstruction cases with 75% of these events leading to flap failure (Amy et al. ). Similarly, a different study investigating thrombosis in microvascular tissue transfer in head and neck surgery found a rate of 8%–14% with many of these events leading to flap failure (Brands et al. ). These statistics are causes for concern, prompting surgeons to find ways to decrease the risk of thrombosis. Aside from meticulous microvascular technique, microsurgeons often resort to some form of pharmacological risk mitigation, such as anticoagulation or use of antiplatelet agents. Pharmacologic regimens postoperatively vary depending on surgeon preference. A survey conducted in 2023 showed that 66.3% of microvascular surgeons preferred to give aspirin immediately postoperatively (Philips et al. ). Similar or higher rates of aspirin usage are seen in other surgical specialties (Korinth, Gilsbach, and Weinzierl ; Sharda, Fatovic, and Bauer ). The widespread adoption of aspirin postoperatively primarily stems from its well‐known mechanism of preventing platelet aggregation, suggesting a possibility to reduce thrombotic events (Vane and Botting ; Arif ). Several studies have validated aspirin's usage in preventing vascular events, such as the ASPIRE trial (Brighton et al. ) and the WARFASA trial (Becattini et al. ), both showing net clinical benefit in preventing venous thromboembolism (VTEs)/recurrent VTEs. However, despite these studies showing the benefit of aspirin, there has not been a consensus in the literature in regard to the benefit of aspirin in the context of microvascular surgery. With conflicting schools of thought related to the default administration of aspirin in microvascular plastic surgery, there is a lack of synthetization of current research investigating its advantages and disadvantages. In this systematic review, we hope to (1) present, in a thorough manner, the current evidence on aspirin usage postoperatively, (2) identify the benefits/harms of aspirin usage, and (3) provide recommendations to surgeons, patients, researchers, and other members of the healthcare team on the management of patients after microvascular surgery. We aim to discuss the implications of these findings and provide guidance in clinical decision‐making.
Methods 2.1 Search Strategy Our initial search identified 263 total articles, 211 from PubMed and 52 from other resources such as Google Scholar and SCOPUS. Our search strategy is described in the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines (Figure ). Search terms utilized were “aspirin,” “microvascular surgery,” “microsurgery,” “plastic surgery,” “ASA,” and “acetylsalicylic acid.” These terms were combined with one or more text words, such as “AND/OR” and “outcomes” to increase search yield. Articles were initially screened based on relevancy related to their title. A total of 15 duplicate articles were found and removed. The remaining 248 articles were then scrutinized based on the exclusion criteria as follows: pediatric patients (< 18 years old), studies with less than 50 patients/participants, animal studies, conservative management/no surgical intervention, review articles, letters to the editor, book chapters, and other meta‐analyses. Studies were then extracted for relevant information related to the aims of the project. We primarily sought to assess the outcomes, benefits/drawbacks, and recommendations provided in the literature related to aspirin usage postoperatively on patient complication rates. Secondary aims included aspirin regimens, patient demographics, and success/failure rates of surgery. 2.2 Data Extraction We surveyed the literature using the above‐mentioned strategy in order to extract relevant information from qualifying articles. Prior to extraction, articles were screened based on title, abstract, and then full textual review as well as subject to comparison to the exclusion criteria to evaluate for inclusion. Study information related to aspirin recommendations is shown in Table : (1) author and year, (2), title of the study, (3) study type, (4) procedure performed for patients included in the study, and (5) recommendations regarding the continuation or discontinuation of aspirin. Perioperative antiplatelet regimens are included in Table : (1) patient groups, (2) aspirin dosing, (3) timing of aspirin administration, (4) length of administration, and (5) other relevant anticoagulants. Outcome measures that were collected included: (1) number of patients in each study, (2) sex of patients, (3) postoperative complications, and (4) follow‐up characteristics. During the primary extraction, other variables were collected to further organize the studies, such as study aim, AHA level of evidence, limitations, recommendations, and conclusions. Studies were grouped based on the comparison of aspirin with placebo or a respective “non‐aspirin” equivalent regimen. Recommendations were recorded and integrated into analysis. References of the articles included in the final extraction were screened. 2.3 Statistical Analysis Following the extraction of relevant information for the aforementioned variables, we sought to compare the patients in the experimental group (those receiving aspirin) to the control group (those not receiving aspirin). To do so, flap type of procedure was compared using Fisher's exact test with a Holm p ‐value adjustment for multiple hypothesis testing. For the endpoints of total complications, total flap loss, thrombosis, and hematoma, risk ratios (RRs) were pooled and analyzed via the Mantel–Haenszel method. Statistical heterogeneity was calculated using Cochran's Q test and I 2 Index (West et al. ). All meta‐analysis was completed using RStudio and the R package meta (R Core Team ; Balduzzi, Rücker, and Schwarzer ).
Search Strategy Our initial search identified 263 total articles, 211 from PubMed and 52 from other resources such as Google Scholar and SCOPUS. Our search strategy is described in the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines (Figure ). Search terms utilized were “aspirin,” “microvascular surgery,” “microsurgery,” “plastic surgery,” “ASA,” and “acetylsalicylic acid.” These terms were combined with one or more text words, such as “AND/OR” and “outcomes” to increase search yield. Articles were initially screened based on relevancy related to their title. A total of 15 duplicate articles were found and removed. The remaining 248 articles were then scrutinized based on the exclusion criteria as follows: pediatric patients (< 18 years old), studies with less than 50 patients/participants, animal studies, conservative management/no surgical intervention, review articles, letters to the editor, book chapters, and other meta‐analyses. Studies were then extracted for relevant information related to the aims of the project. We primarily sought to assess the outcomes, benefits/drawbacks, and recommendations provided in the literature related to aspirin usage postoperatively on patient complication rates. Secondary aims included aspirin regimens, patient demographics, and success/failure rates of surgery.
Data Extraction We surveyed the literature using the above‐mentioned strategy in order to extract relevant information from qualifying articles. Prior to extraction, articles were screened based on title, abstract, and then full textual review as well as subject to comparison to the exclusion criteria to evaluate for inclusion. Study information related to aspirin recommendations is shown in Table : (1) author and year, (2), title of the study, (3) study type, (4) procedure performed for patients included in the study, and (5) recommendations regarding the continuation or discontinuation of aspirin. Perioperative antiplatelet regimens are included in Table : (1) patient groups, (2) aspirin dosing, (3) timing of aspirin administration, (4) length of administration, and (5) other relevant anticoagulants. Outcome measures that were collected included: (1) number of patients in each study, (2) sex of patients, (3) postoperative complications, and (4) follow‐up characteristics. During the primary extraction, other variables were collected to further organize the studies, such as study aim, AHA level of evidence, limitations, recommendations, and conclusions. Studies were grouped based on the comparison of aspirin with placebo or a respective “non‐aspirin” equivalent regimen. Recommendations were recorded and integrated into analysis. References of the articles included in the final extraction were screened.
Statistical Analysis Following the extraction of relevant information for the aforementioned variables, we sought to compare the patients in the experimental group (those receiving aspirin) to the control group (those not receiving aspirin). To do so, flap type of procedure was compared using Fisher's exact test with a Holm p ‐value adjustment for multiple hypothesis testing. For the endpoints of total complications, total flap loss, thrombosis, and hematoma, risk ratios (RRs) were pooled and analyzed via the Mantel–Haenszel method. Statistical heterogeneity was calculated using Cochran's Q test and I 2 Index (West et al. ). All meta‐analysis was completed using RStudio and the R package meta (R Core Team ; Balduzzi, Rücker, and Schwarzer ).
Results 3.1 Electronic Search Yield PRISMA guidelines for this search (Figure ) describe the number of articles at each stage of evaluation. An initial 263 articles were identified. After scrutiny via exclusion criteria, 244 articles were excluded and four articles remained. These four articles (Liu et al. ; Zhou et al. ; Enajat et al. ; Lighthall et al. ) provided direct comparison between aspirin regimens and respective “control regimens” which did not include aspirin. 3.2 Aspirin Recommendations Table displays current recommendations for aspirin prescription when compared to other anticoagulation regimens. A majority of the studies included in our analysis involved some form of reconstructive flap, with deep inferior epigastric perforator (DIEP) flaps being a common theme, amongst all studies. All four of the studies included in our analysis found no significant difference in outcomes and complication rates between regimens that include aspirin and those that do not. Zhou et al. ( ) and Enajat et al. ( ) found that aspirin increased hematoma formation, while Lighthall et al. ( ) noted a generalized increase in complication rate. All four studies recommended against the default administration of aspirin postoperatively due to the lack of efficacy at follow‐up. 3.3 Antiplatelet Regimens Antiplatelet regimens are displayed in Table . All of the studies broke the patient population into two groups: a group receiving aspirin and a group not receiving aspirin. All patients received aspirin solely postoperatively. The most common aspirin dosage used was 40 mg. The average length of time aspirin was used was 22.75 days postoperatively (SD ± 16.5 days). Other postoperative VTE prophylaxis compounds used in these studies included enoxaparin, heparin, and nadroparin; however, if present, these other compounds were held constant across both experimental and control groups and were accounted for by the studies in their respective analyses. 3.4 Patient Characteristics Across the four studies, a total of 1196 patients were included in our analysis. These characteristics are highlighted in Table . There were 637 patients who received aspirin (considered the experimental group, Group A), and 559 patients who did not (and were part of the control group, Group B). The average age of patients receiving aspirin was 51.7 versus 53.7 years in the non‐aspirin group. In terms of gender distribution, the male to female ratio in the aspirin group was 0.33:1, while the male‐to‐female ratio in the non‐aspirin group was 0.55:1. The type of procedure performed in these studies was categorized into six over‐arching groups: DIEP, transverse rectus abdominis myocutaneous (TRAM), superficial inferior epigastric artery (SIEA), fibula, anterolateral thigh flap, and radial forearm flaps. DIEP flaps were found to be significantly associated with aspirin usage (288, 45.2% vs. 167, 30%, p < 0.0001). TRAM flaps ( n = 72, 11.3% vs. n = 68, 12.2%, p = 0.47), anterolateral thigh flaps ( n = 53, 8.3% vs. n = 64, 11.4%, n = 100, 15.7% vs. n = 99, 17.7%, respectively, p = 0.12), radial forearm flaps ( n = 100, 15.7% vs. n = 99, 17.7%, p = 0.42), and SIEA flaps ( n = 7, 1.1% vs. n = 0, 0%, p = 0.07) were not found to be significantly correlated with aspirin or with the control group. Patients undergoing fibula flaps were found to significantly use aspirin less often ( n = 108, 17% vs. n = 130, 23.3%, p = 0.011) when compared to the control group. 3.5 Complications and Follow‐Up A total of 317 complications were noted across all patients. Patients receiving aspirin had 185 complications noted, while those without aspirin had 132 noted. On meta‐analysis, there was no significant difference between the groups with regard to overall complication rate. The pooled RR was calculated at 1.13 (random‐effects model, 95% CI 0.78–1.63, Figure ). Moderate heterogeneity was noted between the studies ( I 2 = 36%, p = 0.20, Figure ). On analysis of specific complications of interest, there was no significant difference between the groups with regard to total flap loss or thrombosis. Three studies reported incidence of total flap loss. The pooled RR was calculated at 0.96 (random‐effects model, 95% CI 0.44–2.08, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.77, Figure ). Two studies reported incidence of thrombosis. For thrombosis, the pooled RR was calculated at 0.94 (random‐effects model, 95% CI 0.14–6.47, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.64, Figure ). A significant difference was identified between the groups with regard to hematoma formation. All four studies reported incidence of hematoma formation. The pooled RR was calculated at 1.70 (random‐effects model, 95% CI 1.19–2.44, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.92, Figure ). The rates of minor complications including partial flap necrosis, skin necrosis, and seroma are summarized in Table . One study reported death in three patients receiving postoperative aspirin (Table ). No other deaths were reported. In terms of follow‐up, patients receiving Acetylsalicylic acid (ASA) were followed for a longer amount of time (237.6 vs. 115.2, p < 0.05), however, both groups had similar length of stay in the hospital (4.6 vs. 4.0 days), indicating longer follow‐up outpatient. In terms of final follow‐up, a majority of patients in both groups achieved therapeutic goals at follow‐up (90.2% vs. 88.6%).
Electronic Search Yield PRISMA guidelines for this search (Figure ) describe the number of articles at each stage of evaluation. An initial 263 articles were identified. After scrutiny via exclusion criteria, 244 articles were excluded and four articles remained. These four articles (Liu et al. ; Zhou et al. ; Enajat et al. ; Lighthall et al. ) provided direct comparison between aspirin regimens and respective “control regimens” which did not include aspirin.
Aspirin Recommendations Table displays current recommendations for aspirin prescription when compared to other anticoagulation regimens. A majority of the studies included in our analysis involved some form of reconstructive flap, with deep inferior epigastric perforator (DIEP) flaps being a common theme, amongst all studies. All four of the studies included in our analysis found no significant difference in outcomes and complication rates between regimens that include aspirin and those that do not. Zhou et al. ( ) and Enajat et al. ( ) found that aspirin increased hematoma formation, while Lighthall et al. ( ) noted a generalized increase in complication rate. All four studies recommended against the default administration of aspirin postoperatively due to the lack of efficacy at follow‐up.
Antiplatelet Regimens Antiplatelet regimens are displayed in Table . All of the studies broke the patient population into two groups: a group receiving aspirin and a group not receiving aspirin. All patients received aspirin solely postoperatively. The most common aspirin dosage used was 40 mg. The average length of time aspirin was used was 22.75 days postoperatively (SD ± 16.5 days). Other postoperative VTE prophylaxis compounds used in these studies included enoxaparin, heparin, and nadroparin; however, if present, these other compounds were held constant across both experimental and control groups and were accounted for by the studies in their respective analyses.
Patient Characteristics Across the four studies, a total of 1196 patients were included in our analysis. These characteristics are highlighted in Table . There were 637 patients who received aspirin (considered the experimental group, Group A), and 559 patients who did not (and were part of the control group, Group B). The average age of patients receiving aspirin was 51.7 versus 53.7 years in the non‐aspirin group. In terms of gender distribution, the male to female ratio in the aspirin group was 0.33:1, while the male‐to‐female ratio in the non‐aspirin group was 0.55:1. The type of procedure performed in these studies was categorized into six over‐arching groups: DIEP, transverse rectus abdominis myocutaneous (TRAM), superficial inferior epigastric artery (SIEA), fibula, anterolateral thigh flap, and radial forearm flaps. DIEP flaps were found to be significantly associated with aspirin usage (288, 45.2% vs. 167, 30%, p < 0.0001). TRAM flaps ( n = 72, 11.3% vs. n = 68, 12.2%, p = 0.47), anterolateral thigh flaps ( n = 53, 8.3% vs. n = 64, 11.4%, n = 100, 15.7% vs. n = 99, 17.7%, respectively, p = 0.12), radial forearm flaps ( n = 100, 15.7% vs. n = 99, 17.7%, p = 0.42), and SIEA flaps ( n = 7, 1.1% vs. n = 0, 0%, p = 0.07) were not found to be significantly correlated with aspirin or with the control group. Patients undergoing fibula flaps were found to significantly use aspirin less often ( n = 108, 17% vs. n = 130, 23.3%, p = 0.011) when compared to the control group.
Complications and Follow‐Up A total of 317 complications were noted across all patients. Patients receiving aspirin had 185 complications noted, while those without aspirin had 132 noted. On meta‐analysis, there was no significant difference between the groups with regard to overall complication rate. The pooled RR was calculated at 1.13 (random‐effects model, 95% CI 0.78–1.63, Figure ). Moderate heterogeneity was noted between the studies ( I 2 = 36%, p = 0.20, Figure ). On analysis of specific complications of interest, there was no significant difference between the groups with regard to total flap loss or thrombosis. Three studies reported incidence of total flap loss. The pooled RR was calculated at 0.96 (random‐effects model, 95% CI 0.44–2.08, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.77, Figure ). Two studies reported incidence of thrombosis. For thrombosis, the pooled RR was calculated at 0.94 (random‐effects model, 95% CI 0.14–6.47, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.64, Figure ). A significant difference was identified between the groups with regard to hematoma formation. All four studies reported incidence of hematoma formation. The pooled RR was calculated at 1.70 (random‐effects model, 95% CI 1.19–2.44, Figure ). Low heterogeneity was noted between the studies ( I 2 = 0%, p = 0.92, Figure ). The rates of minor complications including partial flap necrosis, skin necrosis, and seroma are summarized in Table . One study reported death in three patients receiving postoperative aspirin (Table ). No other deaths were reported. In terms of follow‐up, patients receiving Acetylsalicylic acid (ASA) were followed for a longer amount of time (237.6 vs. 115.2, p < 0.05), however, both groups had similar length of stay in the hospital (4.6 vs. 4.0 days), indicating longer follow‐up outpatient. In terms of final follow‐up, a majority of patients in both groups achieved therapeutic goals at follow‐up (90.2% vs. 88.6%).
Discussion Our study highlights several interesting points about the widely adopted and trusted practice of utilizing aspirin after microvascular surgery. We noted that there was significant variance in the prescribing regimen of aspirin, with no consistent dosage or length across the literature, though the most commonly used dose was 40 mg, which was surprising given that the usual dose of ASA is 81 or 325 mg. Two studies (Liu et al. ; Enajat et al. ) in our analysis utilized additional compounds in their postoperative anticoagulation regimens, in addition to aspirin. Although these compounds were consistent across both the experimental and control groups, there may be a confounding effect present. The patients receiving aspirin were not significantly different from those that did not receive it in terms of preoperative characteristics; however, in terms of type of operation, DIEP flaps were associated with greater odds of using perioperative aspirin than others. DIEP flaps were the most common form of procedure performed overall, possibly related to the greater utility of microvascular surgery in breast reconstruction, as opposed to other indications. Postoperatively, we found that aspirin did not have a protective effect on patient course in terms of reducing complications. In fact, the rates of most complications were not significantly different, with the exception of hematomas, which were more common in the aspirin group. Though follow‐up characteristics (length of follow‐up and the rate of achieving therapeutic goals) and mortality rates were not significantly different, our results provide an important commentary into the practice of adding aspirin into the perioperative regimen of patients undergoing microvascular surgery. In the present meta‐analysis, we provide unique insight into the perceived benefits of aspirin. Though aspirin utilization is known to increase hematoma formation, we provide evidence of its reduced utility in preventing thrombosis, complete or partial flap necrosis, and seroma formation. Aspirin is a common adjunct to standard VTE prophylaxis in many surgical settings, offering promising results for both intraoperative (Rothweiler et al. ) and possible postoperative settings, including in the plastic surgery literature. However, there is significant discourse on the true validity of aspirin in these postoperative settings. Not only is this a discussion in plastic surgery, but other surgical specialties have also noted the seemingly under‐powered rationale behind including aspirin consistently in a postoperative regimen (Chen and Hu ; Biccard et al. ), with several studies reporting little to no effect of aspirin in postoperative settings. All four of the studies included in our analysis were unable to find significant improvement in patient course with addition of aspirin. Liu et al. ( ) and Zhou et al. ( ) analyzed the utility of aspirin in the context of a broader anticoagulation regimen and saw that aspirin did not significantly enhance the function of the other anticoagulants, indicating a lack of a synergistic effect. The lack of improvement in outcomes in combined regimens reduces the utility of aspirin as an independent agent and an adjunct to other anticoagulation regimens. While this finding was echoed in the papers by Enajat et al. ( ) and Lighthall et al. ( ), in the setting of aspirin alone, these two studies also endorsed a higher complication rate, especially bleeding and hematomas, highlighting the dangers of aspirin in the context of microvascular surgery. When characterizing the current usage of aspirin perioperatively, we noted that there was a wide range of included dosing regimens, which is consistent with what is reported in the literature. Though dosing schemes vary, there is no reported benefit of utilizing a larger or smaller dose, with both seeming to be equal in terms of complications or protective effect (Karamanos et al. ). There was also significant variance in the length of aspirin prescription within our study, with no significant commentary in the literature on longer or shorter dosing for improved outcomes. This may be related to reports that aspirin has to achieve rates of effectiveness at doses as low as 40 mg (Buchanan and Hirsh ), indicating that large doses may not necessarily equate to improved effectiveness in postsurgical settings. Though the exact effective dose varies based on the etiology treated, there is no established effective dose postsurgically. Aspirin, in our study, did not significantly improve complication rates and actually increased rates of postoperative hematoma, when compared to the aspirin‐naïve group. Aspirin's reported tendency to increase postoperative bleeding is one of the biggest concerns with its utilization (Ling et al. ; Hood et al. ). It may also explain this increased rate, as this is not a finding unique to our study (Hood et al. ). Not only is aspirin noted to increase rates of bleeding when taken postoperatively, but Hood et al. ( ) found that those who took aspirin preoperatively had increased rates of bleeding postoperatively. This unique finding provides important context into the usage of aspirin perioperatively, as our study recommends against the usage of aspirin in the preoperative period as well, not only postoperatively. In terms of long‐term success in surgical procedures, aspirin did not decrease flap failure rates, with no article in our study showing those receiving aspirin as having lower rates of complications. In both our study and reported literature, there is no compelling evidence for the utilization of aspirin to increase success rates of microvascular surgery. Though there are several reports on the promising safety profile of aspirin and its outcomes (Raggio et al. ; Lippi and Cervellin ), there are no studies that indicate aspirin promotes long‐term success in the plastic surgery literature. Based on the available evidence, we recommend against the use of ASA in microvascular surgery. Further randomized clinical trials are needed to fully explore this effect. 4.1 Limitations There are several limitations associated with this literature review. One limitation is the potential for selection bias as only studies that matched our inclusion criteria were included in our analysis. Additionally, there was significant variance in the reporting of data between the articles in terms of postoperative outcomes. Another limitation includes the extrapolation of these recommendations to children; aspirin usage in this population is confounded by the risk of complications, such as Reye's syndrome. Our study comments on the utility of aspirin in microvascular surgery in the mentioned surgery types in adult patients, representing an exclusive group in plastic surgery. To fully optimize long‐term anticoagulation needs for a patient, a multidisciplinary team should be utilized on a case‐by‐case basis to promote custom treatment plans for patients undergoing surgery.
Limitations There are several limitations associated with this literature review. One limitation is the potential for selection bias as only studies that matched our inclusion criteria were included in our analysis. Additionally, there was significant variance in the reporting of data between the articles in terms of postoperative outcomes. Another limitation includes the extrapolation of these recommendations to children; aspirin usage in this population is confounded by the risk of complications, such as Reye's syndrome. Our study comments on the utility of aspirin in microvascular surgery in the mentioned surgery types in adult patients, representing an exclusive group in plastic surgery. To fully optimize long‐term anticoagulation needs for a patient, a multidisciplinary team should be utilized on a case‐by‐case basis to promote custom treatment plans for patients undergoing surgery.
Conclusion Using aspirin in microvascular surgery is a popular intervention that is done to prevent thrombosis of microvascular anastomoses and subsequent flap failure. However, there is a lack of consensus regarding this topic, as there is a dearth of evidence‐based commentary regarding the effectiveness of ASA. Our study surveys the available literature to showcase that the routine usage of aspirin perioperatively is not indicated, with comparable rates of thrombosis when compared to controls. Not only does aspirin not confer a significant protective effect, but it may actually increase bleeding and hematoma formation postoperatively. Thus, we recommend against the blanket use of ASA in microvascular surgery. Until further evidence is available, its use should be considered on a case‐by‐case basis.
Conceptualization: Andrei Odobescu and Faraaz Azam. Data curation: Faraaz Azam. Writing – original draft preparation: Faraaz Azam. Writing – review and editing: Faraaz Azam, Cyril Awaida, Anca Dogaroiu, and Andrei Odobescu. All authors have read and agreed to the published version of this manuscript.
This study was written in compliance with our institutional ethical review board requirements.
The authors declare no conflicts of interest.
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Immune checkpoint inhibitors-associated thrombosis in patients with lung cancer and melanoma: a study of the Spanish society of medical oncology (SEOM) thrombosis and cancer group | a1660d93-d201-4401-9cf6-1bd98bef8528 | 9418291 | Internal Medicine[mh] | Per se, cancer patients display certain clinical factors that can promote the development of thrombosis. However, apart from these elements, reasonable doubt remains as to whether Immune Checkpoint Inhibitors (ICI) increases thrombotic risk. ICI has represented a highly significant change in the management of certain oncological patient profiles. Leading clinical guidelines on immunotoxicity report enteritis, endocrinopathies, neurological disorders, skin alterations, and more. The latest update published by the American Society of Medical Oncology (ASCO) recognizes thrombotic events as one such possible adverse effects associated with ICI . Similarly, the literature also contains several case reports speculating on possible causal relationships between the use of ICI and the development of venous or arterial thromboembolic disease, with pembrolizumab, nivolumab, or ipilimumab [ – ]. Molecular studies yield additional answers. T-cell activation, bolstered by ICI, is known to be capable of inducing cytokine release, especially interferon gamma, which leads to increased tissue factor expression by circulating monocytes/macrophages, provoking a state of hypercoagulability . Furthermore, other studies suggest that PD1 blockade can induce the formation of atherosclerotic plaques, which would account for the appearance of arterial phenomena . Likewise, ICI can trigger alterations in the fibrinolysis system that induce greater propensity toward pro-thrombotic states, which seems more likely in individuals with tumors that express PD1 ligand (PDL1) in greater quantities, as well as in the early stages of ICI . With all this information in hand, this study was designed to probe the relationship between thrombosis and ICI in patients in routine clinical practice.
This is a study sponsored by the Thrombosis and Cancer Section of the Spanish Society of Medical Oncology (SEOM). It is a retrospective, multicenter study (13 centers participated). Data from patients with melanoma and lung cancer who initiated ICI between 01/01/2015 and 31/12/2019 were collected. Selection was independent of tumor stage, type of ICI, or intentionality of treatment. Participants had to have a minimum follow-up of 6 months (unless it was not possible because of death). Two independent cohorts were established, one containing cases of lung cancer and the other, melanoma. For both cohorts, the primary objective was to calculate the incidence of thrombosis associated with ICI. Two secondary objectives were defined. The first was to examine the impact of thrombosis on survival among subjects treated with ICI, using the Kaplan–Meier method and log-rank test. The second was to find predictor variables for the development of thrombosis in individuals treated with ICI using multivariate analysis techniques (Cox Proportional-Hazards Model). Prior to its implementation, the study was submitted to the Ethics Committee of each participating centers and obtained the corresponding approval. The processing, communication, and transfer of all personal data complied with the provisions of Organic Law 15/1999, dated December 13, 1999, regarding the protection of personal data and of Organic Law 3/2018, dated December 5, 2018, since its entry into force.
Lung cancer A total of 665 patients were recruited; baseline characteristics are displayed in Table . This cohort had a median age of 64 years; most were male (69.6%). Functional status in this group was good (92.9% with ECOG 0–1). Most had adenocarcinoma-like histology (57.7%) and disseminated oncological disease (91.2%, stage IV) when they started ICI. ICI was mainly used in the context of first- (47.1%) or second-line (36.1%) for advanced disease. Almost half (42.7%) of the present cohort received pembrolizumab in monotherapy as an antineoplastic treatment modality. Among those patients in whom the determination of PDL1 could be performed ( n = 453), the majority (68.6%) had an expression greater than 50%. Regarding thrombotic history, 5.1% of the subjects had a previous history of VTE/AT that had been diagnosed prior to 6 months before diagnosis of lung cancer. In the interval between cancer diagnosis and date of ICI initiation, 8.7% the cases had VTE/AT. The incidence of VTE/AT associated with ICI during follow-up (median 14 months) was 8.4% (95% confidence interval [CI] 6.23–10.6) ( n = 56). A median of 5 ICI cycles administered at the time of diagnosis of VTE/AT (interquartile range [IQR] 1.25–11). At the time of VTE/AT diagnosis, 25.86% of the patients in the cohort were receiving anticoagulant therapy (13.8% at prophylactic doses, 12.06% at therapeutic doses). With respect to the characteristics of the VTE/AT episodes (Table ), the most common form of thrombosis was pulmonary embolism (PE) (46.4%). As for arterial events, 7% of patients had suffered a cerebral stroke, while 5.4% had suffered heart stroke. In those cases in which reevaluation was performed coinciding with the diagnosis of thrombosis, oncological disease was found to be progressing in more than half of the participants (52.27%). Approximately half of the events (44.66%) occurred within the first 3 months of initiating ICI. Two thirds (66.1%) of the thromboses were symptomatic. Initial management was undertaken in hospital in 51.8% of the cohort, although most subjects (82.1%) were diagnosed in an outpatient setting. After VTE/AT, 41.1% of the patients in the cohort had their ICI suspended. Suspension was marked, because thrombosis was associated with progression. In only one case was ICI discontinuation motivated by the severity of the thrombotic event. Regarding post-VTE/AT complications, within the follow-up period there was the same percentage of rethrombosis and bleeding (8.9%). The multivariate analysis (Table ) revealed a statistically significant association of three variables with the risk of VTE/AT: hemoglobin levels < 10.9 g/dL at the start of ICI, neutrophil/lymphocyte ratio (NLR) > 4.55 at the beginning of ICI, and diagnosis of thrombosis during the interval between cancer diagnosis and initiation of ICI. Survival analysis (Fig. ) revealed that median OS was lower in the group with VTE/AT (12 months, 95% CI 4.84–19.16) than in the group without VTE/AT (19 months 95% CI 16.11–21.9); the differences were statistically significant ( p = 0.0049). Melanoma A total of 291 patients were recruited. Their baseline characteristics can be seen in Table . This cohort had a median age of 62 years, with a similar proportion of men to women (52.6% and 47.4%, respectively). Their functional status was good (92.9% ECOG 0–1). At the start of ICI, 82.5% of the subjects had stage IV disease. From a molecular point of view, 29.5% of patients were BRAF mutated. PD-L1 had been determined in only 8.93% of the patients in the cohort with most (84.6%) being PD-L1 negative (< 1%). ICI was mainly used in first-line setting (62.5%); the percentages of ICI in second-line/adjuvant setting were the same (17.5%). The most commonly used treatment regimens consisted of nivolumab (40.2%) and pembrolizumab (36.1%) in monotherapy. In terms of thrombotic history, 3.4% of patients had a previous history of VTE/AT; these events had been diagnosed within 6 months prior to the diagnosis of melanoma. During the time period between cancer diagnosis and start of onset of ICI, 1.4% of the participants developed VTE/AT. The incidence of VTE/AT associated with ICI during follow-up (median 17 months) was 5.8% (95% CI 3.34–9.18) ( n = 17). A median of 8 ICI cycles had been administered at diagnosis of VTE/AT (interquartile range 2–11.75). At the time of VTE/AT diagnosis, 11.8% of patients in the cohort were receiving anticoagulant therapy (5.9% at prophylactic doses, 5.9% at therapeutic doses). As for the characteristics of the VTE/AT episodes (Table ), PE was the most common form of thrombosis (52.9%). With respect to arterial events, 5.9% of the cohort suffered a cerebral stroke, while 5.9% had an heart stroke. In those cases in which reevaluation was performed coinciding with the diagnosis of thrombosis, more than half (46.15%) were found to be in progression. Approximately half of the events (41.2%) occurred after the first 6 months of ICI. More than half (58.8%) of the thromboses were symptomatic. Initial management was inpatient in 58.8% of the cohort, although most patients (64.7%) were diagnosed in an outpatient setting. ICI was discontinued after VTE/AT in 64.7% of the subjects. Suspension was indicated because of progression in 54.5%, while in 45.5%, ICI was interrupted due to the severity of the thrombotic episode. Apropos post-VTE/AT complications, the same percentage of rethrombosis and bleeding (11.8%) occurred during follow-up. Multivariate analysis (Table ) revealed a statistically significant association of two variables with the risk of VTE/AT. These variables were: LDH > 198 U/L and NLR > 3.01%. Survival analysis (Fig. ) evidenced that median OS was lower in the group with VTE/AT (10 months 95% CI 0.0–20.27) in contrast to the group without VTE/AT (29 months 95% CI 19.58–36.42); differences were statistically significant ( p = 0.034).
A total of 665 patients were recruited; baseline characteristics are displayed in Table . This cohort had a median age of 64 years; most were male (69.6%). Functional status in this group was good (92.9% with ECOG 0–1). Most had adenocarcinoma-like histology (57.7%) and disseminated oncological disease (91.2%, stage IV) when they started ICI. ICI was mainly used in the context of first- (47.1%) or second-line (36.1%) for advanced disease. Almost half (42.7%) of the present cohort received pembrolizumab in monotherapy as an antineoplastic treatment modality. Among those patients in whom the determination of PDL1 could be performed ( n = 453), the majority (68.6%) had an expression greater than 50%. Regarding thrombotic history, 5.1% of the subjects had a previous history of VTE/AT that had been diagnosed prior to 6 months before diagnosis of lung cancer. In the interval between cancer diagnosis and date of ICI initiation, 8.7% the cases had VTE/AT. The incidence of VTE/AT associated with ICI during follow-up (median 14 months) was 8.4% (95% confidence interval [CI] 6.23–10.6) ( n = 56). A median of 5 ICI cycles administered at the time of diagnosis of VTE/AT (interquartile range [IQR] 1.25–11). At the time of VTE/AT diagnosis, 25.86% of the patients in the cohort were receiving anticoagulant therapy (13.8% at prophylactic doses, 12.06% at therapeutic doses). With respect to the characteristics of the VTE/AT episodes (Table ), the most common form of thrombosis was pulmonary embolism (PE) (46.4%). As for arterial events, 7% of patients had suffered a cerebral stroke, while 5.4% had suffered heart stroke. In those cases in which reevaluation was performed coinciding with the diagnosis of thrombosis, oncological disease was found to be progressing in more than half of the participants (52.27%). Approximately half of the events (44.66%) occurred within the first 3 months of initiating ICI. Two thirds (66.1%) of the thromboses were symptomatic. Initial management was undertaken in hospital in 51.8% of the cohort, although most subjects (82.1%) were diagnosed in an outpatient setting. After VTE/AT, 41.1% of the patients in the cohort had their ICI suspended. Suspension was marked, because thrombosis was associated with progression. In only one case was ICI discontinuation motivated by the severity of the thrombotic event. Regarding post-VTE/AT complications, within the follow-up period there was the same percentage of rethrombosis and bleeding (8.9%). The multivariate analysis (Table ) revealed a statistically significant association of three variables with the risk of VTE/AT: hemoglobin levels < 10.9 g/dL at the start of ICI, neutrophil/lymphocyte ratio (NLR) > 4.55 at the beginning of ICI, and diagnosis of thrombosis during the interval between cancer diagnosis and initiation of ICI. Survival analysis (Fig. ) revealed that median OS was lower in the group with VTE/AT (12 months, 95% CI 4.84–19.16) than in the group without VTE/AT (19 months 95% CI 16.11–21.9); the differences were statistically significant ( p = 0.0049).
A total of 291 patients were recruited. Their baseline characteristics can be seen in Table . This cohort had a median age of 62 years, with a similar proportion of men to women (52.6% and 47.4%, respectively). Their functional status was good (92.9% ECOG 0–1). At the start of ICI, 82.5% of the subjects had stage IV disease. From a molecular point of view, 29.5% of patients were BRAF mutated. PD-L1 had been determined in only 8.93% of the patients in the cohort with most (84.6%) being PD-L1 negative (< 1%). ICI was mainly used in first-line setting (62.5%); the percentages of ICI in second-line/adjuvant setting were the same (17.5%). The most commonly used treatment regimens consisted of nivolumab (40.2%) and pembrolizumab (36.1%) in monotherapy. In terms of thrombotic history, 3.4% of patients had a previous history of VTE/AT; these events had been diagnosed within 6 months prior to the diagnosis of melanoma. During the time period between cancer diagnosis and start of onset of ICI, 1.4% of the participants developed VTE/AT. The incidence of VTE/AT associated with ICI during follow-up (median 17 months) was 5.8% (95% CI 3.34–9.18) ( n = 17). A median of 8 ICI cycles had been administered at diagnosis of VTE/AT (interquartile range 2–11.75). At the time of VTE/AT diagnosis, 11.8% of patients in the cohort were receiving anticoagulant therapy (5.9% at prophylactic doses, 5.9% at therapeutic doses). As for the characteristics of the VTE/AT episodes (Table ), PE was the most common form of thrombosis (52.9%). With respect to arterial events, 5.9% of the cohort suffered a cerebral stroke, while 5.9% had an heart stroke. In those cases in which reevaluation was performed coinciding with the diagnosis of thrombosis, more than half (46.15%) were found to be in progression. Approximately half of the events (41.2%) occurred after the first 6 months of ICI. More than half (58.8%) of the thromboses were symptomatic. Initial management was inpatient in 58.8% of the cohort, although most patients (64.7%) were diagnosed in an outpatient setting. ICI was discontinued after VTE/AT in 64.7% of the subjects. Suspension was indicated because of progression in 54.5%, while in 45.5%, ICI was interrupted due to the severity of the thrombotic episode. Apropos post-VTE/AT complications, the same percentage of rethrombosis and bleeding (11.8%) occurred during follow-up. Multivariate analysis (Table ) revealed a statistically significant association of two variables with the risk of VTE/AT. These variables were: LDH > 198 U/L and NLR > 3.01%. Survival analysis (Fig. ) evidenced that median OS was lower in the group with VTE/AT (10 months 95% CI 0.0–20.27) in contrast to the group without VTE/AT (29 months 95% CI 19.58–36.42); differences were statistically significant ( p = 0.034).
Medical oncology is currently witnessing an era in which the use of ICI is spreading to more and more neoplasia, as well as to a greater number of indications within each of these diseases. We are able to identify toxicities that have not been reported in pivotal clinical trials. ICI-associated VTE/AT is one such toxicity. The purpose of this research project was to provide more information within this area of medical oncology by dint of patients from routine clinical practice. The authors contend that there are three fundamental aspects that must be discussed: the incidence of IT-associated VTE/AT, its impact on OS in the oncological patient, and the identification of factors that can predict this type of complication. As concerns incidence, Solinas et al. published a systematic review in which they sought out the incidence of VTE/AT in individuals treated with ICI, within the framework of the leading clinical studies conducted with this type of therapy. They established that the incidence was low: 2.7% (95% CI 1.8–4) and 1.1% (95% CI 0.5–2.1) for VTE and AT, respectively. However, studies published subsequently and including cases in routine clinical practice reported higher figures. For example, Wang et al. performed a bibliographic review of VTE/AT associated with ICI. The patient profile most often associated with this type of complication was male, with stage IV disease, and with a primary lung, kidney, or melanoma. The data is comparable with our series, inasmuch as the cohorts comprise subjects with lung cancer and melanoma; moreover, in both groups, males with stage IV disease are the majority. According to Wang et al. the cumulative incidence of VTE was 5–8% and 10% at 6 months and 12 months from the start of ICI, respectively. As for arterial events, the incidence was 1–5% at 12 months from ICI initiation. While venous and arterial events were analyzed jointly in our series, this did not generate a significant variation in the percentages reported (8.7% in the lung cancer group and 5.7% in the melanoma group). Other authors have also independently studied the incidence of venous and arterial events. Moik et al. published a study of cases treated at the University Hospital of Vienna. All patients treated with ICI between 2015 and 2018 were enrolled in their research piece. This work included individuals with different cancers, in contrast to this series. Nonetheless, the most prevalent ones were melanoma (30.4%) and non-small cell lung cancer (24.1%). After a median follow-up of 8.5 months, the incidence of VTE was 12.9% and that of AT was 1.8%. In contrast, the results of the study by Ando Y et al. are striking in that they detected an incidence rate of VTE that was lower (4.1%) than that of AT (4.9%). The literature also includes other publications in which the scope of study has been limited to venous events. One example is the work carried out by Kewan et al. , who performed a retrospective, multicenter study that enrolled a total of 552 patients with stage IV cancer treated with ICI. The incidence of VTE was 10.5%. Of similar note in this field is the study conducted by Gong et al. that retrospectively analyzed a total of 2,854 subjects in a single-center study. They established that the risk of VTE increased as the time of exposure to IT increased; thus, at 6 months, they found a 7.4% risk and a 13.8% risk at 12 months. Deschênes-Simard et al. performed a retrospective, multicenter, cohort study involving 593 patients with non-small cell lung cancer from three centers in Canada and France. The cumulative incidence of VTE was 14.8%, which was almost twofold the rate reported in the lung cancer cohort in our series (8.7%). Similarly, Sussman et al. conducted a retrospective, cohort study of melanoma patients who received ICI at the Cleveland Clinic. The sample size ( n = 228) was slightly smaller than our melanoma cohort ( n = 291). While there were commonalities, such as a majority of stage IV disease, the cumulative incidence of VTE post IT initiation was 9.3% at 6 months and 16% at 12 months, higher than the rates we report (5.7%). Finally, in this section of the discussion dedicated to discussing incidence, the work carried out by Gutierrez-Sainz et al. is worth noting. Theirs was a single-center, retrospective study. They recruited a total of 229 patients. Like some of the previously mentioned authors, they studied venous events exclusively and described an incidence of 7%, occurring more frequently in patients with lung cancer and melanoma. These figures are closer to the ones we report for our series, which is interesting, given that this study was conducted at a Spanish center and in Spanish patients, as are ours. All the data reflected in the previous paragraphs, together with those of our series, only confirm what the review by Goel et al. concluded: there is a reasonable incidence of VTE/AT among individuals receiving IT, despite the fact that the figures do vary. The second aspect to be addressed in this discussion is the impact of ICI-associated VTE/AT on survival in this population. It is well known that thrombosis negatively affects the prognosis of cancer patients and, in fact, it is reported as the second leading cause of death among people afflicted with cáncer . The data from this series indicate that for people with either melanoma or lung treated with ICI, the development of VTE/AT is statistically significantly associated with worse survival. In fact, among those patients in whom it was possible to reevaluate the underlying oncological disease, most were found to be in progression, lending further credence to the concept that thrombosis generally reflects adverse tumor biology . However, not all papers published to date are unanimous with respect to the impact of VTE/AT on survival in among oncological patients treated with ICI. For example, Moik et al. established that median OS was lower among subjects with VTE (25.5 vs. 11.6 months, p < 0.001) although they did not find that AT influenced prognosis. The series by Sussman et al. also detected that ICI-associated thrombosis affected survival, with a median OS for cases with VTE of 20 months, while in those cases that did not develop VTE, the median was not reached. However, works by Deschênes-Simard et al. and Gutierrez-Sainz et al. failed to detect any statistically significant relationship between survival and development of ICI-associated VTE. Finally, we proceed to address the identification of factors that can predict VTE/AT in subjects treated with ICI. As it pertains to our series, it is worth noting that in both patients with lung cancer and those with melanoma, elevated NLR at the beginning of ICI increases the risk of subsequent VTE/AT. This is not surprising given that studies have already been published about how this parameter is linked to thrombotic burden . In the case of melanoma in particular, it is also interesting to remark on the greater probability of VTE/AT associated with ICI when LDH at the start of this treatment modality is elevated. Elevated LDH negatively affects the prognosis of a patient with melanoma thus, it seems only logical that it should correlate with the risk of VTE/AT when starting ICI, given the impact of this type of event on survival, as evinced by the series studied in this work. Some of the previously referenced works attempt to describe predictor variables of VTE/AT. Moik et al. , Ando et al. , and Gong et al. report a history of VTE as being predictive of ICI-associated thrombosis. Our study population bears out this finding. Nevertheless, there are two points that cause the data not to be entirely comparable. The first is that we have found the association when thrombosis occurs in the interval between the diagnosis of cancer and the onset of ICI, while the second is that this association is only apparent in patients with lung cancer. In contrast, it is worth mentioning that Kewan et al. report anemia at the onset of ICI to be a prognostic factor, albeit in our series, this has only been described as being associated with the risk of VTE/AT in patients with lung cancer. Finally, other factors described in other studies as predictors of VTE/AT in subjects treated with ICI should be highlighted, although no association was found in our series. These variables are high Khorana scores [ , , ], ECOG of < 2 , HBP , age < 65 years PDL1 > 1% , treatment with a combination of two immunotherapy agents , history of coronary artery disease , anticoagulant therapy at the start of ICI and being female . Despite the weighty data obtained, this study has some limitations. The first limitation is its retrospective nature. However, this weakness is compensated by two strengths that we deem significant: it is a multicenter study (unlike others that have been presented throughout the discussion section) and the large sample size (especially the lung cancer cohort that consisted of 665 cases). The participating centers are from different parts of Spain, so the data enable us to draw conclusions that are representative of the heterogeneity of patients in our country. Second, the fact that the incidence rates reported may vary as subsequent series are published. Bearing in mind that ICI has become more widespread in recent years, VTE/AT figures may increase due to that this treatment modality is becoming accessible to more and more people. Likewise, the increased survival associated with this type of treatment implies that the periods during which thrombotic risk is high (either due to persistence of an advanced-stage tumor or to longer exposure to ICI) are becoming more prolonged. Consequently, the possibility of developing VTE/AT increases. This could account for the fact that some of the series discussed have failed to detect an association between survival and VTE/AT. The third, and last limitation that we would like to mention is the lack of homogeneity with respect to other studies in finding predictors of thrombosis in cancer patients who initiate ICI. We were unable to find a justification for this issue. It is conceivable that larger sample sizes and stratified studies based on different tumor pathologies would enable us to obtain more precise data, given that thrombotic risk is not equivalent across all types of cancer.
ICI increases thrombotic risk in individuals with lung cancer and melanoma. These thrombotic events impact OS in this population.
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Implementing an initiative to promote evidence-informed practice: part 1 — a description of the Evidence Rounds programme | 85d53a2b-c71c-4bef-97c5-775f45fd495d | 6402167 | Pediatrics[mh] | Evidence-informed practice is central to the delivery of quality care and is associated with improvements in patient outcomes. Emparanza and colleagues demonstrated that mortality and duration of hospital stay figures were reduced among patients treated in an evidence-based practice unit, when compared to either a standard practice unit or previous practice by the same health care professionals (HCPs). Nevertheless, a well-reported gap exists between clinical practice and much of the evidence available to HCPs . When evidence is not translated into practice or there is a delay in the process, patients may be exposed to unnecessary risks or suboptimal care. There are multiple barriers to evidence uptake and evidence-informed practice. Information overload [ – ] is a barrier which can cause HCPs to become overwhelmed by the volume of available literature when seeking to access the most relevant and up to date research . We have long been in an era of information overload with, for example, more than 1 million publications related to biomedical research captured within the PubMed database each year . Many health care workers have limited time to devote to reading research evidence . Conversely, for some healthcare topics, there can be a lack of evidence or indeed, high quality evidence . There is a need for evidence-informed, theory-based educational and knowledge translation initiatives aimed at HCPs to promote evidence-informed practice and the implementation of evidence where appropriate. There is also a knowledge gap regarding the implementation process of these type of initiatives. One of the most frequently used theories in research looking at the adoption of evidence based practice and implementation science is Everett Rogers’ diffusion of innovations theory (1983). Rogers identified four key elements instrumental to the adoption of an innovation; the innovation itself, communication channels (hereby referred to as modes of delivery), time, and the social system. He categorised stakeholders into five groups according to how they adopt innovations over time; innovators, early adopters, early majority, late majority and laggards . Grimshaw and colleagues , highlight that there is a considerable body of evidence relating to KT strategies yet it remains incomplete. A much-debated question is whether combined or single component strategies are more effective . Intuitively, a multicomponent strategy might be more effective when seeking to engage as many clinicians as possible, some of whom may have preferences or circumstances that makes a particular component work for them. However, Squires et al. found that interventions with multiple components were no more effective than single component interventions. They also concluded that the effectiveness of multifaceted interventions did not increase incrementally as the number of components increased. It might be that multiple components used in some studies addressed the same rather than diverse issues or barriers and if so, then this might explain why they were not judged to be more effective. In a systematic review by McCormack et al. multicomponent dissemination strategies focusing on reach, motivation and ability strategies were more likely to affect clinicians’ behaviours than single-component strategies. Another systematic review demonstrated that multifaceted interventions focused on educational meetings to increase implementation of physiotherapy clinical guidelines may improve some outcomes relating to practice but failed to have a positive impact on patient health outcomes or reducing costs . Educational meetings on their own or in combination with other interventions may improve clinical practice or patient outcomes but may not change complex behaviours . A Cochrane systematic review reported that interprofessional education may improve patient outcomes and improve adherence to clinical guidelines although the evidence was judged to be low quality . Wallace and colleagues found that targeted messaging, summaries of research evidence and educational visits may improve the uptake of key research findings . The inclusion of local opinion leaders in an intervention may make it more likely to align HCP behaviours with the desired practice . In a before-and-after study by Segovis, the provision of food was identified by HCPs as a motivating factor to attend grand rounds . According to the National Implementation Research Network (NIRN) based in the United States, an enabling context is an essential component of evidence-based programs for increasing their usefulness . Implementation outcomes and the use of evidence can be driven to a large extent by contextual factors and their methods of delivery [ – ]. Contextual influences on implementation can be both barriers and enablers to different people at different times, under varying circumstances. In a recent systematic review, Geerligs et al. found that barriers and facilitators to implementation processes identified by HCPs were experienced at system, staff and intervention levels . The authors recommend taking these three domains into account when designing implementation strategies. Hamilton and Mittman and Proctor have highlighted the need for further research to describe the implementation of these types of initiatives in sufficient detail. Informed by this evidence, Evidence Rounds featured a multifaceted strategy centred around educational meetings and focused on increasing the reach of evidence and the motivation and ability to use and apply evidence. We also took an interprofessional approach, by involving multiple professions (midwifery, neonatology and obstetrics) and working with opinion leaders. We designed the initiative to address individual and organizational level factors and adapted it when necessary throughout the implementation process. We arranged for a local catering service to provide food at each session. Our description of the implementation of Evidence Rounds adds to the literature on educational initiatives in applied health services research. There is a general paucity in the existing literature of studies that provide insight into how contextual factors have influenced dissemination and implementation efforts. Evidence Rounds was based loosely on an intervention conceived by Jacqui Le May, former Head of Knowledge Services at University Hospitals Coventry and Warwickshire, NHS Trust in the United Kingdom (UK). There, members of the Clinical Evidence Based Information Service (CEBIS) team run Evidence in Practice Groups to examine evidence in various departments within the hospital. Topics and questions are linked to a specific patient cases, series of patient cases or other general topics. As well as incorporating the best available evidence into our group sessions, we used evidence from key findings of systematic reviews and other research to inform the design and implementation of the initiative. The goal of Evidence Rounds was to bridge the gap between evidence and practice through an educational initiative aimed at HCPs. The objectives were to disseminate the best available evidence to HCPs on topics of their choosing during group sessions; to promote evidence-informed practice through the provision of an in-person group platform for staff to discuss the implications of the evidence, the barriers and facilitators to its implementation and, to enhance evidence-informed practice by identifying and assigning resulting actions where appropriate. The aims of this paper are to describe the process of planning, designing and implementing this multi-component educational initiative, to report data on quantitative performance indicators monitoring engagement during the implementation process and to provide follow up information regarding the implementation or lack of implementation of the evidence. The second paper in this two-part series reports the findings of focus groups and interviews about Evidence Rounds with HCPs who attended or presented at the group educational sessions .
In Fig. , we present a logic model developed iteratively to demonstrate the underlying logic behind the implementation strategy for Evidence Rounds. We designed it with the understanding that implementation processes and health systems are complex. May and colleagues advised that implementation processes be understood as “non-linear, emergent and dynamic events within systems.” The model focuses on the components of the initiative, our planned activities and what we hoped to achieve through the initiative. We informed the pre-implementation and the implementation phases by adapting aspects of the CEBIS Evidence in Practice Groups, Rogers’ diffusion of innovations theory , the framework for knowledge transfer and the Knowledge Translation Planning Template . We used Rogers’ diffusion of innovation theory to drive the implementation strategy . The organising framework for knowledge transfer strategies conceived by Lavis et al. was used to develop the implementation strategy. This framework asks five key questions: 1. What should be transferred to decision makers? 2. To whom should research knowledge be transferred? 3. By whom should research knowledge be transferred? 4. How should research knowledge be transferred? 5. With what effect should research knowledge be transferred? What should be transferred to decision makers? To improve the likelihood of evidence uptake, HCPs were invited to select topics or clinical questions relating to treatment or diagnostic interventions. A member of staff who later confirmed with colleagues their agreement on her chosen topic suggested the topic for the first group session at a planning meeting. For subsequent sessions, a collective decision was made at group sessions about the topic to be covered in the next session. Sometimes, several suggestions were considered before a decision was made. At the request of one HCP, a topic suggestion sheet was passed around during sessions to accommodate staff who were reluctant to propose topics in front of their colleagues. HCPs were asked to submit suggestions based on gaps they perceived in their knowledge of the evidence or where there was a perceived gap between the evidence and their own practice. Topics were not limited to those known to have clear and conclusive evidence and suggestions covering controversial treatments, those that had conflicting evidence findings, or a lack of evidence, were encouraged. Our aim was to transfer the best available, most up to date, relevant and applicable evidence. A list of sub-questions or topics for each educational session is featured in Table . At the start of each session, national and international official guidance was explored to increase awareness of current recommendations. All of the selected topics and clinical questions involved healthcare interventions so we were particularly interested in accessing and presenting randomised trials and systematic reviews of trials. However, for all topics, we also included non-randomised or observational studies so that qualitative aspects of topics could be taken into consideration. For some sessions, HCPs requested and found it valuable to read reports on what other units were doing and compare and contrast their own practice. The final selected topics are presented in Table . To whom should research knowledge be transferred? Our target audience consisted of HCPs working in the neonatal and obstetric departments in the women and children’s division of an urban hospital in Ireland. We took a multi-disciplinary and interprofessional approach to maximise the potential for the dissemination and implementation of evidence and to promote collaboration with the ultimate goal of implementation of evidence where appropriate. We also invited staff members outside of key departments when deemed appropriate to the topic. For example, laboratory staff were invited to attend the fourth session: antenatal screening for group B streptococcus. When these staff were identified, invitations were extended through the presenting HCPs. The implementation team also invited students who were on placement in the departments during the time of the sessions. By whom should research knowledge be transferred? We took a team approach to the transfer of knowledge. Three HCPs presented at each session with representatives from both medical and nursing and midwifery staff in each session. Staff from the neonatal and obstetric departments presented when the topic covered both disciplines. To recruit HCPs to present, staff were asked to volunteer during group sessions or previous presenters contacted individuals they perceived as suitable candidates. The KT professional who is an author on this paper (AC) introduced each session, discussed the literature search process, the breadth of the literature on the chosen topic, and directed discussion to decide on the next topic. How should research knowledge be transferred? The KT strategy involved both active and passive methods of promotion, communication and dissemination. In line with Rogers’ diffusion of innovations theory , we accepted that our target audience was likely to adopt the evidence presented in the educational initiative at different points in time. Therefore, we deemed it appropriate to use a multifaceted educational strategy. To increase the reach of the evidence: We identified and arranged meetings with key staff at the hospital - to build an implementation team and identify potential champions or opinion leaders that could help us communicate with HCPs and disseminate evidence. Our group sessions targeted multiple disciplines and professions to increase the impact. We employed a variety of communication and dissemination modes of delivery (See Table ) e.g. face-to-face meetings, telephone calls, emails, an open access website, based on the assumption that we were likely to encounter stakeholder groups similar to those identified by Rogers who may adopt the initiative at different points in the process and for a variety of reasons. To increase motivation to use and apply the evidence: HCPs took ownership by choosing topics that had the potential to improve their practice and that were meaningful and timely for them. We focused on the applicability of the evidence to the local context. When requested, we presented information on how other national and international units were providing healthcare services relating to the topic for benchmarking purposes. In 3 of the 6 sessions, retrospective audit data were presented to capture data relating to recent practice and potentially act as a driving force to change future practice. To increase the ability to use and apply the evidence: We addressed the issue of information overload by designing and performing pragmatic yet comprehensive search strategies, sifting through the frequently large volume of search results and discarding obviously irrelevant records. Searches were ran on appropriate databases and websites including; the Cochrane Library databases, Medline or PubMed, CINAHL, Embase, Google (to identify guidelines and grey literature), relevant professional bodies and organisations’ websites, healthcare organisations’ websites, DynaMed, Trip Database Pro and the Geneva Foundation for Medical Education and Research (GFMER). Presenting HCPs were provided with a significantly reduced number of records to screen for inclusion. After feedback from the first session, a “Quick Guide for Presenters” (see Additional file ) was provided to HCPs who had signed up to present. Key data and findings from multiple studies were extracted and summarised during group sessions. We fostered an environment where critical appraisal was key and highlighted the strengths and weaknesses of included evidence. The KT professional provided support and enabling services to presenters to reduce their workload and improve levels of health information literacy e.g. obtaining full text of papers, helping with interpreting statistical data e.g. forest plots and key statistical concepts such as P values and confidence intervals, identifying appropriate critical appraisal tools, sourcing images to put into presentations (in compliance with licensing and copyright restrictions), providing feedback on presentation slides, populating reference sections, extracting key information and data, providing guidance on selecting papers for inclusion etc. During the discussion forum, obstacles to the implementation of evidence were identified to increase the likelihood that they would be addressed and plans for change could be tailored . At the initial planning meetings, we emphasized that we did not intend on imposing the Evidence in Practice Groups model from the UK on staff at our hospital. Baumann recommends taking an adaptive approach to implementation because no single intervention will be a perfect fit in all settings . Proactive adaptation played a key role in our strategy so that we could shape the initiative in response to important individual, organisational and contextual factors. We tailored it to suit the local context with currently available information before implementation and adapted it iteratively throughout in accordance with feedback loops, observations and performance indicator monitoring. See the Table for a list of core components and some adaptations. 5) With what effect should research knowledge be transferred? The main aims of Evidence Rounds were to provide an educational program that disseminated evidence to health care professionals and promoted evidence-informed practice. We undertook process evaluation by capturing and monitoring data for key indicators throughout the initiative. Firstly, we distributed sign-in sheets at group sessions to record attendance figures. We wanted to track neonatal and obstetric staff attendances and identify potential patterns. Secondly, we monitored usage analytics on our dedicated website. Both informed us of the penetration of Evidence Rounds to the HCP community within the department. Thirdly, our focus groups and interviews provided self-reported data on how the HCPs were receiving the educational initiative and how they viewed it in relation to their own evidence-informed practice. Using this data, we identified individual, organisational and intervention level barriers and facilitators to attending and presenting at Evidence Rounds. We were better able to understand the complexity of the behaviours and gauge opinions on whether and how Evidence Rounds was promoting evidence-informed practice for them. These results are published in the second paper of this two part series . Fourthly, we followed up with the implementation team to check the status of evidence implementation. Dissemination strategies play an essential role but on their own, do not guarantee the implementation of evidence . For this reason, and when appropriate during the discussion forum, barriers, facilitators and specific actions to aid implementation of evidence were identified, discussed and actions were assigned to specific HCPs as appropriate. Three months after the final group session, we followed up with HCPs on the implementation team to see whether Evidence Rounds had influenced practice. They reported that a small number of recommendations from Evidence Rounds had been implemented. When implementation happens, the process can be slow, particularly for more complex issues. In the interviews and focus groups, several HCPs explained that changes in practice often cannot occur until the desired change is firstly made a part of a clinical guideline . Writing and updating guidelines can be a lengthy process. Further follow up with the same HCPs occurred 16 and 21 months later. We took measures to plan for sustainability (continuation of the initiative after support from the KT Specialist ended) such as developing tools that could be handed over easily. For example, we chose a web hosting platform that allowed us to build the website and create content using high quality templates without the need for coding or programming skills. Our choice was deemed the most likely option to promote sustainability because at the end of the period of support from the KT specialist, it could easily been handed over to a HCP lacking advanced technical skills of website design and administration/maintenance. We also linked in with library staff to confirm that they would be willing to design and conduct future searches, had conversations with key people, discussed it during our focus groups and interviews and offered guidance during a handover period. We planned to assess sustainability by following up with the implementation team to find out whether the educational initiative had continued to be delivered. We employed the Template for Intervention Description and Replication (TIDieR) checklist, to complement the reporting of the initiative . This reporting guideline has been recommended for use to report intervention implementation . We collected and report a number of quantitative measures: website analytics captured by our website hosting platform. We report figures spanning the period from one month before the first group session, during the group sessions and one month after the last group session: unique visitors defined as the number of visitors visiting for the first time visits defined as the number of browsing sessions and can involve multiple page views page views defined as the number of times a webpage from our website was fully loaded by a browser the total number of HCPs and other attendees who attended each Evidence Round session (other attendees included academic partners and students from health-related higher education courses on placement at the hospital site) the total number of HCPs who presented at an Evidence Rounds session. We contacted the 5 HCP members of the implementation team three, 16 and 21 months after the initiative ended to find out whether Evidence Rounds had led to the implementation of research findings.
Six Evidence Rounds group sessions were run over a 9-month period. There was a total of 148 attendees of which 85 were unique (individuals who signed the attendance sheet at a minimum of one session). See Table for a breakdown of attendance numbers by educational session. Attendance numbers fluctuated according to factors such as the chosen topic (some of which were common to midwifery, neonatology and obstetrics, and some of which were primarily neonatology-focused), level of interest in the topic subject matter and clinical staffing levels. Seventeen HCPs who worked at the hospital presented during the period of implementation. One external HCP (DD, who is an author of this paper), was asked to present at a session because he authored two relevant papers that were selected for inclusion in the presentation (session number 6). Between 01/06/2016 and 29/04/2017, 188 unique visitors, 331 visits and 862 page views were recorded on the website. See Fig. for a breakdown of these figures. In Table , we present the clinical questions and topics explored, the resulting actions identified during the discussion forum and the actual resulting actions that were carried out for each of the 6 educational sessions. This information was gathered during follow up with the implementation team. Follow up with the implementation team also confirmed that the educational program was not sustained beyond the period of support from the KT Specialist.
Limitations and lessons learned We would like to acknowledge that our study has several limitations. Firstly, the six educational sessions were carried out over nine months. It is unlikely that this was a sufficient duration of implementation to allow for the initiative to realise its full potential, become fully integrated or adopted by staff that Rogers might describe as the late majority and laggards. In this way, the potential of Evidence Rounds to demonstrate sustainability may have been restricted. Secondly, our theoretical approach did not include pedagogical theory to develop our educational initiative. Thirdly, attendance data collected through sign-in sheets can be viewed as a conservative estimate of actual attendance figures. We are aware of several attendees who did not sign in during sessions for reasons such as being bleeped or called away to attend to a patient. Fourthly, the number of unique visitors recorded using website analytics may be inaccurate because the same person could potentially access the website multiple times using more than one IP address or computer. This would have resulted in them being counted as more than one user. Fifthly, our initiative was implemented at one institution and may be received differently by HCPs in other settings. Sixthly, the information presented in Table regarding follow up lacks quantitative data measures of practice changes following the educational sessions, compared to prior practice. The study by Emparanza provides a good example of quantitative outcome measurement. In terms of implications for practice, the issue of sustainability is important to consider. Despite the steps we describe in the Methods section aimed at increasing the sustainability of the initiative, it was not sustained beyond the period of support from the KT professional. Without a nominated person or team with dedicated professional hours and taking into consideration the time spent planning and developing, we were aware that there was reduced potential to sustain the initiative at our busy hospital setting. Ideally, future initiatives will have a longer period of implementation to allow for appropriate capacity building and so that they have a better chance of integration and becoming accepted and adopted by staff. A key learning point for us has been that initiatives like Evidence Rounds are only as strong as the people involved. We recommend collaboration and partnership with the target audience starting from the planning stages and continuing throughout. The multi-disciplinary and interprofessional approach worked very successfully for Evidence Rounds and according to informal feedback and our focus group and interview data it was highly valued by our target audience. We engaged with them, listened to their feedback and found ways to address their identified needs when possible. Our key message in this regard would be to network and engage with champions, opinion leaders, enthusiastic individuals, early adopters and do not wait around for laggards . Involving an Information Specialist or Librarian or someone who has knowledge of appropriate databases and other online resources and is experienced in carrying out systematic and detailed literature searches is essential. They can help to address issues of information overload and reduce the workload of HCPs involved in presenting. Adaptation and adherence to a small number of core components was a fundamental of the initiative. Baker et al. , found that positive outcomes are more likely if an adaptive approach is taken to implementing interventions when compared to no intervention or dissemination alone. Feedback from HCPs who participated in our focus groups and interviews suggested that choosing topics based on when guidelines are being created or updated increases the likelihood of implementation of evidence. Further studies are required to assess the effectiveness of Evidence Rounds, similar educational initiatives including those implemented in settings in the developing world. Evaluation could include pre and post-testing of knowledge of topics the initiative addressed, impact on HCP behaviour and patient care outcomes. More studies are needed to better understand and identify additional underlying mechanisms and contextual factors that influence educational programs. Additional research is also needed to understand how a social media strategy might be optimised for use in the delivery of similar initiatives.
We would like to acknowledge that our study has several limitations. Firstly, the six educational sessions were carried out over nine months. It is unlikely that this was a sufficient duration of implementation to allow for the initiative to realise its full potential, become fully integrated or adopted by staff that Rogers might describe as the late majority and laggards. In this way, the potential of Evidence Rounds to demonstrate sustainability may have been restricted. Secondly, our theoretical approach did not include pedagogical theory to develop our educational initiative. Thirdly, attendance data collected through sign-in sheets can be viewed as a conservative estimate of actual attendance figures. We are aware of several attendees who did not sign in during sessions for reasons such as being bleeped or called away to attend to a patient. Fourthly, the number of unique visitors recorded using website analytics may be inaccurate because the same person could potentially access the website multiple times using more than one IP address or computer. This would have resulted in them being counted as more than one user. Fifthly, our initiative was implemented at one institution and may be received differently by HCPs in other settings. Sixthly, the information presented in Table regarding follow up lacks quantitative data measures of practice changes following the educational sessions, compared to prior practice. The study by Emparanza provides a good example of quantitative outcome measurement. In terms of implications for practice, the issue of sustainability is important to consider. Despite the steps we describe in the Methods section aimed at increasing the sustainability of the initiative, it was not sustained beyond the period of support from the KT professional. Without a nominated person or team with dedicated professional hours and taking into consideration the time spent planning and developing, we were aware that there was reduced potential to sustain the initiative at our busy hospital setting. Ideally, future initiatives will have a longer period of implementation to allow for appropriate capacity building and so that they have a better chance of integration and becoming accepted and adopted by staff. A key learning point for us has been that initiatives like Evidence Rounds are only as strong as the people involved. We recommend collaboration and partnership with the target audience starting from the planning stages and continuing throughout. The multi-disciplinary and interprofessional approach worked very successfully for Evidence Rounds and according to informal feedback and our focus group and interview data it was highly valued by our target audience. We engaged with them, listened to their feedback and found ways to address their identified needs when possible. Our key message in this regard would be to network and engage with champions, opinion leaders, enthusiastic individuals, early adopters and do not wait around for laggards . Involving an Information Specialist or Librarian or someone who has knowledge of appropriate databases and other online resources and is experienced in carrying out systematic and detailed literature searches is essential. They can help to address issues of information overload and reduce the workload of HCPs involved in presenting. Adaptation and adherence to a small number of core components was a fundamental of the initiative. Baker et al. , found that positive outcomes are more likely if an adaptive approach is taken to implementing interventions when compared to no intervention or dissemination alone. Feedback from HCPs who participated in our focus groups and interviews suggested that choosing topics based on when guidelines are being created or updated increases the likelihood of implementation of evidence. Further studies are required to assess the effectiveness of Evidence Rounds, similar educational initiatives including those implemented in settings in the developing world. Evaluation could include pre and post-testing of knowledge of topics the initiative addressed, impact on HCP behaviour and patient care outcomes. More studies are needed to better understand and identify additional underlying mechanisms and contextual factors that influence educational programs. Additional research is also needed to understand how a social media strategy might be optimised for use in the delivery of similar initiatives.
Evidence Rounds presents a novel educational initiative to support a knowledge translation strategy targeted at HCPs. It moves beyond the journal club model that was familiar to our target audience. It was designed and implemented based on feedback obtained by proactively engaging with staff. We have helped address the need for more research that provides a detailed account of the implementation of knowledge translation strategies . We have also highlighted the contextual factors and modes of delivery that influence implementation outcomes. This paper therefore, will help others to understand the process involved in implementing an educational initiative. Evidence Rounds was a complex initiative to implement due to individual, contextual and intervention-level factors. We used a multi-faceted strategy to disseminate key research findings to our clinical audience and promote evidence-informed practice. We collaborated with and involved our target audience from the start of the planning phase and throughout implementation. This paper provides useful insight into processes and mechanisms involved in rolling out an initiative. We describe the practical aspects or the process of implementing an educational initiative. The level of detail we have provided will aid reproducibility for those wishing to roll out a similar program or elements of the program. We highlighted contextual factors that had an impact on implementation in our setting so that others might use them to inform the planning of their own initiatives.
Additional file 1: Quick guide for presenters (DOCX 59 kb) Additional file 2: Sample poster promoting Evidence Rounds (PDF 8151 kb) Additional file 3: Sample certificate of attendance (PDF 103 kb) Additional file 4: Sample certificate of participation (PDF 103 kb)
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The effectiveness of adjunctive measures in managing peri-implant mucositis: an umbrella review | 94b2b784-6bdd-487c-b8fa-e3fd9b2da4a0 | 9177933 | Dental[mh] | Peri-implant mucositis (PIM) is defined as inflammation of peri-implant mucosa without evidence of continuing marginal bone loss after initial bone remodeling , whereas peri-implantitis is defined as inflammation of peri-implant mucosa and additional marginal bone loss after initial bone healing . Bacterial biofilm is the primary etiological agent in peri-implant mucositis and peri-implantitis . Considering that peri-implant mucositis precedes peri-implantitis, treatment of peri-implant mucositis is considered as the primary preventive modality for peri-implantitis . The resolution of peri-implant mucositis may be achieved effectively by professional non-surgical mechanical debridement (NSMD) and enhanced oral hygiene practice (EOH) . In addition, adjunctive treatments, including air-polishing, laser and photodynamics, antiseptics, and antibiotics, have been proposed to improve the outcomes of this treatment. Several systematic reviews (SRs) and meta-analyses (MA) have analyzed the effect of various adjunctive treatments compared to NSMD alone. SRs provide a comprehensive synthesis of all available evidence (clinical studies) related to a specific intervention. This type of evidence synthesis focuses on a narrow review question, typically of direct comparison between two therapies and provides the highest level of evidence to designate health care decisions . However, with the increasing number of systematic reviews and meta-analyses, treatment decisions can entail reading several systematic reviews. Therefore, it is appropriate to conduct an overview of reviews or "umbrella review" to compile data from multiple systematic reviews to support health care decision-making . Umbrella reviews use a systematic method similar to systematic reviews, to compile information from systematic reviews instead of individual studies. In addition, umbrella reviews may examine different interventions for a particular disease, while systematic reviews usually focus on a single intervention. The comparison of similar systematic reviews can indicate the consistent or conflicting nature of evidence and addresses the knowledge gap in available evidence for future research . The present umbrella review aimed to gather and summarize the data from published systematic reviews that compared NSMD with adjunctive treatments and NSMD alone for managing PIM. The focus questions of the present umbrella review were: What is the effectiveness of the NSMD with adjunctive measures compared with NSMD alone in managing PIM? What is the quality of the systematic reviews concerning the effectiveness of adjunctive treatment in managing PIM?
The protocol was developed and registered on PROSPERO (CRD42021254350) before the systematic search for the systematic reviews. The SRs included in this umbrella review reported a comparison of the effectiveness of NSMD combined with adjunctive interventions versus NSMD alone. The eligibility criteria and search strategy were constructed with the aid of the following PICOS elements: Population—adult patients with the diagnosis of peri-implant mucositis Intervention—non-surgical mechanical debridement with adjunctive interventions Comparison—non-surgical mechanical debridement alone Outcomes—clinical, microbiological and immunological parameters Study design—systematic reviews with or without meta-analysis. Search strategy Seven electronic databases, including Cochrane Library, Embase (via Ovid), MEDLINE (via Pubmed), Proquest, Prospero, Scopus and Web of Science, were identified for published reviews. The search for unpublished and informally published reviews was further attempted in the last four databases. The search term "(peri-implant OR periimplant) AND (mucositis OR disease* OR infect* OR inflammation) AND (treatment OR therapy* OR intervention OR management OR managing OR instrumentation OR "plaque removal" OR intervention)" was used to search for title, abstract and keywords when applicable. Two search strategies were applied for each database. The first strategy was the keyword search with a document-type filter for reviews or systematic reviews. The second strategy was the keyword search without a document-type filter, but the additional "systematic review" term was incorporated into the original search term. Combining two search strategies ensures comprehensiveness of the results since the search with a document-type filter might be of limited sensitivity, and some electronic databases such as Embase could not provide a search filter to identify systematic reviews successfully . In addition, the search was restricted to the English language. All the seven electronic databases were searched for relevant reviews with a publication date until September 15th, 2021. The references, journal title, study title, authors, years of publication and abstract of searched results were exported to an EndNote library (using the management software EndNote X9.3.3, macOS Big Sur). Any duplication was removed before constructing the final list for review selection. Review selection and additional searches The review selection included two steps. The first step was screening the reviews by assessing the title and abstract. The second step involved screening by appraising the full text using the table of eligibility criteria (Additional file : Table S1). All steps were performed independently, by two reviewers (SC and AA). Any disparity was settled down by consensus and consultation with the third independent person in the team (GP). The eligible systematic reviews were required to include the primary studies of adult patients diagnosed with peri-implant mucositis. The SRs that exclusively appraised treatment for peri-implantitis were excluded. The included systematic reviews summarized the outcome of primary studies and may also synthesize the data using descriptive analysis or meta-analysis. The primary studies included in the potential SRs were assessed against PICO elements using the same table of eligibility criteria (Additional file : Table S1). The irrelevant studies were identified and excluded. The SRs included in this umbrella review contain a minimum of one eligible primary study. Cohen's k statistic was used to calculate an agreement between two reviewers. The inter-rater agreement for the title and abstract screening was 99.84%, and the Cohen kappa value was 0.97. The inter-rater agreement for full-text selection was 95%, and the Cohen kappa value was 0.89. In addition, hand-searching of the reference lists of the included systematic reviews was carried out to identify additional systematic reviews relevant to the PICO framework of this umbrella review. Data collection One of the reviewers (SC) performed the data collection systematically. The data were entered directly into the spreadsheet and checked by the other reviewer (AA). Any disparity in data extraction was resolved by consensus. All included SRs were extracted for the data on the general characteristics of the reviews, clinical and methodological characteristics, synthesized results and conclusion. In addition, the data of the primary studies reported in the selected systematic reviews were also extracted for bibliographic details, clinical and methodology characteristics, result and conclusion, and quality assessment (risk of bias). The data items of the systematic reviews and primary studies are listed in Additional file : document 1. The data were cross-checked with the original articles or the other systematic reviews to correct any reporting errors or completing the required information when the SR report was unclear. In cases where the original reviewers did not provide the overall risk-of-bias of each primary study, the suggested algorithm in the Cochrane handbook for systematic reviews of interventions was applied . The risks were summarized as low, unclear or high based on the presence of the greatest risk in the key domains within the individual studies. Assessment of methodological quality of systematic reviews The SRs included in the present umbrella review were assessed for the quality of methodology using AMSTAR 213. AMSTAR 2 is widely used to identify the quality of systematic reviews that include randomized or non-randomized trials of healthcare interventions. The overall confidence of each SR was determined based on the flaws or weaknesses in seven critical and nine non-critical domains . The overall confidence of a systematic review was high when there was none of the critical flaw or only one non-critical flaw. The overall confidence was moderate when there was no critical flow or more than one non-critical flaw. The overall confidence was low when there was one critical flaw, and the overall confidence was critically low when there was more than one critical flaw. The assessment was performed independently by two reviewers (SC and AA). Any disparity in the assessment was settled by consensus. Data synthesis Most of the SRs did not provide a definitive conclusion concerning the effect on the outcome measurement (e.g., bleeding on probing or probing depth of peri-implant sulcus) but tabulated the data from the included primary studies, a decision was made to apply the vote-counting method and present the ratio of the primary studies of each outcome parameter to illustrate the outcome of the available evidence in each systematic review. An additional conclusion was further made based on the ratio of the primary studies . A minimum of three primary studies in each SR was required to conclude the effect of the adjunctive interventions. The adjunctive treatment was considered an additional benefit if more than two-thirds of the primary studies presented significant positive results.
Seven electronic databases, including Cochrane Library, Embase (via Ovid), MEDLINE (via Pubmed), Proquest, Prospero, Scopus and Web of Science, were identified for published reviews. The search for unpublished and informally published reviews was further attempted in the last four databases. The search term "(peri-implant OR periimplant) AND (mucositis OR disease* OR infect* OR inflammation) AND (treatment OR therapy* OR intervention OR management OR managing OR instrumentation OR "plaque removal" OR intervention)" was used to search for title, abstract and keywords when applicable. Two search strategies were applied for each database. The first strategy was the keyword search with a document-type filter for reviews or systematic reviews. The second strategy was the keyword search without a document-type filter, but the additional "systematic review" term was incorporated into the original search term. Combining two search strategies ensures comprehensiveness of the results since the search with a document-type filter might be of limited sensitivity, and some electronic databases such as Embase could not provide a search filter to identify systematic reviews successfully . In addition, the search was restricted to the English language. All the seven electronic databases were searched for relevant reviews with a publication date until September 15th, 2021. The references, journal title, study title, authors, years of publication and abstract of searched results were exported to an EndNote library (using the management software EndNote X9.3.3, macOS Big Sur). Any duplication was removed before constructing the final list for review selection.
The review selection included two steps. The first step was screening the reviews by assessing the title and abstract. The second step involved screening by appraising the full text using the table of eligibility criteria (Additional file : Table S1). All steps were performed independently, by two reviewers (SC and AA). Any disparity was settled down by consensus and consultation with the third independent person in the team (GP). The eligible systematic reviews were required to include the primary studies of adult patients diagnosed with peri-implant mucositis. The SRs that exclusively appraised treatment for peri-implantitis were excluded. The included systematic reviews summarized the outcome of primary studies and may also synthesize the data using descriptive analysis or meta-analysis. The primary studies included in the potential SRs were assessed against PICO elements using the same table of eligibility criteria (Additional file : Table S1). The irrelevant studies were identified and excluded. The SRs included in this umbrella review contain a minimum of one eligible primary study. Cohen's k statistic was used to calculate an agreement between two reviewers. The inter-rater agreement for the title and abstract screening was 99.84%, and the Cohen kappa value was 0.97. The inter-rater agreement for full-text selection was 95%, and the Cohen kappa value was 0.89. In addition, hand-searching of the reference lists of the included systematic reviews was carried out to identify additional systematic reviews relevant to the PICO framework of this umbrella review.
One of the reviewers (SC) performed the data collection systematically. The data were entered directly into the spreadsheet and checked by the other reviewer (AA). Any disparity in data extraction was resolved by consensus. All included SRs were extracted for the data on the general characteristics of the reviews, clinical and methodological characteristics, synthesized results and conclusion. In addition, the data of the primary studies reported in the selected systematic reviews were also extracted for bibliographic details, clinical and methodology characteristics, result and conclusion, and quality assessment (risk of bias). The data items of the systematic reviews and primary studies are listed in Additional file : document 1. The data were cross-checked with the original articles or the other systematic reviews to correct any reporting errors or completing the required information when the SR report was unclear. In cases where the original reviewers did not provide the overall risk-of-bias of each primary study, the suggested algorithm in the Cochrane handbook for systematic reviews of interventions was applied . The risks were summarized as low, unclear or high based on the presence of the greatest risk in the key domains within the individual studies.
The SRs included in the present umbrella review were assessed for the quality of methodology using AMSTAR 213. AMSTAR 2 is widely used to identify the quality of systematic reviews that include randomized or non-randomized trials of healthcare interventions. The overall confidence of each SR was determined based on the flaws or weaknesses in seven critical and nine non-critical domains . The overall confidence of a systematic review was high when there was none of the critical flaw or only one non-critical flaw. The overall confidence was moderate when there was no critical flow or more than one non-critical flaw. The overall confidence was low when there was one critical flaw, and the overall confidence was critically low when there was more than one critical flaw. The assessment was performed independently by two reviewers (SC and AA). Any disparity in the assessment was settled by consensus.
Most of the SRs did not provide a definitive conclusion concerning the effect on the outcome measurement (e.g., bleeding on probing or probing depth of peri-implant sulcus) but tabulated the data from the included primary studies, a decision was made to apply the vote-counting method and present the ratio of the primary studies of each outcome parameter to illustrate the outcome of the available evidence in each systematic review. An additional conclusion was further made based on the ratio of the primary studies . A minimum of three primary studies in each SR was required to conclude the effect of the adjunctive interventions. The adjunctive treatment was considered an additional benefit if more than two-thirds of the primary studies presented significant positive results.
Description of included systematic reviews The final list of 701 search results was constructed after de-duplication. The title and abstract screening resulted in the exclusion of 679 references. Out of the potential 22 references for full-text screening, ten references were excluded after assessing the full text. The reasons for the exclusion of each study are presented in Additional file : Table S2. Twelve SRs were included in the present umbrella review. All were published outside the Cochrane Database of Systematic Reviews (CDSR) from 2015 to 2020. The flow diagram of the review selection process is illustrated in Fig. . The PICO frameworks in the included SRs differed. Some included populations with PIM and peri-implantitis or compared different adjunctive treatments. Among the included SRs, only one had a specific focus population and adjunctive treatment , analyzing adjunctive laser and photodynamic therapy for PIM. Eight SRs reviewed a specific adjunctive intervention for both peri-implant mucositis and peri-implantitis, which encompassed antiseptics probiotics [ – ] air-polishing , and laser and photodynamic treatment . Two SRs reviewed all adjunctive treatments for PIM, and one reviewed all adjunctive intervention for both PIM and peri-implantitis. The summary of bibliographic information and the PICOS frameworks of included SRs are presented in Table . The assessment of each AMSTAR 2 criteria and the overall confidence of the systematic reviews are presented in Table . Affected by critical flaws, seven systematic reviews were scored as "low" in overall confidence, while the other five were scored as "critically low". The most common critical flaw was the lack of interpretation of the risk of bias when discussing the result, in nine systematic reviews [ , , – ]. The second frequent flaw was lack of publication bias assessment, in five systematic reviews [ – ]. Two SRS did not present the list of excluded studies and the reason for exclusion and two did not use appropriate methods for the statistical combination when performing a meta-analysis. Description of primary studies included in SRs The included SRs assessed clinical studies published between 2014 and 2020, including 17 clinical trials (CTs):16 randomized controlled clinical trials (RCTs) and one controlled clinical trial (CCT) . Twelve SRs included two to ten relevant CTs. Some of these 17 individual studies were included in more than one systematic review. The overlaps in the CTs among the SRs are presented as a citation network in Fig. . The summary of the outcome, meta-analysis and vote-counting is presented in Table , grouped by type of the adjunctive treatment. The characteristics of the primary studies and overlapping among the systematic reviews are presented grouped by type of adjunctive treatment in Additional file : Table S3–S7. The risk of bias of the clinical trials varied from low to high. The SRs used different tools to assess included CTs. Most used the first version of the Cochrane risk-of-bias tool . One used the updated version 30 and one used its original criteria. Notably, the risk of bias assigned to these individual primary studies differed between systematic reviews even if the grading system was the same. Interventions and comparators in included primary studies The included SRs reviewed five RCTs [ – ] regarding adjunctive antiseptic treatment. Chlorhexidine gluconate was used in all trials in the form of gel, solution or spray with different concentrations: 0.12%, 0.2%, 0.5%. The application period differed from 10 days to 12 weeks among those studies. Six RCTs [ – ] of adjunctive probiotic treatment were identified. Most studies use probiotics containing Lactobacillus reuteri in lozenges, which were dissolved in the mouth. Only one study40 used probiotics containing Lactobacillus brevis and Lactobacillus plantarum . This study also provided a probiotic mixture applied in the peri-implant sulcus in the clinic before letting the patients continue with the lozenges. The administration time for the probiotic lozenges varied from 3 weeks to 3 months. The studies of air-polishing included one randomized controlled clinical trial and one controlled clinical trial . Both trials experimented with a glycine powder air-polishing device by applying at a submucosal level for five seconds on each affected implant site. Two RCTs assessed adjunctive laser and photodynamic treatment. They both used a diode laser in pulse mode by applying for 30 s per surface; however, the wavelength and power settings differed between the two studies. Two adjunctive antibiotic treatment RCTs were reviewed. One study assessed the systemic antibiotic Azithromycin, prescribed for 5 days . Another study evaluated local antibiotic therapy, applying tetracycline HCl fibres in the peri-implant sulcus for ten days . All the controlled trials compared the adjunctive treatment with NSMD (using either hand or ultrasonic instrument), polishing (using polishing paste and rubber cup), or both. However, some studies include adjunctive treatments in their conventional treatment protocol. One of the probiotic treatment studies had photodynamic therapy as part of the control treatment. Some studies included peri-implant sulcus irrigation using 3% hydrogen peroxide , 0.12% CHX + 0.05% CPC45, or 0.12% CHX mouth rinsing in their control treatment. Data analysis in included SRs All included SRs summarized the data of the individual studies and provided a narrative conclusion regarding the effectiveness of the adjunctive treatments. However, six SRs [ – , , ] performed MA of effects for additional benefits of the adjunctive treatment for peri-implant mucositis. These MAs showed no significant difference in probing depth, bleeding on probing, clinical attachment level, or plaque index outcomes between control (conventional treatment or NSMD) and test (conventional treatment with adjunctive therapy) groups. Four SRs [ – , ] did not conduct MA owing to heterogeneity present in the clinical trials concerning population (i.e., dental implant and restoring unit, peri-implant case definition), adjunctive treatment protocol, conventional treatment protocol, and outcome measurement (i.e., clinical parameters and follow-up period for evaluation). Two SRs conducted the MA of similar clinical outcomes parameters (bleeding on probing, gingival index and probing depth) of different types of adjunctive treatment (antibiotic, antiseptic, air-polishing and probiotic treatment); therefore, the present umbrella review analyzed the MA outcomes of these two SRs .
The final list of 701 search results was constructed after de-duplication. The title and abstract screening resulted in the exclusion of 679 references. Out of the potential 22 references for full-text screening, ten references were excluded after assessing the full text. The reasons for the exclusion of each study are presented in Additional file : Table S2. Twelve SRs were included in the present umbrella review. All were published outside the Cochrane Database of Systematic Reviews (CDSR) from 2015 to 2020. The flow diagram of the review selection process is illustrated in Fig. . The PICO frameworks in the included SRs differed. Some included populations with PIM and peri-implantitis or compared different adjunctive treatments. Among the included SRs, only one had a specific focus population and adjunctive treatment , analyzing adjunctive laser and photodynamic therapy for PIM. Eight SRs reviewed a specific adjunctive intervention for both peri-implant mucositis and peri-implantitis, which encompassed antiseptics probiotics [ – ] air-polishing , and laser and photodynamic treatment . Two SRs reviewed all adjunctive treatments for PIM, and one reviewed all adjunctive intervention for both PIM and peri-implantitis. The summary of bibliographic information and the PICOS frameworks of included SRs are presented in Table . The assessment of each AMSTAR 2 criteria and the overall confidence of the systematic reviews are presented in Table . Affected by critical flaws, seven systematic reviews were scored as "low" in overall confidence, while the other five were scored as "critically low". The most common critical flaw was the lack of interpretation of the risk of bias when discussing the result, in nine systematic reviews [ , , – ]. The second frequent flaw was lack of publication bias assessment, in five systematic reviews [ – ]. Two SRS did not present the list of excluded studies and the reason for exclusion and two did not use appropriate methods for the statistical combination when performing a meta-analysis.
The included SRs assessed clinical studies published between 2014 and 2020, including 17 clinical trials (CTs):16 randomized controlled clinical trials (RCTs) and one controlled clinical trial (CCT) . Twelve SRs included two to ten relevant CTs. Some of these 17 individual studies were included in more than one systematic review. The overlaps in the CTs among the SRs are presented as a citation network in Fig. . The summary of the outcome, meta-analysis and vote-counting is presented in Table , grouped by type of the adjunctive treatment. The characteristics of the primary studies and overlapping among the systematic reviews are presented grouped by type of adjunctive treatment in Additional file : Table S3–S7. The risk of bias of the clinical trials varied from low to high. The SRs used different tools to assess included CTs. Most used the first version of the Cochrane risk-of-bias tool . One used the updated version 30 and one used its original criteria. Notably, the risk of bias assigned to these individual primary studies differed between systematic reviews even if the grading system was the same.
The included SRs reviewed five RCTs [ – ] regarding adjunctive antiseptic treatment. Chlorhexidine gluconate was used in all trials in the form of gel, solution or spray with different concentrations: 0.12%, 0.2%, 0.5%. The application period differed from 10 days to 12 weeks among those studies. Six RCTs [ – ] of adjunctive probiotic treatment were identified. Most studies use probiotics containing Lactobacillus reuteri in lozenges, which were dissolved in the mouth. Only one study40 used probiotics containing Lactobacillus brevis and Lactobacillus plantarum . This study also provided a probiotic mixture applied in the peri-implant sulcus in the clinic before letting the patients continue with the lozenges. The administration time for the probiotic lozenges varied from 3 weeks to 3 months. The studies of air-polishing included one randomized controlled clinical trial and one controlled clinical trial . Both trials experimented with a glycine powder air-polishing device by applying at a submucosal level for five seconds on each affected implant site. Two RCTs assessed adjunctive laser and photodynamic treatment. They both used a diode laser in pulse mode by applying for 30 s per surface; however, the wavelength and power settings differed between the two studies. Two adjunctive antibiotic treatment RCTs were reviewed. One study assessed the systemic antibiotic Azithromycin, prescribed for 5 days . Another study evaluated local antibiotic therapy, applying tetracycline HCl fibres in the peri-implant sulcus for ten days . All the controlled trials compared the adjunctive treatment with NSMD (using either hand or ultrasonic instrument), polishing (using polishing paste and rubber cup), or both. However, some studies include adjunctive treatments in their conventional treatment protocol. One of the probiotic treatment studies had photodynamic therapy as part of the control treatment. Some studies included peri-implant sulcus irrigation using 3% hydrogen peroxide , 0.12% CHX + 0.05% CPC45, or 0.12% CHX mouth rinsing in their control treatment.
All included SRs summarized the data of the individual studies and provided a narrative conclusion regarding the effectiveness of the adjunctive treatments. However, six SRs [ – , , ] performed MA of effects for additional benefits of the adjunctive treatment for peri-implant mucositis. These MAs showed no significant difference in probing depth, bleeding on probing, clinical attachment level, or plaque index outcomes between control (conventional treatment or NSMD) and test (conventional treatment with adjunctive therapy) groups. Four SRs [ – , ] did not conduct MA owing to heterogeneity present in the clinical trials concerning population (i.e., dental implant and restoring unit, peri-implant case definition), adjunctive treatment protocol, conventional treatment protocol, and outcome measurement (i.e., clinical parameters and follow-up period for evaluation). Two SRs conducted the MA of similar clinical outcomes parameters (bleeding on probing, gingival index and probing depth) of different types of adjunctive treatment (antibiotic, antiseptic, air-polishing and probiotic treatment); therefore, the present umbrella review analyzed the MA outcomes of these two SRs .
This umbrella review included 12 systematic reviews to examine the effect of adjunctive measures on PIM treatment. Considering PICOS framework, not all of the included reviews established definite and narrow PICOS frameworks. There was also variability in PICOS elements (i.e., population, intervention and comparators, outcomes, and study types) among the included systematic reviews. The population and intervention elements were not well specified in most of the included systematic reviews. The focused populations had both PIM and peri-implantitis and intervention included all types of adjunctive treatments reported in literature. For instance, two systematic reviews included studies of peri-implant mucositis exclusively; however, they did not specify the types of the studied intervention. Considering case definition of PIM, most systematic reviews did not specify the diagnostic criteria. The inclusion of the studies of peri-implant mucositis was based on the diagnosis assigned in the respective publications. Only one systematic review referred to the 2017 World Workshop classification . Most SRS used more than one parameter to assess the treatment outcome. The most studied outcome was probing depth, followed by bleeding on probing, plaque index and clinical attachment level. There were differences between the control treatments among the individual studies. While most studies had NSMD as conventional treatment, some also added antiseptic treatment [ , , , , ] or photodynamic treatment in their control treatments. In addition, there were discrepancies in NSMD protocol, as included studies used curettes or ultrasonic devices, rubber cups and polishing paste, or both. Some SRs also specified a minimum follow-up time of 1 month or 3 months . The follow-up period of the included primary studies ranged from 1 to 8 months. Most of the studies presented no significant difference between the test and control groups throughout the period of their follow-up. Only two primary studies regarding adjunctive antiseptic treatments showed significant differences that favored the test groups in the short term of the first 3 months; however, the studies did not continue the follow-up to see whether the effect would persist in a longer follow-up period. Three SRs [ – ] (SRs) reviewed different adjunctive treatments and concluded that there was no additional benefit in the adjunctive treatment of PIM when compared to NSMD. Five SRs which reviewed antiseptics air-polishing , probiotics , and laser and photodynamic treatment also concluded that the adjunctive treatment was not superior to conventional treatment. Four SRs regarding probiotics and laser and photodynamic therapy suggested that the benefit of adjunctive treatment was inconclusive and called for further clinical trials. Three SRs regarding antiseptic treatment that performed MA indicated no significant difference in probing depth [ , , ] bleeding on probing , and clinical attachment level between groups of conventional treatment and adjunctive treatment. MA for effects of adjunctive probiotic treatment was carried out in two SRs .and noted no significant difference between conventional and adjunctive treatment groups in probing depth, bleeding on probing, and plaque index outcomes. Only one SR of adjunctive laser and photodynamic treatment conducted MA. Adjunctive laser therapy did not significantly differ in probing depth from conventional treatment. The effectiveness of the adjunctive treatments presented in the SRs was further determined by vote-counting based on a statistically significant difference in comparison of clinical parameters. Adjunctive antiseptic treatment shows no additional benefit in improving probing depth 16 and bleeding on probing . There was also no additional benefit of adjunctive probiotic treatment in improving probing depth, bleeding on probing, and plaque index . The effectiveness of the other adjunctive treatments could not be synthesized by vote-counting as the SRs included less than three primary studies. The included SRs' overall confidence (AMSTAR 2) ranged from low to critically low. Overall, the summarized evidence indicated that adjunctive treatments did not significantly improve the clinical outcome parameters compared to NSMD. Despite a rigorous methodology, this umbrella review has limitations. Firstly, the included systematic reviews and clinical trials were not of high quality and were few in number, including 12 SRs and 17 primary studies. About two-thirds of the primary studies presented with a high risk of bias. The confidence of the SRs was also low to critically low, according to the AMSTAR 2 assessment. Furthermore, the included SRs analyzed overlapping primary studies, which could account for their consistent findings. Finally, the present umbrella review opted for a non-statistical approach in by implementing the vote-counting method to identify adjunctive treatment effectiveness for each clinical parameter. However, this approach has limitations as vote-counting does not consider the effect size and the precision of the statistical estimate of the primary studies. Systematic reviews with a narrow scope were lacking and this umbrella review also demonstrated a lack of randomized controlled clinical trials. Sufficient RCTs of good quality need to be available to enable systematic reviews with a clear and narrow scope. While the conclusion of this umbrella review does not support the general use of adjunctive treatment in managing PIM, patient subsets that may receive benefit from these therapies remain an open question. Clinical trials in patients with a history of periodontitis, diabetes or smoking with increased risk for peri-implant diseases are warranted. In addition, the adjunctive treatment for implants with local risk indicators may be considered . PIM around the deep mucosal tunnel implant presents delayed disease resolution after non-surgical debridement . Implant design with an over-contour prosthetic profile also could pose risks for peri-implant health . The role of adjunctive treatments in such situations needs further investigation. Furthermore, there are several reported adjuncts to NSMD for peri-implant disease including ozone therapy , desiccant application , electrolytic cleaning procedures and herbal medications for which no evidence was synthesized in the systematic reviews of peri-implant mucositis included in the present study. Therefore, conclusions regarding the efficacy of these measures cannot be drawn from the present study. More clinical trials and subsequent SRs are warranted in order to clarify the effectiveness of emerging therapies.
A small number of primary studies and SRs address outcomes of adjunctive treatment for peri-implant mucositis and the quality of available SRs is generally low. Most of the primary studies have a high risk of bias, with discrepancy in the outcome measurements and follow-up times reported. Within these limitations, the present umbrella review failed to show significant benefit from adjunctive treatments to improve the outcome of NSMD in PIM and no specific adjunctive therapies have emerged as clearly superior to NSMD, so far.
Additional file 1: Table S1. Eligibility criteria form. Table S2. Excluded reviews at the assessment of full-text and the main reasons for exclusion. Table S3. Characteristic of primary studies and overlap amongst systematic reviews of adjunctive antiseptic treatment. Table S4. Characteristic of primary studies and overlap amongst systematic reviews of adjunctive probiotic treatment. Table S5. Characteristic of primary studies and overlap amongst systematic reviews of adjunctive air-polishing treatment. Table S6. Characteristic of primary studies and overlap amongst systematic reviews of adjunctive laser and photodynamic treatment. Table S7. Characteristic of primary studies and overlap amongst systematic reviews of adjunctive local and systemic antibiotic treatment. Additional document 1. Data items of the systematic reviews and primary studies .
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Perceived determinants of the use of coercion in inpatient child and adolescent psychiatry: a qualitative interview study with staff | b6a1eda5-1432-45af-8763-e31f22b759c3 | 11912791 | Psychiatry[mh] | Coercive measures (i.e., mechanical and physical restraint, seclusion, and involuntary treatment including medication and forced tube-feeding) remain commonly used both in adult psychiatry and in child and adolescent psychiatry (CAP) , despite considerable concerns regarding possible negative effects [ – ]. Coercive measures are usually applied to manage conflict (e.g., severe self-harm or aggression towards others) or to enforce patient adherence to treatment. There is a growing movement to reduce or even abolish coercion in mental health services; the Council of Europe has urged member states to abolish coercive practices , while the World Psychiatric Association calls for strategies that respect patient autonomy and promote non-coercive care . Efforts to reduce the use of coercive measures include different multimodal approaches, often combining prevention strategies, staff training, patient-centred care, and organisational changes [ – ]. However, as these multicomponent interventions target both individual and structural factors, isolating the effects of specific components remains challenging . Formal coercion refers to legally authorised interventions, including involuntary hospitalisation, and coercive measures. A dimension of coercion that remains less explored is informal coercion , sometimes referred to as “treatment pressures” . Informal coercion lacks a comprehensive and universally accepted definition, but it refers to various non-legal strategies and interpersonal dynamics employed by healthcare professionals to influence treatment decisions . The coercion hierarchy proposed by Szmukler and Appelbaum outlines increasing levels of influence on patient decisions: from persuasion and interpersonal leverage (e.g., staff expressing disappointment about non-adherence) to inducements (e.g., offering incentives for treatment adherence), threats, and deception or strategic dishonesty. More recent additions to the conceptualisation of informal coercion include using a disciplinary style (e.g., enforcing ward rules through structured consequences, such as withholding food if the patient arrives late for dinner), referring to rules and routines, and coercion from other stakeholders . Despite its frequent occurrence in clinical practice , informal coercion has not yet received the same scientific attention as formal coercion. Systematic reviews of adult psychiatric staff attitudes towards coercive practices suggest that while coercive measure use is viewed as unavoidable and necessary at times, their administration is generally a negative experience for staff . Moreover, a paradigm shift seems to have occurred; from perceiving coercive measures as therapeutic with beneficial effects for the patient to viewing them as undesirable but necessary for ensuring safety . Another integrative review also found adult psychiatry nurses’ decision-making regarding coercive measures to be influenced by factors such as safety for all patients and staff, the perception of restraint as a necessary intervention but also to be used as a “last resort”, role conflicts, and their psychological impact on staff . This review also highlighted the importance of staffing levels and staffing experience in the decision-making process. Further, a scoping review of both quantitative and qualitative studies from adult psychiatry indicated highly variable attitudes towards coercive practices, in part shaped by professional background, cultural context and work experience . One previous qualitative study used ethical diaries to examine staff ethical considerations in inpatient CAP , indicating that participants rarely perceived formal coercion as problematic. However, some coercive measures were described as emotionally difficult to carry out. Apart from that study’s ethical perspective, no study to date has explored inpatient CAP staff understanding and attitudes towards coercive practices from a broader perspective. Exploring staff attitudes towards both formal and informal coercion is important to identify factors influencing its use; filling this knowledge gap could further inform the development of interventions to mitigate coercive practices. Study aims We aimed to explore inpatient CAP staff perceptions, clinical use and perceived determinants of coercive measures and informal coercion.
We aimed to explore inpatient CAP staff perceptions, clinical use and perceived determinants of coercive measures and informal coercion.
Study design We conducted a qualitative study on staff working in inpatient CAP in Sweden using semi-structured individual online video interviews. Setting Swedish CAP care is publicly funded and governed by national legislation, with inpatient care provided at specialised psychiatric units, typically separate from adult psychiatric care. In 2023, 2789 individuals received inpatient CAP care in Sweden, accounting for 39,495 inpatient days, with a median length of stay of 8.7 days, an overall bed occupancy rate of 75%, and 20% of all admissions being compulsory. . A survey across 28 European countries found that Sweden had the lowest inpatient CAP bed capacity per capita . This limited capacity may contribute to increased work-related stress, with more than half of staff in a recent Swedish inpatient CAP study considering resigning at least a few times per month . Further details, including the legislative framework, are provided in the supplementary material of our previous publication ( ) . Participant recruitment and sampling The inclusion criteria for participants required them to be working as nurses, senior consultants in child and adolescent psychiatry (psychiatrists), or heads of units in inpatient CAP units in Sweden for at least 6 months before and 6 months after a legal change regarding coercive measures on July 1, 2020. These occupational categories were selected because nurses implement coercive measures, senior consultants make the formal decisions, and heads of units oversee the overall practices within their units. Participant recruitment was halted in October 2021 following a critical statement issued by the Swedish Chief Parliamentary Ombudsman regarding legal practices related to the use of coercive measures in CAP inpatient care . This statement was considered likely to influence participants’ responses, potentially preventing them from accurately reflecting upon their current or prior practices. We recruited participants through e-mails to all regional heads of CAP in Sweden on April 28, 2021 (a reminder email was sent on May 10), requesting dissemination to all staff in inpatient CAP (i.e., a recruitment process in qualitative research referred to as gatekeepers). Staff interested in participation were asked to contact the project coordinator AM. Twelve potential participants reached out to the coordinator; two were not included due to insufficient clinical experience, and a third was excluded due to ongoing scheduling conflicts for the interview. A total of nine participants were included, see Table for an overview of participant characteristics. Data collection Individual interviews with participants were 73–110 min long (Mdn = 87 min) with a total audio recording time of 13 h and 28 min. AM (at the time a late-stage child and adolescent psychiatry resident) conducted the interviews in Swedish during May–August, 2021. No follow-up interviews with participants were conducted, and only AM and the individual participant was present during each interview. AM took field notes during and immediately after the interviews. Only the audio from the video interviews was recorded and transcribed verbatim by AM. Two participants were previously acquainted with AM through working in the same organisation. All participants were informed of AM’s interest in coercive measures and related legislation, her involvement in the research group, and her residency status. No further information about AM’s personal views on coercive measures or legislation was disclosed. The interviews partly addressed the impact of a newly introduced (July 1, 2020) stricter legislation regarding coercive measure use in Sweden. We analysed these data separately and presented them elsewhere . The interview guide was initially tested through a pilot interview with a child and adolescent psychiatry resident (not included in the study), after which it was revised for clarity. Information from a second planned pilot interview was included in the study, as feedback from that participant only led to minor changes in the wording of the guide. The interview guide (available in the appendix) was constructed to assess practices of compulsory care and coercive measure use, professionals’ comprehension of the changed legislation, and the use of informal coercion. To examine staff approaches to various complex patient behaviours, we constructed and used a fictional patient scenario (available in the appendix) featuring aggressive conduct, severe self-harm, and medication refusal based on clinical experience of the authors. We created the interview guide based on different theoretical frameworks, encompassing the Swedish legal framework, an implementation outcomes framework (reported elsewhere ) and Szmukler and Appelbaum’s suggested hierarchy of informal coercion . In this study, we use the term “informal coercion” rather than “treatment pressures” to reflect the inherently coercive nature of inpatient child and adolescent psychiatric care and the potentially heightened vulnerability of young patients to various forms of coercion. Our use of “informal coercion” focuses on this spectrum of practices that may affect patient autonomy, regardless of whether they are perceived as coercive by staff or patients or not. Data analysis Interview data were analysed using reflexive thematic analysis , a method for examining qualitative data that involves a reflexive and transparent approach by the researcher to develop meaningful themes. It includes six phases: 1) familiarizing with the data, 2) generating initial codes, 3) generating initial themes, 4) reviewing themes, 5) defining and naming themes, and 6) producing the report. An example of the coding process and theme development: Interviewer: “Something that has also been ongoing is the COVID-19 pandemic, which started even before the legal change and is still ongoing. How would you say it has affected your work, and the care provided in the ward?” Nurse: “Well, we have seen quite a significant increase in patients with worsening conditions, not at the beginning of COVID, and not in the first half-year, but now. When people are returning to school, many haven’t managed with school during the past year, parents have lost their jobs, there is financial hardship, and families are in crisis. For us, this means dealing with more difficult and severely ill patients, where the entire system is failing. Otherwise, we work a lot with networks, with parents to help them provide support, security, routines, and structure, but that has collapsed. So, COVID-19 has really undermined those families where the situation is most difficult. In cases where the parents have been affected — financially, losing their jobs, and with children at home more, spending more time together — it hasn’t been good for many children with mental health issues. So, for us, it’s coming to a head now; we also work very closely with the emergency department, being in the same unit, and there has been a huge increase in the number of families seeking help. And it increased, I mean, we are now fully occupied all the time; we previously have never had a situation like this since I started here in 2015, but now there are never any available places. So now we have to prioritize discharging fairly ill patients to make room for even more severely ill patients, and that feels sad, very sad. That it has come to this. With the number of beds we have, we end up discharging patients who are still not well, which we are not used to. They used to be as stable as possible and ready to be discharged into a secure network, but that is not the case now. We are discharging them into unsafe, uncertain situations. The social services are failing on their part; there aren’t enough resources. My impression — and I have no proof for this, just my experience — is that many children are falling between the cracks and suffering, and many come back to us, and we see that things have gone badly. And that feels very disheartening.” We initially coded this passage as Covid: sicker patients, Covid: more problems for families, Covid: substantial increase in patients, Covid: fully occupied, increased pressure, Covid: discharging ill patients, and Covid: ethical stress, lower quality of care . While the preliminary theme was labelled “Covid”, it was later revised to “ ” to encompass broader effects on the wards beyond those specifically related to the Covid pandemic. Under the supervision of AR, AM alone conducted a complete inductive coding of the interviews, using Microsoft Excel (version 365). Upon the initial analysis, we decided to report the data involving the potential impacts of the legal change separately. Further, given the paucity of evidence on the subject from inpatient CAP, data regarding informal coercion were deductively analysed using previously described hierarchies and theoretical models for informal coercion [ , , ]. Coding and theme development were iterative processes, with findings regularly discussed among the author group to refine themes and ensure consistency. Participant quotes included in the manuscript were translated using ChatGPT. To ensure accuracy and preserve the original nuances, AM carefully reviewed both the initial statements and their translations. Lived experience involvement and research team reflexivity The study findings were discussed comprehensively with a young adult with prior lived experience of compulsory inpatient CAP care and coercive measures. She was recruited through outreach on social media in collaboration with a former lived experience council. Based on this discussion, AM drafted the lived experience commentary in Swedish, which was then translated into English, reviewed, and approved by the expert. Reflexive thematic analysis acknowledges the active role of the researcher in developing themes, recognising that analysis is shaped by the researcher’s perspectives and interpretations. Throughout the process, we engaged in reflexivity by reflecting on our assumptions and how these may have influenced the analysis. NL (male), AM (female), SB (female) and RK (female) are child and adolescent psychiatrists and AM, RK (and formerly SB) currently serve as consultants at inpatient CAP units and have authorised the use of coercive measures for patients. AR (male) is a clinical psychologist who previously worked in adult psychiatric care. This study is part of a larger research project on inpatient CAP, with a specific focus on compulsory care and the use of coercive measures. Additional, partly related research areas, encompass risk factors for, and assessment and treatment of antisocial behaviour in adolescents (NL, RK), and patient-controlled admissions to psychiatric inpatient care (AR). Ethical considerations We submitted a consultative ethics application to the Swedish Ethical Review Authority, which determined that the study did not require an ethical permit as it did not involve the collection or management of any personal records (dnr: 2020–06898). Written and verbal informed consent were obtained from all participants before the interviews. The study is reported following the Consolidated Criteria for Reporting Qualitative Research (COREQ) .
We conducted a qualitative study on staff working in inpatient CAP in Sweden using semi-structured individual online video interviews.
Swedish CAP care is publicly funded and governed by national legislation, with inpatient care provided at specialised psychiatric units, typically separate from adult psychiatric care. In 2023, 2789 individuals received inpatient CAP care in Sweden, accounting for 39,495 inpatient days, with a median length of stay of 8.7 days, an overall bed occupancy rate of 75%, and 20% of all admissions being compulsory. . A survey across 28 European countries found that Sweden had the lowest inpatient CAP bed capacity per capita . This limited capacity may contribute to increased work-related stress, with more than half of staff in a recent Swedish inpatient CAP study considering resigning at least a few times per month . Further details, including the legislative framework, are provided in the supplementary material of our previous publication ( ) .
The inclusion criteria for participants required them to be working as nurses, senior consultants in child and adolescent psychiatry (psychiatrists), or heads of units in inpatient CAP units in Sweden for at least 6 months before and 6 months after a legal change regarding coercive measures on July 1, 2020. These occupational categories were selected because nurses implement coercive measures, senior consultants make the formal decisions, and heads of units oversee the overall practices within their units. Participant recruitment was halted in October 2021 following a critical statement issued by the Swedish Chief Parliamentary Ombudsman regarding legal practices related to the use of coercive measures in CAP inpatient care . This statement was considered likely to influence participants’ responses, potentially preventing them from accurately reflecting upon their current or prior practices. We recruited participants through e-mails to all regional heads of CAP in Sweden on April 28, 2021 (a reminder email was sent on May 10), requesting dissemination to all staff in inpatient CAP (i.e., a recruitment process in qualitative research referred to as gatekeepers). Staff interested in participation were asked to contact the project coordinator AM. Twelve potential participants reached out to the coordinator; two were not included due to insufficient clinical experience, and a third was excluded due to ongoing scheduling conflicts for the interview. A total of nine participants were included, see Table for an overview of participant characteristics.
Individual interviews with participants were 73–110 min long (Mdn = 87 min) with a total audio recording time of 13 h and 28 min. AM (at the time a late-stage child and adolescent psychiatry resident) conducted the interviews in Swedish during May–August, 2021. No follow-up interviews with participants were conducted, and only AM and the individual participant was present during each interview. AM took field notes during and immediately after the interviews. Only the audio from the video interviews was recorded and transcribed verbatim by AM. Two participants were previously acquainted with AM through working in the same organisation. All participants were informed of AM’s interest in coercive measures and related legislation, her involvement in the research group, and her residency status. No further information about AM’s personal views on coercive measures or legislation was disclosed. The interviews partly addressed the impact of a newly introduced (July 1, 2020) stricter legislation regarding coercive measure use in Sweden. We analysed these data separately and presented them elsewhere . The interview guide was initially tested through a pilot interview with a child and adolescent psychiatry resident (not included in the study), after which it was revised for clarity. Information from a second planned pilot interview was included in the study, as feedback from that participant only led to minor changes in the wording of the guide. The interview guide (available in the appendix) was constructed to assess practices of compulsory care and coercive measure use, professionals’ comprehension of the changed legislation, and the use of informal coercion. To examine staff approaches to various complex patient behaviours, we constructed and used a fictional patient scenario (available in the appendix) featuring aggressive conduct, severe self-harm, and medication refusal based on clinical experience of the authors. We created the interview guide based on different theoretical frameworks, encompassing the Swedish legal framework, an implementation outcomes framework (reported elsewhere ) and Szmukler and Appelbaum’s suggested hierarchy of informal coercion . In this study, we use the term “informal coercion” rather than “treatment pressures” to reflect the inherently coercive nature of inpatient child and adolescent psychiatric care and the potentially heightened vulnerability of young patients to various forms of coercion. Our use of “informal coercion” focuses on this spectrum of practices that may affect patient autonomy, regardless of whether they are perceived as coercive by staff or patients or not.
Interview data were analysed using reflexive thematic analysis , a method for examining qualitative data that involves a reflexive and transparent approach by the researcher to develop meaningful themes. It includes six phases: 1) familiarizing with the data, 2) generating initial codes, 3) generating initial themes, 4) reviewing themes, 5) defining and naming themes, and 6) producing the report. An example of the coding process and theme development: Interviewer: “Something that has also been ongoing is the COVID-19 pandemic, which started even before the legal change and is still ongoing. How would you say it has affected your work, and the care provided in the ward?” Nurse: “Well, we have seen quite a significant increase in patients with worsening conditions, not at the beginning of COVID, and not in the first half-year, but now. When people are returning to school, many haven’t managed with school during the past year, parents have lost their jobs, there is financial hardship, and families are in crisis. For us, this means dealing with more difficult and severely ill patients, where the entire system is failing. Otherwise, we work a lot with networks, with parents to help them provide support, security, routines, and structure, but that has collapsed. So, COVID-19 has really undermined those families where the situation is most difficult. In cases where the parents have been affected — financially, losing their jobs, and with children at home more, spending more time together — it hasn’t been good for many children with mental health issues. So, for us, it’s coming to a head now; we also work very closely with the emergency department, being in the same unit, and there has been a huge increase in the number of families seeking help. And it increased, I mean, we are now fully occupied all the time; we previously have never had a situation like this since I started here in 2015, but now there are never any available places. So now we have to prioritize discharging fairly ill patients to make room for even more severely ill patients, and that feels sad, very sad. That it has come to this. With the number of beds we have, we end up discharging patients who are still not well, which we are not used to. They used to be as stable as possible and ready to be discharged into a secure network, but that is not the case now. We are discharging them into unsafe, uncertain situations. The social services are failing on their part; there aren’t enough resources. My impression — and I have no proof for this, just my experience — is that many children are falling between the cracks and suffering, and many come back to us, and we see that things have gone badly. And that feels very disheartening.” We initially coded this passage as Covid: sicker patients, Covid: more problems for families, Covid: substantial increase in patients, Covid: fully occupied, increased pressure, Covid: discharging ill patients, and Covid: ethical stress, lower quality of care . While the preliminary theme was labelled “Covid”, it was later revised to “ ” to encompass broader effects on the wards beyond those specifically related to the Covid pandemic. Under the supervision of AR, AM alone conducted a complete inductive coding of the interviews, using Microsoft Excel (version 365). Upon the initial analysis, we decided to report the data involving the potential impacts of the legal change separately. Further, given the paucity of evidence on the subject from inpatient CAP, data regarding informal coercion were deductively analysed using previously described hierarchies and theoretical models for informal coercion [ , , ]. Coding and theme development were iterative processes, with findings regularly discussed among the author group to refine themes and ensure consistency. Participant quotes included in the manuscript were translated using ChatGPT. To ensure accuracy and preserve the original nuances, AM carefully reviewed both the initial statements and their translations.
The study findings were discussed comprehensively with a young adult with prior lived experience of compulsory inpatient CAP care and coercive measures. She was recruited through outreach on social media in collaboration with a former lived experience council. Based on this discussion, AM drafted the lived experience commentary in Swedish, which was then translated into English, reviewed, and approved by the expert. Reflexive thematic analysis acknowledges the active role of the researcher in developing themes, recognising that analysis is shaped by the researcher’s perspectives and interpretations. Throughout the process, we engaged in reflexivity by reflecting on our assumptions and how these may have influenced the analysis. NL (male), AM (female), SB (female) and RK (female) are child and adolescent psychiatrists and AM, RK (and formerly SB) currently serve as consultants at inpatient CAP units and have authorised the use of coercive measures for patients. AR (male) is a clinical psychologist who previously worked in adult psychiatric care. This study is part of a larger research project on inpatient CAP, with a specific focus on compulsory care and the use of coercive measures. Additional, partly related research areas, encompass risk factors for, and assessment and treatment of antisocial behaviour in adolescents (NL, RK), and patient-controlled admissions to psychiatric inpatient care (AR).
We submitted a consultative ethics application to the Swedish Ethical Review Authority, which determined that the study did not require an ethical permit as it did not involve the collection or management of any personal records (dnr: 2020–06898). Written and verbal informed consent were obtained from all participants before the interviews. The study is reported following the Consolidated Criteria for Reporting Qualitative Research (COREQ) .
Addressing aspects reportedly influencing the use of coercion, we identified the theme Trust and distrust in coercive or non-coercive approaches , with the subthemes Ward culture , and Available resources and strain . See Fig. for a synthesised view of how different aspects possibly influence the use of coercion or non-coercion. Data on informal coercion were described separately using previously proposed hierarchies of informal coercion, as detailed in the Background. Trust and distrust in coercive or non-coercive approaches This theme addresses different care aspects affecting trust and distrust in using coercion or non-coercion when managing conflicts at the ward. Trust or distrust in these strategies appeared to shape staff decision-making, with those expressing greater trust in non-coercive methods being more likely to use theses as first-line approaches, while staff with less trust more frequently relied on coercion. These attitudes were influenced not only by individual beliefs but also by broader structural and cultural factors at the ward level, as described in the two subthemes Ward culture and Available resources and strain . All participants perceived coercive measures as effective for solving exceedingly difficult acute situations with patients. They considered coercive measures justified in managing aggressive and violent patients, or severely self-harming patients, who were otherwise sometimes difficult to manage safely. A head of unit stated: “It’s the last resort as far as possible. Of course, one should appeal to voluntary participation and try to find solutions if possible to avoid them. Sometimes we end up in situations where we have to; there’s simply no other way.” Mechanical restraint was considered highly effective in securely containing patients and ensuring unit safety during dangerous situations. While some participants approved of seclusion as a safety measure, others found it unhelpful in managing patient behaviour, particularly when designated safe seclusion rooms were lacking. Some participants also viewed coercive measures as therapeutic: with tube-feeding and forced pharmacological injections aiding clinical recovery; seclusions and forced sedative injections soothing the patient; and physical and mechanical restraint establishing “behavioural boundaries” and calming the patients. However, coercive measures were generally seen as a failure for both the care system and staff, with some participants viewing them as such even when deemed necessary for patient care and management. A nurse said: “It’s always a failure on our part to have to use coercive measures. That means somewhere along the way we haven’t succeeded earlier, of course. So, I can’t say there’s anything positive about it other than, if there’s no other way out, then you have to do it in the best possible way.” Coercive measures were also considered by some participants as the “easy way out” compared to using non-coercive strategies, which were seen as requiring more effort from staff. In contrast, a few participants described coercive measures as something very rarely used, but highly necessary when used and then perceived as positive for the patient. Great trust in non-coercive approaches was expressed by some participants, who advocated their use as a first choice and highlighted their general effectiveness. In response to the fictional case of managing a psychotic youth with violent behaviour who had smashed a chair and was armed with the leg of the chair, a head of unit described: “If it’s a patient I know well, I would probably back out of the room and sit down—now, this may sound completely bizarre, but that’s likely what I would do first to see if we can change the situation, if we can change the patient’s experience. Because what I think is that they feel extremely cornered, pressured and that there is a lot of fear involved; that is what I would assume when I know so little.” In contrast, other participants saw non-coercive approaches as ideal but appeared to have low trust in their effectiveness and reported using coercive measures often at their units. A consultant described the response to the same fictional patient scenario: “I would of course press the alarm for help […], and we would make sure there were enough people… the question is how we would remove the weapon; that always makes it much, much more difficult. […] but there are two scenarios: getting people there and then […] overpowering the patient, bringing them down to the floor, and then disarming them, if possible. But when there’s a weapon involved, we are also quite quick to press the police alarm, and it’s precisely in such situations where it’s used, when there’s a weapon involved, because that makes it extremely difficult. […] It would probably be more about administering an injection right there and then, and then trying to seclude the patient.” When opting to use coercive measures, participants described the difficult balance between creating an immediate, potentially traumatic situation and preventing greater harm in the near future. For instance, while forcibly administering intramuscular injections could erode the patient’s trust in psychiatry, it was seen as ultimately necessary for their clinical recovery. Although aware of the risk of inducing acute or post-traumatic stress-related disorders, participants generally believed that immediate care needs should take precedence. Further, participants also stressed that using coercive measures (in contrast to non-coercive strategies) did not help patients develop new skills in demanding situations, a head of unit stated: “The idea is that the patient should be able to manage and survive with their anxiety, but instead, it’s like you’re waiting and just dealing with the anxiety when it comes [using coercive measures] rather than working on it.” Most interviewees advocated using coercive measures as a last option, emphasising the importance of exhausting voluntary options first and applying coercion only when absolutely necessary. Nonetheless, some participants stressed using coercive measures promptly to prevent escalation and harm to patients, staff, and property. Delaying the intervention was viewed as potentially harmful for the patient and unethical, especially regarding involuntary medication for severely ill patients with psychosis. Conversely, others argued against resorting to coercive measures too quickly, preferring to tolerate property damage rather than using force. Some participants reported that once coercive measures were applied to a patient, it became increasingly difficult to discontinue their use, indicating a possible negative spiral of coercion for both patient and staff. Two heads of units independently described: “One time might be okay, but not a second time, because then it’s like, it’s hard to turn back once you’ve started. Twice becomes a habit, you know.” “It must not become a habit to use coercive measures, not for the staff but also not for the patient to be subjected to coercive measures. That must not become a habit either, because I think that is absolutely negative.” In cases where patients were perceived as particularly challenging to manage, coercive approaches were often seen as inevitable, resulting in some individuals being subjected to multiple interventions. Several participants expressed a sense of resignation about using coercive measures, feeling forced to do so to manage acute situations, even when they believed it was not in the patient’s best interest. Also, some participants observed that certain patients seemed to deliberately provoke the use of coercive measures, either as a form of self-harm or to manage anxiety. This left some staff feeling powerless and forced to use coercive measures when confronted with escalating patient behaviour. Ward culture This subtheme captures various aspects of ward culture affecting trust or distrust in coercive practices, including staff feeling sanctioned to use coercion, perceived staff competence to manage conflict, and attitudes to patient involvement in care. All participants expressed a strong sense of responsibility for their patients’ well-being. They explicitly aimed to prevent harm, uphold the law, maintain patient dignity, and foster trust in psychiatric care. Participants saw their authority over patients as sanctioned by parents, the care system, the legal system (in compulsory care), and their role as adults caring for children. In addition to feeling responsible for the child’s well-being, participants also described a sense of responsibility for preserving the parent–child relationship. Staff sometimes assumed the”bad guy” role to protect parents from being seen as enforcers of coercion, aiming to maintain trust between the child and their family. In severe conflict situations, coercive measures were seen as essential to protect the patient and fellow staff. This combination of factors appeared to make participants feel sanctioned to use coercion if necessary: both formally authorised and informally validated. Those with experience from working in adult psychiatry noted more frequent use of coercion in the care for children and adolescents, particularly rapid responses to self-harm as compared to slower action against violence. This was attributed to a higher perceived urgency in preventing self-harm and a hesitancy to coerce violent children: attitudes that appeared to be rooted in ward culture and shaped by collective staff beliefs about appropriate responses in child/youth care. Participants had varied attitudes towards patient involvement in care . Most highlighted efforts to collaborate with patients, ensuring some control over their own care also when compulsorily treated. This included encouraging patient participation in care planning and adapting to their needs. Some argued for empowering the patients and prioritising their opinions, even when these conflicted with the care team’s views. There was a strong emphasis on understanding the patient and his/her behaviour, with some participants wishing for a greater focus on understanding the motivations behind non-cooperation. Coercive measures were perceived to clash with a caring perspective and negatively impact patient autonomy, though some staff tried to involve patients even during coercion, such as asking about their preferences when under restraint. One participant noted that in what was described as dysfunctional wards, staff could become cynical and lose curiosity in understanding the patient. Two participants stated that when staff made mistakes, they were encouraged to apologise to the patient and repair the relationship. In contrast, a few participants believed that staff knew what was best for patients and should disregard conflicting patient opinions. Some participants described rarely giving power to the patient regarding their care and stressed the importance of not questioning decisions in front of the patient, even if they personally disagreed with them. The level of perceived staff competence in managing conflict varied. Most participants considered risk situations as preventable or at least foreseeable, emphasising the importance of staff interventions such as de-escalation and diversion to avoid harm and coercion. Most participants believed experienced staff to be able to professionally manage conflicts, de-escalate situations when possible, and if necessary, use coercion effectively and respectfully. As stated by a nurse: “But then, when it starts, okay, now a situation is beginning to escalate, there is still a lot that can be done before needing to resort to a coercive measure. [...] Especially if you start with a low-arousal approach, talk the patient down, and offer medication, and so on. In my experience, this works nine times out of ten, or 99 times out of 100, if you have well-trained staff, a confident team, a good team leader, and confident doctors, along with routines in place.” Some expressed confidence in their colleagues’ ability to prevent and manage acute situations, ensuring voluntary patient cooperation. They trusted that inexperienced staff would receive support from experienced colleagues during a conflict. However, due to a shortage of experienced staff, other participants described a lack of trust in the ward’s overall competence to manage conflicts. Strategies for dealing with patient conflict varied. Some participants reported a clear ward strategy in dealing with patient behaviour that threatens the safety of the patient or others, always making active choices to engage in conflict or not, weighing in the risk of escalation and coercive measure use. Others described a more reactive, unstructured response to conflicts, risking quick escalation to coercion. Several interview subjects expressed a desire to work more preventively and noted that coercive measures had become routine, with insufficient efforts to provide alternative, non-coercive strategies. Available resources and strain This subtheme describes how the care was negatively affected by participant-reported increased work strain on the wards, paired with fewer resources. See Fig. for a proposed model of the subtheme. All participants reported substantial increases in patients seeking psychiatric emergency care and requiring hospitalisation, leading to high bed occupancy. In particular, involuntarily hospitalised patients with severe restrictive eating disorders had increased over the last years. Stricter requirements for admission following the shortage of beds resulted in admissions of only the most severely ill, mostly compulsorily treated patients being admitted, leaving few beds available for voluntary patients. High bed occupancy and increased severity of patient morbidity were described to negatively affect care quality. Participants perceived the wards as becoming more dysfunctional, with staff struggling to properly manage patients’ psychiatric symptoms, leading to worsened symptoms among patients that the staff had previously been able to manage. Some participants noted more frequent use of coercive measures, with incidents of violence, threats, and self-harm becoming more common. A senior consultant described: “What I can see is a worrying trend with more admissions under compulsory psychiatric care, increased pressure, and a minor system collapse that risks undermining the protective factors that have previously been important for preventing the need for coercive measures. […] because the situations have become more strained, and the staffing shortages are becoming more troubling, with experienced staff leaving, and so on.” Coercive measure use was perceived as a negative, stressful, and potentially traumatising experience for both patients and staff. Interviewees linked coercive measure use to increased staff sick leave or job resignation and highlighted the risk that they would be used as punishment and their detrimental impact on patient-staff relationships. As described above, participants highlighted that increased strain on the wards was compounded by insufficient resources. Most participants reported high staff turnover with difficulties to attract and keep experienced personnel, further reducing care quality. However, one head of unit described a well-functioning ward with many experienced personnel and low staff turnover: “Staffing, staffing, staffing, and then we also prevent a lot of coercive measures. […] And the young people go to bed around ten or eleven, and then it’s pretty quiet and calm, except if someone is really struggling, in which case there are two people who can take care of them, find other ways to handle it. If they need three, then there are three; if they need four, then there are four. This winter, they needed five, so they got five. I mean, it costs money to run inpatient care, but it also costs to provide good care.” Participants reported that the Covid-19 pandemic impacted noticeably on the wards, initially leading to a decrease in patients seeking inpatient care. However, by late 2020 and early 2021, admission rates increased again substantially; patients were then often more severely ill than before. Participants attributed this to reduced access to outpatient care, missed or cancelled appointments, or an inability to engage in digital consultations (many outpatient meetings were scheduled as digital meetings). The pandemic’s broader societal effects, particularly on socioeconomically disadvantaged families, were also seen as contributors to increased strain on psychiatric services. Using informal coercion Overall, informal coercion was primarily used to ensure adherence to treatment deemed to be in the patient’s best interest. Participants justified its use when they believed the care team knew better than the patient. Strategies for handling non-cooperative patients varied according to at least two different processes. Some participants maintained a consistent level of treatment pressure, mostly with repeated persuasion efforts over time to wear down patient resistance to intervention. Others employed a stepped approach, gradually increasing pressure until the patient complied with the least amount of coercion necessary. We found that all participants employed persuasion : some aimed to decide on the patient’s behalf, while others tried to motivate patients to accept voluntary care by discussing the pros and cons and encouraging ongoing treatment. A consultant stated: “I believe more in this kind of flexibility and thinking about what we can let this young person ‘win’ over, sort of like negotiating, and I often talk a lot about compromising and trying to explain what that word means, that you can’t always get everything you want, like ‘you’re thinking that you should get this, but you can’t have it all, but would you take half? If we try to meet halfway, where would we end up?’ and so on.” However, some participants emphasised that in acute states of mental illness, attempts at negotiating or persuading waste precious time and can be counterproductive, as patients are rarely responsive during these periods. Others described extended efforts to obtain voluntary treatment agreements. Interpersonal leverage seemed to be used rarely. Some participants reported coercion by others as frequently exercised , usually by parents, while others intentionally avoided involving parents in treatment adherence, allowing the care staff to take on the role of the “bad” enforcer and leaving the parents as the supportive “good” figures. Inducements seemed to be perceived as less problematic than treatment pressures lower down in the informal coercion hierarchy . Participants described efforts to find motivating factors; for instance, offering children a soft drink, ice cream or sweets as a positive enforcer to take their medication, combining them with persuasion. A nurse said: “Yeah, but you do that sometimes anyway, like, ‘come on, just take your medicine and then we’ll go play ping pong’ – it can be the simplest thing in the world. Or like, yeah, you'll get your favourite soft drink or something, yeah absolutely, you do that.” All participants frowned upon direct approaches to tricking patients into treatment adherence, such as putting medicine in their drink or food without informing them. Occasionally, parents requested staff assistance to trick the child into taking medication, but participants reported not aiding with this. Participants describe the acceptability of such deception to vary with ward culture. Most participants, however, found strategic dishonesty more acceptable. This involved withholding certain information, such as not presenting available options or pretending options existed when they did not. Some also described not informing patients about changes in types of medication or dosages to prevent failure in treatment adherence. Threats appeared to be the least approved form of informal coercion, with most participants believing threats should not be part of a care culture. However, some perceived threats being frequently used while others observed them being employed by certain staff, particularly when staff were tired. Participants generally agreed that threats were ineffective in improving patient outcomes. However, some emphasised perceiving threats as less invasive and traumatic than formal coercive measures, such as threatening to force-feed patients with restrictive eating disorders if they did not eat voluntarily. All participants found it difficult to distinguish between informing patients of the consequences of non-adherence and threatening them with formal coercion, creating an ethical conflict about how to inform patients without threatening them. For example, some saw informing a patient about the necessity of an involuntary injection if they refused oral medication as a definite threat with one senior consultant reporting it as a coercive measure. Others did not interpret it as a threat given that the intention was to inform the patient. A senior consultant said: “Because there comes a point where you have to, like, either talk about it in advance or it hits like a bolt from the blue.” Some participants described referring to rules and routines to manage patient behaviour, as well as using a disciplinary style to get the patient to adhere to ward rules.
This theme addresses different care aspects affecting trust and distrust in using coercion or non-coercion when managing conflicts at the ward. Trust or distrust in these strategies appeared to shape staff decision-making, with those expressing greater trust in non-coercive methods being more likely to use theses as first-line approaches, while staff with less trust more frequently relied on coercion. These attitudes were influenced not only by individual beliefs but also by broader structural and cultural factors at the ward level, as described in the two subthemes Ward culture and Available resources and strain . All participants perceived coercive measures as effective for solving exceedingly difficult acute situations with patients. They considered coercive measures justified in managing aggressive and violent patients, or severely self-harming patients, who were otherwise sometimes difficult to manage safely. A head of unit stated: “It’s the last resort as far as possible. Of course, one should appeal to voluntary participation and try to find solutions if possible to avoid them. Sometimes we end up in situations where we have to; there’s simply no other way.” Mechanical restraint was considered highly effective in securely containing patients and ensuring unit safety during dangerous situations. While some participants approved of seclusion as a safety measure, others found it unhelpful in managing patient behaviour, particularly when designated safe seclusion rooms were lacking. Some participants also viewed coercive measures as therapeutic: with tube-feeding and forced pharmacological injections aiding clinical recovery; seclusions and forced sedative injections soothing the patient; and physical and mechanical restraint establishing “behavioural boundaries” and calming the patients. However, coercive measures were generally seen as a failure for both the care system and staff, with some participants viewing them as such even when deemed necessary for patient care and management. A nurse said: “It’s always a failure on our part to have to use coercive measures. That means somewhere along the way we haven’t succeeded earlier, of course. So, I can’t say there’s anything positive about it other than, if there’s no other way out, then you have to do it in the best possible way.” Coercive measures were also considered by some participants as the “easy way out” compared to using non-coercive strategies, which were seen as requiring more effort from staff. In contrast, a few participants described coercive measures as something very rarely used, but highly necessary when used and then perceived as positive for the patient. Great trust in non-coercive approaches was expressed by some participants, who advocated their use as a first choice and highlighted their general effectiveness. In response to the fictional case of managing a psychotic youth with violent behaviour who had smashed a chair and was armed with the leg of the chair, a head of unit described: “If it’s a patient I know well, I would probably back out of the room and sit down—now, this may sound completely bizarre, but that’s likely what I would do first to see if we can change the situation, if we can change the patient’s experience. Because what I think is that they feel extremely cornered, pressured and that there is a lot of fear involved; that is what I would assume when I know so little.” In contrast, other participants saw non-coercive approaches as ideal but appeared to have low trust in their effectiveness and reported using coercive measures often at their units. A consultant described the response to the same fictional patient scenario: “I would of course press the alarm for help […], and we would make sure there were enough people… the question is how we would remove the weapon; that always makes it much, much more difficult. […] but there are two scenarios: getting people there and then […] overpowering the patient, bringing them down to the floor, and then disarming them, if possible. But when there’s a weapon involved, we are also quite quick to press the police alarm, and it’s precisely in such situations where it’s used, when there’s a weapon involved, because that makes it extremely difficult. […] It would probably be more about administering an injection right there and then, and then trying to seclude the patient.” When opting to use coercive measures, participants described the difficult balance between creating an immediate, potentially traumatic situation and preventing greater harm in the near future. For instance, while forcibly administering intramuscular injections could erode the patient’s trust in psychiatry, it was seen as ultimately necessary for their clinical recovery. Although aware of the risk of inducing acute or post-traumatic stress-related disorders, participants generally believed that immediate care needs should take precedence. Further, participants also stressed that using coercive measures (in contrast to non-coercive strategies) did not help patients develop new skills in demanding situations, a head of unit stated: “The idea is that the patient should be able to manage and survive with their anxiety, but instead, it’s like you’re waiting and just dealing with the anxiety when it comes [using coercive measures] rather than working on it.” Most interviewees advocated using coercive measures as a last option, emphasising the importance of exhausting voluntary options first and applying coercion only when absolutely necessary. Nonetheless, some participants stressed using coercive measures promptly to prevent escalation and harm to patients, staff, and property. Delaying the intervention was viewed as potentially harmful for the patient and unethical, especially regarding involuntary medication for severely ill patients with psychosis. Conversely, others argued against resorting to coercive measures too quickly, preferring to tolerate property damage rather than using force. Some participants reported that once coercive measures were applied to a patient, it became increasingly difficult to discontinue their use, indicating a possible negative spiral of coercion for both patient and staff. Two heads of units independently described: “One time might be okay, but not a second time, because then it’s like, it’s hard to turn back once you’ve started. Twice becomes a habit, you know.” “It must not become a habit to use coercive measures, not for the staff but also not for the patient to be subjected to coercive measures. That must not become a habit either, because I think that is absolutely negative.” In cases where patients were perceived as particularly challenging to manage, coercive approaches were often seen as inevitable, resulting in some individuals being subjected to multiple interventions. Several participants expressed a sense of resignation about using coercive measures, feeling forced to do so to manage acute situations, even when they believed it was not in the patient’s best interest. Also, some participants observed that certain patients seemed to deliberately provoke the use of coercive measures, either as a form of self-harm or to manage anxiety. This left some staff feeling powerless and forced to use coercive measures when confronted with escalating patient behaviour.
This subtheme captures various aspects of ward culture affecting trust or distrust in coercive practices, including staff feeling sanctioned to use coercion, perceived staff competence to manage conflict, and attitudes to patient involvement in care. All participants expressed a strong sense of responsibility for their patients’ well-being. They explicitly aimed to prevent harm, uphold the law, maintain patient dignity, and foster trust in psychiatric care. Participants saw their authority over patients as sanctioned by parents, the care system, the legal system (in compulsory care), and their role as adults caring for children. In addition to feeling responsible for the child’s well-being, participants also described a sense of responsibility for preserving the parent–child relationship. Staff sometimes assumed the”bad guy” role to protect parents from being seen as enforcers of coercion, aiming to maintain trust between the child and their family. In severe conflict situations, coercive measures were seen as essential to protect the patient and fellow staff. This combination of factors appeared to make participants feel sanctioned to use coercion if necessary: both formally authorised and informally validated. Those with experience from working in adult psychiatry noted more frequent use of coercion in the care for children and adolescents, particularly rapid responses to self-harm as compared to slower action against violence. This was attributed to a higher perceived urgency in preventing self-harm and a hesitancy to coerce violent children: attitudes that appeared to be rooted in ward culture and shaped by collective staff beliefs about appropriate responses in child/youth care. Participants had varied attitudes towards patient involvement in care . Most highlighted efforts to collaborate with patients, ensuring some control over their own care also when compulsorily treated. This included encouraging patient participation in care planning and adapting to their needs. Some argued for empowering the patients and prioritising their opinions, even when these conflicted with the care team’s views. There was a strong emphasis on understanding the patient and his/her behaviour, with some participants wishing for a greater focus on understanding the motivations behind non-cooperation. Coercive measures were perceived to clash with a caring perspective and negatively impact patient autonomy, though some staff tried to involve patients even during coercion, such as asking about their preferences when under restraint. One participant noted that in what was described as dysfunctional wards, staff could become cynical and lose curiosity in understanding the patient. Two participants stated that when staff made mistakes, they were encouraged to apologise to the patient and repair the relationship. In contrast, a few participants believed that staff knew what was best for patients and should disregard conflicting patient opinions. Some participants described rarely giving power to the patient regarding their care and stressed the importance of not questioning decisions in front of the patient, even if they personally disagreed with them. The level of perceived staff competence in managing conflict varied. Most participants considered risk situations as preventable or at least foreseeable, emphasising the importance of staff interventions such as de-escalation and diversion to avoid harm and coercion. Most participants believed experienced staff to be able to professionally manage conflicts, de-escalate situations when possible, and if necessary, use coercion effectively and respectfully. As stated by a nurse: “But then, when it starts, okay, now a situation is beginning to escalate, there is still a lot that can be done before needing to resort to a coercive measure. [...] Especially if you start with a low-arousal approach, talk the patient down, and offer medication, and so on. In my experience, this works nine times out of ten, or 99 times out of 100, if you have well-trained staff, a confident team, a good team leader, and confident doctors, along with routines in place.” Some expressed confidence in their colleagues’ ability to prevent and manage acute situations, ensuring voluntary patient cooperation. They trusted that inexperienced staff would receive support from experienced colleagues during a conflict. However, due to a shortage of experienced staff, other participants described a lack of trust in the ward’s overall competence to manage conflicts. Strategies for dealing with patient conflict varied. Some participants reported a clear ward strategy in dealing with patient behaviour that threatens the safety of the patient or others, always making active choices to engage in conflict or not, weighing in the risk of escalation and coercive measure use. Others described a more reactive, unstructured response to conflicts, risking quick escalation to coercion. Several interview subjects expressed a desire to work more preventively and noted that coercive measures had become routine, with insufficient efforts to provide alternative, non-coercive strategies.
This subtheme describes how the care was negatively affected by participant-reported increased work strain on the wards, paired with fewer resources. See Fig. for a proposed model of the subtheme. All participants reported substantial increases in patients seeking psychiatric emergency care and requiring hospitalisation, leading to high bed occupancy. In particular, involuntarily hospitalised patients with severe restrictive eating disorders had increased over the last years. Stricter requirements for admission following the shortage of beds resulted in admissions of only the most severely ill, mostly compulsorily treated patients being admitted, leaving few beds available for voluntary patients. High bed occupancy and increased severity of patient morbidity were described to negatively affect care quality. Participants perceived the wards as becoming more dysfunctional, with staff struggling to properly manage patients’ psychiatric symptoms, leading to worsened symptoms among patients that the staff had previously been able to manage. Some participants noted more frequent use of coercive measures, with incidents of violence, threats, and self-harm becoming more common. A senior consultant described: “What I can see is a worrying trend with more admissions under compulsory psychiatric care, increased pressure, and a minor system collapse that risks undermining the protective factors that have previously been important for preventing the need for coercive measures. […] because the situations have become more strained, and the staffing shortages are becoming more troubling, with experienced staff leaving, and so on.” Coercive measure use was perceived as a negative, stressful, and potentially traumatising experience for both patients and staff. Interviewees linked coercive measure use to increased staff sick leave or job resignation and highlighted the risk that they would be used as punishment and their detrimental impact on patient-staff relationships. As described above, participants highlighted that increased strain on the wards was compounded by insufficient resources. Most participants reported high staff turnover with difficulties to attract and keep experienced personnel, further reducing care quality. However, one head of unit described a well-functioning ward with many experienced personnel and low staff turnover: “Staffing, staffing, staffing, and then we also prevent a lot of coercive measures. […] And the young people go to bed around ten or eleven, and then it’s pretty quiet and calm, except if someone is really struggling, in which case there are two people who can take care of them, find other ways to handle it. If they need three, then there are three; if they need four, then there are four. This winter, they needed five, so they got five. I mean, it costs money to run inpatient care, but it also costs to provide good care.” Participants reported that the Covid-19 pandemic impacted noticeably on the wards, initially leading to a decrease in patients seeking inpatient care. However, by late 2020 and early 2021, admission rates increased again substantially; patients were then often more severely ill than before. Participants attributed this to reduced access to outpatient care, missed or cancelled appointments, or an inability to engage in digital consultations (many outpatient meetings were scheduled as digital meetings). The pandemic’s broader societal effects, particularly on socioeconomically disadvantaged families, were also seen as contributors to increased strain on psychiatric services.
Overall, informal coercion was primarily used to ensure adherence to treatment deemed to be in the patient’s best interest. Participants justified its use when they believed the care team knew better than the patient. Strategies for handling non-cooperative patients varied according to at least two different processes. Some participants maintained a consistent level of treatment pressure, mostly with repeated persuasion efforts over time to wear down patient resistance to intervention. Others employed a stepped approach, gradually increasing pressure until the patient complied with the least amount of coercion necessary. We found that all participants employed persuasion : some aimed to decide on the patient’s behalf, while others tried to motivate patients to accept voluntary care by discussing the pros and cons and encouraging ongoing treatment. A consultant stated: “I believe more in this kind of flexibility and thinking about what we can let this young person ‘win’ over, sort of like negotiating, and I often talk a lot about compromising and trying to explain what that word means, that you can’t always get everything you want, like ‘you’re thinking that you should get this, but you can’t have it all, but would you take half? If we try to meet halfway, where would we end up?’ and so on.” However, some participants emphasised that in acute states of mental illness, attempts at negotiating or persuading waste precious time and can be counterproductive, as patients are rarely responsive during these periods. Others described extended efforts to obtain voluntary treatment agreements. Interpersonal leverage seemed to be used rarely. Some participants reported coercion by others as frequently exercised , usually by parents, while others intentionally avoided involving parents in treatment adherence, allowing the care staff to take on the role of the “bad” enforcer and leaving the parents as the supportive “good” figures. Inducements seemed to be perceived as less problematic than treatment pressures lower down in the informal coercion hierarchy . Participants described efforts to find motivating factors; for instance, offering children a soft drink, ice cream or sweets as a positive enforcer to take their medication, combining them with persuasion. A nurse said: “Yeah, but you do that sometimes anyway, like, ‘come on, just take your medicine and then we’ll go play ping pong’ – it can be the simplest thing in the world. Or like, yeah, you'll get your favourite soft drink or something, yeah absolutely, you do that.” All participants frowned upon direct approaches to tricking patients into treatment adherence, such as putting medicine in their drink or food without informing them. Occasionally, parents requested staff assistance to trick the child into taking medication, but participants reported not aiding with this. Participants describe the acceptability of such deception to vary with ward culture. Most participants, however, found strategic dishonesty more acceptable. This involved withholding certain information, such as not presenting available options or pretending options existed when they did not. Some also described not informing patients about changes in types of medication or dosages to prevent failure in treatment adherence. Threats appeared to be the least approved form of informal coercion, with most participants believing threats should not be part of a care culture. However, some perceived threats being frequently used while others observed them being employed by certain staff, particularly when staff were tired. Participants generally agreed that threats were ineffective in improving patient outcomes. However, some emphasised perceiving threats as less invasive and traumatic than formal coercive measures, such as threatening to force-feed patients with restrictive eating disorders if they did not eat voluntarily. All participants found it difficult to distinguish between informing patients of the consequences of non-adherence and threatening them with formal coercion, creating an ethical conflict about how to inform patients without threatening them. For example, some saw informing a patient about the necessity of an involuntary injection if they refused oral medication as a definite threat with one senior consultant reporting it as a coercive measure. Others did not interpret it as a threat given that the intention was to inform the patient. A senior consultant said: “Because there comes a point where you have to, like, either talk about it in advance or it hits like a bolt from the blue.” Some participants described referring to rules and routines to manage patient behaviour, as well as using a disciplinary style to get the patient to adhere to ward rules.
We interviewed staff across Swedish inpatient CAP services and found that trust in coercion or non-coercion appeared to influence the use of coercive approaches, along with a reliance on informal coercion in clinical practice. Our findings suggest that trust encompasses both staff beliefs in the effectiveness of coercive and non-coercive strategies and their confidence — individually and collectively — in managing conflict in a safe and patient-centred way. We propose the existence of coercion processes in the use of both formal and informal coercion: with a hypothesised negative spiral of increasing coercion, and an informal coercion process with either repeated reliance on the same level of coercion or a tiered approach. Staff dependence on coercion may be understandable based on our findings of a strong staff sense of responsibility for the patient; combined with trusting coercion to keep the patient safe, alongside limited resources and low trust in non-coercive alternatives. This reliance on coercion within the safety paradigm reflects a perceived lack of viable alternatives in acute situations, aligning with previous research of the safety paradigm’s role in coercion use and the prioritisation of patient safety in adult psychiatry settings . While evidence on a direct relationship between staff experience and reduced use of coercion is inconclusive , adult psychiatry staff perspectives suggest that a combination of experience, effective de-escalation skills, and sufficient resources may better equip teams to implement non-coercive interventions . Further, our findings emphasising trust in managing approaches agree with an integrative review of decision-making regarding coercive practices in adult psychiatry; that greater trust in staff team skills may enable more prolonged efforts at de-escalation before resorting to coercive measures . However, our findings contrast with a quantitative questionnaire study of adult psychiatry staff’s implicit and explicit attitudes toward coercion . These authors found no associations between attitudes and coercion use at the overall clinic level, although results might have differed if data had been analysed unit-wise. Our findings on the reported impact of different ward cultures suggest that obtaining and examining more fine-grained data is important. The negative spiral of increasing coercion suggested here may contribute to understanding why some units seem to get caught in more coercive care practices while others successfully adopt non-coercive approaches. This negative spiral implies that once coercive measures are used by a staff constellation, the individual patient is at risk of “being stuck” in this approach, influenced by both staff and patient beliefs about the effectiveness of coercion or non-coercion in managing situations. Further, based on prior staff experiences of coercive approaches, subsequent inpatients in conflict with staff could also risk being coercively managed. This aligns with our recent systematic review suggesting both extensive variability in coercive measure use across CAP settings and that a small inpatient subgroup is frequently exposed to coercive measures . The latter is also supported by prior adult psychiatry studies [ – ] and the newly proposed “Maintenance Model of Restrictive Practices” . This model posits that restrictive practices are maintained through a self-sustaining cycle involving patient behaviours being perceived as dangerous, staff emotional responses (such as feelings of threat and distress), and coercive measure use being reinforced by creating a sense of safety among staff. The model also highlights the importance of contextual factors, including past traumatic experiences, power imbalances, and broader organisational influences such as leadership, policy clarity, staff training, and the physical and sensory ward environment . Our own more decision-focused lens provides a complementary insight into how coercion processes unfold within the everyday clinical environment, adding granularity to the broader systemic factors described by the Maintenance Model of Restrictive Practices. One can hypothesise that a corresponding positive spiral of non-coercion could also exist. Hence, if patients experience and staff employ non-coercive methods with positive outcomes, they could be more likely to respond positively to or use non-coercion in future challenging situations, with the same patient or others. Staff beliefs in their efficacy could, at least partly, contribute to why targeted programs with non-coercive approaches might be successful. We suggest that strengthened trust in non-coercive approaches could be achieved by interventions fostering (perceived) competence to handle conflict, reduced views that the use of coercion is sanctioned, and increased patient involvement. Importantly, sufficient and qualified resources and reduced strain on inpatient services appear vital to maintaining non-coercive approaches, highlighting the need for both individual- and structural-level interventions. Coercion as a process has previously been defined from a patient perspective, a systematic review indicated that adult psychiatric patients subjected to coercive measures changed their interactions with staff out of fear of being subjected to coercive measures again . This is in line with the idea of a “coercion shadow” in psychiatry ; with the knowledge of the risk of coercive treatment as an alternative, the patient obliges to avoid formal coercion. However, such a choice can also reflect self-determination; that the patient is actively making decisions and managing his/her behaviour. This capacity for autonomous decision-making could also be viewed as a positive outcome, indicating retained agency. The conceptualisation of a threat as an intentional prediction of negative consequences to influence behaviour, while a warning conveys possible outcomes without an intent to harm , may be clear in a hypothetical scenario. However, the distinction is often more blurred in clinical settings, as patients may perceive a warning as coercive. Consistent with findings from adult psychiatry , our results underscore this fine line between informing patients about the consequences of their actions and threatening them. The use of informal coercion in inpatient CAP is largely unknown but our data indicate similarities with findings from adult psychiatry and mostly support previously described hierarchies and theoretical models [ , , ]. However, interestingly, the use of strategic dishonesty seems more accepted, perhaps due to an inherently paternalistic viewpoint towards children; withholding information or using strategic dishonesty might be more accepted with the argument of protecting the child’s best interests. Our findings suggest that staff seldom used interpersonal leverage. However, it might still be applied, for example by parents, without staff knowledge. In line with findings from adult psychiatry , small inducements were considered unproblematic and often combined with persuasion. However, depending on the maturity of the child, different inducements could render independent decisions difficult. Participants seemed to perceive inducements as less problematic than persuasion, in contrast to the originally proposed coercion hierarchy; a possible explanation could be that small inducements were seen as supportive rather than coercive, particularly when framed as encouraging cooperation rather than enforcing compliance. The present findings regarding the continued use of the same level of informal coercion as a strategy to wear down resistance to non-adherence have not been described elsewhere and may be more specific to the inpatient treatment of children and adolescents. This study focused on staff perceptions and did not explore patients’ reports of coercive experiences. Hempeler and colleagues proposed a context-sensitive definition of informal coercion, where service users have a justified belief that they will face negative consequences if they do not follow caregiver recommendations. An important contextual factor in this model is patient dependency on caregivers, which may be more pronounced in CAP than in adult psychiatry, as children and adolescents typically rely more heavily on adults for care, support, and decision-making. This heightened dependency could increase their vulnerability to experiencing treatment pressures as coercive. In contrast, children may be more accustomed to being coerced and compliant with many societal norms (e.g., not being aggressive despite frustration, attending school, doing homework, obeying parental and family rules etc.) and then possibly be less sensitive to experience coercion. However, a previous study from Norwegian inpatient CAP reported that one-third of patients perceived high levels of coercion, similar to levels reported from Norwegian adult psychiatry . Further research is needed to understand the patient coercive experiences in CAP compared to adult psychiatry, alongside continued investigation of staff perceptions and decision-making. Lived experience commentary In contrast to the staff-based interview findings, our expert with lived experience (who prefers to remain anonymous) described that it was often the most experienced staff who routinely used coercive measures, sometimes even as punishment or discipline. New staff members attempted to build relationships and engage with patients, but many did not stay long, as the ward culture often clashed with their values. Negative aspects of the ward culture included an “us vs. them” attitude between staff and patients, a lack of patient involvement and insufficient explanations of decisions regarding their own care. As the expert put it: “It didn’t feel like they treated me as a human being, more like an object.” The expert also shared experiences from when the ward was overcrowded; how resource shortages and overall strain on the system often affected patients. When staff appeared more stressed, this led her to avoid seeking help from trusted staff members to not add to their burden. When the ward was overcrowded, parents were not allowed to stay overnight, which increased stress for patients, who often relied on their parents for support and comfort. She also described having guilt feelings when staff implied that she was “taking up space” that could have been used for someone in greater need. Regarding informal coercion, the expert described the harmful effects of threats, such as being threatened with mechanical restraint or being denied visits from loved ones if treatment rules were not followed. She also recounted experiences of being deceived by staff, where promises were made to encourage compliance but were not fulfilled. This strategic dishonesty, combined with the absence of promised rewards, led her to lose trust in the staff. The difficulty of distinguishing between threats and information, which was raised by some staff participants, was seen as less problematic by the expert. She believed the difference was usually clear and could be discerned from the staff’s tone and way of expression. The expert also emphasised the importance of not using parents as tools to enforce coercion. When parents were placed in such a role, it created fractures in the relationship, and parents were perceived as threatening rather than as a source of safety. She argued that coercion should be carried out by staff, while parents should provide support and a sense of security. Creating a positive spiral of non-coercive care was seen by the expert as possible, particularly for patients. She reflected that if she had been met with a more respectful and inclusive approach and allowed to participate in her care, she might have received help earlier and prevented her problems from becoming so severe. This could also have made the ward a safe place to turn to in times of need. Strengths and limitations This is one of the first studies to explore staff perspectives on coercive measures and informal coercion in inpatient CAP. Yet, there are limitations to consider. First, the small sample size, perhaps attributed to the acute and busy nature of the inpatient clinical settings involved or potential reluctance from staff to discuss sensitive issues and clinical practices. However, three different professional roles and nationwide variations in the geographic and urbanicity of workplace settings provided a range of perspectives on coercive practices, contributing to data source triangulation . While we believe the sample was sufficient to address the study aims, a larger sample could have provided more nuanced insights into differences between professional roles and the diverse range of coercive practices. Including different occupational categories captured a broader range of perspectives on decision-making surrounding coercion but might also have introduce complexity that may have limited the depth of discipline-specific experiences. Nonetheless, the diversity of views contributed to a more comprehensive understanding of the systemic and contextual factors influencing coercion use. Notably, we considered data saturation concerns not relevant, given the use of reflexive thematic analysis . Second, the broad conceptualisation of coercion, spanning both formal and informal coercion, was intentional to reflect the complexity of how coercion manifests in everyday clinical settings. We recognise that this breadth may have reduced the focus on any single type of coercion, but it allowed us to capture the full spectrum of coercive dynamics relevant to clinical decision-making. Narrowing the focus in future research could enable more detailed exploration of specific coercive practices. Third, the recruitment strategy, which relied on gatekeepers, helped streamline the recruitment process but could have led to the selection of participants holding particularly strong views, positive or negative, potentially affecting the representativeness of our sample compared to the broader inpatient CAP staff population. Fourth, while interviews were in-depth and produced rich, detailed data on coercive practices, participants were not invited to review transcripts or provide feedback on the findings, a step that could have added to the study’s credibility. Fifth, one single researcher (PhD student) conducted the coding process, albeit under supervision. This approach, while providing consistency and a deep understanding of the data, might still be problematic given the reliance on a single perspective. Even so, the researcher’s involvement in every stage — from recruitment and interviewing to transcription, coding and manuscript drafting — ensured considerable familiarity with the data, strengthening the trustworthiness of the findings. Sixth, research team expertise within the clinical context and prior understanding of the research topics may present both strengths and weaknesses. While this familiarity might have enabled nuanced interpretation of participant responses it could also lead to interpretations that reflect pre-existing assumptions or expectations. Last, the interviewer’s position as a resident in child and adolescent psychiatry during the interviews may have influenced responses, potentially affecting how they framed their experiences, or the level of detail provided. To enhance judgments about the transferability of our findings to other settings and to support dependability and confirmability, we provide a detailed description of our analytical process in the methods section, with the interview guide available in the appendix. For details on the Swedish Compulsory Psychiatric Care Act and additional details on the Swedish inpatient CAP settings see the supplementary materials from our previous study . Future directions and clinical implications Our findings suggest that staff may feel compelled to use coercive measures due to a perceived lack of alternatives or inadequate resources. Interventions that promote confidence in non-coercive approaches — along with proper training, support, and resources — are necessary to foster a culture shift. These clinical implications align with the WPA Position Statement and Call to Action: Implementing Alternatives to Coercion , underscoring the importance of enhancing staff competence in de-escalation strategies, promoting patient involvement, and addressing structural barriers to non-coercive care. By improving staff trust in non-coercive approaches and supporting patient-centred interventions, clinical practice could shift towards safer, more respectful care environments while reducing reliance on coercion. Future research should further explore what factors enhance this trust and how to effectively implement these practices across different settings. The proposed negative spiral of coercion model presented here may help in understanding why some patients are repeatedly subjected to coercive measures, and why certain staff constellations or settings use coercive measures more than others; in turn highlighting the need for empirically informed strategies to interrupt this cycle. Further research may examine the validity of the suggested model, if informal coercion differs in CAP compared to adult inpatient settings, and factors that contribute to greater staff reliance on non-coercive practices. Also, exploring how violence or resistance from child inpatients is perceived and managed differently compared to adults, could help inform our understanding of when and how coercion is used. Insights from lived experience highlight the need to address ward culture and staff dynamics, particularly the reliance of experienced staff on coercive measures and associated impact on patient trust and staff retention. The harmful effects of informal coercion such as threats and broken promises should also be explored, as these can undermine trust and patient well-being. Future research should focus on promoting inclusive care where patients and families are involved in decisions, helping to create a positive spiral of non-coercive care.
In contrast to the staff-based interview findings, our expert with lived experience (who prefers to remain anonymous) described that it was often the most experienced staff who routinely used coercive measures, sometimes even as punishment or discipline. New staff members attempted to build relationships and engage with patients, but many did not stay long, as the ward culture often clashed with their values. Negative aspects of the ward culture included an “us vs. them” attitude between staff and patients, a lack of patient involvement and insufficient explanations of decisions regarding their own care. As the expert put it: “It didn’t feel like they treated me as a human being, more like an object.” The expert also shared experiences from when the ward was overcrowded; how resource shortages and overall strain on the system often affected patients. When staff appeared more stressed, this led her to avoid seeking help from trusted staff members to not add to their burden. When the ward was overcrowded, parents were not allowed to stay overnight, which increased stress for patients, who often relied on their parents for support and comfort. She also described having guilt feelings when staff implied that she was “taking up space” that could have been used for someone in greater need. Regarding informal coercion, the expert described the harmful effects of threats, such as being threatened with mechanical restraint or being denied visits from loved ones if treatment rules were not followed. She also recounted experiences of being deceived by staff, where promises were made to encourage compliance but were not fulfilled. This strategic dishonesty, combined with the absence of promised rewards, led her to lose trust in the staff. The difficulty of distinguishing between threats and information, which was raised by some staff participants, was seen as less problematic by the expert. She believed the difference was usually clear and could be discerned from the staff’s tone and way of expression. The expert also emphasised the importance of not using parents as tools to enforce coercion. When parents were placed in such a role, it created fractures in the relationship, and parents were perceived as threatening rather than as a source of safety. She argued that coercion should be carried out by staff, while parents should provide support and a sense of security. Creating a positive spiral of non-coercive care was seen by the expert as possible, particularly for patients. She reflected that if she had been met with a more respectful and inclusive approach and allowed to participate in her care, she might have received help earlier and prevented her problems from becoming so severe. This could also have made the ward a safe place to turn to in times of need.
This is one of the first studies to explore staff perspectives on coercive measures and informal coercion in inpatient CAP. Yet, there are limitations to consider. First, the small sample size, perhaps attributed to the acute and busy nature of the inpatient clinical settings involved or potential reluctance from staff to discuss sensitive issues and clinical practices. However, three different professional roles and nationwide variations in the geographic and urbanicity of workplace settings provided a range of perspectives on coercive practices, contributing to data source triangulation . While we believe the sample was sufficient to address the study aims, a larger sample could have provided more nuanced insights into differences between professional roles and the diverse range of coercive practices. Including different occupational categories captured a broader range of perspectives on decision-making surrounding coercion but might also have introduce complexity that may have limited the depth of discipline-specific experiences. Nonetheless, the diversity of views contributed to a more comprehensive understanding of the systemic and contextual factors influencing coercion use. Notably, we considered data saturation concerns not relevant, given the use of reflexive thematic analysis . Second, the broad conceptualisation of coercion, spanning both formal and informal coercion, was intentional to reflect the complexity of how coercion manifests in everyday clinical settings. We recognise that this breadth may have reduced the focus on any single type of coercion, but it allowed us to capture the full spectrum of coercive dynamics relevant to clinical decision-making. Narrowing the focus in future research could enable more detailed exploration of specific coercive practices. Third, the recruitment strategy, which relied on gatekeepers, helped streamline the recruitment process but could have led to the selection of participants holding particularly strong views, positive or negative, potentially affecting the representativeness of our sample compared to the broader inpatient CAP staff population. Fourth, while interviews were in-depth and produced rich, detailed data on coercive practices, participants were not invited to review transcripts or provide feedback on the findings, a step that could have added to the study’s credibility. Fifth, one single researcher (PhD student) conducted the coding process, albeit under supervision. This approach, while providing consistency and a deep understanding of the data, might still be problematic given the reliance on a single perspective. Even so, the researcher’s involvement in every stage — from recruitment and interviewing to transcription, coding and manuscript drafting — ensured considerable familiarity with the data, strengthening the trustworthiness of the findings. Sixth, research team expertise within the clinical context and prior understanding of the research topics may present both strengths and weaknesses. While this familiarity might have enabled nuanced interpretation of participant responses it could also lead to interpretations that reflect pre-existing assumptions or expectations. Last, the interviewer’s position as a resident in child and adolescent psychiatry during the interviews may have influenced responses, potentially affecting how they framed their experiences, or the level of detail provided. To enhance judgments about the transferability of our findings to other settings and to support dependability and confirmability, we provide a detailed description of our analytical process in the methods section, with the interview guide available in the appendix. For details on the Swedish Compulsory Psychiatric Care Act and additional details on the Swedish inpatient CAP settings see the supplementary materials from our previous study .
Our findings suggest that staff may feel compelled to use coercive measures due to a perceived lack of alternatives or inadequate resources. Interventions that promote confidence in non-coercive approaches — along with proper training, support, and resources — are necessary to foster a culture shift. These clinical implications align with the WPA Position Statement and Call to Action: Implementing Alternatives to Coercion , underscoring the importance of enhancing staff competence in de-escalation strategies, promoting patient involvement, and addressing structural barriers to non-coercive care. By improving staff trust in non-coercive approaches and supporting patient-centred interventions, clinical practice could shift towards safer, more respectful care environments while reducing reliance on coercion. Future research should further explore what factors enhance this trust and how to effectively implement these practices across different settings. The proposed negative spiral of coercion model presented here may help in understanding why some patients are repeatedly subjected to coercive measures, and why certain staff constellations or settings use coercive measures more than others; in turn highlighting the need for empirically informed strategies to interrupt this cycle. Further research may examine the validity of the suggested model, if informal coercion differs in CAP compared to adult inpatient settings, and factors that contribute to greater staff reliance on non-coercive practices. Also, exploring how violence or resistance from child inpatients is perceived and managed differently compared to adults, could help inform our understanding of when and how coercion is used. Insights from lived experience highlight the need to address ward culture and staff dynamics, particularly the reliance of experienced staff on coercive measures and associated impact on patient trust and staff retention. The harmful effects of informal coercion such as threats and broken promises should also be explored, as these can undermine trust and patient well-being. Future research should focus on promoting inclusive care where patients and families are involved in decisions, helping to create a positive spiral of non-coercive care.
Our study suggests that staff trust or distrust in the effectiveness of coercive and non-coercive approaches is crucial in how staff-patient conflicts are managed in inpatient CAP. A lack of trust in non-coercive methods, combined with perceived limitations in resources and alternatives, may contribute to a negative spiral of increasing reliance on coercive measures.
Supplementary Material 1.
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Engineering natural microbiomes toward enhanced bioremediation by microbiome modeling | 9a68ebd0-5ad5-4cd5-b00d-ae6b22118bf7 | 11144243 | Microbiology[mh] | Microbiomes are ubiquitous in nature and play important roles in almost all biogeochemical cycles occurring on this planet, such as the metabolism of nutrients – , agriculture , , food fermentation , , element cycling , , biofuels – , and pollutant degradation – . Synthetic microbiomes, which are based on interacting relationships within microbiomes, can perform more complicated tasks with higher efficiency compared to single strains and natural microbiomes, showing promising applications in industry, health, and the environment – . These synthetic microbiomes provide a new strategy to realize the re-establishment of complex metabolic functions by combining the metabolic capacities of multiple strains, which will help to overcome the limitations of the metabolic capacity of a single strain. In addition, synthetic microbiomes provide a viable option for sharing unwanted metabolic burdens among strains in a community . Although many efforts have been made to construct synthetic strains – , research on synthetic microbiomes is still in its infancy, and many unknowns and challenges have emerged during the engineering of microbiomes. To date, practically applicable principles and tools for natural microbiome engineering are still lacking . Bottom-up and top-down strategies have been proposed to engineer microbiomes . The former involves artificially designing synthetic microbiomes by strain combination based on the understanding of different single strains . The limitation of this strategy is that the targeted strains are usually chosen by experience and intuition based on historical knowledge rather than selecting strains with fundamental benefits obtained from natural microbiomes, which might neglect naturally occurring microbial interactions. In contrast, the top-down strategy starts from natural microbiomes and then carefully optimizes the complex natural microbiomes to display desired functions – . Although this strategy is easier to carry out, it is less controllable and easily misses information on microbial metabolic interactions. In addition, functional microbiomes obtained by the top-down strategy are usually not simple enough for the application, and the largely unknown metabolic interactions among keystone species of the functional microbiomes hinder their further simplification. Therefore, obtaining a simplified functional microbiome from natural microbiomes and capturing complex interspecies interactions within the functional microbiomes are essential for natural microbiome engineering. Recently, progress in sequencing technologies has greatly promoted the description and understanding of natural microbiomes in response to environmental perturbations at both the taxonomic and functional levels – , laying the foundations for the identification of keystone species. However, limited information on metabolic activities and interactions among keystones could be inferred by sequencing. Until now, experimental determination of metabolic interactions in a microbiome has remained a major challenge, even for simple consortia with two members . Advances in computational tools such as genome-scale metabolic models (GSMMs) and their simulation algorithms enable the in silico analysis of the metabolic activities of a strain and the interspecies interactions in microbiomes – . Here, we developed a new microbiome modeling framework called Super C ommunity C ombinations (SuperCC) to simulate the performances of different microbiomes. Different from most available multistrain metabolic modeling frameworks that are inclined to simulate cooperative interactions in simple microbial consortia , , SuperCC is focused on comparing the performances of different microbiomes that cover all combinations of sets of given strains. In addition, SuperCC adapts to both syntrophic and competitive consortia and has no limitations of numbers in simulated microbiomes, which is suitable for both simple and complex microbiomes. Furthermore, SuperCC can also provide a new strategy for the computational design of a synthetic cell by learning microbiomes based on metabolic interactions. Such synthetic cells mimicking the functions of synthetic microbiomes could provide a solution for synthetic microbiomes containing plant or animal pathogens as keystones that are not suitable for practical application. Environmental organic pollutants, including pesticides, pharmaceuticals, industrial chemicals, and many others, have become a severe worldwide problem urgently requiring solutions – . For example, bromoxynil octanoate (BO), a systemic herbicide, has been increasingly used in the past few years to replace atrazine for postemergence control of annual broadleaved weeds . BO is highly toxic to fish and aquatic invertebrates – and moderately toxic to earthworms . BO and its metabolic intermediate (3,5-dibromo-4-hydroxybenzoate, DBHB) have been detected in many environmental samples , , and their removal from polluted sites is crucial for environmental safety. The metabolic activities of microbiomes rather than single strains are essential for bioremediation . It should be noted that the compositions of microbiomes and the interactions between their members affect both the growth and degradation efficiency of microbiomes , . However, microbiomes in nature are usually not functional or have low efficiency for the biodegradation of pollutants. Here, we present a framework to engineer natural microbiomes and construct synthetic microbiomes based on a balanced combination of top-down and bottom-up strategies to optimize the performance of herbicide biodegradation (Fig. ). We started with constructing a functional microbiome with enhanced bioremediation efficiency. Then we screened keystones in the functional microbiome to construct a simplified microbiome, which was used to substitute for the complex functional microbiome. Next, we used SuperCC to simulate the performances of the simplified microbiomes with different combinations of keystones. The simulation predicted not only the optimized combination of strains but also microbial metabolic interactions. We subsequently mixed isolated strains to create an optimized synthetic microbiome for testing. Our results provide important insights into microbiome engineering, and the framework of synthetic microbiome/cell construction has a wide range of applications, from the bioremediation of contamination to the biosynthesis of industrial products.
Constructing the effective functional microbiome for bioremediation To test whether herbicide application and/or herbicide-degrader inoculation could efficiently produce a functional microbiome with improved pollutant-biodegrading capability from natural microbiomes, different initial microbiomes collected from three totally different soils were used, including red (pH = 5.0), yellow cinnamon (pH = 7.3) and purple soils (pH = 8.1) (Fig. and Supplementary Fig. ). We also used two different types of pollutants, including a complex pollutant (here, BO) that can only be degraded by a synergistic consortium ( Pseudoxanthomonas sp. X-1 and Comamonas sp. 7D-2 , ) and a simple pollutant (here, DBHB) that can be degraded by different single strains ( Comamonas sp. 7D-2 or Pigmentiphaga sp. H8 ). Correspondingly, three different inocula, including a single strain (H8 or 7D-2), a synergistic consortium (X-1 and 7D-2), and a competitive consortium (H8 and 7D-2), were used. The initial microbiomes were treated with (1) herbicide (BO or DBHB) application; (2) microbial consortium (combination of strains 7D-2 and X-1, 7D-2&X-1) inoculation; (3) the combination of herbicide application and microbial consortium inoculation (BO&7D-2&X-1 or DBHB&7D-2&H8); and (4) the combination of herbicide application and single-strain inoculation (DBHB&7D-2 or DBHB&H8). To obtain an effective inoculation strategy, we compared the performances of single and repeated inoculation, as well as low- and high-dose of inoculation (Supplementary Fig. and Supplementary Fig. ). Treatments with high-dose of inoculation repeatedly had a more remarkable influence on bacterial community and showed much higher BO-degrading ability compared to other treatments. Therefore, we used the strategy of repeated inoculation of degrading strains with high doses to decrease the experimental time. The detailed study design is described in the Methods. All treatments markedly improved the degradation efficiency of both BO and DBHB, although the three initial microbiomes showed differences in degradation efficiency (Fig. and Supplementary Fig. ). Specifically, inoculation of the synergistic consortium (BO&7D-2&X-1 or 7D-2&X-1) for degradation of complex pollutants (here, BO, nondegradable by each single strain of 7D-2 or X-1) was effective. In addition, inoculation with the functional competitive consortium (DBHB&7D-2&H8) was more effective than inoculation with a single functional strain (DBHB&7D-2 or DBHB&H8). These results showed inoculation of degrading consortia was feasible for both simple and complex pollutants. Together, we showed herbicide application and herbicide-degrader inoculation were an efficient top-down method to obtain a functional microbiome with enhanced pollutant-biodegrading capability. Reassembly of natural microbiome at the taxonomic and functional levels To explore the dynamic process of microbiome reassembly driven by herbicide and inoculum applications, we investigated changes in microbiomes over a period of 30 days after different treatments. The α -diversity analysis revealed significant decreases in diversity (illustrated by a decreased Shannon index) over time during treatments in all soils (Fig. , Supplementary Fig. ). In nonmetric multidimensional scaling (NMDS) analysis, the initial microbiomes from different soils were separated from each other, revealing great differences among them (Fig. ). The microbiomes of the herbicide treatment were clustered together with their corresponding initial microbiomes, indicating that slight changes occurred in bacterial composition between the initial and herbicide treatment microbiomes. However, inoculation treatments caused greater changes in microbiomes. More importantly, the Day 30 samples from the inoculation treatments (except for strain H8) were clustered closer than the Day 0 or Day 3 samples (Fig. ), and the distances among inoculation treatment (rather than herbicide treatment) microbiomes from different soils decreased over time (Fig. ). These results showed a convergent succession of microbiomes at the taxonomic level in the three soils caused by inoculation, resulting in a more similar bacterial composition in the functional microbiomes. Metagenomic analyses were performed to gain insights into the functional differences among treated microbiomes (Fig. ). The Day 30 and Day 0 samples from the BO&7D-2&X-1 treatment were selected to represent the treated and initial microbiomes, respectively. In principal component analyses (PCA) of the functional profiles, the treated microbiomes were clustered together and separated from the initial microbiomes (Fig. ). Enzymes involved in the BO biodegradation pathways, including the nitrilase, nitrile hydratase, and nitrile hydroxylation pathways, were traced based on their functional profiles (Fig. ). The initial microbiomes had a relatively low abundance of genes encoding BO-degrading enzymes, which was consistent with the low efficiency of BO degradation in the initial soils (Fig. ). The treatment increased the abundance of degrading genes, contributing to the enhanced degrading capability (Fig. ), which was consistent with the increased relative abundance of 7D-2 in treated microbiome (Supplementary Fig. ). Notably, 52%-100% of nitrilase (the key enzyme for BO degradation) in the treated microbiome was from 7D-2, indicating most of the degradation was driven by the inoculated bacteria, especially for the yellow cinnamon soil (Supplementary Fig. ). Then, we classified these degrading genes taxonomically at the phylum, order, class, and genus levels (Fig. and Supplementary Fig. ). The dominant phyla containing the degrading genes were similar in the three soils and included Proteobacteria and Actinobacteria (Fig. ). These results demonstrated the convergent succession in microbiomes at the functional level. Identification of keystone species for simplifying the functional microbiome The taxonomic and functional convergence of microbiomes pointed out that specific species in microbiomes that were affected by treatments could functionally modify the microbiome activity for enhanced degrading efficiency. The acquisition of these specific species (called keystone species) provided an easy way to construct a simplified functional microbiome. To identify keystone species that were affected by treatments, we screened genera and ASVs whose abundances were differentiated along with treatments. LEfSe analysis (LDA > 3.0) revealed a total of 133, 54, and 62 bacterial genera with different abundances in the late phase in BO&7D-2&X-1 compared to the early phase in purple, yellow cinnamon, and red soils, respectively (Fig. ). Among them, 27, 6, and 17 genera with significant change in abundance were shared across treatments for the three respective soils. Meanwhile, 67, 71, and 35 genera showed different abundances in the DBHB&7D-2&H8 treatments of the three soils, respectively (Supplementary Fig. ). However, only a few of these identified genera showed increased abundances over time. For example, only 11 (purple), 11 (red), and 40 (yellow cinnamon) genera were enriched in the BO&7D-2&X-1 treatment, and 11 (purple), 8 (red), and 12 (yellow cinnamon) were enriched in the DBHB&7D-2&H8 treatment (Supplementary Fig. ). More than 40% of these significantly changed genera were same among the three different soils with the same treatments, especially for yellow cinnamon soils (>65%, Fig. ), indicating that genera with significant changes in abundance were common among different soils with the same treatments. Specifically, Bacillus and Sphingobacterium showed significantly increased abundances in all three soils in the BO groups. These results are consistent with the convergent succession of different microbiomes. In parallel to bacterial community analysis, we carried out independent isolation of BO and DBHB degraders in original and treated soils. In total, 290 typical isolates were isolated and selected for subsequent 16S rRNA gene sequencing to classify their taxonomy and investigate their degradation abilities (Supplementary Table ). Among them, 133 isolates belonged to the significantly enriched genera identified by LEfSe analysis. Traditionally, these isolates could be used to construct simplified microbiomes to substitute for complex functional microbiomes through experience/intuition or trial-and-error experiments – . To reduce the time and cost for simplified microbiome construction, community metabolic modeling was used to model community functions and simulate the performances of alternative community combinations. By modeling, the optimization of microbial composition and environmental conditions was predicted, and metabolic interactions that improved community performance were documented. To this end, we used random forest analysis to identify the key ASVs in the significantly changed genera identified by LEfSe. A total of 18 specific key species for modeling were identified through phylogenetic analysis of isolated strains and key ASVs, including Comamonas , Pseudoxanthomonas , Pigmentiphaga , Pseudarthrobacter , Sphingobacterium , Bacillus , Sphingomonas , Lysinibacillus , Streptomyces , Arthrobacter , Aliihoeflea , Sinomonas , Bradyrhizobium , Acinetobacter , Nocardioides , Achromobacter and Pseudomonas (Fig. , Supplementary Fig. , and Supplementary Table ). GSMMs were constructed for each of the 18 keystones and manually curated (Supplementary Table , Supplementary Data ). Interspecies interactions in the inoculated synergistic and competitive consortia To determine detailed metabolic interactions between strains in the inoculated consortium, including the synergistic (7D-2&X-1) and competitive consortia (7D-2&H8), a two-strain community model was constructed and analyzed (Fig. , Supplementary Fig. ). By simulation, the strain X-1 only transformed BO to bromoxynil, thus could not grow using BO or bromoxynil as the sole carbon source; the strain 7D-2 could degrade bromoxynil, but it was unable to degrade BO into bromoxynil (Fig. ). Therefore, the strain 7D-2 could not grow using BO as the sole carbon source, but it could grow using bromoxynil as the sole carbon source (Fig. , Supplementary Fig. ). However, the synergistic consortium of X-1 and 7D-2 could degrade BO completely by metabolic cooperation, and both strains grew well using BO as the sole carbon source (Fig. , Supplementary Fig. ). These predictions were supported by experimental validations (Fig. ). For example, the predictions of no growth of X-1 or 7D-2 for single-culture but growth of both strains for co-cultured were verified by the growth experiment (Fig. ). Both strains 7D-2 and H8 could degrade DBHB and grew using DBHB as the sole carbon source (Supplementary Fig. ). However, the combination of 7D-2 and H8 did not improve the DBHB-degrading efficiency or biomass of the consortium (Supplementary Fig. ). For 7D-2&X-1, we predicted mutual exchange fluxes between strains 7D-2 and X-1 (Fig. ). Simulations predicted that strain X-1 absorbed BO and secreted bromoxynil, hypoxanthine, D-glucosamine, and L-proline that were consumed by strain 7D-2. In return, strain 7D-2 secreted xanthine, D-mannose, NH 4 + , and L-glutamate that were utilized by strain X-1, maintaining the growth of strain X-1 (Fig. ). Interestingly, for DBHB degradation, although the two strains H8 and 7D-2 were competitive for DBHB, mutual exchange fluxes were predicted in the process of cogrowth (Supplementary Fig. ). Strain H8 consumed DBHB and NH 4 + to maintain its growth and secreted fumarate, L-proline, D-glucosamine, D-mannose, and hypoxanthine that were utilized by strain 7D-2 (Supplementary Fig. ). In return, strain 7D-2 secreted succinate and L-glutamate that were consumed by strain H8 (Supplementary Fig. ). The full map of predicted metabolic interactions between 7D-2&X-1 is detailed in Supplementary Fig. , describing the metabolic routes leading to production and consumption of the exchange metabolites specified in Fig. . The thermodynamic analysis of the predicted metabolic interaction confirmed its thermodynamic feasibility (Supplementary Table , Supplementary Table ). To verify the predicted exchange fluxes, we used liquid chromatography–mass spectrometry (LC–MS) to detect the exchanged metabolites in co-cultures of these two strains (Supplementary Fig. ). All the exchanged metabolites were successfully detected in LC–MS. In addition, we tested the growth and BO/bromoxynil/DBHB degradation in monocultures of the three species (X-1, 7D-2, and H8) grown on minimal media, each supplemented by the relevant exchange metabolites. The growth and degradation were enhanced in the supplemented medium for strains X-1, 7D-2, and H8 (Supplementary Fig. ), which were consistent with predictions. In addition, we detected the exchanged metabolites in monocultures of the three species and compared to those in the co-cultures to test the source of the exchanged metabolites. For 7D-2&X-1, the hypoxanthine was secreted by X-1 (Supplementary Fig. ); for 7D-2&H8, succinate and L-glutamate were secreted by 7D-2 (Supplementary Fig. ). To further validate the validity of the predicted metabolic pathways underlying the mutualism between strains X-1 and 7D-2, gene expression profiling of the two strains was compared in single-cultures versus co-cultures (Supplementary Fig. , Supplementary Table ). The expression levels of most genes encoding enzymes that participate in the synthesis of the secreted metabolites were up-regulated in co-culture compared to single-culture. These results indicate that the strains 7D-2 and X-1 possess all the enzymes required for the metabolic interactions and genes coding these enzymes were expressed during metabolic interactions. Therefore, the results of transcriptomic profiling confirmed the predicted metabolic interaction. To explore the effect of BO concentration on the relative abundance of strains in the synergistic consortium, we simulated the optimal biomass of strains 7D-2 and X-1 co-cultured under different BO concentrations (Supplementary Fig. ). With decreasing BO concentration, the biomasses of these two strains decreased correspondingly, but the biomass ratio between strains 7D-2 and X-1 increased sharply (Supplementary Fig. ). The prediction was experimentally supported: after reaching the maximum biomass, the biomass ratio of the two strains gradually increased over time, along with the decreased BO concentration (Supplementary Fig. ). The prediction was also consistent with the biomass ratio of strain 7D-2 and strain X-1 in soils in treatment BO-7D-2&X-1, as revealed by 16 S rRNA gene amplicon sequencing (Supplementary Fig. ). The enhanced soil degradation ability over time resulted in a decrease in the BO concentration in soils, and the ratio of the two strains increased correspondingly over time. Predicting performances of combinations of different keystones and characterization of metabolic interactions among keystones with SuperCC For the simulation of complex microbiomes, we developed a modeling framework, SuperCC, to predict metabolic flux distributions in microbiomes under different nutritional conditions. SuperCC was scalable to a large number of species suitable for both simple and complex microbiomes. To compare the performances of combinations of different keystones, we constructed a set of compartmented community models representing all possible combinations of keystones by SuperCC. Growth simulations were carried out in minimal mineral medium (MM medium) containing BO as the sole nitrogen and carbon source (BO medium) and BO medium supplemented with different nitrogen and carbon sources, including glucose, NH 4 + , and NO 3 - (Fig. ). With SuperCC, we simulated the performances of communities from the three soils to predict combinations that could enhance community growth. In BO medium, the combination of two strains, including LM5 (for red and yellow cinnamon soils) and P56 (for all three soils), with 7D-2&X-1 exhibited enhanced community growth compared to 7D-2&X-1 only (Fig. ). The addition of NH 4 + (BO-NH 4 + medium) promoted community growth, and the combination of AC6&LM5 (for yellow cinnamon soil) with 7D2&X-1 showed the maximal biomass, while strains B2 (for yellow cinnamon soil) and Y13 (purple soil) also promoted the growth of communities. For BO medium supplemented with NO 3 - (BO-NO 3 - medium), no growth promotion was detected except for strain BR1, suggesting that those strains could not assimilate NO 3 - except for strain BR1. Although no growth promotion by the addition of glucose (BO-G medium) was detected compared to BO medium, the BO medium supplemented with both glucose and NH 4 + (BO-G-NH 4 + medium) markedly improved the community growth, suggesting that a nitrogen source could be an enhancer for BO degradation. The above predictions were verified experimentally in soils with the three-species consortium (Fig. ). We used the combination of 7D-2&X-1 with Escherichia coli as a negative control. The combination of 7D-2&X-1 with P56, LM5, B2, or AC6 showed the highest degradation rates in yellow cinnamon soils (>80%), and the combination of 7D-2&X-1 with P56, LM5, or BR1 showed the highest degradation rates in red soils (>80%), consistent with the simulations. In purple soils, we did not detect any strains that could improve the degradation rate by combination, which may be due to the original high degradation rate (>80%) achieved by 7D-2&X-1. The strains E44 and A8 did not show improvement in any soils, which also agreed with the predictions. We also tested growth promotion by adding glucose and/or NH 4 + to MM medium (Fig. ). The results showed a marked enhancement of community growth with additional carbon or nitrogen sources, which was also consistent with the prediction. Similar simulations were conducted for communities from DBHB-treated groups. Again, the predictions were consistent with the experimental results (Supplementary Fig. - ). To better understand the metabolic interactions among these keystones and inoculated strains, we predicted exchange fluxes in communities (Supplementary Fig. ). Exchanges of small molecules such as amino acids and hypoxanthine among strains were detected. Particular attention was given to strain BR1, which was predicted to utilize NO 3 - and secrete NH 4 + to strain 7D-2 (Supplementary Fig. ). Through experimentation, we verified that strain BR1 could utilize NO 3 - , while strain 7D-2 could not (Fig. ). Meanwhile, the combination of strains 7D-2 and BR1 showed much higher biomass than the sum of the biomass of each strain grown separately (Fig. ). Similar to the verification for two-strain community models (7D-2&X-1 and 7D-2&H8), we detected the exchanged metabolites in co-cultures of 7D-2&X-1&BR1 to test the perdition of three-strain model (Supplementary Table ). All the 9 exchanged metabolites were successfully detected in LC–MS (except for 2-oxoglutarate). Then we compared the exchanged metabolites in monocultures with the co-cultures to test the source of the exchanged metabolites for 7D-2&X-1&BR1. The results showed that fumarate, 4-hydroxybenzoate, succinate, L-lysine, and (R)−3-hydroxybutanoate were exchanged metabolites between 7D-2 and BR1, while hypoxanthine, L-glutamate, and xanthine were between 7D-2 and X-1, which were consistent with the predictions (Supplementary Table ). Finally, we used DNA stable isotope probing (SIP) combined with amplicon sequencing to detect the strains that involved in the degradation of BO indicated by the assimilation of 13 C carbon. We used 13 C-labled 4-hydroxybenzoic acid (the intermediate metabolite for BO degradation), as no 13 C-labled BO could be purchased. In the co-cultures of 7 strains (including 7D-2, X-1, P56, E44, LM5, B2, and E. coli ), 4 strains (7D-2, X-1, LM5, and B2) were involved in the assimilation of 13 C carbon while 2 strains (E44 and E. coli ) were not (Supplementary Fig. ). The results were agreed with the perditions (except for P56) that strains LM5 and B2 could improve the BO degradation by 7D-2&X-1 while E44 could not. No assimilation of 13 C carbon was detected for strain P56, which might result from the insufficient amount of 13 C carbon used in the study and/or the competition among strains P56, LM5, and B2. Computational cell design based on mimicking the metabolic network of functional microbiomes Based on metabolic interactions in the simplified functional microbiomes revealed by SuperCC, we put forward the concept of computational design of synthetic cells by learning functional microbiomes by identifying and adding key metabolic reactions that promote degradation and biomass in the functional microbiomes to a target cell. The computationally designed synthetic cell could achieve the target strain from non-degradable to degradable for biodegradation, from nonsynthetic to synthetic for bioproduction, or from low to high efficiency (Fig. ). With SuperCC, 10 reactions were determined to be essential for BO degradation for the 7D-2&X-1 consortium (Supplementary Table ). By adding the essential reactions to strain 7D-2 or X-1, both computational synthetic 7D-2 and X-1 cells could degrade BO (Fig. ). In the 7D-2&X-1&BR1 consortium, three essential reactions for NO 3 - utilization were identified, and addition of the reactions to the above computational synthetic cells (7D-2 or X-1) helped the synthetic cell utilize NO 3 - (Fig. ). Interestingly, the synthetic cells substituting the 7D-2&X-1&BR1 consortium with essential reactions were able to recover the function of the consortium in BO medium rather than in DBHB-NH 4 + or BO-NO 3 - medium. We further identified another three reactions in strain X-1 that enabled the synthetic cells to recover the function of the consortium in DBHB-NH 4 + or BO-NO 3 - medium (Fig. ). Although the three reactions were not essential for biomass production, they were helpful for utilizing nitrogen resources. The results also showed the advantages of synthetic microbiomes in the utilization of nitrogen sources based on complex metabolic interactions in microbiomes.
To test whether herbicide application and/or herbicide-degrader inoculation could efficiently produce a functional microbiome with improved pollutant-biodegrading capability from natural microbiomes, different initial microbiomes collected from three totally different soils were used, including red (pH = 5.0), yellow cinnamon (pH = 7.3) and purple soils (pH = 8.1) (Fig. and Supplementary Fig. ). We also used two different types of pollutants, including a complex pollutant (here, BO) that can only be degraded by a synergistic consortium ( Pseudoxanthomonas sp. X-1 and Comamonas sp. 7D-2 , ) and a simple pollutant (here, DBHB) that can be degraded by different single strains ( Comamonas sp. 7D-2 or Pigmentiphaga sp. H8 ). Correspondingly, three different inocula, including a single strain (H8 or 7D-2), a synergistic consortium (X-1 and 7D-2), and a competitive consortium (H8 and 7D-2), were used. The initial microbiomes were treated with (1) herbicide (BO or DBHB) application; (2) microbial consortium (combination of strains 7D-2 and X-1, 7D-2&X-1) inoculation; (3) the combination of herbicide application and microbial consortium inoculation (BO&7D-2&X-1 or DBHB&7D-2&H8); and (4) the combination of herbicide application and single-strain inoculation (DBHB&7D-2 or DBHB&H8). To obtain an effective inoculation strategy, we compared the performances of single and repeated inoculation, as well as low- and high-dose of inoculation (Supplementary Fig. and Supplementary Fig. ). Treatments with high-dose of inoculation repeatedly had a more remarkable influence on bacterial community and showed much higher BO-degrading ability compared to other treatments. Therefore, we used the strategy of repeated inoculation of degrading strains with high doses to decrease the experimental time. The detailed study design is described in the Methods. All treatments markedly improved the degradation efficiency of both BO and DBHB, although the three initial microbiomes showed differences in degradation efficiency (Fig. and Supplementary Fig. ). Specifically, inoculation of the synergistic consortium (BO&7D-2&X-1 or 7D-2&X-1) for degradation of complex pollutants (here, BO, nondegradable by each single strain of 7D-2 or X-1) was effective. In addition, inoculation with the functional competitive consortium (DBHB&7D-2&H8) was more effective than inoculation with a single functional strain (DBHB&7D-2 or DBHB&H8). These results showed inoculation of degrading consortia was feasible for both simple and complex pollutants. Together, we showed herbicide application and herbicide-degrader inoculation were an efficient top-down method to obtain a functional microbiome with enhanced pollutant-biodegrading capability.
To explore the dynamic process of microbiome reassembly driven by herbicide and inoculum applications, we investigated changes in microbiomes over a period of 30 days after different treatments. The α -diversity analysis revealed significant decreases in diversity (illustrated by a decreased Shannon index) over time during treatments in all soils (Fig. , Supplementary Fig. ). In nonmetric multidimensional scaling (NMDS) analysis, the initial microbiomes from different soils were separated from each other, revealing great differences among them (Fig. ). The microbiomes of the herbicide treatment were clustered together with their corresponding initial microbiomes, indicating that slight changes occurred in bacterial composition between the initial and herbicide treatment microbiomes. However, inoculation treatments caused greater changes in microbiomes. More importantly, the Day 30 samples from the inoculation treatments (except for strain H8) were clustered closer than the Day 0 or Day 3 samples (Fig. ), and the distances among inoculation treatment (rather than herbicide treatment) microbiomes from different soils decreased over time (Fig. ). These results showed a convergent succession of microbiomes at the taxonomic level in the three soils caused by inoculation, resulting in a more similar bacterial composition in the functional microbiomes. Metagenomic analyses were performed to gain insights into the functional differences among treated microbiomes (Fig. ). The Day 30 and Day 0 samples from the BO&7D-2&X-1 treatment were selected to represent the treated and initial microbiomes, respectively. In principal component analyses (PCA) of the functional profiles, the treated microbiomes were clustered together and separated from the initial microbiomes (Fig. ). Enzymes involved in the BO biodegradation pathways, including the nitrilase, nitrile hydratase, and nitrile hydroxylation pathways, were traced based on their functional profiles (Fig. ). The initial microbiomes had a relatively low abundance of genes encoding BO-degrading enzymes, which was consistent with the low efficiency of BO degradation in the initial soils (Fig. ). The treatment increased the abundance of degrading genes, contributing to the enhanced degrading capability (Fig. ), which was consistent with the increased relative abundance of 7D-2 in treated microbiome (Supplementary Fig. ). Notably, 52%-100% of nitrilase (the key enzyme for BO degradation) in the treated microbiome was from 7D-2, indicating most of the degradation was driven by the inoculated bacteria, especially for the yellow cinnamon soil (Supplementary Fig. ). Then, we classified these degrading genes taxonomically at the phylum, order, class, and genus levels (Fig. and Supplementary Fig. ). The dominant phyla containing the degrading genes were similar in the three soils and included Proteobacteria and Actinobacteria (Fig. ). These results demonstrated the convergent succession in microbiomes at the functional level.
The taxonomic and functional convergence of microbiomes pointed out that specific species in microbiomes that were affected by treatments could functionally modify the microbiome activity for enhanced degrading efficiency. The acquisition of these specific species (called keystone species) provided an easy way to construct a simplified functional microbiome. To identify keystone species that were affected by treatments, we screened genera and ASVs whose abundances were differentiated along with treatments. LEfSe analysis (LDA > 3.0) revealed a total of 133, 54, and 62 bacterial genera with different abundances in the late phase in BO&7D-2&X-1 compared to the early phase in purple, yellow cinnamon, and red soils, respectively (Fig. ). Among them, 27, 6, and 17 genera with significant change in abundance were shared across treatments for the three respective soils. Meanwhile, 67, 71, and 35 genera showed different abundances in the DBHB&7D-2&H8 treatments of the three soils, respectively (Supplementary Fig. ). However, only a few of these identified genera showed increased abundances over time. For example, only 11 (purple), 11 (red), and 40 (yellow cinnamon) genera were enriched in the BO&7D-2&X-1 treatment, and 11 (purple), 8 (red), and 12 (yellow cinnamon) were enriched in the DBHB&7D-2&H8 treatment (Supplementary Fig. ). More than 40% of these significantly changed genera were same among the three different soils with the same treatments, especially for yellow cinnamon soils (>65%, Fig. ), indicating that genera with significant changes in abundance were common among different soils with the same treatments. Specifically, Bacillus and Sphingobacterium showed significantly increased abundances in all three soils in the BO groups. These results are consistent with the convergent succession of different microbiomes. In parallel to bacterial community analysis, we carried out independent isolation of BO and DBHB degraders in original and treated soils. In total, 290 typical isolates were isolated and selected for subsequent 16S rRNA gene sequencing to classify their taxonomy and investigate their degradation abilities (Supplementary Table ). Among them, 133 isolates belonged to the significantly enriched genera identified by LEfSe analysis. Traditionally, these isolates could be used to construct simplified microbiomes to substitute for complex functional microbiomes through experience/intuition or trial-and-error experiments – . To reduce the time and cost for simplified microbiome construction, community metabolic modeling was used to model community functions and simulate the performances of alternative community combinations. By modeling, the optimization of microbial composition and environmental conditions was predicted, and metabolic interactions that improved community performance were documented. To this end, we used random forest analysis to identify the key ASVs in the significantly changed genera identified by LEfSe. A total of 18 specific key species for modeling were identified through phylogenetic analysis of isolated strains and key ASVs, including Comamonas , Pseudoxanthomonas , Pigmentiphaga , Pseudarthrobacter , Sphingobacterium , Bacillus , Sphingomonas , Lysinibacillus , Streptomyces , Arthrobacter , Aliihoeflea , Sinomonas , Bradyrhizobium , Acinetobacter , Nocardioides , Achromobacter and Pseudomonas (Fig. , Supplementary Fig. , and Supplementary Table ). GSMMs were constructed for each of the 18 keystones and manually curated (Supplementary Table , Supplementary Data ).
To determine detailed metabolic interactions between strains in the inoculated consortium, including the synergistic (7D-2&X-1) and competitive consortia (7D-2&H8), a two-strain community model was constructed and analyzed (Fig. , Supplementary Fig. ). By simulation, the strain X-1 only transformed BO to bromoxynil, thus could not grow using BO or bromoxynil as the sole carbon source; the strain 7D-2 could degrade bromoxynil, but it was unable to degrade BO into bromoxynil (Fig. ). Therefore, the strain 7D-2 could not grow using BO as the sole carbon source, but it could grow using bromoxynil as the sole carbon source (Fig. , Supplementary Fig. ). However, the synergistic consortium of X-1 and 7D-2 could degrade BO completely by metabolic cooperation, and both strains grew well using BO as the sole carbon source (Fig. , Supplementary Fig. ). These predictions were supported by experimental validations (Fig. ). For example, the predictions of no growth of X-1 or 7D-2 for single-culture but growth of both strains for co-cultured were verified by the growth experiment (Fig. ). Both strains 7D-2 and H8 could degrade DBHB and grew using DBHB as the sole carbon source (Supplementary Fig. ). However, the combination of 7D-2 and H8 did not improve the DBHB-degrading efficiency or biomass of the consortium (Supplementary Fig. ). For 7D-2&X-1, we predicted mutual exchange fluxes between strains 7D-2 and X-1 (Fig. ). Simulations predicted that strain X-1 absorbed BO and secreted bromoxynil, hypoxanthine, D-glucosamine, and L-proline that were consumed by strain 7D-2. In return, strain 7D-2 secreted xanthine, D-mannose, NH 4 + , and L-glutamate that were utilized by strain X-1, maintaining the growth of strain X-1 (Fig. ). Interestingly, for DBHB degradation, although the two strains H8 and 7D-2 were competitive for DBHB, mutual exchange fluxes were predicted in the process of cogrowth (Supplementary Fig. ). Strain H8 consumed DBHB and NH 4 + to maintain its growth and secreted fumarate, L-proline, D-glucosamine, D-mannose, and hypoxanthine that were utilized by strain 7D-2 (Supplementary Fig. ). In return, strain 7D-2 secreted succinate and L-glutamate that were consumed by strain H8 (Supplementary Fig. ). The full map of predicted metabolic interactions between 7D-2&X-1 is detailed in Supplementary Fig. , describing the metabolic routes leading to production and consumption of the exchange metabolites specified in Fig. . The thermodynamic analysis of the predicted metabolic interaction confirmed its thermodynamic feasibility (Supplementary Table , Supplementary Table ). To verify the predicted exchange fluxes, we used liquid chromatography–mass spectrometry (LC–MS) to detect the exchanged metabolites in co-cultures of these two strains (Supplementary Fig. ). All the exchanged metabolites were successfully detected in LC–MS. In addition, we tested the growth and BO/bromoxynil/DBHB degradation in monocultures of the three species (X-1, 7D-2, and H8) grown on minimal media, each supplemented by the relevant exchange metabolites. The growth and degradation were enhanced in the supplemented medium for strains X-1, 7D-2, and H8 (Supplementary Fig. ), which were consistent with predictions. In addition, we detected the exchanged metabolites in monocultures of the three species and compared to those in the co-cultures to test the source of the exchanged metabolites. For 7D-2&X-1, the hypoxanthine was secreted by X-1 (Supplementary Fig. ); for 7D-2&H8, succinate and L-glutamate were secreted by 7D-2 (Supplementary Fig. ). To further validate the validity of the predicted metabolic pathways underlying the mutualism between strains X-1 and 7D-2, gene expression profiling of the two strains was compared in single-cultures versus co-cultures (Supplementary Fig. , Supplementary Table ). The expression levels of most genes encoding enzymes that participate in the synthesis of the secreted metabolites were up-regulated in co-culture compared to single-culture. These results indicate that the strains 7D-2 and X-1 possess all the enzymes required for the metabolic interactions and genes coding these enzymes were expressed during metabolic interactions. Therefore, the results of transcriptomic profiling confirmed the predicted metabolic interaction. To explore the effect of BO concentration on the relative abundance of strains in the synergistic consortium, we simulated the optimal biomass of strains 7D-2 and X-1 co-cultured under different BO concentrations (Supplementary Fig. ). With decreasing BO concentration, the biomasses of these two strains decreased correspondingly, but the biomass ratio between strains 7D-2 and X-1 increased sharply (Supplementary Fig. ). The prediction was experimentally supported: after reaching the maximum biomass, the biomass ratio of the two strains gradually increased over time, along with the decreased BO concentration (Supplementary Fig. ). The prediction was also consistent with the biomass ratio of strain 7D-2 and strain X-1 in soils in treatment BO-7D-2&X-1, as revealed by 16 S rRNA gene amplicon sequencing (Supplementary Fig. ). The enhanced soil degradation ability over time resulted in a decrease in the BO concentration in soils, and the ratio of the two strains increased correspondingly over time.
For the simulation of complex microbiomes, we developed a modeling framework, SuperCC, to predict metabolic flux distributions in microbiomes under different nutritional conditions. SuperCC was scalable to a large number of species suitable for both simple and complex microbiomes. To compare the performances of combinations of different keystones, we constructed a set of compartmented community models representing all possible combinations of keystones by SuperCC. Growth simulations were carried out in minimal mineral medium (MM medium) containing BO as the sole nitrogen and carbon source (BO medium) and BO medium supplemented with different nitrogen and carbon sources, including glucose, NH 4 + , and NO 3 - (Fig. ). With SuperCC, we simulated the performances of communities from the three soils to predict combinations that could enhance community growth. In BO medium, the combination of two strains, including LM5 (for red and yellow cinnamon soils) and P56 (for all three soils), with 7D-2&X-1 exhibited enhanced community growth compared to 7D-2&X-1 only (Fig. ). The addition of NH 4 + (BO-NH 4 + medium) promoted community growth, and the combination of AC6&LM5 (for yellow cinnamon soil) with 7D2&X-1 showed the maximal biomass, while strains B2 (for yellow cinnamon soil) and Y13 (purple soil) also promoted the growth of communities. For BO medium supplemented with NO 3 - (BO-NO 3 - medium), no growth promotion was detected except for strain BR1, suggesting that those strains could not assimilate NO 3 - except for strain BR1. Although no growth promotion by the addition of glucose (BO-G medium) was detected compared to BO medium, the BO medium supplemented with both glucose and NH 4 + (BO-G-NH 4 + medium) markedly improved the community growth, suggesting that a nitrogen source could be an enhancer for BO degradation. The above predictions were verified experimentally in soils with the three-species consortium (Fig. ). We used the combination of 7D-2&X-1 with Escherichia coli as a negative control. The combination of 7D-2&X-1 with P56, LM5, B2, or AC6 showed the highest degradation rates in yellow cinnamon soils (>80%), and the combination of 7D-2&X-1 with P56, LM5, or BR1 showed the highest degradation rates in red soils (>80%), consistent with the simulations. In purple soils, we did not detect any strains that could improve the degradation rate by combination, which may be due to the original high degradation rate (>80%) achieved by 7D-2&X-1. The strains E44 and A8 did not show improvement in any soils, which also agreed with the predictions. We also tested growth promotion by adding glucose and/or NH 4 + to MM medium (Fig. ). The results showed a marked enhancement of community growth with additional carbon or nitrogen sources, which was also consistent with the prediction. Similar simulations were conducted for communities from DBHB-treated groups. Again, the predictions were consistent with the experimental results (Supplementary Fig. - ). To better understand the metabolic interactions among these keystones and inoculated strains, we predicted exchange fluxes in communities (Supplementary Fig. ). Exchanges of small molecules such as amino acids and hypoxanthine among strains were detected. Particular attention was given to strain BR1, which was predicted to utilize NO 3 - and secrete NH 4 + to strain 7D-2 (Supplementary Fig. ). Through experimentation, we verified that strain BR1 could utilize NO 3 - , while strain 7D-2 could not (Fig. ). Meanwhile, the combination of strains 7D-2 and BR1 showed much higher biomass than the sum of the biomass of each strain grown separately (Fig. ). Similar to the verification for two-strain community models (7D-2&X-1 and 7D-2&H8), we detected the exchanged metabolites in co-cultures of 7D-2&X-1&BR1 to test the perdition of three-strain model (Supplementary Table ). All the 9 exchanged metabolites were successfully detected in LC–MS (except for 2-oxoglutarate). Then we compared the exchanged metabolites in monocultures with the co-cultures to test the source of the exchanged metabolites for 7D-2&X-1&BR1. The results showed that fumarate, 4-hydroxybenzoate, succinate, L-lysine, and (R)−3-hydroxybutanoate were exchanged metabolites between 7D-2 and BR1, while hypoxanthine, L-glutamate, and xanthine were between 7D-2 and X-1, which were consistent with the predictions (Supplementary Table ). Finally, we used DNA stable isotope probing (SIP) combined with amplicon sequencing to detect the strains that involved in the degradation of BO indicated by the assimilation of 13 C carbon. We used 13 C-labled 4-hydroxybenzoic acid (the intermediate metabolite for BO degradation), as no 13 C-labled BO could be purchased. In the co-cultures of 7 strains (including 7D-2, X-1, P56, E44, LM5, B2, and E. coli ), 4 strains (7D-2, X-1, LM5, and B2) were involved in the assimilation of 13 C carbon while 2 strains (E44 and E. coli ) were not (Supplementary Fig. ). The results were agreed with the perditions (except for P56) that strains LM5 and B2 could improve the BO degradation by 7D-2&X-1 while E44 could not. No assimilation of 13 C carbon was detected for strain P56, which might result from the insufficient amount of 13 C carbon used in the study and/or the competition among strains P56, LM5, and B2.
Based on metabolic interactions in the simplified functional microbiomes revealed by SuperCC, we put forward the concept of computational design of synthetic cells by learning functional microbiomes by identifying and adding key metabolic reactions that promote degradation and biomass in the functional microbiomes to a target cell. The computationally designed synthetic cell could achieve the target strain from non-degradable to degradable for biodegradation, from nonsynthetic to synthetic for bioproduction, or from low to high efficiency (Fig. ). With SuperCC, 10 reactions were determined to be essential for BO degradation for the 7D-2&X-1 consortium (Supplementary Table ). By adding the essential reactions to strain 7D-2 or X-1, both computational synthetic 7D-2 and X-1 cells could degrade BO (Fig. ). In the 7D-2&X-1&BR1 consortium, three essential reactions for NO 3 - utilization were identified, and addition of the reactions to the above computational synthetic cells (7D-2 or X-1) helped the synthetic cell utilize NO 3 - (Fig. ). Interestingly, the synthetic cells substituting the 7D-2&X-1&BR1 consortium with essential reactions were able to recover the function of the consortium in BO medium rather than in DBHB-NH 4 + or BO-NO 3 - medium. We further identified another three reactions in strain X-1 that enabled the synthetic cells to recover the function of the consortium in DBHB-NH 4 + or BO-NO 3 - medium (Fig. ). Although the three reactions were not essential for biomass production, they were helpful for utilizing nitrogen resources. The results also showed the advantages of synthetic microbiomes in the utilization of nitrogen sources based on complex metabolic interactions in microbiomes.
In recent decades, the rapidly increasing number of microbiome studies has greatly improved our understanding of human health and diseases, agricultural production, and environmental remediation – , showing the promising application potential of microbiomes. However, the synthetic microbiome, the basis of taking microbiomes from discovery to application, remains challenging, as the mechanisms underlying microbiome successions and the complex metabolic interactions in microbiomes are still largely unknown. Recent advances in systems biology provide effective methods to understand the various physiological processes and interactions of microbial strains , providing the possibility for the optimal design of synthetic microbiomes. Here, we first showed the reassembly of different microbiomes in response to herbicide and inoculum applications, laying a foundation for functional microbiome construction from a natural microbiome. We then presented a framework to construct synthetic microbiomes based on functional microbiomes and modeling technologies. The framework not only obtained target organisms from natural microbiomes based on microbial interdependences in the natural environments but also captured information on the metabolic interactions in the synthetic microbiome. The reassembly of natural microbiomes driven by herbicide and inoculation treatments is the basic assumption of the top-down phase in our frameworks to construct a functional microbiome. We showed that these treatments strongly shaped the metabolic function of different natural microbiomes toward enhancing their pollutant-degrading efficiency. Similarly, many other studies have reported nutrition- or host-driven reassembly of natural microbial communities – , indicating that reassembly might be a common feature of microbiome evolution under certain selective pressures. We also showed that treatments with high-dose of inoculation had more remarkable influence on bacterial community compared to those with low-dose inoculation, indicating the effects of inoculation on natural microbiomes might be dose-dependent. Actually, for most bioaugmetation treatments, a final concentration of 10 8 CFU/g soil is usually used, and the high dose of inoculation causes significant influences on natural microbiomes – . With decreased concentration (10 7 CFU/g soil), the inoculation causes temporary impacts , and the inoculation is not the main factor influencing the bacterial community structure compared to the herbicide application . The low-dose of inoculation (10 6 CFU/g soil) shows a relatively weak impact on the soil bacterial community . Notably, the initial microbiome from yellow cinnamon soils did not have BO or DBHB degradation ability, but functional microbiomes with high pollutant-degrading efficiency were still obtained. The results demonstrated the feasibility of the bioremediation of new contaminated soils with indigenous microbiomes lacking targeted pollutant-degrading capabilities. The functional microbiomes directly obtained by top-down strategy are usually not suitable for further applications, as there are generally many unknowns in the functional microbiomes, such as taxa compositions and their interactions in the microbiome , . These uncertain factors usually result in unstable microbiome structures and/or metabolic efficiency. For example, microbiomes with a better or worse atrazine-degrading efficiency could be derived from the same original microbiome with atrazine-degrading ability in different environments . Thus, it is necessary to construct a simplified microbiome with a known composition and metabolic interactions substituted for a complex functional microbiome. Traditionally, strain isolations followed by trial-and-error experiments were used to construct simplified microbiomes , . However, the strategy was time-consuming and could miss metabolic information in the functional microbiome. Here, we used sequencing technologies to obtain information on the compositional shifts in microbiomes associated with functional modification for keystone selections. Meanwhile, microbiome modeling was used to characterize the performances of different keystone combinations under various nutritional conditions to optimize simplified functional microbiomes. We showed that this bottom-up pipeline enables the construction of an optimal combination of keystones consisting of both degraders and helper strains. More importantly, these strains were almost all in situ bacteria isolated from soils, giving a stronger environmental adaptability to the simplified microbiome. Based on our framework, eighteen species, including three inoculated strains, were selected as potential keystones for simplified functional microbiome construction based on abundance shifts as well as strain isolation. Not surprisingly, the combination of all keystones was not the most cost-effective and degrading-efficient option, possibly because each strain in the combination is resource-consuming. The newly developed SuperCC aimed to quickly establish optimal and simplified combinations and capture the metabolite exchange of combinations in various media. By simulation and experimental validation, four species, Bacillus sp. (P56), Lysinibacillus sp. (LM5), Acinetobacter sp. (AC6), and Bradyrhizobium sp. (BR1), were identified to improve the growth of inoculated consortia, thus enhancing metabolic efficiency. The other potential keystones that were not functional showed that the abundance shift driven by demonstration might not be directly involved in functional modification. One possible explanation was the microbiome interactions that led to the abundance shift. Simulations predicted that additional NH 4 + could promote microbiome growth. Furthermore, strain BR1 was predicted to utilize NO 3 - , while strain 7D-2 could not, and the combination of strain BR1 with degraders could help the microbiome assimilate NO 3 - . These results suggest that NH 4 + or these predicted strains could be used as biostimulation agents. Currently, the view that antagonistic interactions are ecologically more important than synergistic interactions (such as mutualism) in microbial communities is widely held . However, the function of microbial mutualism in natural environments might be underestimated as metabolic exchanges are difficult to assess within natural systems , . In the present study, metabolic exchanges were detected between herbicide-degraders and keystone strains in soils by metabolic modeling, showing the application potential of metabolic modeling in exploring mutualism in natural environments. Recently, metabolic modeling has been increasingly used to explore microbial metabolic interactions in both free-living and host-associated natural communities – . These studies showed metabolic exchanges are ubiquitous in natural microbial communities , which is consistent with our results. Besides, we showed the metabolic exchanges enhanced pollutant-biodegrading capability of microbial communities. Similar results have been detected, showing that cross-feeding in microbial communities not only improves survival but also promotes pollutant degradation – . Exploring and validating metabolic interactions is a challenging task. We developed a modeling tool to predict metabolic interactions and provided a series of testable predictions for experimental validation. These include: (1) the predicted exchanged metabolites could be detected in the medium of co-culture; (2) the strain growth could be improved by the exchanged metabolites in single-culture; (3) SIP experiments could be employed to validate the assimilation of the exchanged metabolites; 4) transcriptome profiling could be used to test the expression of genes required for metabolic reactions. The modeling tool combined with the validation strategy could greatly facilitate the application of metabolic modeling. Until now, the dominant strategy for microbe application has been synthetic cells designed for specific functions, although the synthetic microbiome has shown promising application prospects – . The typical workflow to engineer a microbial strain has a number of common steps and requires a large number of decisions on how to improve strain behavior, which are mostly based on a trial-and-error approach . In this study, we provide a new strategy for computational strain design based on mimicking the metabolic network of microbial communities, which could pave the way for efficient strain design workflows to achieve synthetic strains with the capabilities of functional microbial communities. Techniques for genome editing (such as CRISPR , ) and assembly and synthesis of DNA sequences , are expected to enable the construction of complex synthetic biological systems.
Experimental design and soil sample collection Three different kinds of soils, including yellow cinnamon, purple, and red soils (0-20 cm soil layer), were collected in June 2018 from cropping fields located in Nanjing (Jiangsu Province; 32° 01′ N, 118° 51′ E), Mianyang (Sichuan Province; 32° 01′ N, 105° 24′ E), and Yingtan (Jiangxi Province; 28° 12′ N, 116° 55′ E), respectively (Fig. ). Each 1.5 kg of soil sample was ground, passed through a 0.84-mm mesh sieve and placed into a plastic pot. The soil was kept at 40-60% water-holding capacity (WHC). Soil samples were treated by BO or DBHB with four repeats. In the BO group, the microcosm treatments were set as follows: i) BO treatment (BO): adding 2.5 mL of methanol containing 3000 mg/L of BO (the final concentration of BO was 5 mg/kg soil, close to the concentration of field application); ii) inoculation treatment (X-1&7D-2): inoculating two strains X-1 and 7D-2 at a ratio of 1:1, with a final concentration of approximately 2 × 10 8 CFU/g soil for each strain, and adding 2.5 mL of methanol unified with other treatments; and iii) bioaugmentation treatment by X-1 and 7D-2 (BO&X-1&7D-2): adding 5 mg/kg of BO and inoculating both strains X-1 and 7D-2 with the same final concentration to treatment ii. Similarly, the microcosm treatments of the DBHB group were iv) DBHB treatment (DBHB): adding 5 mg/kg of DBHB dissolved in 2.5 mL methanol; v) bioaugmentation treatment by 7D-2 (DBHB&7D-2): adding 5 mg/kg of DBHB and inoculating the strain 7D-2 with a final concentration of approximately 2 × 10 8 CFU/g soil; (vi) bioaugmentation treatment by H8 (DBHB&H8): adding 5 mg/kg of DBHB and inoculating the strain H8 with same final concentration to treatment v; and (vii) bioaugmentation treatment by 7D-2 and H8 (DBHB&7D-2&H8): adding 5 mg/kg DBHB and inoculating two strains (7D-2&H8, 1:1) with the final concentration to treatment v. The herbicides and inoculating strains were added repeatedly every three days a total of 10 times. Before each repeated addition, 0.5 g of soil was collected to assess the degrading ability of BO or DBHB with high-performance liquid chromatography (HPLC). The large-scale pot experiments were conducted indoors in November 2018 in Nanjing, China. Soil samples of Days 0, 3, 9, 18, and 30 from each type of soil and treatment were collected and frozen at −80 °C until DNA extraction. HPLC analysis To detect the degrading ability of BO or DBHB by microbial communities with different treatments, 0.5 g of soil was collected from different samples and transferred into fresh MM media containing BO or DBHB (50 mg/L). Following incubating on a shaker at 30 °C for 10 h, 1 mL of the liquid medium was extracted for the detection of residual BO, bromoxynil, or DBHB. BO was extracted from the medium by shaking with an equal volume of dichloromethane for 5 min. The extract (1 mL) was then dried over anhydrous Na 2 SO 4 and evaporated using a vacuum rotary evaporator at room temperature. The residue was redissolved in 1 mL of methanol and analyzed using a Thermo Scientific Dionex UltiMate 3000 Rapid Separation LC (RSLC) system (Germering, Germany) equipped with a Syncronis C 18 reversed-phase column (4.6 mm × 250 mm, 5 μm particle size). The mobile phase was pure methanol and the flow rate was 1.0 mL/min. BO was detected at 231 nm, and the BO concentration was determined from the peak area ratio relative to individual standard calibration curves. The column was maintained at 30 °C, and the injection volume was set to 20 μL. Under these conditions, BO exhibited a retention time of 4.8 minutes. For analysis of bromoxynil and DBHB, 1 mL of the medium was centrifuged at 16,000 g for 1 min. The supernatant was then analyzed by HPLC. The mobile phase was acetonitrile/water/acetic acid (50/49.5/0.5, v/v/v), and the flow rate was 1.0 mL/min. Bromoxynil and DBHB were detected at 221 nm and 250 nm, respectively. Concentrations were determined from peak area ratios relative to individual standard calibration curves. The retention times for bromoxynil and DBHB were 9.2 min and 4.8 min, respectively. DNA extraction and microbial community sequencing A total of 348 soil samples were analyzed by 16S rRNA gene amplicon sequencing. Microbial DNA was extracted using the EZNA Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to manufacturer’s protocols. The V3-V4 region of the bacteria 16S ribosomal RNA gene was amplified by PCR using the 341F/806R primer set (341F: 5′-CCTAYGGGRBGCASCAG-3′, 806R: 5′-GGACTACNNGGGTATCTAAT-3′). The DNA product was used to construct Illumina Pair-End library following Illumina’s genomic DNA library preparation procedure. Then the amplicon library was sequenced on an Illumina Miseq PE250 platform (Shanghai BIOZERON Biotech. Co., Ltd, Shanghai, China) according to the standard protocols. A total of 28 soil samples were found to be contaminated or low in sequencing quality and were deleted, leaving 320 samples for further analysis. After filtration, the sequences were dereplicated and subjected to the DADA2 algorithm to identify indel mutations and substitutions by QIIME2 . The phylogenetic affiliation of each 16S rRNA gene sequence (here called amplicon sequence variants, ASVs) was analyzed by the Silva (SSU132) 16S rRNA database using a confidence threshold of 70% , . In addition to taxonomic composition analysis, we also performed a metagenomic analysis to gain insights into the functional differences between untreated and treated microbiomes with bioaugmentation. A total of 18 soil samples (soil samples from Days 0 and 30 from BO&X-1&7D-2 with three repeats) were selected for metagenomic analysis. Statistical analyses and keystone selection Rarefaction analysis based on Mothur (v1.21.1) was conducted to reveal the Shannon index. β -diversity was calculated using the “vegan” package (v2.5-7). The microbiome function based on gene profiles from the metagenome was ordinated by PCA using unweighted UniFrac distance with KEGG modules. For each treatment, LEfSe was used to explore the most discriminating genus between early (samples in Days 0, 3, and 9) and late phases (samples in Days 18 and 30). A random forest approach was also used to identify marker ASVs discriminating treatment times using the randomForest package (v4.6-14) in R (v4.0.3). In the random forest model, 80% of the data were used as the training set, 20% were used as the test set, and 100,000 trees were constructed. To reduce the deviation caused by a single run, each model was run 20 times. Keystones of BO&X-1&7D-2 and DBHB&7D-2&H8 were first selected by LEfSe analysis at the genus level, whose abundance in soils was significantly increased or decreased by treatments. Then, a random forest classifier was used to identify the top 30 important ASVs at the species level. Furthermore, the soil strains were isolated and identified to obtain the keystone strains. In total, 290 strains were isolated from the in situ soils by dilution separation methods on Luria-Bertani (LB) agar, and phylogenetic analysis of 16S rRNA genes of the isolates was performed. The ASVs from LEfSe and random forest analysis with isolated strains in soils were used as specific keystones for further synthetic microbiome construction. Data were analyzed using GraphPad Prism version 8.0 (GraphPad Software, Inc., La Jolla, CA, USA). Graphs of the microbiome data were created using the “ggplot2” (v3.3.0), “pheatmap” (v1.0.12) and “VennDiagram” (v1.6.20) packages. Metagenomic sequencing The DNA was fragmented to an average size of about 400 bp using Covaris M220 (Gene Company Limited, China) for paired-end library construction. The NEXTFLEX Rapid DNA-Seq kit (Bioo Scientific, Austin, TX, USA) was used to construct the paired-end library, where adapters containing the full complement of sequencing primer hybridization sites were ligated to the blunt ends of the fragments. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) according to the manufacturer’s instructions. Metagenomics data were assembled using MEGAHIT (v1.1.2) . Open reading frames (ORFs) were predicted from each assembled contig using Prodigal/MetaGene with a minimum length of 100 bp. A non-redundant gene catalog was constructed with CD-HIT (v4.6.1) at 90% sequence identity and coverage. High-quality reads were aligned to this non-redundant gene catalogs to calculate gene abundance with 95% identity using SOAPaligner (v2.21) . Representative sequences from the gene catalog were then annotated for taxonomy using Diamond (v0.8.35) against the non-redundant (NR at NCBI) database with an e-value cutoff of 1e −5 . Further annotations included clustering of orthologous groups of proteins (COG) using Diamond (v0.8.35) against the eggNOG database and KEGG annotations performed against the KEGG database, both with the same e-value cutoff of 1e −5 . Whole genome sequencing The genomic DNA was extracted using a Bacteria DNA Kit (OMEGA) according to the manufacturer’s instructions. Whole-genome sequencing of strains X-1, 7D-2, H8, and AT5 was conducted using the Illumina NovaSeq 6000 platform (Shanghai BIOZERON Biotech. Co., Ltd, Shanghai, China). Quality control of the raw paired-end reads was performed using Trimmomatic (v0.36) . Genome assembly was carried out with Unicycler (v0.4.8) using default parameters. Ab initio gene prediction was performed, and gene models were identified using GeneMark . Functional annotation of all gene models was conducted using the blastp against databases such as NR, SwissProt, KEGG, and COG. Additionally, tRNA genes were identified using tRNAscan-SE (v1.23) , and rRNA genes were identified using RNAmmer (v1.2) . Reconstruction of single-species models A total of eighteen species were selected for model construction. Genomes of four strains were obtained by genome sequencing. Genome sequences of 14 other species were downloaded from public resources (NCBI and JGI ). The draft models were first constructed by ModelSEED and then curated using COBRAToolbox-3.0 , . We tested the growth of each strain in MM medium with different carbon and nitrogen sources and cofactors, and these experimental results were used for model curation (Supplementary Fig. ). Generally, the draft models could not produce every biomass component under specific nutrients in which strain growth was feasible, as proven by experiments. The potentially missing reactions were first identified through an automated gap-filling process , and only reactions with gene evidence in the genomes of the strain or its phylogenetically closely related species were retained. Then, we artificially complemented missing reactions by gene/enzyme annotation according to public databases, such as KEGG , , UniProt , , BiGG , IMG , and MetaCyc . In addition, all reaction IDs from different databases were converted for consistency; elementally imbalanced reactions on the basis of chemical formulae were checked and balanced; and futile loops were removed. For the raw model, all the transport reactions were supported by transporter annotations in the genome. For model curation, a transport reaction was added when it was supported by experimental data, considering the possibility of imperfect genome annotation. For example, the experimental data showing that the strain can assimilate a compound, the transport reaction of the compound should be added into the model. In summary, all transport reactions have genomic or experimental supports. After iterative revision, the final models were able to produce all biomass components in MM medium with alternative carbon and nitrogen sources, which was consistent with the experimental results. Microbiome model construction and optimal community combination analysis For microbiome simulation, we developed a modeling framework called SuperCC for predicting metabolic flux distributions in microbial communities under different nutritional environments. Briefly, we integrated different single-species models into a multicompartment model. Each single model was considered a distinct compartment, simulating an independent cell where reactions occurred. Additionally, a shared community compartment was established to facilitate the exchange of metabolites among species, mimicking the co-culture medium. Transport reactions were added to enable each cell to absorb or secrete metabolites from the culture medium, while exchange reactions represented the accumulation or consumption of metabolites in the medium obtained from the environment. The number of single-species models in the framework was not limited; thus, SuperCC was scalable to a large number of species suitable for both simple and complex microbiomes. We provided four commonly used scenarios, including: (1) equal abundance for each organism; (2) no limitations for any organisms, meaning that the biomass of each organism could be zero; (3) defining the biomass of a specific organism as the community biomass (used to identify organisms in a community that could improve the growth of the target organism); and (4) any defined abundances. To compare the performances of communities with different organisms, a set of compartmented community models was constructed covering all possible combinations of given organisms. The biomass functions are weighted combinations of molecules that are required for cellular growth and reproduction and are scaled such that the units are 1/h; concentrations are expressed in units of mmol/gDW. The community biomass was defined as linear combinations of biomass of each individual species. We extended the FBA by integrating different single-species models into a multicompartment model . The fluxes were calculated by the parsimonious FBA method (pFBA) , optimizing the biomass function while minimizing the flux of each nutrient exchange reaction through the model. Flux variability analysis (FVA) was used to identify the key reactions that contributed to improving the performance of the community. The key reactions were then added to the model of the target organism to construct a synthetic cell achieving improved function. The mathematical framework of SuperCC is shown below. All species in the community are represented as K . The FBA for predicting maximum growth for each species k in K is described as: max [12pt]{minimal}
$${v}_{{biomass}}^{k}$$ v b i o m a s s k subject to 1 [12pt]{minimal}
$$ {S}_{{ab}}^{k}\,{v}_{b}^{k}=0,{ }_{a} {A}^{k},{ }_{b} {B}^{k}$$ ∑ S a b k v b k = 0 , ∀ a ∈ A k , ∀ b ∈ B k 2 [12pt]{minimal}
$${{LB}}_{b}^{k} {v}_{b}^{k} {{UB}}_{b}^{k}\,,\,{ }_{b} {B}^{k}$$ L B b k ≤ v b k ≤ U B b k , ∀ b ∈ B k where: [12pt]{minimal}
$${S}_{{ab}}^{k}$$ S a b k is the stoichiometry for metabolite a in reaction b . [12pt]{minimal}
$${v}_{b}^{k}$$ v b k is the flux of reaction b , set to—mmol gDW −1 h −1 for general metabolic reactions, and h −1 for the biomass reaction. Each metabolite a and reaction b of organism k are in the set of metabolites and reactions represented as A k and B k . [12pt]{minimal}
$${{LB}}_{b}^{k}$$ L B b k is the lower bound that represents the amount of metabolite absorbed by species k . [12pt]{minimal}
$${{UB}}_{b}^{k}$$ U B b k is the upper bound for secreting metabolite b . Each reaction is limited by lower bounds ( LB ) and upper bounds ( UB ). The mass balance of secretions and uptakes of each species in the extracellular space in the microbial community is stated as follows: 3 [12pt]{minimal}
$$({}_{k K}{v[{ex}]}_{a}^{k})+{{IP}}_{a}^{k}-{{OP}}_{a}^{k}=0,{ }_{a} {A}^{{com}}$$ ∑ k ∈ K v e x a k + I P a k − O P a k = 0 , ∀ a ∈ A c o m 4 [12pt]{minimal}
$$ {}_{k K}{c}^{k}{v}_{{biomass}}^{k}$$ max ∑ k ∈ K c k v b i o m a s s k where: [12pt]{minimal}
$${v[{ex}]}_{a}^{k}$$ v e x a k is the flux of the exchange reaction for metabolite a in the metabolic model of species k . [12pt]{minimal}
$${{IP}}_{a}^{k}$$ I P a k and [12pt]{minimal}
$${{OP}}_{a}^{k}$$ O P a k are the community import and outport rates of metabolites a . A com is a set of metabolites shared in the community. The objective function of the community model is defined to contain the sum of the biomass fluxes of each organism in equation [4]. c k is a vector of weights indicating how much each [12pt]{minimal}
$${v}_{{biomass}}^{k}$$ v b i o m a s s k contributes. Testing the computational predictions To test the predicted metabolic interactions among strains experimentally, co-cultures of different strains were used to detect secreted metabolites by strain. Strains X-1 and 7D-2 (with OD 600 = 0.35 for each strain, washed three times with sterile water) were inoculated into MM medium supplemented with BO as a sole carbon and nitrogen source at 30 °C for 6 h, and then the predicted metabolites were screened by LC–MS. Similarly, strains 7D-2 and H8 were grown in MM medium supplemented with DBHB and NH 4 + . Pure compounds, including hypoxanthine, L-glutamate, xanthine, D-mannose, fumarate, succinate, D-glucosamine, and L-proline, were used as reference standards. The exchanged metabolites in the medium were detected by a LC–MS system (G2-XS QTof, Waters). A 2 μL solution was injected into the UPLC column (2.1 mm × 100 mm, ACQUITY UPLC BEH C 18 column containing 1.7 μm particles) at a flow rate of 0.4 mL/min. Buffer A consisted of 0.1% formic acid in water, and buffer B consisted of 0.1% formic acid in acetonitrile. The gradient was 5% Buffer B for 1 min, 5–95% Buffer B for 11 min, and 95% Buffer B for 2 min. Mass spectrometry was performed using MSe acquisition mode with a selected mass range of 50–1200 m/z (electrospray ionization in positive or negative ion mode). The ionisation parameters were the following: capillary voltage was 3.0 kV, cone voltage was 30 V, source temperature was 120 °C, and desolvation gas temperature was 400 °C. Collision energy was 20–40 eV. Data was acquired and processed using MassLynx 4.1, with ion chromatograms extracted at a 0.01 Da width. The signal-to-noise ratio thresholds for detection and quantitation were set at 3 and 10, respectively. The chromatographic process facilitated the separation of sample components, which were then identified and quantified based on their mass and retention times relative to known standards (Supplementary Table ). Each metabolite concentration was determined using individual standard calibration curves. BO and DBHB degradation by different consortia in both MM medium and in situ soils was measured to test the computational predictions experimentally. Detailed information on the eighteen isolates used is provided in Supplementary Table . BO degradation levels by two-member (X-1&7D-2, 1:1) and three-member consortia (combination of A8, AC6, B2, BR1, E44, LM5, P1, P56, R1 or Y13, with X-1&7D-2, 1:1:1) were measured. For DBHB degradation, two-member (H8&7D-2, 1:1) and three-member consortia (combination of AT5, B2, E3, P1, P29, P56, R1, R3, Y13 or Y3, with H8&7D-2, 1:1:1) were measured. The model microorganism E. coli was used to construct a negative three-member consortium with X-1&7D-2 or 7D-2&H8. Strains in each combination (OD 600 = 0.03) were inoculated into 20 mL MM medium containing 50 mg/l BO or DBHB and enriched at 30 °C for 18 hours. In addition, the performances of different consortia were also tested in MM medium with BO/DBHB and glucose/NH 4 + . The biomass and remaining BO or DBHB were detected. Since BO is insoluble in water-forming emulsions, strain biomass in media with BO was detected by dilution plating on LB agar, while biomass in media with DBHB was detected through OD 600 using a Thermo Scientific Evolution 220 UV–Visible spectrophotometer. The in situ soil experiments were performed in sterilized soils. The two- and three-member consortia were inoculated into the corresponding soils with a final concentration of approximately 2 × 10 8 CFU·g −1 soil for each strain. The degradation ability of each combination in soils was detected as described above. Similar to BO-treated groups (Fig. ), simulations were conducted and tested for communities from DBHB-treated groups. Growth simulations were carried out in MM medium containing DBHB and NH 4 + /NO 3 - as the nitrogen and carbon sources (DBHB-NH 4 + /NO 3 - medium) and in DBHB-NH 4 + medium supplemented with glucose (DBHB-NH 4 + -G medium) (Supplementary Fig. ). We did not detect any strains that could improve growth except for strain P56. Again, the predictions were consistent with the experimental results (Supplementary Fig. ). The weak enhancement of degradation by combining strain P56 may be due to the original high degradation rate by 7D-2&H8, especially in yellow cinnamon soils (>95%). We tested the growth promotion in MM medium with glucose and/or NH 4 + (Supplementary Fig. ). The results showed no effects or even inhibition of community growth by the combination of 7D-2&H8 with other strains, which was also consistent with the simulations. DNA SIP experiment Since 4-hydroxybenzoic acid is the major intermediate metabolite of BO and could not be degraded by most species (Supplementary Fig. ), the synthetic microbiome (containing strains X-1, 7D-2, B2, LM5, E44, P56, and E. coli ) from yellow cinnamon soils was fed with normal 4-hydroxybenzoic acid or 13 C-labled 4-hydroxybenzoic acid to explore metabolic interactions. In this consortium, only strain 7D-2 could degrade 4-hydroxybenzoic acid and E. coli was used as a negative control. Due to the ability of strain AC6 to degrade 4-hydroxybenzoic acid, it was excluded from this test. After adjusting the cell density to 0.03 (OD 600 ), the cultures were diluted 20 times and then inoculated into 40 mL MM medium containing either 25 mg/L of 12 C 4-hydroxybenzoic acid or 25 mg/L of 13 C-labled 4-hydroxybenzoic acid at 3 % v/v. After 8 h of incubation at 30 °C, approximately 80% of the 4-hydroxybenzoic acid was degraded, and the total DNA was extracted using the FastDNA Spin Kit (Solon, USA) according to the manufacturer’s instructions. The experiments were carried out in triplicate. For ultra-high density centrifugation, 1600 μg of DNA from each sample was dissolved in Tris-EDTA (pH 8.0)-CsCl solution, and the final buoyant density was adjusted to 1.85 g/mL. Then, the samples were transferred into a Quick-Seal centrifuge tube (13 × 51 mm; Beckman Coulter, Pasadena, CA). The buoyant density was detected using a digital refractometer (model AR200; Leica Microsystems Inc., Buffalo Grove, IL). After heat sealing and equilibration, the centrifuge tubes were ultra-centrifuged (Optima L-100XP; Beckman Coulter, USA) at 190,000 g (20 °C) for 44 h, and DNA was fractionated in the tube. Subsequently, different fractions were collected by a fraction recovery system (Beckman Coulter). Finally, 14 fractions were collected within each sample, and the fractionated DNA was purified using the Universal DNA Purification Kit (TIANGEN Biotech, Beijing). The effectiveness of density gradient centrifugation was determined by measuring the refractive index of different DNA samples. Fractions 1-2, 3-4, 5-6, 7-8, 9-10, 11-12, and 13-14 were merged for microbial community sequencing. Transcriptome analysis To explore possible physiological explanations for mutualism between X-1 and 7D-2, we conducted gene expression profiling of the two strains using RNA-seq. For X-1, the strain was pre-cultured in LB medium containing 50 mg/L BO for 24 h to ensure a consistent metabolic state for all cells. Subsequently, the pre-cultured X-1 was cultured in a new LB medium (OD 600 = 0.2) containing 50 mg/L BO for 1 h to activate gene expressions. The cells were then collected by centrifugation for further processing. For 7D-2, the strain was pre-cultured in LB medium containing 50 mg/L bromoxynil for 24 h. Similar to X-1, cells of 7D-2 were first cultured in a new LB medium (OD 600 = 0.2) containing 50 mg/L bromoxynil for 1 h, and then collected for further treatments. The following treatments were set as follows: i) X-1 growing in MM medium containing BO for 1.5 h (single-culture of X-1), ii) 7D-2 growing in MM medium containing bromoxynil for 1.5 h (single-culture of 7D-2), and iii) X-1 and 7D-2 co-culturing in MM medium containing BO for 1.5 h (co-cultures). Total RNA was extracted using TRIzol Reagent according to the manufacturer’s instructions. RNA-seq strand-specific libraries were prepared following TruSeq RNA sample preparation Kit from Illumina (San Diego, CA, USA), using 5 μg of total RNA. The paired-end libraries were sequenced using the Illumina NovaSeq 6000 sequencing platform at Shanghai BIOZERON Biotech. Co., Ltd (Shanghai, China). The raw reads were trimmed and quality-controlled using Trimmomatic . Then clean reads were aligned separately to the reference genome using Rockhopper software which was also used to calculate gene expression levels with default parameters. The expression level for each transcript was calculated using the transcripts per kilobase million (TPM) method. Significantly differential expression genes (DEGs) were identified using edgeR with a false discovery rate (FDR) < 0.05 and an absolute of fold change ≥ 2. Reporting summary Further information on research design is available in the linked to this article.
Three different kinds of soils, including yellow cinnamon, purple, and red soils (0-20 cm soil layer), were collected in June 2018 from cropping fields located in Nanjing (Jiangsu Province; 32° 01′ N, 118° 51′ E), Mianyang (Sichuan Province; 32° 01′ N, 105° 24′ E), and Yingtan (Jiangxi Province; 28° 12′ N, 116° 55′ E), respectively (Fig. ). Each 1.5 kg of soil sample was ground, passed through a 0.84-mm mesh sieve and placed into a plastic pot. The soil was kept at 40-60% water-holding capacity (WHC). Soil samples were treated by BO or DBHB with four repeats. In the BO group, the microcosm treatments were set as follows: i) BO treatment (BO): adding 2.5 mL of methanol containing 3000 mg/L of BO (the final concentration of BO was 5 mg/kg soil, close to the concentration of field application); ii) inoculation treatment (X-1&7D-2): inoculating two strains X-1 and 7D-2 at a ratio of 1:1, with a final concentration of approximately 2 × 10 8 CFU/g soil for each strain, and adding 2.5 mL of methanol unified with other treatments; and iii) bioaugmentation treatment by X-1 and 7D-2 (BO&X-1&7D-2): adding 5 mg/kg of BO and inoculating both strains X-1 and 7D-2 with the same final concentration to treatment ii. Similarly, the microcosm treatments of the DBHB group were iv) DBHB treatment (DBHB): adding 5 mg/kg of DBHB dissolved in 2.5 mL methanol; v) bioaugmentation treatment by 7D-2 (DBHB&7D-2): adding 5 mg/kg of DBHB and inoculating the strain 7D-2 with a final concentration of approximately 2 × 10 8 CFU/g soil; (vi) bioaugmentation treatment by H8 (DBHB&H8): adding 5 mg/kg of DBHB and inoculating the strain H8 with same final concentration to treatment v; and (vii) bioaugmentation treatment by 7D-2 and H8 (DBHB&7D-2&H8): adding 5 mg/kg DBHB and inoculating two strains (7D-2&H8, 1:1) with the final concentration to treatment v. The herbicides and inoculating strains were added repeatedly every three days a total of 10 times. Before each repeated addition, 0.5 g of soil was collected to assess the degrading ability of BO or DBHB with high-performance liquid chromatography (HPLC). The large-scale pot experiments were conducted indoors in November 2018 in Nanjing, China. Soil samples of Days 0, 3, 9, 18, and 30 from each type of soil and treatment were collected and frozen at −80 °C until DNA extraction.
To detect the degrading ability of BO or DBHB by microbial communities with different treatments, 0.5 g of soil was collected from different samples and transferred into fresh MM media containing BO or DBHB (50 mg/L). Following incubating on a shaker at 30 °C for 10 h, 1 mL of the liquid medium was extracted for the detection of residual BO, bromoxynil, or DBHB. BO was extracted from the medium by shaking with an equal volume of dichloromethane for 5 min. The extract (1 mL) was then dried over anhydrous Na 2 SO 4 and evaporated using a vacuum rotary evaporator at room temperature. The residue was redissolved in 1 mL of methanol and analyzed using a Thermo Scientific Dionex UltiMate 3000 Rapid Separation LC (RSLC) system (Germering, Germany) equipped with a Syncronis C 18 reversed-phase column (4.6 mm × 250 mm, 5 μm particle size). The mobile phase was pure methanol and the flow rate was 1.0 mL/min. BO was detected at 231 nm, and the BO concentration was determined from the peak area ratio relative to individual standard calibration curves. The column was maintained at 30 °C, and the injection volume was set to 20 μL. Under these conditions, BO exhibited a retention time of 4.8 minutes. For analysis of bromoxynil and DBHB, 1 mL of the medium was centrifuged at 16,000 g for 1 min. The supernatant was then analyzed by HPLC. The mobile phase was acetonitrile/water/acetic acid (50/49.5/0.5, v/v/v), and the flow rate was 1.0 mL/min. Bromoxynil and DBHB were detected at 221 nm and 250 nm, respectively. Concentrations were determined from peak area ratios relative to individual standard calibration curves. The retention times for bromoxynil and DBHB were 9.2 min and 4.8 min, respectively.
A total of 348 soil samples were analyzed by 16S rRNA gene amplicon sequencing. Microbial DNA was extracted using the EZNA Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to manufacturer’s protocols. The V3-V4 region of the bacteria 16S ribosomal RNA gene was amplified by PCR using the 341F/806R primer set (341F: 5′-CCTAYGGGRBGCASCAG-3′, 806R: 5′-GGACTACNNGGGTATCTAAT-3′). The DNA product was used to construct Illumina Pair-End library following Illumina’s genomic DNA library preparation procedure. Then the amplicon library was sequenced on an Illumina Miseq PE250 platform (Shanghai BIOZERON Biotech. Co., Ltd, Shanghai, China) according to the standard protocols. A total of 28 soil samples were found to be contaminated or low in sequencing quality and were deleted, leaving 320 samples for further analysis. After filtration, the sequences were dereplicated and subjected to the DADA2 algorithm to identify indel mutations and substitutions by QIIME2 . The phylogenetic affiliation of each 16S rRNA gene sequence (here called amplicon sequence variants, ASVs) was analyzed by the Silva (SSU132) 16S rRNA database using a confidence threshold of 70% , . In addition to taxonomic composition analysis, we also performed a metagenomic analysis to gain insights into the functional differences between untreated and treated microbiomes with bioaugmentation. A total of 18 soil samples (soil samples from Days 0 and 30 from BO&X-1&7D-2 with three repeats) were selected for metagenomic analysis.
Rarefaction analysis based on Mothur (v1.21.1) was conducted to reveal the Shannon index. β -diversity was calculated using the “vegan” package (v2.5-7). The microbiome function based on gene profiles from the metagenome was ordinated by PCA using unweighted UniFrac distance with KEGG modules. For each treatment, LEfSe was used to explore the most discriminating genus between early (samples in Days 0, 3, and 9) and late phases (samples in Days 18 and 30). A random forest approach was also used to identify marker ASVs discriminating treatment times using the randomForest package (v4.6-14) in R (v4.0.3). In the random forest model, 80% of the data were used as the training set, 20% were used as the test set, and 100,000 trees were constructed. To reduce the deviation caused by a single run, each model was run 20 times. Keystones of BO&X-1&7D-2 and DBHB&7D-2&H8 were first selected by LEfSe analysis at the genus level, whose abundance in soils was significantly increased or decreased by treatments. Then, a random forest classifier was used to identify the top 30 important ASVs at the species level. Furthermore, the soil strains were isolated and identified to obtain the keystone strains. In total, 290 strains were isolated from the in situ soils by dilution separation methods on Luria-Bertani (LB) agar, and phylogenetic analysis of 16S rRNA genes of the isolates was performed. The ASVs from LEfSe and random forest analysis with isolated strains in soils were used as specific keystones for further synthetic microbiome construction. Data were analyzed using GraphPad Prism version 8.0 (GraphPad Software, Inc., La Jolla, CA, USA). Graphs of the microbiome data were created using the “ggplot2” (v3.3.0), “pheatmap” (v1.0.12) and “VennDiagram” (v1.6.20) packages.
The DNA was fragmented to an average size of about 400 bp using Covaris M220 (Gene Company Limited, China) for paired-end library construction. The NEXTFLEX Rapid DNA-Seq kit (Bioo Scientific, Austin, TX, USA) was used to construct the paired-end library, where adapters containing the full complement of sequencing primer hybridization sites were ligated to the blunt ends of the fragments. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) according to the manufacturer’s instructions. Metagenomics data were assembled using MEGAHIT (v1.1.2) . Open reading frames (ORFs) were predicted from each assembled contig using Prodigal/MetaGene with a minimum length of 100 bp. A non-redundant gene catalog was constructed with CD-HIT (v4.6.1) at 90% sequence identity and coverage. High-quality reads were aligned to this non-redundant gene catalogs to calculate gene abundance with 95% identity using SOAPaligner (v2.21) . Representative sequences from the gene catalog were then annotated for taxonomy using Diamond (v0.8.35) against the non-redundant (NR at NCBI) database with an e-value cutoff of 1e −5 . Further annotations included clustering of orthologous groups of proteins (COG) using Diamond (v0.8.35) against the eggNOG database and KEGG annotations performed against the KEGG database, both with the same e-value cutoff of 1e −5 .
The genomic DNA was extracted using a Bacteria DNA Kit (OMEGA) according to the manufacturer’s instructions. Whole-genome sequencing of strains X-1, 7D-2, H8, and AT5 was conducted using the Illumina NovaSeq 6000 platform (Shanghai BIOZERON Biotech. Co., Ltd, Shanghai, China). Quality control of the raw paired-end reads was performed using Trimmomatic (v0.36) . Genome assembly was carried out with Unicycler (v0.4.8) using default parameters. Ab initio gene prediction was performed, and gene models were identified using GeneMark . Functional annotation of all gene models was conducted using the blastp against databases such as NR, SwissProt, KEGG, and COG. Additionally, tRNA genes were identified using tRNAscan-SE (v1.23) , and rRNA genes were identified using RNAmmer (v1.2) .
A total of eighteen species were selected for model construction. Genomes of four strains were obtained by genome sequencing. Genome sequences of 14 other species were downloaded from public resources (NCBI and JGI ). The draft models were first constructed by ModelSEED and then curated using COBRAToolbox-3.0 , . We tested the growth of each strain in MM medium with different carbon and nitrogen sources and cofactors, and these experimental results were used for model curation (Supplementary Fig. ). Generally, the draft models could not produce every biomass component under specific nutrients in which strain growth was feasible, as proven by experiments. The potentially missing reactions were first identified through an automated gap-filling process , and only reactions with gene evidence in the genomes of the strain or its phylogenetically closely related species were retained. Then, we artificially complemented missing reactions by gene/enzyme annotation according to public databases, such as KEGG , , UniProt , , BiGG , IMG , and MetaCyc . In addition, all reaction IDs from different databases were converted for consistency; elementally imbalanced reactions on the basis of chemical formulae were checked and balanced; and futile loops were removed. For the raw model, all the transport reactions were supported by transporter annotations in the genome. For model curation, a transport reaction was added when it was supported by experimental data, considering the possibility of imperfect genome annotation. For example, the experimental data showing that the strain can assimilate a compound, the transport reaction of the compound should be added into the model. In summary, all transport reactions have genomic or experimental supports. After iterative revision, the final models were able to produce all biomass components in MM medium with alternative carbon and nitrogen sources, which was consistent with the experimental results.
For microbiome simulation, we developed a modeling framework called SuperCC for predicting metabolic flux distributions in microbial communities under different nutritional environments. Briefly, we integrated different single-species models into a multicompartment model. Each single model was considered a distinct compartment, simulating an independent cell where reactions occurred. Additionally, a shared community compartment was established to facilitate the exchange of metabolites among species, mimicking the co-culture medium. Transport reactions were added to enable each cell to absorb or secrete metabolites from the culture medium, while exchange reactions represented the accumulation or consumption of metabolites in the medium obtained from the environment. The number of single-species models in the framework was not limited; thus, SuperCC was scalable to a large number of species suitable for both simple and complex microbiomes. We provided four commonly used scenarios, including: (1) equal abundance for each organism; (2) no limitations for any organisms, meaning that the biomass of each organism could be zero; (3) defining the biomass of a specific organism as the community biomass (used to identify organisms in a community that could improve the growth of the target organism); and (4) any defined abundances. To compare the performances of communities with different organisms, a set of compartmented community models was constructed covering all possible combinations of given organisms. The biomass functions are weighted combinations of molecules that are required for cellular growth and reproduction and are scaled such that the units are 1/h; concentrations are expressed in units of mmol/gDW. The community biomass was defined as linear combinations of biomass of each individual species. We extended the FBA by integrating different single-species models into a multicompartment model . The fluxes were calculated by the parsimonious FBA method (pFBA) , optimizing the biomass function while minimizing the flux of each nutrient exchange reaction through the model. Flux variability analysis (FVA) was used to identify the key reactions that contributed to improving the performance of the community. The key reactions were then added to the model of the target organism to construct a synthetic cell achieving improved function. The mathematical framework of SuperCC is shown below. All species in the community are represented as K . The FBA for predicting maximum growth for each species k in K is described as: max [12pt]{minimal}
$${v}_{{biomass}}^{k}$$ v b i o m a s s k subject to 1 [12pt]{minimal}
$$ {S}_{{ab}}^{k}\,{v}_{b}^{k}=0,{ }_{a} {A}^{k},{ }_{b} {B}^{k}$$ ∑ S a b k v b k = 0 , ∀ a ∈ A k , ∀ b ∈ B k 2 [12pt]{minimal}
$${{LB}}_{b}^{k} {v}_{b}^{k} {{UB}}_{b}^{k}\,,\,{ }_{b} {B}^{k}$$ L B b k ≤ v b k ≤ U B b k , ∀ b ∈ B k where: [12pt]{minimal}
$${S}_{{ab}}^{k}$$ S a b k is the stoichiometry for metabolite a in reaction b . [12pt]{minimal}
$${v}_{b}^{k}$$ v b k is the flux of reaction b , set to—mmol gDW −1 h −1 for general metabolic reactions, and h −1 for the biomass reaction. Each metabolite a and reaction b of organism k are in the set of metabolites and reactions represented as A k and B k . [12pt]{minimal}
$${{LB}}_{b}^{k}$$ L B b k is the lower bound that represents the amount of metabolite absorbed by species k . [12pt]{minimal}
$${{UB}}_{b}^{k}$$ U B b k is the upper bound for secreting metabolite b . Each reaction is limited by lower bounds ( LB ) and upper bounds ( UB ). The mass balance of secretions and uptakes of each species in the extracellular space in the microbial community is stated as follows: 3 [12pt]{minimal}
$$({}_{k K}{v[{ex}]}_{a}^{k})+{{IP}}_{a}^{k}-{{OP}}_{a}^{k}=0,{ }_{a} {A}^{{com}}$$ ∑ k ∈ K v e x a k + I P a k − O P a k = 0 , ∀ a ∈ A c o m 4 [12pt]{minimal}
$$ {}_{k K}{c}^{k}{v}_{{biomass}}^{k}$$ max ∑ k ∈ K c k v b i o m a s s k where: [12pt]{minimal}
$${v[{ex}]}_{a}^{k}$$ v e x a k is the flux of the exchange reaction for metabolite a in the metabolic model of species k . [12pt]{minimal}
$${{IP}}_{a}^{k}$$ I P a k and [12pt]{minimal}
$${{OP}}_{a}^{k}$$ O P a k are the community import and outport rates of metabolites a . A com is a set of metabolites shared in the community. The objective function of the community model is defined to contain the sum of the biomass fluxes of each organism in equation [4]. c k is a vector of weights indicating how much each [12pt]{minimal}
$${v}_{{biomass}}^{k}$$ v b i o m a s s k contributes.
To test the predicted metabolic interactions among strains experimentally, co-cultures of different strains were used to detect secreted metabolites by strain. Strains X-1 and 7D-2 (with OD 600 = 0.35 for each strain, washed three times with sterile water) were inoculated into MM medium supplemented with BO as a sole carbon and nitrogen source at 30 °C for 6 h, and then the predicted metabolites were screened by LC–MS. Similarly, strains 7D-2 and H8 were grown in MM medium supplemented with DBHB and NH 4 + . Pure compounds, including hypoxanthine, L-glutamate, xanthine, D-mannose, fumarate, succinate, D-glucosamine, and L-proline, were used as reference standards. The exchanged metabolites in the medium were detected by a LC–MS system (G2-XS QTof, Waters). A 2 μL solution was injected into the UPLC column (2.1 mm × 100 mm, ACQUITY UPLC BEH C 18 column containing 1.7 μm particles) at a flow rate of 0.4 mL/min. Buffer A consisted of 0.1% formic acid in water, and buffer B consisted of 0.1% formic acid in acetonitrile. The gradient was 5% Buffer B for 1 min, 5–95% Buffer B for 11 min, and 95% Buffer B for 2 min. Mass spectrometry was performed using MSe acquisition mode with a selected mass range of 50–1200 m/z (electrospray ionization in positive or negative ion mode). The ionisation parameters were the following: capillary voltage was 3.0 kV, cone voltage was 30 V, source temperature was 120 °C, and desolvation gas temperature was 400 °C. Collision energy was 20–40 eV. Data was acquired and processed using MassLynx 4.1, with ion chromatograms extracted at a 0.01 Da width. The signal-to-noise ratio thresholds for detection and quantitation were set at 3 and 10, respectively. The chromatographic process facilitated the separation of sample components, which were then identified and quantified based on their mass and retention times relative to known standards (Supplementary Table ). Each metabolite concentration was determined using individual standard calibration curves. BO and DBHB degradation by different consortia in both MM medium and in situ soils was measured to test the computational predictions experimentally. Detailed information on the eighteen isolates used is provided in Supplementary Table . BO degradation levels by two-member (X-1&7D-2, 1:1) and three-member consortia (combination of A8, AC6, B2, BR1, E44, LM5, P1, P56, R1 or Y13, with X-1&7D-2, 1:1:1) were measured. For DBHB degradation, two-member (H8&7D-2, 1:1) and three-member consortia (combination of AT5, B2, E3, P1, P29, P56, R1, R3, Y13 or Y3, with H8&7D-2, 1:1:1) were measured. The model microorganism E. coli was used to construct a negative three-member consortium with X-1&7D-2 or 7D-2&H8. Strains in each combination (OD 600 = 0.03) were inoculated into 20 mL MM medium containing 50 mg/l BO or DBHB and enriched at 30 °C for 18 hours. In addition, the performances of different consortia were also tested in MM medium with BO/DBHB and glucose/NH 4 + . The biomass and remaining BO or DBHB were detected. Since BO is insoluble in water-forming emulsions, strain biomass in media with BO was detected by dilution plating on LB agar, while biomass in media with DBHB was detected through OD 600 using a Thermo Scientific Evolution 220 UV–Visible spectrophotometer. The in situ soil experiments were performed in sterilized soils. The two- and three-member consortia were inoculated into the corresponding soils with a final concentration of approximately 2 × 10 8 CFU·g −1 soil for each strain. The degradation ability of each combination in soils was detected as described above. Similar to BO-treated groups (Fig. ), simulations were conducted and tested for communities from DBHB-treated groups. Growth simulations were carried out in MM medium containing DBHB and NH 4 + /NO 3 - as the nitrogen and carbon sources (DBHB-NH 4 + /NO 3 - medium) and in DBHB-NH 4 + medium supplemented with glucose (DBHB-NH 4 + -G medium) (Supplementary Fig. ). We did not detect any strains that could improve growth except for strain P56. Again, the predictions were consistent with the experimental results (Supplementary Fig. ). The weak enhancement of degradation by combining strain P56 may be due to the original high degradation rate by 7D-2&H8, especially in yellow cinnamon soils (>95%). We tested the growth promotion in MM medium with glucose and/or NH 4 + (Supplementary Fig. ). The results showed no effects or even inhibition of community growth by the combination of 7D-2&H8 with other strains, which was also consistent with the simulations.
Since 4-hydroxybenzoic acid is the major intermediate metabolite of BO and could not be degraded by most species (Supplementary Fig. ), the synthetic microbiome (containing strains X-1, 7D-2, B2, LM5, E44, P56, and E. coli ) from yellow cinnamon soils was fed with normal 4-hydroxybenzoic acid or 13 C-labled 4-hydroxybenzoic acid to explore metabolic interactions. In this consortium, only strain 7D-2 could degrade 4-hydroxybenzoic acid and E. coli was used as a negative control. Due to the ability of strain AC6 to degrade 4-hydroxybenzoic acid, it was excluded from this test. After adjusting the cell density to 0.03 (OD 600 ), the cultures were diluted 20 times and then inoculated into 40 mL MM medium containing either 25 mg/L of 12 C 4-hydroxybenzoic acid or 25 mg/L of 13 C-labled 4-hydroxybenzoic acid at 3 % v/v. After 8 h of incubation at 30 °C, approximately 80% of the 4-hydroxybenzoic acid was degraded, and the total DNA was extracted using the FastDNA Spin Kit (Solon, USA) according to the manufacturer’s instructions. The experiments were carried out in triplicate. For ultra-high density centrifugation, 1600 μg of DNA from each sample was dissolved in Tris-EDTA (pH 8.0)-CsCl solution, and the final buoyant density was adjusted to 1.85 g/mL. Then, the samples were transferred into a Quick-Seal centrifuge tube (13 × 51 mm; Beckman Coulter, Pasadena, CA). The buoyant density was detected using a digital refractometer (model AR200; Leica Microsystems Inc., Buffalo Grove, IL). After heat sealing and equilibration, the centrifuge tubes were ultra-centrifuged (Optima L-100XP; Beckman Coulter, USA) at 190,000 g (20 °C) for 44 h, and DNA was fractionated in the tube. Subsequently, different fractions were collected by a fraction recovery system (Beckman Coulter). Finally, 14 fractions were collected within each sample, and the fractionated DNA was purified using the Universal DNA Purification Kit (TIANGEN Biotech, Beijing). The effectiveness of density gradient centrifugation was determined by measuring the refractive index of different DNA samples. Fractions 1-2, 3-4, 5-6, 7-8, 9-10, 11-12, and 13-14 were merged for microbial community sequencing.
To explore possible physiological explanations for mutualism between X-1 and 7D-2, we conducted gene expression profiling of the two strains using RNA-seq. For X-1, the strain was pre-cultured in LB medium containing 50 mg/L BO for 24 h to ensure a consistent metabolic state for all cells. Subsequently, the pre-cultured X-1 was cultured in a new LB medium (OD 600 = 0.2) containing 50 mg/L BO for 1 h to activate gene expressions. The cells were then collected by centrifugation for further processing. For 7D-2, the strain was pre-cultured in LB medium containing 50 mg/L bromoxynil for 24 h. Similar to X-1, cells of 7D-2 were first cultured in a new LB medium (OD 600 = 0.2) containing 50 mg/L bromoxynil for 1 h, and then collected for further treatments. The following treatments were set as follows: i) X-1 growing in MM medium containing BO for 1.5 h (single-culture of X-1), ii) 7D-2 growing in MM medium containing bromoxynil for 1.5 h (single-culture of 7D-2), and iii) X-1 and 7D-2 co-culturing in MM medium containing BO for 1.5 h (co-cultures). Total RNA was extracted using TRIzol Reagent according to the manufacturer’s instructions. RNA-seq strand-specific libraries were prepared following TruSeq RNA sample preparation Kit from Illumina (San Diego, CA, USA), using 5 μg of total RNA. The paired-end libraries were sequenced using the Illumina NovaSeq 6000 sequencing platform at Shanghai BIOZERON Biotech. Co., Ltd (Shanghai, China). The raw reads were trimmed and quality-controlled using Trimmomatic . Then clean reads were aligned separately to the reference genome using Rockhopper software which was also used to calculate gene expression levels with default parameters. The expression level for each transcript was calculated using the transcripts per kilobase million (TPM) method. Significantly differential expression genes (DEGs) were identified using edgeR with a false discovery rate (FDR) < 0.05 and an absolute of fold change ≥ 2.
Further information on research design is available in the linked to this article.
Supplementary Information Peer Review File Description of Additional Supplementary Files Supplementary Data 1 Reporting Summary
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Bacteria degrading both | 5fbd1a4f-f834-43f1-8262-7c123424f7d9 | 10799122 | Microbiology[mh] | Crude oil and its derivatives are complex mixtures containing large amounts of hydrocarbons, which display different chemical structures, physicochemical properties, and reactivity. n -alkanes are the major constituents; however, aromatic compounds (both mono- and polycyclic aromatic hydrocarbons, PAHs) pose risks to living organisms because of their toxicity and carcinogenicity (Kuppusamy et al. ; Stading et al. ; Jesus et al. ). Soil contamination with petroleum products is a global problem causing devastating damage to natural habitats (Davoodi et al. ), disturbing the proper functioning of the ecosystem (Gao et al. ), and it is a threat with its emerging concerns for the environmental and human health. Thus, there is an urgent need to clean up polluted sites. An environmentally friendly and cost-effective solution is bioremediation (Davoodi et al. ), which is based on microbial metabolic capabilities to utilize hydrocarbons as carbon sources and finally transform them into less or non-toxic metabolites (Das and Chandran ; Imam et al. ). Although bacteria, fungi, and yeasts may convert those substances, the former ones are key degraders (thereafter Das and Chandran ). Diverse bacteria have evolved with great complexity of metabolic pathways as a response to the natural diversity existing among hydrocarbon compounds. Biodegradation may occur under both aerobic and anaerobic conditions; however, aerobic processes take place much faster and are energetically favorable. Taking into account metabolic profile, there are two groups of hydrocarbon-degraders, namely: (a) the first one, consisting of bacteria with extended catabolic preferences and able to utilize both n -alkanes and aromatic hydrocarbons (Brzeszcz and Kaszycki ), and (b) the second one, whith members revealing limited metabolic capabilities (i.e., only alkane degraders). Hydrocarbons are aerobically biodegraded through a cascade of subsequent biochemical reactions, which lead to the substrate transformation into intermediates of central metabolism. Hence, this process starts from (1) upper pathways composing of an activation/attacking the C-H bond and production of central intermediate compounds, followed by (2) lower pathways, involving conversion of these intermediates of central metabolism, which are afterward mineralized to CO 2 (Somee et al. ). To illustrate, alkanes are oxidized by hydroxylases to corresponding primary alcohols, which are further metabolized to aldehydes and fatty acids that are channeled into the β-oxidation (Das and Chandran ; Varjani ). In turn, the initial oxidation of the aromatic ring is performed by mono- or dioxygenases, followed by a systematic breakdown of the compound to CO 2 (Ghosal et al. ; Imam et al. ). BTEX (benzene, toluene, ethylbenzene and xylene) may be converted via a ring hydroxylating pathway or alkyl substituent pathway (excluding benzene) with cis -dihydrodiols or phenols as by-products (Ghosal et al. ). In the case of both BTEX and PAHs, the key reaction is the opening of the activated ring rather than hydroxylation. It should be emphasized that the enzymes, catalyzing the hydroxylation step, are pivotal for the described processes, while proteins involved in the lower pathways are prevalent among bacteria and participate also in numerous, diverse catabolic pathways. The high complexity of metabolic apparatus (both various enzymatic systems and numerous catabolic routes) involved in hydrocarbon transformation is a clue to obtaining energy from a huge variety of these chemicals. There are several n -alkane hydroxylating systems with differentiated specificity, e.g., widely represented three-component AlkB-type alkane hydroxylases (encoded by alkB ) and CYP153, enzyme belonging to a family of soluble P-450 cytochromes (van Beilen and Funhoff ; Moreno and Rojo ). The presence of these enzymes within the single bacterial cell is not mutually exclusive. Also, a wide set of aromatic-ring-cleavage dioxygenases (e.g., 1,2-dihydroxynaphthalene dioxygenase) has been recognized. They are categorized into three classes (extradiol, intradiol and gentisate/homogentisate), which are characterized by the distinct substrate specificity and the position where the ring fission occurs relative to the hydroxyl group. Bacteria revealing mentioned extended degradation preferences, carry the enzymes for both aliphatic and aromatic degradation pathways. The active maintenance of these pathways and the transfer of genetic information about them to other generations should be a heavy load for bacterial cells (Brzeszcz and Kaszycki ). On the other hand, possessing such capabilities may be a benefit since these degraders should be subjected to lower competition pressure than specialized organisms. Bacterial species that can use different hydrocarbon classes as the sole carbon and energy source exist in the environment (Brzeszcz and Kaszycki and the references therein, Kiamarsi et al. ; Medić et al. , Mullaeva et al. ; Ivanova et al. ). However, no unambiguous data are indicating the prevalence of these degraders, since they are subjected to a very limited number of studies. Moreover, the fact that multi-degrading capabilities are often not tested creates a situation in which the significance of the aforementioned bacterial group is undervalued. We hypothesized that these microbes should be widespread, colonizing both hydrocarbon-contaminated and unpolluted soils. If we are correct (that is, they are ubiquitous), one should be able to obtain valuable strains from every tested soil. This study aimed to isolate and identify bacterial strains displaying degradation capabilities towards both n -alkanes and aromatic hydrocarbons (BTEX and PAHs) from various soil environments. Additionally, a culture-independent approach, whole-metagenome shotgun sequencing (WMS), was applied to characterize the functional potential towards hydrocarbon degradation of uncontaminated and contaminated soil communities.
Chemicals, microbiological media and substrates PAHs were obtained from Sigma-Aldrich (USA). Used inorganic compounds, n -alkanes, monoaromatic hydrocarbons, and solvents (acetone) were purchased from Avantor Performance Materials (Gliwice, Poland). Pristane (iso-C 15 , 2,6,10,14-tetramethylpentadecane) and p -iodo-nitrotetrazolium chloride (INT) were purchased from Koch Light Laboratories (UK) and Fluka (Germany), respectively. Noble agar and nutrient media (BD Difco nutrient agar, BD Difco nutrient broth) were from Difco (Becton Dickinson, USA). Unless otherwise stated, all chemicals were of analytical grade. Crude oil (sterilized) from the Barnówko-Mostno-Buszewo oilfield (Poland) was used as a substrate. Soil sample collection In this study, the soils were sampled within three climatic zones: Alpine (Austria), temperate (Poland), and arid (Kuwait and Israel). The unpolluted soils were taken in sites with no presence of anthropogenic contamination with hydrocarbons such as national parks (BIAL, KAM, BW) and uncontaminated areas in the proximity of polluted ones (KWU, I2; more details in Table ). The polluted soil samples were collected from the waste pits, petrol stations, oil mines, and over natural gas fields (more details in Table ). At each sampling point, after the removal of vegetation, up to 10 surface subsamples from the top 20 cm of the soil profile were taken from several non-overlapping areas (20 cm width × 20 cm length). The soils were immediately mixed to produce homogenized pooled sample (500–800 g) and placed into ice boxes and transported. Upon arrival to the laboratory, selected samples (GC, SC, BIAL, KAM, KWC, KWU, BW, MG) were stored at − 80 °C prior to molecular analyses, and all samples were kept at 4 °C prior processing for chemical analyses. Gas chromatographic analysis of contamination Total petroleum hydrocarbon (TPH) content was assessed by gas chromatography with flame ionization detector (GC/FID) as described previously (Steliga et al. ). In brief, soil samples were homogenized, and hydrocarbons were isolated by ultrasonically modified dichloromethane extraction method (Chaîneau et al. ). The extraction was carried out at 40 °C for 20–35 min. TPH recovery yield was 95.9%. No artifacts were found in the sonication process. The analytes’ contents were enriched above the traceable limit. The recovery ratio of the analytes was determined by o -terphenyl. Purification was performed using columns with florisil sorbent (van Delft et al. ; Waksmundzka-Hajnos ). A Clarus 580 chromatograph (GC/FID, PerkinElmer), a Quadrex 007–1 capillary column (30 m × 0.53 mm, Panalytica), and a helium flow rate of 20 ml·min −1 were used to identify and quantitatively determine the amount of n -alkanes and compounds from the isoprenoid group. The temperatures of the PPS injector and the detector were 290 °C and 300 °C, respectively. The following temperature program was applied: 28 °C (2 min, isothermic), 28–105 °C (rate of 10 °C·min −1 ), 105–285 °C (rate of 5 °C·min −1 ), and 285 °C (20 min, isothermic). A set of calibration standards (Tusnovic Instruments) was used to determine the TPH content. The total hydrocarbon concentration was calculated as the total area under the obtained profiles. Isolation of potential hydrocarbon-degrading bacteria Ten grams of soil sample was suspended in 90.0 ml of sterile NaCl (0.9% (w/v) with added sodium pyrophosphate (0.1% (w/v)) and shaken for 1 h at room temperature and 150 rpm. Of serial dilutions of suspension, 1.0 ml was surface spread onto crude oil-coated Bushnell-Haas (BH) agar plates (1 g·l −1 K 2 HPO 4 , 1 g·l −1 KH 2 PO 4 , 1 g·l −1 NH 4 NO 3 , 0.02 g·l −1 CaCl 2 , 0.05 g·l −1 FeCl 3 , 0.2 g·l −1 MgSO 4 , 2 g·l −1 NaCl, 20.0 g·l −1 Noble agar, final pH 7.0 ± 0.2, supplemented with 1.0 ml of SL-10 trace element solution), and incubated at (a) 4 °C and 20 °C — Alpine samples, (b) room temperature — temperate samples, and (c) 40 °C — arid samples, for 30 days. From the highest dilutions (10 5 –10 6 ), the obtained isolates growing in the presence of crude oil were subsequently purified by streak plating on nutrient agar supplemented with sodium acetate (0.2% (w/v)). The obtained strains were maintained on nutrient agar. Hydrocarbon-degrading capabilities of pure bacterial strains Apart from crude oil-metabolizing strains obtained in this study, some organisms, capable of hydrocarbon transformation (IN47, IN53) isolated previously (Brzeszcz et al. ), were also included in this test phase. Each microorganism was tested for the ability to utilize selected hydrocarbons, i.e., n -alkanes: n C 7 , n C 10 , n C 16 ; iso-alkane: iso-C 15 ; monoaromatic compounds: toluene, a mixture of xylenes; PAHs: naphthalene, anthracene, phenanthrene, fluorene, fluoranthene, chrysene. The liquid compounds (at room temperature) were sterilized by filtration through a 0.2-μm membrane filter. A stock solution of each PAH (1% (w/v)) was prepared in acetone and sterilized. A loop full of a bacterial culture was inoculated in 10 ml of BH mineral medium containing a single liquid (at 20–40 °C) compound (0.5 ml). The capability to grow in the presence of PAH was tested using solidified BH medium coated with a single PAH. PAH solution in acetone was homogenously spread on the surface of BH pre-dried agar plate, and acetone was left to evaporate under sterile conditions. The modification of this approach (aliphatic compound spread on the surface of BH plate) was also used to evaluate the alkane-metabolizing capabilities of Alpine bacterial strains cultured at 4 °C. Then, the bacterial cells were transferred. The growth test with volatile compounds (toluene, xylenes) was conducted in sealed bottles to prevent solvent evaporation. The BH medium (20 ml) was placed in 50-ml bottle; next, 10 ml of tested compound was added, followed by bacterial inoculation. The bottles were sealed and placed in the desiccator. The incubation was performed at 4 °C and 20 °C (Alpine samples), room temperature (temperate samples), and 40 °C (arid samples) for 2–3 months. The bacterial growth was regularly monitored. The occurrence of bacterial biomass on the interface BH medium-hydrocarbon was counted as a positive score. The capability to grow in the PAH presence was assessed by the occurrence (a positive score) or lack (a negative score) of colonies on the PAH-coated BH agar plates. Sterile hydrocarbon-containing BH medium/plates as well as inoculating medium/plates without carbon source served as negative controls. To verify the degrading capabilities of the studied strains, a 96-well microplate, colorimetric test based on dehydrogenase activity, was applied (Wrenn and Venosa ). The reduction of p -iodo-nitrotetrazolium chloride (INT) into a colored (red) formazan form by bacterial activity is indirect evidence for metabolic capabilities towards the tested compound. Briefly, bacterial strain was cultured for 3–5 days in the nutrient medium with sodium acetate (0.2% (w/v)) to obtain suspension of 10 6 colony forming units·ml −1 (CFU·ml −1 ). The suspension was centrifuged and washed three times in phosphate-buffered saline (1 × PBS, pH 7.4) to remove culture broth. The pellet was resuspended in 1 ml of 1 × PBS. Of BH medium, 180 μl was placed into each well; then, 20 μl of prepared bacterial suspension and 5 μl of single liquid hydrocarbon were added. In the case of PAHs, firstly, compound solution (10 μl) was added; after acetone evaporation, the BH medium and bacterial cells were placed in the well. After the 60-day incubation period, 50 μl of filter-sterilized INT (3 g·l −1 ) was added and plates were reincubated in the dark overnight. Afterward, the color change was assessed visually. The appearance of yellow or brown color was noted as a positive score in case of PAH plates, and red color — in case of other plates. For each experimental variant (strain and compound), double replicates were carried out. Non-inoculated BH medium with added tested substance served as a negative control. Observation of biofilm formed by hydrocarbon-degrading bacteria using optical microscopy and SEM To observe the biofilm formed by hydrocarbon-degrading bacterium on the PAH crystals, we carried out analyses using an optical microscopy and SEM. The biofilm observations using the optical microscope were performed for each bacterial strain producing double positive score in previous phase (Wrenn-Venosa test and growth on mineral medium with the tested PAH). The SEM analyses were carried out for two strains (IN129 and IN53). The detailed description of these analyses was included into Supplementary Material. Bacterial identification Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) was applied for bacterial identification according to previously described method (Brzeszcz et al. ). The bacterial strains that could not be identified by MALDI-TOF MS were identified genetically. In brief, DNA was isolated using the Genomic Mini kit (A&A Biotechnology, Poland) according to the manufacturer's protocol. The quality and quantity of obtained material were assessed spectrophotometrically (NanoDrop200, Thermo Fisher Scientific, USA). The primer pair of 8F (5′-AGAGTTTGATCCTGGCTCAG–3′) and 1492R (5′-TACCTTGTTACGACTT-3′) was used to amplify the 16S rRNA gene (Turner et al. ). PCR was performed in a total volume of 25 μl containing Tris HCl (10 mM, pH 8.8), MgCl 2 (1.5 mM), KCl (50 mM), Nonidet P40 (0.08%, Fermentas, Lithuania), primers (5 pmol), deoxyribonucleotide (0.02 mM, Fermentas, Lithuania), Taq polymerase (2 U, Fermentas, Lithuania), and DNA (2 μl). The amplification cycle conditions were as follows: denaturation (94 °C, 30 s), primer annealing (55 °C, 30 s), and product extension (72 °C, 120 s). The PCR product was visualized on agarose gel (1.5%) and then purified enzymatically using exonuclease I of Escherichia coli (Fermentas, Lithuania) and FastAP™ (Fermentas, Lithuania). Purified amplicons were sequenced in both directions with corresponding primers using BigDye Terminator version 3.0 Ready Reaction Cycle Sequencing Kit (Amersham Bioscience Ltd., UK ) according to the manufacturer’s protocol. The products were analyzed in an automatic DNA sequencer ABI Prism 377XL (Applied Biosystems, USA). The obtained sequences were edited using Bioedit software version 7.1.9 (Hall ). 16S rDNA sequences were compared to known sequences in GenBank with BLAST (basic local alignment search tool) algorithm (Altschul et al. ), and chimeric sequences were checked with Bellerophon (Huber et al. ). Genome sequencing, assembly and annotation The genome sequencing was performed for strains: IN53, IN129, and IN118. The DNA was isolated using Sherlock AX kit (A&A Biotechnology, Poland) following the manufacturer’s protocol; then, DNA was quantified using Quant-it™ PicoGreen dsDNA Kit (Thermo Fisher Scientific, USA). DNA libraries were obtained with NEBNext DNA Library Prep Master Mix Set for Illumina (Illumina, USA). Short insert paired-end libraries (insert size 350 bp) and mate-pair libraries were sequenced on the MiSeq Illumina platform (Illumina, USA) in the paired-end reads technology (2 × 250 bp) using MiSeq Reagent Kit v2 (500 cycles, Illumina, USA). Adapter trimming and quality filtering of raw reads were conducted with Cutadapt version 3.0 (Martin ). The de novo assembly was done using Spades version 3.15.5 (Bankevich et al. ); the resulted assemblies were polished with Pilon (Walker et al. ). The genome sequences were annotated by the NCBI Prokaryotic Genomes Annotation Pipeline (PGAP; Tatusova et al. ). The genome sequences were deposited in the NCBI GenBank; the accession numbers are provided in Supplementary material, Table . Metagenomic DNA extraction and sequencing using Illumina MiSeq platform Metagenomic sequencing was performed for selected samples: MG, BW, GC, SC, KAM, BIAL, KWC, and KWU. DNA was extracted from 0.5 g of each soil sample using Bead-Beat Micro AX Gravity (A&A Biotechnology, Poland) according to the manufacturer’s instructions. The quality of DNA was verified by electrophoresis and spectrophotometry (260/280 nm ratio, NanoDrop, Thermo Fisher Scientific, Waltham, MA, USA); then, all DNAs were quantified using Quant-it™ PicoGreen dsDNA Kit (Thermo Fisher Scientific, USA). High-quality metagenomic DNA (mgDNA) samples were sequenced by Genomed S.A. (Warszawa, Poland). The mgDNA was sheared using Covaris E210 (Covaris, USA) with parameters recommended by Illumina (Illumina Inc, San Diego, CA, USA). The fragments were end-repaired using NEBNext® Ultra DNA Library Prep Kit for Illumina (New England BioLabs Ltd., UK) according to the manufacturer’s instructions. The adaptor-ligation, including the incorporation of sample index barcodes, was performed using TruSeq DNA HT Sample Prep Kit (Illumina, Inc., San Diego, CA, USA) according to Illumina’s instructions. The final products were amplified in eight PCR cycles. The average size of libraries was 430 bp (base pair). The libraries were normalized to 4 nM solutions and pooled prior to sequencing. Paired-end sequencing (2 × 250 bp) was performed on an Illumina MiSeq sequencer (Illumina, Inc., San Diego, CA, USA) using the MiSeq Reagent kit v2 (Illumina, Inc., San Diego, CA, USA) and following the standard run protocols. Data analysis All the paired-end reads of each dataset were joined to decrease the sequencing errors and were submitted directly in MG-RAST (Metagenome Rapid Annotation using Subsystem Technology (MG-RAST, http://metagenomics.anl.gov/ , Meyer et al. ) for downstream analysis. Quality control was performed on sequences in MG-RAST, including dereplication, ambiguous base filtering, quality filtering, and length filtering. The details regarding quality control are provided in Table . The raw sequences were filtered using usearch10 to remove short and low-quality reads (Edgar ). Then quality-filtered metagenomes were used for gene-targeted assembly (Wang et al. ). The analyses were performed for the genes that encode alkane monooxygenase ( alkB ) and alpha subunit of aromatic ring hydroxylating dioxygenases (ARHDs), such as nahAc , nahA3 , nagAc , ndoB , ndo , pahAc , pahA3 , phnAc , phnA1 , bphAc , bphA1 , dntAc , arhA1 , tod , tmo , narAa , phdA / pdoA2 , nidA / pdoA1 , and nidA3 / fadA1 . The applied strategy, Xander assembler, uses protein hidden Markov models (HMM) of known genes, what results in the assembly of longer and higher quality contigs than other assembly methods for specific genes of interest. Seed sequences, hidden Markov models (HMM), nucleotide, and amino acid sequences of the hydrocarbon-degrading genes were downloaded from the Ribosomal Database Project’s (RDP) Fungene repository ( https://fungene.cme.msu.edu ; Fish et al. ). The minimal cutoff of sequences and HMM coverage was set to 300 amino acids and 80%, respectively. The hidden Markov models were built and used to assemble sequences from the metagenomes as described ( https://github.com/rdpstaff/Xander_assembler ). In most instances, default assembly parameters were used, expect MIN_LENGTH parameter which was decreased to 50. No chimeras were identified from any of the assembled gene contigs. The obtained contigs were clustered at the 95% amino acid similarity level, and the longest contig was used as a representative of each cluster. The closest taxonomic affiliation of the representative contig was determined against the reference gene database and nonredundant protein sequence database (nr, NCBI GenBank, 10 October 2023) using the BLASTP algorithm. The top hit of the representative sequences to the NCBI GenBank database had a similarity higher than 60%. Operational taxonomic units (OTUs) for each gene were generated using the get_OTUabundance.sh script in Xander using a distance of 0.05 (Wang et al. ). Data availability The shotgun metagenomic sequences were deposited in the NCBI under the BioProjects: PRJNA558243 (Alpine soil samples), PRJNA983109 (arid soil samples), and PRJNA983128 (temperate soil samples), and in MG-RAST platform under the accession numbers: mgp13360 (Alpine soils) and mgp81634 (temperate and arid soil samples). The 16S rRNA sequences of the obtained strains were deposited to the NCBI GenBank under accession numbers given in Supplementary material, Table .
PAHs were obtained from Sigma-Aldrich (USA). Used inorganic compounds, n -alkanes, monoaromatic hydrocarbons, and solvents (acetone) were purchased from Avantor Performance Materials (Gliwice, Poland). Pristane (iso-C 15 , 2,6,10,14-tetramethylpentadecane) and p -iodo-nitrotetrazolium chloride (INT) were purchased from Koch Light Laboratories (UK) and Fluka (Germany), respectively. Noble agar and nutrient media (BD Difco nutrient agar, BD Difco nutrient broth) were from Difco (Becton Dickinson, USA). Unless otherwise stated, all chemicals were of analytical grade. Crude oil (sterilized) from the Barnówko-Mostno-Buszewo oilfield (Poland) was used as a substrate.
In this study, the soils were sampled within three climatic zones: Alpine (Austria), temperate (Poland), and arid (Kuwait and Israel). The unpolluted soils were taken in sites with no presence of anthropogenic contamination with hydrocarbons such as national parks (BIAL, KAM, BW) and uncontaminated areas in the proximity of polluted ones (KWU, I2; more details in Table ). The polluted soil samples were collected from the waste pits, petrol stations, oil mines, and over natural gas fields (more details in Table ). At each sampling point, after the removal of vegetation, up to 10 surface subsamples from the top 20 cm of the soil profile were taken from several non-overlapping areas (20 cm width × 20 cm length). The soils were immediately mixed to produce homogenized pooled sample (500–800 g) and placed into ice boxes and transported. Upon arrival to the laboratory, selected samples (GC, SC, BIAL, KAM, KWC, KWU, BW, MG) were stored at − 80 °C prior to molecular analyses, and all samples were kept at 4 °C prior processing for chemical analyses.
Total petroleum hydrocarbon (TPH) content was assessed by gas chromatography with flame ionization detector (GC/FID) as described previously (Steliga et al. ). In brief, soil samples were homogenized, and hydrocarbons were isolated by ultrasonically modified dichloromethane extraction method (Chaîneau et al. ). The extraction was carried out at 40 °C for 20–35 min. TPH recovery yield was 95.9%. No artifacts were found in the sonication process. The analytes’ contents were enriched above the traceable limit. The recovery ratio of the analytes was determined by o -terphenyl. Purification was performed using columns with florisil sorbent (van Delft et al. ; Waksmundzka-Hajnos ). A Clarus 580 chromatograph (GC/FID, PerkinElmer), a Quadrex 007–1 capillary column (30 m × 0.53 mm, Panalytica), and a helium flow rate of 20 ml·min −1 were used to identify and quantitatively determine the amount of n -alkanes and compounds from the isoprenoid group. The temperatures of the PPS injector and the detector were 290 °C and 300 °C, respectively. The following temperature program was applied: 28 °C (2 min, isothermic), 28–105 °C (rate of 10 °C·min −1 ), 105–285 °C (rate of 5 °C·min −1 ), and 285 °C (20 min, isothermic). A set of calibration standards (Tusnovic Instruments) was used to determine the TPH content. The total hydrocarbon concentration was calculated as the total area under the obtained profiles.
Ten grams of soil sample was suspended in 90.0 ml of sterile NaCl (0.9% (w/v) with added sodium pyrophosphate (0.1% (w/v)) and shaken for 1 h at room temperature and 150 rpm. Of serial dilutions of suspension, 1.0 ml was surface spread onto crude oil-coated Bushnell-Haas (BH) agar plates (1 g·l −1 K 2 HPO 4 , 1 g·l −1 KH 2 PO 4 , 1 g·l −1 NH 4 NO 3 , 0.02 g·l −1 CaCl 2 , 0.05 g·l −1 FeCl 3 , 0.2 g·l −1 MgSO 4 , 2 g·l −1 NaCl, 20.0 g·l −1 Noble agar, final pH 7.0 ± 0.2, supplemented with 1.0 ml of SL-10 trace element solution), and incubated at (a) 4 °C and 20 °C — Alpine samples, (b) room temperature — temperate samples, and (c) 40 °C — arid samples, for 30 days. From the highest dilutions (10 5 –10 6 ), the obtained isolates growing in the presence of crude oil were subsequently purified by streak plating on nutrient agar supplemented with sodium acetate (0.2% (w/v)). The obtained strains were maintained on nutrient agar.
Apart from crude oil-metabolizing strains obtained in this study, some organisms, capable of hydrocarbon transformation (IN47, IN53) isolated previously (Brzeszcz et al. ), were also included in this test phase. Each microorganism was tested for the ability to utilize selected hydrocarbons, i.e., n -alkanes: n C 7 , n C 10 , n C 16 ; iso-alkane: iso-C 15 ; monoaromatic compounds: toluene, a mixture of xylenes; PAHs: naphthalene, anthracene, phenanthrene, fluorene, fluoranthene, chrysene. The liquid compounds (at room temperature) were sterilized by filtration through a 0.2-μm membrane filter. A stock solution of each PAH (1% (w/v)) was prepared in acetone and sterilized. A loop full of a bacterial culture was inoculated in 10 ml of BH mineral medium containing a single liquid (at 20–40 °C) compound (0.5 ml). The capability to grow in the presence of PAH was tested using solidified BH medium coated with a single PAH. PAH solution in acetone was homogenously spread on the surface of BH pre-dried agar plate, and acetone was left to evaporate under sterile conditions. The modification of this approach (aliphatic compound spread on the surface of BH plate) was also used to evaluate the alkane-metabolizing capabilities of Alpine bacterial strains cultured at 4 °C. Then, the bacterial cells were transferred. The growth test with volatile compounds (toluene, xylenes) was conducted in sealed bottles to prevent solvent evaporation. The BH medium (20 ml) was placed in 50-ml bottle; next, 10 ml of tested compound was added, followed by bacterial inoculation. The bottles were sealed and placed in the desiccator. The incubation was performed at 4 °C and 20 °C (Alpine samples), room temperature (temperate samples), and 40 °C (arid samples) for 2–3 months. The bacterial growth was regularly monitored. The occurrence of bacterial biomass on the interface BH medium-hydrocarbon was counted as a positive score. The capability to grow in the PAH presence was assessed by the occurrence (a positive score) or lack (a negative score) of colonies on the PAH-coated BH agar plates. Sterile hydrocarbon-containing BH medium/plates as well as inoculating medium/plates without carbon source served as negative controls. To verify the degrading capabilities of the studied strains, a 96-well microplate, colorimetric test based on dehydrogenase activity, was applied (Wrenn and Venosa ). The reduction of p -iodo-nitrotetrazolium chloride (INT) into a colored (red) formazan form by bacterial activity is indirect evidence for metabolic capabilities towards the tested compound. Briefly, bacterial strain was cultured for 3–5 days in the nutrient medium with sodium acetate (0.2% (w/v)) to obtain suspension of 10 6 colony forming units·ml −1 (CFU·ml −1 ). The suspension was centrifuged and washed three times in phosphate-buffered saline (1 × PBS, pH 7.4) to remove culture broth. The pellet was resuspended in 1 ml of 1 × PBS. Of BH medium, 180 μl was placed into each well; then, 20 μl of prepared bacterial suspension and 5 μl of single liquid hydrocarbon were added. In the case of PAHs, firstly, compound solution (10 μl) was added; after acetone evaporation, the BH medium and bacterial cells were placed in the well. After the 60-day incubation period, 50 μl of filter-sterilized INT (3 g·l −1 ) was added and plates were reincubated in the dark overnight. Afterward, the color change was assessed visually. The appearance of yellow or brown color was noted as a positive score in case of PAH plates, and red color — in case of other plates. For each experimental variant (strain and compound), double replicates were carried out. Non-inoculated BH medium with added tested substance served as a negative control.
To observe the biofilm formed by hydrocarbon-degrading bacterium on the PAH crystals, we carried out analyses using an optical microscopy and SEM. The biofilm observations using the optical microscope were performed for each bacterial strain producing double positive score in previous phase (Wrenn-Venosa test and growth on mineral medium with the tested PAH). The SEM analyses were carried out for two strains (IN129 and IN53). The detailed description of these analyses was included into Supplementary Material.
Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) was applied for bacterial identification according to previously described method (Brzeszcz et al. ). The bacterial strains that could not be identified by MALDI-TOF MS were identified genetically. In brief, DNA was isolated using the Genomic Mini kit (A&A Biotechnology, Poland) according to the manufacturer's protocol. The quality and quantity of obtained material were assessed spectrophotometrically (NanoDrop200, Thermo Fisher Scientific, USA). The primer pair of 8F (5′-AGAGTTTGATCCTGGCTCAG–3′) and 1492R (5′-TACCTTGTTACGACTT-3′) was used to amplify the 16S rRNA gene (Turner et al. ). PCR was performed in a total volume of 25 μl containing Tris HCl (10 mM, pH 8.8), MgCl 2 (1.5 mM), KCl (50 mM), Nonidet P40 (0.08%, Fermentas, Lithuania), primers (5 pmol), deoxyribonucleotide (0.02 mM, Fermentas, Lithuania), Taq polymerase (2 U, Fermentas, Lithuania), and DNA (2 μl). The amplification cycle conditions were as follows: denaturation (94 °C, 30 s), primer annealing (55 °C, 30 s), and product extension (72 °C, 120 s). The PCR product was visualized on agarose gel (1.5%) and then purified enzymatically using exonuclease I of Escherichia coli (Fermentas, Lithuania) and FastAP™ (Fermentas, Lithuania). Purified amplicons were sequenced in both directions with corresponding primers using BigDye Terminator version 3.0 Ready Reaction Cycle Sequencing Kit (Amersham Bioscience Ltd., UK ) according to the manufacturer’s protocol. The products were analyzed in an automatic DNA sequencer ABI Prism 377XL (Applied Biosystems, USA). The obtained sequences were edited using Bioedit software version 7.1.9 (Hall ). 16S rDNA sequences were compared to known sequences in GenBank with BLAST (basic local alignment search tool) algorithm (Altschul et al. ), and chimeric sequences were checked with Bellerophon (Huber et al. ).
The genome sequencing was performed for strains: IN53, IN129, and IN118. The DNA was isolated using Sherlock AX kit (A&A Biotechnology, Poland) following the manufacturer’s protocol; then, DNA was quantified using Quant-it™ PicoGreen dsDNA Kit (Thermo Fisher Scientific, USA). DNA libraries were obtained with NEBNext DNA Library Prep Master Mix Set for Illumina (Illumina, USA). Short insert paired-end libraries (insert size 350 bp) and mate-pair libraries were sequenced on the MiSeq Illumina platform (Illumina, USA) in the paired-end reads technology (2 × 250 bp) using MiSeq Reagent Kit v2 (500 cycles, Illumina, USA). Adapter trimming and quality filtering of raw reads were conducted with Cutadapt version 3.0 (Martin ). The de novo assembly was done using Spades version 3.15.5 (Bankevich et al. ); the resulted assemblies were polished with Pilon (Walker et al. ). The genome sequences were annotated by the NCBI Prokaryotic Genomes Annotation Pipeline (PGAP; Tatusova et al. ). The genome sequences were deposited in the NCBI GenBank; the accession numbers are provided in Supplementary material, Table .
Metagenomic sequencing was performed for selected samples: MG, BW, GC, SC, KAM, BIAL, KWC, and KWU. DNA was extracted from 0.5 g of each soil sample using Bead-Beat Micro AX Gravity (A&A Biotechnology, Poland) according to the manufacturer’s instructions. The quality of DNA was verified by electrophoresis and spectrophotometry (260/280 nm ratio, NanoDrop, Thermo Fisher Scientific, Waltham, MA, USA); then, all DNAs were quantified using Quant-it™ PicoGreen dsDNA Kit (Thermo Fisher Scientific, USA). High-quality metagenomic DNA (mgDNA) samples were sequenced by Genomed S.A. (Warszawa, Poland). The mgDNA was sheared using Covaris E210 (Covaris, USA) with parameters recommended by Illumina (Illumina Inc, San Diego, CA, USA). The fragments were end-repaired using NEBNext® Ultra DNA Library Prep Kit for Illumina (New England BioLabs Ltd., UK) according to the manufacturer’s instructions. The adaptor-ligation, including the incorporation of sample index barcodes, was performed using TruSeq DNA HT Sample Prep Kit (Illumina, Inc., San Diego, CA, USA) according to Illumina’s instructions. The final products were amplified in eight PCR cycles. The average size of libraries was 430 bp (base pair). The libraries were normalized to 4 nM solutions and pooled prior to sequencing. Paired-end sequencing (2 × 250 bp) was performed on an Illumina MiSeq sequencer (Illumina, Inc., San Diego, CA, USA) using the MiSeq Reagent kit v2 (Illumina, Inc., San Diego, CA, USA) and following the standard run protocols.
All the paired-end reads of each dataset were joined to decrease the sequencing errors and were submitted directly in MG-RAST (Metagenome Rapid Annotation using Subsystem Technology (MG-RAST, http://metagenomics.anl.gov/ , Meyer et al. ) for downstream analysis. Quality control was performed on sequences in MG-RAST, including dereplication, ambiguous base filtering, quality filtering, and length filtering. The details regarding quality control are provided in Table . The raw sequences were filtered using usearch10 to remove short and low-quality reads (Edgar ). Then quality-filtered metagenomes were used for gene-targeted assembly (Wang et al. ). The analyses were performed for the genes that encode alkane monooxygenase ( alkB ) and alpha subunit of aromatic ring hydroxylating dioxygenases (ARHDs), such as nahAc , nahA3 , nagAc , ndoB , ndo , pahAc , pahA3 , phnAc , phnA1 , bphAc , bphA1 , dntAc , arhA1 , tod , tmo , narAa , phdA / pdoA2 , nidA / pdoA1 , and nidA3 / fadA1 . The applied strategy, Xander assembler, uses protein hidden Markov models (HMM) of known genes, what results in the assembly of longer and higher quality contigs than other assembly methods for specific genes of interest. Seed sequences, hidden Markov models (HMM), nucleotide, and amino acid sequences of the hydrocarbon-degrading genes were downloaded from the Ribosomal Database Project’s (RDP) Fungene repository ( https://fungene.cme.msu.edu ; Fish et al. ). The minimal cutoff of sequences and HMM coverage was set to 300 amino acids and 80%, respectively. The hidden Markov models were built and used to assemble sequences from the metagenomes as described ( https://github.com/rdpstaff/Xander_assembler ). In most instances, default assembly parameters were used, expect MIN_LENGTH parameter which was decreased to 50. No chimeras were identified from any of the assembled gene contigs. The obtained contigs were clustered at the 95% amino acid similarity level, and the longest contig was used as a representative of each cluster. The closest taxonomic affiliation of the representative contig was determined against the reference gene database and nonredundant protein sequence database (nr, NCBI GenBank, 10 October 2023) using the BLASTP algorithm. The top hit of the representative sequences to the NCBI GenBank database had a similarity higher than 60%. Operational taxonomic units (OTUs) for each gene were generated using the get_OTUabundance.sh script in Xander using a distance of 0.05 (Wang et al. ).
The shotgun metagenomic sequences were deposited in the NCBI under the BioProjects: PRJNA558243 (Alpine soil samples), PRJNA983109 (arid soil samples), and PRJNA983128 (temperate soil samples), and in MG-RAST platform under the accession numbers: mgp13360 (Alpine soils) and mgp81634 (temperate and arid soil samples). The 16S rRNA sequences of the obtained strains were deposited to the NCBI GenBank under accession numbers given in Supplementary material, Table .
Extended catabolic preferences In this study, total 141 hydrocarbon-utilizing bacteria were isolated from both unpolluted and contaminated soils (Supplementary material, Table ). The range of TPH content was 4046–43,861 and 320–2754 mg kg −1 dry weight of soil (further: dry wt.) in contaminated and uncontaminated samples, respectively (Table ). Two additional stains (IN53 and IN47), isolated in the previous study (Brzeszcz et al. ), were included in this one. Among all studied (143) bacterial strains, 132 organisms exhibited extended metabolic profiles, namely they grew in the presence of both n -alkane and aromatic compound (toluene/xylene and/or some PAHs). The bacteria were isolated from all analyzed samples regardless of the contamination level (Table ; Supplementary material, Table ), and climatic conditions in the sampling sites (Table ; Supplementary material, Table ). To sum up, 63, 25, and 55 hydrocarbon-degrading strains were obtained from alpine, arid and temperate soil samples, respectively (Supplementary material, Table ). The lowest number of degraders were isolated from KWC and KWU samples, respectively, one and three strains (Supplementary material, Table ). The Rhodococcus spp. formed the most considerable group among all obtained strains with extended catabolic preferences (44% of isolated strains were classified to this taxon), followed by the representatives of the Paeniglutamicibacter (12%), Pseudomonas (10%), and Mycolicibacterium genera (Fig. ; Table – ). The described metabolic traits were also found among other genera, i.e., the Ochrobactrum , Arthrobacter , Gordonia , Dietzia , Mycobacterium , Pseudarthrobacter , and Paenarthrobacter taxa (Fig. ); however, the representatives of these taxa were not as frequently isolated as bacteria belonging to abovementioned groups (Table – ). Our observation indicated some temperature preferences among the Alpine degraders belonging to the Rhodococcus , Paeniglutamicibacter , and Pseudomonas genera, namely the majority of Rhodococcus strains were isolated at 20 °C, whereas the representatives of the other taxa were obtained at 4 °C (Supplementary material, Table ). All studied strains grew in the presence of tested linear aliphatic compounds, but they revealed some degrading preferences towards aromatic substances. To illustrate, the representatives of the Rhodococcus , Paeniglutamicibacter , and Pseudomonas genera utilized the wide set of compounds ( n -alkanes, BTEX and selected PAHs), while the majority of bacteria belonging to the Mycolicibacterium taxon grew in the presence of PAHs rather than monoaromatics (Supplementary material, Table ). Additionally, to n -alkanes, a branched compound (pristane) also served as a growth substrate for most of the studied bacteria (Supplementary material, Table ). Low molecular weight PAHs (LMW PAHs: naphthalene, anthracene, phenanthrene and fluorene) were utilized by the majority of analyzed strains (103 strains); in turn, a smaller bacterial group (30 strains) used high molecular weight PAHs (HMW PAHs: pyrene or chrysene) as a carbon source ( Supplementary material, Table ). The bacterial capabilities to grow in the presence of the hydrocarbons were assessed by biomass formation on the interface between hydrophobic substance-mineral medium and dehydrogenase activity evaluated by the Wrenn-Venosa test. Due to the fact that bacterial growth on the PAH crystals is difficult to observe, we decided to apply the optical microscopy and SEM technique to visualize the presence of microbial biofilm on these crystals (Fig. A–D). These approaches let us to notice the biofilm formed by bacterium on the PAH surface. Here, we presented the examples of obtained SEM micrographs, namely those of biofilm formed by Rhodococcus qingshengii IN129 (Fig. A, B) and Mycolicibacterium frederiksbergense IN53 cells (Fig. C, D) on the surface of anthracene and pyrene crystals, respectively. In the case of IN129, the applied environmental-SEM (E-SEM, FEI) was operated in low vacuum mode with the presence of water vapor. Moreover, the sample preparation for examination was not required. Thanks to that, the natural (unamended) state of biofilm could be observed. The SEM analysis of IN53 growing in the presence of four-ring PAH was performed at a low accelerating voltage of the primary beam using Auriga FIB/SEM (Zeiss, Germany). This strategy let to observe the biofilm fragments as a result of more destructive sample preparation for this ex situ microscopic procedure compared to no requirements for E-SEM. On the other hand, the asymmetric shape of bacterial cells characteristic of mycolicibacterial cell division was recorded thanks to the FIB/SEM (Fig. C, D). The degradation capabilities of the studied bacteria were assessed taking into account the observed biofilm on the PAH crystals as well as the detected dehydrogenase activity (positive results of the Wrenn-Venosa test). In case of Rhodococcus qingshengii IN129 and Mycolicibacterium frederiksbergense IN53, these observations indicated that the bacteria grew in the presence of anthracene and pyrene, respectively. Moreover, the cell shape of Mycolicibacterium frederiksbergense IN53 suggested that the pyrene, a sole energy source in this experimental condition, was degraded and the obtained energy was utilized for bacterial growth and proliferation. Although the hydrocarbon degradation capabilities of the individual strain were not evaluated chromatographically (quantitative assessment), the applied approach (the biofilm observation along with growth in the presence of tested compound and dehydrogenase activity) was sufficient to assess the degrading capabilities towards single compound. It should be mentioned that some strains, obtained in this study, were previously tested to verify if they biodegrade various hydrocarbons (Brzeszcz et al. ). These capabilities were assessed chromatographically. It was shown that consortium consisted of the Rhodococcus erythropolis IN119, Rhodococcus sp. IN136, Mycolicibacterium frederiksbergense IN53, Dietzia sp. IN133, Pseudomonas sp. IN132, Arthrobacter sp. IN212, and Gordonia sp. IN138 removed both hydrocarbon classes from contaminated soils during a 60-day bioremediation experiment. The genetic potential towards degradation of both n -alkanes and aromatic hydrocarbons was assessed for the genomes of Rhodococcus qingshengii IN129 and Mycolicibacterium frederiksbergense IN53 (Table ). Based on the NCBI PGAP annotation, alkB genes were found in both genomes (Table ). Moreover, it was detected the genes recognized as the ones encoding for ARHDs and enzymes involved in the lower aromatic pathways ( catA encoding for catechol 1,2-dioxygenase and pcaG and pcaH encoding for α and β subunits of protocatechuate 3,4-dioxygense; Table ). Functional gene profiles involved in aerobic degradation of petroleum compounds We performed taxonomic affiliation of the hydrocarbon-degrading target genes to determine the distribution of microorganisms associated with the mentioned process. The analyses were limited to the selected genes encoding for the enzymes involved in the activation of the substrate (first step of hydrocarbon degradation). The results of Xander assembly are provided in Table (Supplementary material). The community of alkane-degrading bacteria was identified by analysis of the alkB gene encoding the alkane monooxygenase. In turn, the aromatic hydrocarbon-degrading community was analyzed using genes that encode the alpha subunit of aromatic ring hydroxylating dioxygenases (ARHDs), such as nahAc , nahA3 , nagAc , ndoB , ndo , pahAc , pahA3 , phnAc , phnA1 , bphAc , bphA1 , dntAc , arhA1 , tod , narAa , phdA / pdoA2 , nidA / pdoA1 , and nidA3 / fadA1. Additionally, we assembled rplB , a single copy gene. Total counts of rplB were used to normalize the abundance of each alkB and ARHDs sequences. We found that both alkB and ARHDs, assembled using this method, were detected in both contaminated and unpolluted soil samples (Supplementary material, Fig. - ). alkB genes associated with the Mycobacterium , Mycolicibacterium , Rhodococcus , Pseudomonas , Brevundimonas , Acinetobacter , and Nocardioides genera were found in both kinds (unpolluted/polluted) of analyzed samples (Supplementary material, Fig. - ). The alkB reads affiliated with Panacagrimonas were found in samples characterized by the lowest hydrocarbon levels (BW, BIAL, KWU; Supplementary material Fig. ). Interestingly, Noviherbaspirillum -like alkB genes were detected only in the KWU sample (Supplementary material, Fig. - ). The majority of ARHD sequences were linked with the Pseudomonas ( nahAc , bphA , bnzA ), Rhodococcus ( narAa , bphA ), Mycolicibacterium ( nidA/nidA3 ), Sphingobium ( phn ), and Novosphingobium ( phn ) genera (Supplementary material, Fig. ). This gene-targeted assembly aimed to (a) assess if the alkB and ARHD genes sharing common taxonomic affiliation are ubiquitous across the samples and (b) establish the taxonomic affiliation of this gene group. It (this group) was found in seven among eight metagenomes (Table ). Interestingly, determinants encoding for alkB and ARHDs, which share common taxonomic affiliation, were mostly linked not only with the Mycobacterium , Mycolicibacterium , and Rhodococcus genera (frequently detected), but also with the Pseudomonas , Panacagrimonas , and Sphingobium genera (in single samples; Table ).
In this study, total 141 hydrocarbon-utilizing bacteria were isolated from both unpolluted and contaminated soils (Supplementary material, Table ). The range of TPH content was 4046–43,861 and 320–2754 mg kg −1 dry weight of soil (further: dry wt.) in contaminated and uncontaminated samples, respectively (Table ). Two additional stains (IN53 and IN47), isolated in the previous study (Brzeszcz et al. ), were included in this one. Among all studied (143) bacterial strains, 132 organisms exhibited extended metabolic profiles, namely they grew in the presence of both n -alkane and aromatic compound (toluene/xylene and/or some PAHs). The bacteria were isolated from all analyzed samples regardless of the contamination level (Table ; Supplementary material, Table ), and climatic conditions in the sampling sites (Table ; Supplementary material, Table ). To sum up, 63, 25, and 55 hydrocarbon-degrading strains were obtained from alpine, arid and temperate soil samples, respectively (Supplementary material, Table ). The lowest number of degraders were isolated from KWC and KWU samples, respectively, one and three strains (Supplementary material, Table ). The Rhodococcus spp. formed the most considerable group among all obtained strains with extended catabolic preferences (44% of isolated strains were classified to this taxon), followed by the representatives of the Paeniglutamicibacter (12%), Pseudomonas (10%), and Mycolicibacterium genera (Fig. ; Table – ). The described metabolic traits were also found among other genera, i.e., the Ochrobactrum , Arthrobacter , Gordonia , Dietzia , Mycobacterium , Pseudarthrobacter , and Paenarthrobacter taxa (Fig. ); however, the representatives of these taxa were not as frequently isolated as bacteria belonging to abovementioned groups (Table – ). Our observation indicated some temperature preferences among the Alpine degraders belonging to the Rhodococcus , Paeniglutamicibacter , and Pseudomonas genera, namely the majority of Rhodococcus strains were isolated at 20 °C, whereas the representatives of the other taxa were obtained at 4 °C (Supplementary material, Table ). All studied strains grew in the presence of tested linear aliphatic compounds, but they revealed some degrading preferences towards aromatic substances. To illustrate, the representatives of the Rhodococcus , Paeniglutamicibacter , and Pseudomonas genera utilized the wide set of compounds ( n -alkanes, BTEX and selected PAHs), while the majority of bacteria belonging to the Mycolicibacterium taxon grew in the presence of PAHs rather than monoaromatics (Supplementary material, Table ). Additionally, to n -alkanes, a branched compound (pristane) also served as a growth substrate for most of the studied bacteria (Supplementary material, Table ). Low molecular weight PAHs (LMW PAHs: naphthalene, anthracene, phenanthrene and fluorene) were utilized by the majority of analyzed strains (103 strains); in turn, a smaller bacterial group (30 strains) used high molecular weight PAHs (HMW PAHs: pyrene or chrysene) as a carbon source ( Supplementary material, Table ). The bacterial capabilities to grow in the presence of the hydrocarbons were assessed by biomass formation on the interface between hydrophobic substance-mineral medium and dehydrogenase activity evaluated by the Wrenn-Venosa test. Due to the fact that bacterial growth on the PAH crystals is difficult to observe, we decided to apply the optical microscopy and SEM technique to visualize the presence of microbial biofilm on these crystals (Fig. A–D). These approaches let us to notice the biofilm formed by bacterium on the PAH surface. Here, we presented the examples of obtained SEM micrographs, namely those of biofilm formed by Rhodococcus qingshengii IN129 (Fig. A, B) and Mycolicibacterium frederiksbergense IN53 cells (Fig. C, D) on the surface of anthracene and pyrene crystals, respectively. In the case of IN129, the applied environmental-SEM (E-SEM, FEI) was operated in low vacuum mode with the presence of water vapor. Moreover, the sample preparation for examination was not required. Thanks to that, the natural (unamended) state of biofilm could be observed. The SEM analysis of IN53 growing in the presence of four-ring PAH was performed at a low accelerating voltage of the primary beam using Auriga FIB/SEM (Zeiss, Germany). This strategy let to observe the biofilm fragments as a result of more destructive sample preparation for this ex situ microscopic procedure compared to no requirements for E-SEM. On the other hand, the asymmetric shape of bacterial cells characteristic of mycolicibacterial cell division was recorded thanks to the FIB/SEM (Fig. C, D). The degradation capabilities of the studied bacteria were assessed taking into account the observed biofilm on the PAH crystals as well as the detected dehydrogenase activity (positive results of the Wrenn-Venosa test). In case of Rhodococcus qingshengii IN129 and Mycolicibacterium frederiksbergense IN53, these observations indicated that the bacteria grew in the presence of anthracene and pyrene, respectively. Moreover, the cell shape of Mycolicibacterium frederiksbergense IN53 suggested that the pyrene, a sole energy source in this experimental condition, was degraded and the obtained energy was utilized for bacterial growth and proliferation. Although the hydrocarbon degradation capabilities of the individual strain were not evaluated chromatographically (quantitative assessment), the applied approach (the biofilm observation along with growth in the presence of tested compound and dehydrogenase activity) was sufficient to assess the degrading capabilities towards single compound. It should be mentioned that some strains, obtained in this study, were previously tested to verify if they biodegrade various hydrocarbons (Brzeszcz et al. ). These capabilities were assessed chromatographically. It was shown that consortium consisted of the Rhodococcus erythropolis IN119, Rhodococcus sp. IN136, Mycolicibacterium frederiksbergense IN53, Dietzia sp. IN133, Pseudomonas sp. IN132, Arthrobacter sp. IN212, and Gordonia sp. IN138 removed both hydrocarbon classes from contaminated soils during a 60-day bioremediation experiment. The genetic potential towards degradation of both n -alkanes and aromatic hydrocarbons was assessed for the genomes of Rhodococcus qingshengii IN129 and Mycolicibacterium frederiksbergense IN53 (Table ). Based on the NCBI PGAP annotation, alkB genes were found in both genomes (Table ). Moreover, it was detected the genes recognized as the ones encoding for ARHDs and enzymes involved in the lower aromatic pathways ( catA encoding for catechol 1,2-dioxygenase and pcaG and pcaH encoding for α and β subunits of protocatechuate 3,4-dioxygense; Table ).
We performed taxonomic affiliation of the hydrocarbon-degrading target genes to determine the distribution of microorganisms associated with the mentioned process. The analyses were limited to the selected genes encoding for the enzymes involved in the activation of the substrate (first step of hydrocarbon degradation). The results of Xander assembly are provided in Table (Supplementary material). The community of alkane-degrading bacteria was identified by analysis of the alkB gene encoding the alkane monooxygenase. In turn, the aromatic hydrocarbon-degrading community was analyzed using genes that encode the alpha subunit of aromatic ring hydroxylating dioxygenases (ARHDs), such as nahAc , nahA3 , nagAc , ndoB , ndo , pahAc , pahA3 , phnAc , phnA1 , bphAc , bphA1 , dntAc , arhA1 , tod , narAa , phdA / pdoA2 , nidA / pdoA1 , and nidA3 / fadA1. Additionally, we assembled rplB , a single copy gene. Total counts of rplB were used to normalize the abundance of each alkB and ARHDs sequences. We found that both alkB and ARHDs, assembled using this method, were detected in both contaminated and unpolluted soil samples (Supplementary material, Fig. - ). alkB genes associated with the Mycobacterium , Mycolicibacterium , Rhodococcus , Pseudomonas , Brevundimonas , Acinetobacter , and Nocardioides genera were found in both kinds (unpolluted/polluted) of analyzed samples (Supplementary material, Fig. - ). The alkB reads affiliated with Panacagrimonas were found in samples characterized by the lowest hydrocarbon levels (BW, BIAL, KWU; Supplementary material Fig. ). Interestingly, Noviherbaspirillum -like alkB genes were detected only in the KWU sample (Supplementary material, Fig. - ). The majority of ARHD sequences were linked with the Pseudomonas ( nahAc , bphA , bnzA ), Rhodococcus ( narAa , bphA ), Mycolicibacterium ( nidA/nidA3 ), Sphingobium ( phn ), and Novosphingobium ( phn ) genera (Supplementary material, Fig. ). This gene-targeted assembly aimed to (a) assess if the alkB and ARHD genes sharing common taxonomic affiliation are ubiquitous across the samples and (b) establish the taxonomic affiliation of this gene group. It (this group) was found in seven among eight metagenomes (Table ). Interestingly, determinants encoding for alkB and ARHDs, which share common taxonomic affiliation, were mostly linked not only with the Mycobacterium , Mycolicibacterium , and Rhodococcus genera (frequently detected), but also with the Pseudomonas , Panacagrimonas , and Sphingobium genera (in single samples; Table ).
The natural metabolic capabilities of microorganisms are the basis for an effective, efficient, and eco-friendly approach to remediate the contaminated environment. Diversified hydrocarbon structures (aliphatic, aromatic) require the activation of various metabolic pathways to break down them into non-toxic substances. There are some bacterial degraders whose pathways correspond only to one hydrocarbon class (i.e., only aliphatic compounds). However, this strategy seems to be less advantageous compared to bacterium utilizing both n -alkanes and aromatic substances. While the co-occurrence and concurrence of many pathways targeted at different hydrocarbons within an individual bacterium are worth-understanding phenomena, it should be emphasized that the number of studies focusing on this subject is limited. Bacteria with heterogeneous preferences towards mentioned chemicals occupy hydrocarbon-rich soils (Brzeszcz and Kaszycki and references therein). On the other hand, a question arises: is the presence of these bacteria restricted only to these soils? There are pieces of evidence indicating that an unpolluted environment harbors genetic potential for hydrocarbon degradation (Johnsen and Karlson ; Jurelevicius et al. ; Schwarz et al. ), and microorganisms with capabilities toward one class of these compounds may also inhabit mentioned habitats (Margesin et al. ; Schwarz et al. ; Habib et al. ). So far, no unambiguous proof is showing that soils with limited hydrocarbon content are deprived of multi-degrading bacteria. We claim that these extended preferences are common traits among some ubiquitous bacterial degraders. To test our hypothesis, bacteria utilizing both n -alkanes and aromatic hydrocarbons were isolated from soils differing by hydrocarbon content (Supplementary material, Table ). Additionally, qualitative metagenomic analyses of the selected soil samples were performed to evaluate the presence of the key hydrocarbon-degrading genes. The uncontaminated soil is not deprived of hydrocarbons (Whyte et al. ; Margesin et al. ; Delgado et al. ). The sources of naturally occurring hydrocarbons in soil are microorganisms (cyanobacteria, chemotrophic bacteria; Castro et al. ), lichens, mosses (Goss and Wilhem ), and higher plants (Kuhn et al. ). The cuticular wax, which covers the surface of stems, roots, leaves, and needles, is composed of n -alkanes. Thanks to decomposition of these tissues, hydrocarbons enter soil environment as constituents of soil organic matter. The level of background hydrocarbons is differentiated. Some researchers noted that the upper TPH limit in the uncontaminated soil samples did not exceed 200 mg kg −1 dry wt. of soil (Whyte et al. ; Margesin et al. ; Sabaté et al. ). Other reports indicated that this parameter might be as high as 1000 mg kg −1 dry wt. of soil (Gao et al. ; Kalander et al. ) or even higher (3300 mg kg −1 ; Delgado et al. ). In this study, TPH content ranged between 319 and 2753 mg kg −1 dry wt. of soil in the uncontaminated samples (Table ) and was higher compared to the data presented by some authors (Margesin et al. ) but comparable with the results obtained by the others (Kalander et al. ; Delgado et al. ). TPH is a commonly applied parameter to assess the contamination by petroleum hydrocarbons; however, it has some drawbacks such as lack of specificity for these substances. It leads the detection of soil compounds that are neither of petroleum origin nor composed of only hydrogen and carbon (Delgado et al. ). Namely, the extraction method led to the extraction not only of petroleum substances but also of biological organic compounds, such as naturally occurring hydrocarbons, aldehydes, phytosterols, and long-chain primary fatty alcohols. These compounds are conceivably quantified as TPH, although they are not petroleum hydrocarbons. In this study, the majority of analyzed uncontaminated samples were collected in the sites with vegetation cover (BW, KAM, BIAL), leaf litter (BIAL, KAM), and undergrowth (BIAL, KAM) in three climatic zones. The gas chromatograms for contaminated samples were different than those for unpolluted ones. It suggested the TPH level in unpolluted samples was formed by the non-anthropogenic compounds. Our data indicated (a) the presence of genes involved in the activation of n -alkanes, PAHs, and BTEX and (b) the presence of culturable bacterial strains revealing extended capabilities in unamended and contaminated samples (Fig. ). Hence, the polluted soil as well as unpolluted one harbor hydrocarbon degraders, including degraders with preferences towards both structurally differentiated hydrocarbon groups. This study suggested that the degrading potential of soil microbiome is its natural trait regardless the contaminant presence and climatic conditions. Our observation related to the presence of native hydrocarbon degrading community in the uncontaminated soil is in accordance with the findings of the other researchers (Whyte et al. ; Margesin et al. ). Thanks to the indigenous degraders, the undisturbed soil may respond to sudden pollution event similarly as disturbed one, what was noticed by Schwarz et al. ( ). The unaltered soils should be also considered as a valuable source of degraders applied for bioremediation purposes. Taking into account the hydrocarbon level in the uncontaminated soils noted by us and others (Whyte et al. ; Margesin et al. ; Brzeszcz et al. ), it seems that this parameter does not determinate the presence of native degrading community. The cited authors observed such populations in samples with relatively low TPH level (< 200 mg kg −1 dry wt. of soil). This study, for the first time, showed that microorganisms with extended hydrocarbon degrading capabilities are prevalent in soil environment, as well. The ubiquity of mentioned compounds justifies the widespread of soil bacteria capable of catabolizing both aliphatic and aromatic compounds. Our results highlighted the broadened hydrocarbon-degrading potential of the Pseudomonas , Rhodococcus , Mycolicibacterium , and Paeniglutamicibacter taxa, which constituted the most numerous groups among obtained strains. The Pseudomonas , Rhodococcus , and Mycolicibacterium genera are well known for their diverse hydrocarbon-degrading potential (Brzeszcz and Kaszycki ; Mullaeva et al. ). In contrast to these taxa, there are no papers indicating multi-degrading capabilities of the Paeniglutamicibacter genus, including also previous studies (namely, before reclassification of the Arthrobacter genus; Busse ). On the other hand, the Paeniglutamicibacter representatives were isolated from a phenanthrene-degrading consortium (Sakdapetsiri et al. ) and an oil-affected environment (Margesin et al. ; Semenova et al. ). Although hydrocarbon-degrading genes belonging to the mentioned taxon were not identified in the analyzed metagenomes, we are aware that they might be outside the applied gene detection set (i.e., cyp153 ). Moreover, these data put more light on the distribution of this potential among other bacterial genera such as Dietzia , Gordonia , Nocardioides , Micrococcus , Arthrobacter , Pseudarthrobacter , Paenarthrobacter , Bacillus , Paenibacillus , Ochrobactrum , and Pedobacter . Some of these taxa were previously mentioned as degraders with such unique traits (Brzeszcz and Kaszycki and the references therein); however, the capabilities were documented for a much lower number of bacterial strains belonging to these taxa than for the Pseudomonas , Rhodococcus , and Mycobacterium genera. According to our best knowledge, there is the first evidence of Nocardioides sp. capable of transforming both n -alkanes and aromatic compounds. Thus, the possession and maintenance of various metabolic pathways towards both aliphatic and aromatic substances seem not to be so aggravating for bacterial cells since many strains, obtained in this study, were able to utilize these compounds. Adaptation to harsh environmental conditions such as petroleum hydrocarbon pollution, requires the appropriate metabolic repertoire and genetic background which can be acquired by horizontal gene transfer. Interestingly, some strains (i.e., Rhodococcus , Mycolicibacterium ), growing in the presence of mentioned compounds, were obtained from sites never exposed to petroleum contamination (BIAL, KWU, KAM, BW samples), although these soils revealed the presence of biologically derived hydrocarbons. Margesin et al. ( ) claimed that the genotypes containing rhodococcal- alkB genes and mycobacterial- nidA genes occur in substantial number before a contamination event detected. Our functional analysis detected the rhodococci-like and mycobacterium/mycolicibacterium-like alkB and naphthalene dioxygenases ( nahA , nidA ) genes also in the unaffected samples (Supplementary material, Fig - ; Table ). It may suggest that the occurrence of degraders belonging to the Mycobacterium / Mycolicibacterium and Rhodococcus genera is not linked with the contamination presence. Moreover, the genetic potential towards hydrocarbon degradation among the bacteria may be wide distributed or even common. The prevalence of these capabilities was supported by the comparative genome studies (Táncsics et al. ; Garrido-Sanz et al. ). The cited authors indicated that most of the rhodococci possess degrading genes for medium and long-chain alkanes (Táncsics et al. ) and aromatic compounds such as naphthalene ( nahA ), ethylbenzene ( etbA ), and biphenyl ( bphA ) (Garrido-Sanz et al. ). Thus, these findings additionally support our results since they indicate that rhodococci are capable of degrading both hydrocarbon classes. In turn, our data (unpublished) revealed the wide distribution of alkB among the Mycobacterium , Mycolicibacterium , Mycolicibacter , Mycobacteroides , and Mycolicibacillus (previously belonged to the Mycobacterium genus; Gupta et al. ). This gene was found in 99% of genomes belonging to the mentioned taxa (10,803 genomes with alkB vs 10,892 total genomes deposited in NCBI GenBank; data from 30 May 2023 unpublished data). Moreover, this gene was detected in the majority of pathogenic Mycobacterium tuberculosis genomes as well, but the role of alkane catabolism in these bacteria remains unexplained. Although we did not assess the distribution of genes encoding for the ARHDs in the genomes belonging to these genera, it cannot be excluded that the degradation traits towards n -alkanes and aromatic hydrocarbons are common among their members. The genes encoding for the enzymes involved in transformation of aliphatic and aromatic compounds are also present in genomes of the selected strains (IN53 and IN129) sequenced for the purpose of this study (Table ). The widespread of the alkB and genes encoding for the ARHDs among the Rhodococcus and the novel genera created by reclassification of the Mycobacterium taxon implicates questions about whether these genes are part of their core genome. In this context, more detailed studies should be carried out to better understand this phenomenon. The isolation approach used to obtain bacterial strains with extended capabilities should be also mentioned. Application of a hydrocarbon source with the same characteristic as the contamination in the polluted sample could probably mimic this environmental constraint. On the other hand, the heterogenic nature of crude oil makes it a great source of various organic substances ( n -alkanes, aromatic hydrocarbons), which can be easily used by many bacterial strains for growth. Instead of commonly applied isolation strategy on a single compound ( n -alkane, representative of BTEX and PAHs), the choice of crude oil as a selection factor seems to be a reasonable alternative, which enabled to obtain bacteria with wide metabolic preferences. An additional advantage of this approach is higher PAH bioavailability in crude oil since these compounds are dissolved in other oil fractions. Thanks to that, PAHs are more susceptible to microbial attack than when the compounds are supplied as solids. On the other hand, the presence of the easily degradable carbon source in crude oil is a risk to isolate not-metabolizing hydrocarbon organism, but being a symbiont to a bacterium revealing these capabilities. To exclude this possibility, detailed analyses regarding multi-degrading capacities were undertaken. Not only carbon source but also hydrocarbon level may also have an impact on the obtained isolate diversity. Alternative culturing methods, i.e., providing more oxygen access, may enable obtaining higher diversity than that noted herein. The relatively low number of strains was isolated from Kuwaiti soil samples, namely 1 and 3 from, respectively, KWC and KWU (Supplementary material, Table ). On the other hand, the metagenomic data indicated the hydrocarbon-degrading potential of KWC and KWU community (Supplementary material, Fig. - ). The unreliability of the used isolation strategy in this case suggests its modification by, e.g., increasing NaCl content in the BH medium since the range of soil salinity of KWU and KWC was higher than in the rest of the soil samples (data not shown). Only two strains — Streptomyces sp. IN303 and Bacillus sp. IN301 — obtained from the KWU sample exhibited wide hydrocarbon catabolizing preferences (Supplementary material, Table ). The isolation of the spore-forming ( Bacillus ) and thermotolerant ( Streptomyces ) Gram-positive bacteria would be potentially predicted by their ability to survive the high temperature in the sampling sites. The exceptionally frequent isolation of Actinobacteria and Gammaproteobacteria from crude oil-coated BH plates could depend on n -alkane metabolic abilities revealed by members of these two classes (Supplementary material, Table ). The applied approach stimulated the growth of degraders belonging to mentioned taxa, which is convergent with the results of Lo Giudice et al. ( ). However, in contrast to the cited authors, our isolation approach led us to obtain degraders from the Alpha- and Betaproteobacteria classes, Bacteroidetes (namely Sphingobacteriia class), and Firmicutes (namely Bacilli class) phyla, as well (Table ). The predominance of Rhodococcus strains among all isolates may be biased by the applied isolation strategy, i.e., direct plating, the presence of crude oil’s excess, and preferable oxygen conditions (Révész et al. ). These conditions could be more selective for the growth of Rhodococcus spp. Common metabolic features of rhodococci — multiple alkane hydroxylase systems — enable to utilize different ranges of n -alkanes, which are the main constituents of this crude oil. On the other hand, it should not be excluded that some components present in the applied crude oil could be toxic for other potential degraders, but not for the mentioned ones. The detected presence of this taxon in hydrocarbon-metabolizing community indicated its potential contribution in in situ degradation; however, it should be assessed on the metatranscriptome or proteome levels. The identification and taxonomic assignation of genes encoding the enzymes responsible for the substrate activation in some recognized hydrocarbon degrading pathways allowed us to identify the bacterial genera involved in these processes. The genes encoding proteins responsible for the activation of both aliphatic and aromatic compounds were found in almost every sample (Supplementary material, Fig. - ); however, only a limited group of these determinants shared a common taxonomic affiliation. It should be mentioned that the set of the analyzed genes was restricted to the most common ones and did not include all genes involved in hydrocarbon degradation (i.e., cyp153 , almA , ladA ). Additionally, our results have a qualitative character. A more detailed study allowing to quantitatively assess the presence of the mentioned genes in various soils is necessary to be undertaken. Regarding n -alkane hydroxylation, the main role in this process appears to be performed by microorganisms belonging to the Mycobacterium , Mycolicibacterium , Rhodococcus , Pseudomonas , Nocardioides , Paraburkholderia , and Nocardia genera (Supplementary material, Fig. ). The representatives of these genera are well-known alkane degraders (Song et al. ; Zhang et al. ; Yang et al. ; Lee et al. ; Mitzscherling et al. ). Furthermore, we indicated that bacteria so far not recognized as degraders may also participate in alkane conversion; namely the Noviherbaspirillum and Flavihumibacter taxa. Although there are no reports of alkane transformation by these bacteria, the representative of the former genus was previously isolated from oil-contaminated soil (Chaudhary et al. ). Searching for alkB genes in the genomes belonging to these genera revealed the presence of 4 and 3 mentioned genes in respectively 14 genomes of Noviherbaspirillum and 11 genomes of Flavihumibacter (NCBI GenBank data from 31 May 2023, the result of sequence homology analysis performed using Blast). Taking into account the taxonomic diversity among alkane-degraders, functional redundancy may be observed (Supplementary material, Fig. ). Thus, multiple distinct taxa involved in the alkane activation process may coexist. In this context, our observations are in agreement with the findings of Correa-García et al. ( ). Bacteria from the Immundisolibacter , Pseudomonas , Sphingobium , Novosphingobium , Mycobacterium , Mycolicibacterium , Rhodococcus , and Panacagrimonas genera were found to participate in the upper pathways of aromatic compound degradation (Supplementary material, Fig. S2). The majority of these taxa are known to be involved in PAH transformation (Song et al. ; Lyu et al. ; Fu et al. ; Corteselli et al. ; Singh and Tiwary ; Silva et al. ). The broadened metabolic preferences seem to be worth discussing in the context of designing and developing modern bioremediation approaches to clean up highly contaminated soils. Our previous study indicated that a consortium consisting of bacteria with extended capabilities is a better remediation agent than undefined consortium consisting of randomly chosen degraders (Brzeszcz et al. ). During 60-day treatment, the former consortium removed 86.8% of total aliphatic content and 85.2% of total PAH content, while the latter one respectively 69.7% and 64.5% (Brzeszcz et al. ).
Our results showed that metabolic preferences targeted at both n -alkanes and aromatic hydrocarbons are widespread among hydrocarbon degraders. These capabilities have been detected in several strains, mostly belonging to the Mycolicibacterium , Mycobacterium , Rhodococcus , Pseudomonas , and Paeniglutamicibacter genera; however, they are not limited to these taxa. This observation is important since the representatives of the mentioned genera are applied to clean up contaminated soils. The occurrence of microorganisms revealing extended preferences in the different soils regardless of hydrocarbon level creates the possibility to isolate these bacteria from almost every soil using an appropriate isolation approach. The degrading potential of these microbes is promising in the context of their application as remedial agents to develop degrading consortia applied in remediation practice.
Below is the link to the electronic supplementary material. Supplementary file1 (PDF 470 KB)
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Revealing the Unseen: Next-Generation Sequencing for Early Detection of Drug-Resistant Cytomegalovirus Variants Upon Letermovir Prophylaxis Failure | 921bc30e-b044-46a7-832b-0736d4460f13 | 11793059 | Surgical Procedures, Operative[mh] | CMV Nucleic Acid Testing Plasma samples were submitted for CMV DNA load quantification on the automated cobas 6800 platform (Roche) . CMV quantitative nucleic acid testing from biopsy tissue and bronchoalveolar lavage fluid was done with the laboratory developed Basel-CMV-UL111a-77bp as described previously . The conversion factor for copies per milliliter to international units per milliliter was 0.113 . Leftover materials from the clinical specimens were stored at −20 °C until genotypic drug susceptibility testing was performed. Genotypic Drug Susceptibility Testing Genotypic drug susceptibility testing was done on 40 plasma samples, 1 bronchoalveolar lavage sample, and 1 colon biopsy sample. The CMV UL56 gene was amplified in 4 amplicons for the evaluation of letermovir resistance and the CMV UL97 gene in 2 amplicons for the evaluation of ganciclovir resistance . Sanger sequencing was performed on the 3500 Genetic Analyzer (Applied Biosystems), and for NGS, the Nextera XT protocol was used with sequencing on an MiniSeq platform (Illumina). For more detailed descriptions, see the . Immunologic Monitoring CMV pp65- and pp72/IE1-specific EliSpot assays were performed at day +115, day +198, and day +227 post-HCT. Peripheral venous blood samples were collected from the patient to detect T cells producing interferon γ as previously reported and are described in detail in the . Ethics Statement The patient provided written informed consent for the use of his biological material for NGS analysis and his health-related and microbiological data for this study.
Plasma samples were submitted for CMV DNA load quantification on the automated cobas 6800 platform (Roche) . CMV quantitative nucleic acid testing from biopsy tissue and bronchoalveolar lavage fluid was done with the laboratory developed Basel-CMV-UL111a-77bp as described previously . The conversion factor for copies per milliliter to international units per milliliter was 0.113 . Leftover materials from the clinical specimens were stored at −20 °C until genotypic drug susceptibility testing was performed.
Genotypic drug susceptibility testing was done on 40 plasma samples, 1 bronchoalveolar lavage sample, and 1 colon biopsy sample. The CMV UL56 gene was amplified in 4 amplicons for the evaluation of letermovir resistance and the CMV UL97 gene in 2 amplicons for the evaluation of ganciclovir resistance . Sanger sequencing was performed on the 3500 Genetic Analyzer (Applied Biosystems), and for NGS, the Nextera XT protocol was used with sequencing on an MiniSeq platform (Illumina). For more detailed descriptions, see the .
CMV pp65- and pp72/IE1-specific EliSpot assays were performed at day +115, day +198, and day +227 post-HCT. Peripheral venous blood samples were collected from the patient to detect T cells producing interferon γ as previously reported and are described in detail in the .
The patient provided written informed consent for the use of his biological material for NGS analysis and his health-related and microbiological data for this study.
A 63-year-old male with myeloproliferative neoplasm/primary myelofibrosis underwent allogeneic HCT 8 years after diagnosis, receiving peripheral blood stem cells from his haploidentical son. Pretransplant, disease persistence was noted. He underwent a reduced-intensity conditioning regimen and received graft-vs-host disease (GvHD) prophylaxis with high-dose cyclophosphamide, cyclosporine, and mycophenolate mofetil, though mycophenolate mofetil was stopped on day +22 due to gastrointestinal toxicity. High-dose systemic glucocorticoids were initiated on day +16 due to capillary leak syndrome and gradually tapered over 3 weeks. Neutrophil engraftment (>0.5 g/L) occurred on day +32. The donor-recipient pair presented a high-risk profile for CMV reactivation, with the donor being CMV seronegative and the recipient CMV seropositive (CMV D−/R+). Therefore, antiviral prophylaxis was initiated on day +1 with the CMV terminase inhibitor letermovir in a dosage of 240 mg/d. Plasma CMV DNAemia was monitored on days +1, +7, and +14, showing suppressed viral loads. However, despite letermovir prophylaxis, CMV reactivation was detected on day +18, coinciding with the initiation of high-dose glucocorticoids, resulting in a plasma CMV load of 50 IU/mL . Low-level CMV DNAemia (range, 50–100 IU/mL) persisted after the patient was discharged on day +39 and continued during outpatient follow-up. Repeated drug susceptibility testing up to day +63 showed no UL56 gene mutations by traditional Sanger sequencing associated with letermovir resistance, so letermovir prophylaxis was continued . At the 3-month follow-up (day +95), plasma CMV loads surged to 81 000 IU/mL . At that time, a significant deterioration in pulmonary function was observed, with new bipulmonary ground glass opacities in a computed tomography scan of the chest . Bronchoscopy showed slightly inflamed mucous membranes, with CMV loads of 30 600 IU/mL , and positive CMV staining in bronchoalveolar lavage fluid as confirmed by cytopathologic assessment . CMV pneumonitis was diagnosed, and letermovir prophylaxis was switched to intravenous ganciclovir at a therapeutic dosage. The antiviral treatment was combined with intravenous immune globulin therapy (0.5 g/kg weekly), while the immunosuppressive therapy with cyclosporine was tapered off. Genotypic drug susceptibility testing by Sanger sequencing identified a C325R DRM in the UL56 gene at day +67, conferring >5000-fold antiviral resistance to letermovir . Upon retrospective analysis of all available plasma samples from day +18 to day +67 with Sanger sequencing and NGS in parallel, the UL56-C325R minority variant was identified at a frequency of 6% by NGS 2 weeks before its detection by Sanger sequencing ( ; samples at days +52, +59, and +63 outlined in pink). Longitudinal analysis by NGS showed a steady increase in the frequency of UL56-C325R until the drug-resistant CMV variant became the dominant strain in plasma by day +67. Furthermore, genotypic drug susceptibility testing of the bronchoalveolar lavage fluid sample identified the C325R DRM at 100% frequency with Sanger sequencing and NGS on day +95. Treatment with intravenous ganciclovir led to a favorable outcome, allowing a switch to oral valganciclovir (900 mg twice daily) after 3 weeks. Plasma CMV DNAemia decreased to <100 IU/mL within 34 days (day +128), with detection of CMV-specific T cells via EliSpot assay (659 spot-forming cells/10 6 peripheral blood mononuclear cells; ). Valganciclovir dosage was then reduced to prophylactic (900 mg once daily). However, with the emergence of skin GvHD, high-dose glucocorticoids (prednisone, 1 mg/kg daily) and tacrolimus were reintroduced, leading to a rise in plasma CMV DNA levels. Diarrhea prompted sigmoidoscopy and biopsy on day +190, revealing CMV colitis with a viral load of 339 000 IU/mL in biopsy tissue. Diagnosis was confirmed by positive CMV immunohistochemistry staining, with evidence of GvHD of the lower gastrointestinal tract with crypt cell necrosis and apoptosis. Genotypic CMV drug susceptibility testing by Sanger sequencing identified a L595S DRM in the UL97 gene, resulting in an >8-fold increase in resistance to ganciclovir . Retrospective analysis by Sanger sequencing and NGS revealed that the L595S DRM was not present in the plasma samples taken up until day +128. The next plasma sample was collected 28 days later, on day +156. By that time, the L595S DRM was detectable by Sanger sequencing and NGS at a 100% frequency. The UL97-L595S DRM was also identified in the colon biopsy taken on day +190. Foscarnet treatment was initiated, and subsequent therapy with maribavir finally led to sustained viral suppression. Due to supply shortage, maribavir was temporarily halted for 3 weeks, resulting in a resurgence of CMV DNAemia up to 819 IU/mL until resumption. At 12 months posttransplant, the patient showed complete morphologic remission with 100% chimerism, and immunosuppression could be completely discontinued without evidence for GvHD. However, due to a lack of recovery in CMV-specific cell-mediated immunity (as indicated by no increase in pp65- and pp72/IE-1–specific T-cell responses; ), maribavir treatment is continued, maintaining CMV at suppressed levels.
Letermovir has been shown to be highly effective in reducing the incidence of CMV reactivation in patients who are seropositive and at risk of developing CMV-related morbidity and mortality while undergoing allogeneic HCT. However, challenges remain, including the ambiguous interpretation of low-level CMV DNAemia, the emergence of antiviral drug resistance, and viral breakthrough . The clinical significance of low-level CMV, particularly in the context of letermovir prophylaxis, remains contentious, as detection may result from noninfectious free-floating CMV DNA generated during abortive replication rather than infectious virions . This complexity can lead to misinterpretation, unnecessary treatments, increased costs, and delayed immune reconstitution. However, differentiating between low-level CMV replication and the early emergence of drug-resistant CMV is crucial for timely intervention and preventing severe end organ manifestations. Our case study exemplifies this challenge. Initial screening by the gold standard Sanger sequencing method, which requires a minor variant frequency ≥20% , failed to detect the UL56-C325R variant associated with high-level letermovir resistance until day +67. In contrast, NGS identified the emergence of the drug-resistant variant at low frequencies of only 6% already 2 weeks earlier at day +52. This discrepancy underscores the superiority of NGS in detecting low-frequency DRMs as compared with traditional Sanger sequencing methods. As a result, the prevalence of drug-resistant CMV strains may be underestimated by Sanger sequencing, potentially leading to suboptimal management strategies and a consequently increased risk for the development of end organ disease. Observations from prior research and our own studies suggest that significant DRMs may go undetected with conventional methods . This raises concerns—as exemplified in our case—that instances of refractory CMV DNAemia attributed to other causes may in fact be due to undetected drug-resistant CMV variants. Furthermore, the development of antiviral drug resistance poses a formidable challenge in HCT recipients, often resulting in prolonged hospitalization, increased toxicity from antiviral drugs, and heightened mortality rates . Various predisposing factors contribute to the emergence of resistance, including D−/R+ CMV serostatus, receipt of T-cell–depleting therapies, profound immune suppression, prolonged or repeated antiviral therapy, and subtherapeutic drug levels . Our case highlights several of these risk factors, including the D−/R+ CMV serostatus, T-cell depletion with high-dose cyclophosphamide due to haploidentical HCT, and prolonged high doses of immunosuppressive agents with cyclosporine and corticosteroids, as evidenced by the limited CMV-mediated T-cell immune response 12 months after allogeneic HCT. Despite the many advantages of NGS methodology, some limitations should be considered when applying it in clinical diagnostics. One of the main limitations is the high cost of NGS reagents, chemicals, and consumables, as well as the expensive sequencing platforms and the computational infrastructure needed for data analysis and storage. However, unlike Sanger sequencing, NGS can be integrated with fully automated library preparation and data analysis workflows, allowing for the simultaneous processing of many samples and thereby reducing the cost per sample in high-volume settings. Additionally, economies of scale in reagent production, advances in sequencing technology, and increased market competition have all contributed to making NGS more cost-effective over time. Another limitation is the complexity of data analysis. NGS generates vast amounts of data that require sophisticated bioinformatics tools and expertise to interpret. This can be a significant barrier for smaller diagnostic laboratories with limited computational resources or bioinformatics expertise. However, in recent years, commercial software tools became available that offer automated workflows for data analysis and interpretation. Moreover, it is important to consider that a certain number of Illumina sequencing reads is required to identify true low-frequency DRMs at frequencies <5%, as these can be easily obscured by background noise and random sequencing errors. While a high read depth improves the detection of low-frequency DRMs, it also increases the cost of sequencing per sample. Last, implementing NGS in diagnostic practice requires standardized procedures and protocols for sample preparation, sequencing, and data analysis, as well as appropriate internal and external quality control measures to ensure the accuracy, precision, and reproducibility of diagnostic results . Despite these challenges, the successful integration of NGS methodology into diagnostic practice can ultimately lead to more accurate diagnostic information and thereby improve patient outcomes. In conclusion, our case study demonstrates that the use of NGS technology enhances the detection of CMV drug resistance by enabling earlier identification of emerging drug-resistant CMV variants during letermovir prophylaxis failure. Prospective clinical studies are warranted to compare traditional Sanger sequencing with more sensitive NGS methods in transplant recipients to better understand the significance of low-frequency DRMs and their impact on clinical management and treatment outcomes in patients with refractory CMV.
are available at The Journal of Infectious Diseases online ( http://jid.oxfordjournals.org/ ). consist of data provided by the author that are published to benefit the reader. The posted materials are not copyedited. The contents of all are the sole responsibility of the authors. Questions or messages regarding errors should be addressed to the author.
jiae414_Supplementary_Data
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Fatal Intoxications with Zopiclone—A Cause for Concern? | 1fae5a4c-d52e-4b23-81ca-8492e13fff96 | 11182790 | Forensic Medicine[mh] | Zopiclone is a controlled substance used in the treatment of insomnia . It was introduced in Europe in 1987 and is considered the third generation of hypnotics after barbiturates and benzodiazepines . Zopiclone is often grouped with zaleplon and zolpidem, all commonly referred to as Z-drugs . The use of zopiclone (as well as other sedatives) is widespread in Sweden. According to data published by the Swedish National Board of Health and Welfare, approximately 5% of the population over 19 years of age received a prescription for zopiclone in 2020 . The popularity of zopiclone can be attributed to its effectiveness in inducing sleep, and that the safety profile is considered superior compared with benzodiazepines . Early clinical trials of zopiclone failed to show major morbidity or mortality in connection to the drug . However, more recent data show that zopiclone has the potential to cause dependence and withdrawal and is involved in cases of driving under the influence , motor vehicle crashes , and overdoses . Sedative and hypnotic drugs have previously been shown to be commonly detected in intoxication suicides and suicide attempts . Recent observational studies on intoxications with zopiclone are scarce . When studying Z-drugs and their role in intoxications they are often grouped together with benzodiazepines, which complicates the understanding of their role in causing morbidity and mortality . The Swedish National Board of Health and Welfare has published a report concluding that zopiclone was the most frequent drug found in suicides by intoxication between 2012 and 2018 in Sweden . With these findings in mind, further research exploring potential hazards of zopiclone use are needed. The overall aim of this study was to explore the role of zopiclone in fatal intoxications in a Swedish forensic autopsy material during a 9-year period from 2012 to 2020. More specifically, we aimed to identify cases of monointoxications and to compare the demographics and toxicological results between suicides and other manners of death. Forensic Autopsies in Sweden A forensic autopsy is requested by the police authorities when a suspected unnatural death occurs in Sweden. Unnatural deaths comprise fatalities where an external cause of death cannot be ruled out, for example, when there is suspicion of a crime, substance abuse, suicide, or medical malpractice or when the body is of unknown identity. Every year, about 5500 forensic autopsies are performed at the National Board of Forensic Medicine with the purpose of establishing the cause and manner of death. In this process, multiple factors, such as findings from the autopsy, histological samples, and toxicological analyses as well as information from the police are considered. Toxicological analysis of blood and other biological specimens, collected in standardized procedures during the autopsy, is performed at one centralized forensic toxicology laboratory located in Linköping, Sweden. The result of the investigation is reported on the cause of death certificate and in a database held by the National Board of Forensic Medicine. Toxicological Analysis of Postmortem Samples At the forensic toxicology laboratory an extensive toxicological screening for xenobiotics and ethanol is performed routinely. Ethanol in femoral blood and other specimens is analyzed by a headspace gas chromatography flame ionization detector (HS-GC-FID) method . The drug screening procedure is performed in femoral blood using a liquid chromatography/time-of-flight mass spectrometry (LC-TOF-MS) method . Positive findings are verified with different, more specific analytical methods. Zopiclone was quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS). In brief, the femoral blood samples were buffered with borate buffer at pH 9.0 followed by liquid–liquid extraction with ethyl acetate. Sample analysis was performed using a Waters Acquity UPLC I-Class system coupled to a Waters XEVO TQD (Milford, MA, USA). The calibration curve was linear over zopiclone concentrations ranging from 0.01 to 1.0 µg/g. The limit of quantification (LOQ) for zopiclone was 0.01 µg/g. This study utilized preexisting toxicological data collected in connection to the autopsies, no reanalysis of postmortem samples was performed. Data Sources and Study Population This is a register-based study in which the population was identified using the National Board of Forensic Medicine database. Among fatalities undergoing a forensic autopsy between 2012 and 2020, deaths caused by intoxication were identified on the basis of the information on the cause of death certificates issued by the forensic pathologist (Fig. ). The inclusion of cases and the presentation of data were based on the autopsy date. The manner of death and sex of each case were retrieved in the database. Cases positive for zopiclone in femoral blood were selected for further investigation. The first author (LT) reviewed the cause of death certificates to include cases where the forensic pathologist considered zopiclone as a causal drug (solely or in combination with other substances). Information of toxicological findings for all zopiclone intoxications was retrieved. A second assessment of all potential monointoxications with zopiclone was performed by the first author (LT) and a forensic pathologist (CS) to determine whether zopiclone caused the death alone, or if other substances were potential contributors to the lethality of the intoxication. The Swedish Prescribed Drug Register contains information of prescribed and dispensed drugs at Swedish pharmacies . The register was utilized to determine whether the individuals included in the study were prescribed zopiclone or not. A prescription was defined as valid if it was dispensed within 1 year before the death date. The linkage of the registers was performed utilizing the personal identification number assigned to every Swedish citizen . Definitions Zopiclone Intoxications Zopiclone intoxications were defined as intoxication fatalities in which the forensic pathologist registered zopiclone as a causal substance on the cause of death certificate or in the autopsy report. Monointoxications were defined as lethal intoxications caused by a single substance. Substances additional to zopiclone may have been present but were assessed as secondary findings, meaning that they were not potential contributors to the toxicity of the intoxication. Fatalities where zopiclone was the only substance found were classified as “monointoxication with no other findings”. This study included cases classified as intentional intoxications (suicides), accidental intoxications, and intoxications of undetermined intent (unclear). Other Findings Toxicological findings additional to zopiclone in all types of blood were categorized into substance groups on the basis of their pharmacological effects. The Anatomic Therapeutic Chemical (ATC) classification system was used in cases where pharmaceutical drugs were detected. Some exceptions to the ATC-classification system were made. Hypnotics were defined as the following ATC codes: N05BB, N05BE, N05CM, N05CH, R06AD, and R06AA02 (hydroxyzine, promethazine, propiomazine, alimemazine, buspirone, clomethiazole, melatonin, and diphenhydramine ) . Benzodiazepines were defined as ATC codes N05CD and N05BA (alprazolam, diazepam, flunitrazepam, lorazepam, nitrazepam, temazepam, oxazepam, and bromazepam) and Z-drugs as ATC code N05CF (zolpidem and zaleplon). Substances with ATC codes N02A, N07BC02, and R05DA01 (fentanyl, codeine, morphine, oxycodone, tramadol, methadone, buprenorphine, hydrocodone, tapentadol, dextropropoxyphene, and ethylmorphine) were categorized as opioids. Findings of ethanol were included if the femoral blood ethanol concentration was ≥ 0.2%. Fatal Toxicity Index (FTI) Fatal toxicity index (FTI) is a measure that can be applied when investigating relative drug toxicity . In this study, the FTI for zopiclone was calculated by relating the number of autopsied zopiclone fatalities to the sales of zopiclone measured in defined daily dose (DDD) dispensed during a set time period. DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults (7.5 mg for zopiclone) . The Swedish eHealth agency compiled data on the dispensed DDD for zopiclone during 2012–2020 in Sweden, which was utilized in this study. Statistical Analysis Descriptive statistics, including frequencies, median, and percentiles, were used to describe the demographics of the study material and the concentrations of zopiclone. Chi-squared tests were used to compare the distribution of categorical variables between groups. For group comparisons of the median value, Mood’s median test was used, and Bonferroni corrections of the p -values were applied to counteract the multiple-testing problem. Possible time trends were investigated using linear regression with bootstrap-based confidence intervals. The analysis was weighted against the yearly number of performed forensic autopsies. The significance level was set to 5%, with corresponding 95% confidence intervals (CI). All data were analyzed in IBM SPSS® (IBM, Armonk, NY, USA) versions 27.0 and 28.0. A forensic autopsy is requested by the police authorities when a suspected unnatural death occurs in Sweden. Unnatural deaths comprise fatalities where an external cause of death cannot be ruled out, for example, when there is suspicion of a crime, substance abuse, suicide, or medical malpractice or when the body is of unknown identity. Every year, about 5500 forensic autopsies are performed at the National Board of Forensic Medicine with the purpose of establishing the cause and manner of death. In this process, multiple factors, such as findings from the autopsy, histological samples, and toxicological analyses as well as information from the police are considered. Toxicological analysis of blood and other biological specimens, collected in standardized procedures during the autopsy, is performed at one centralized forensic toxicology laboratory located in Linköping, Sweden. The result of the investigation is reported on the cause of death certificate and in a database held by the National Board of Forensic Medicine. At the forensic toxicology laboratory an extensive toxicological screening for xenobiotics and ethanol is performed routinely. Ethanol in femoral blood and other specimens is analyzed by a headspace gas chromatography flame ionization detector (HS-GC-FID) method . The drug screening procedure is performed in femoral blood using a liquid chromatography/time-of-flight mass spectrometry (LC-TOF-MS) method . Positive findings are verified with different, more specific analytical methods. Zopiclone was quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS). In brief, the femoral blood samples were buffered with borate buffer at pH 9.0 followed by liquid–liquid extraction with ethyl acetate. Sample analysis was performed using a Waters Acquity UPLC I-Class system coupled to a Waters XEVO TQD (Milford, MA, USA). The calibration curve was linear over zopiclone concentrations ranging from 0.01 to 1.0 µg/g. The limit of quantification (LOQ) for zopiclone was 0.01 µg/g. This study utilized preexisting toxicological data collected in connection to the autopsies, no reanalysis of postmortem samples was performed. This is a register-based study in which the population was identified using the National Board of Forensic Medicine database. Among fatalities undergoing a forensic autopsy between 2012 and 2020, deaths caused by intoxication were identified on the basis of the information on the cause of death certificates issued by the forensic pathologist (Fig. ). The inclusion of cases and the presentation of data were based on the autopsy date. The manner of death and sex of each case were retrieved in the database. Cases positive for zopiclone in femoral blood were selected for further investigation. The first author (LT) reviewed the cause of death certificates to include cases where the forensic pathologist considered zopiclone as a causal drug (solely or in combination with other substances). Information of toxicological findings for all zopiclone intoxications was retrieved. A second assessment of all potential monointoxications with zopiclone was performed by the first author (LT) and a forensic pathologist (CS) to determine whether zopiclone caused the death alone, or if other substances were potential contributors to the lethality of the intoxication. The Swedish Prescribed Drug Register contains information of prescribed and dispensed drugs at Swedish pharmacies . The register was utilized to determine whether the individuals included in the study were prescribed zopiclone or not. A prescription was defined as valid if it was dispensed within 1 year before the death date. The linkage of the registers was performed utilizing the personal identification number assigned to every Swedish citizen . Zopiclone Intoxications Zopiclone intoxications were defined as intoxication fatalities in which the forensic pathologist registered zopiclone as a causal substance on the cause of death certificate or in the autopsy report. Monointoxications were defined as lethal intoxications caused by a single substance. Substances additional to zopiclone may have been present but were assessed as secondary findings, meaning that they were not potential contributors to the toxicity of the intoxication. Fatalities where zopiclone was the only substance found were classified as “monointoxication with no other findings”. This study included cases classified as intentional intoxications (suicides), accidental intoxications, and intoxications of undetermined intent (unclear). Other Findings Toxicological findings additional to zopiclone in all types of blood were categorized into substance groups on the basis of their pharmacological effects. The Anatomic Therapeutic Chemical (ATC) classification system was used in cases where pharmaceutical drugs were detected. Some exceptions to the ATC-classification system were made. Hypnotics were defined as the following ATC codes: N05BB, N05BE, N05CM, N05CH, R06AD, and R06AA02 (hydroxyzine, promethazine, propiomazine, alimemazine, buspirone, clomethiazole, melatonin, and diphenhydramine ) . Benzodiazepines were defined as ATC codes N05CD and N05BA (alprazolam, diazepam, flunitrazepam, lorazepam, nitrazepam, temazepam, oxazepam, and bromazepam) and Z-drugs as ATC code N05CF (zolpidem and zaleplon). Substances with ATC codes N02A, N07BC02, and R05DA01 (fentanyl, codeine, morphine, oxycodone, tramadol, methadone, buprenorphine, hydrocodone, tapentadol, dextropropoxyphene, and ethylmorphine) were categorized as opioids. Findings of ethanol were included if the femoral blood ethanol concentration was ≥ 0.2%. Fatal Toxicity Index (FTI) Fatal toxicity index (FTI) is a measure that can be applied when investigating relative drug toxicity . In this study, the FTI for zopiclone was calculated by relating the number of autopsied zopiclone fatalities to the sales of zopiclone measured in defined daily dose (DDD) dispensed during a set time period. DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults (7.5 mg for zopiclone) . The Swedish eHealth agency compiled data on the dispensed DDD for zopiclone during 2012–2020 in Sweden, which was utilized in this study. Zopiclone intoxications were defined as intoxication fatalities in which the forensic pathologist registered zopiclone as a causal substance on the cause of death certificate or in the autopsy report. Monointoxications were defined as lethal intoxications caused by a single substance. Substances additional to zopiclone may have been present but were assessed as secondary findings, meaning that they were not potential contributors to the toxicity of the intoxication. Fatalities where zopiclone was the only substance found were classified as “monointoxication with no other findings”. This study included cases classified as intentional intoxications (suicides), accidental intoxications, and intoxications of undetermined intent (unclear). Toxicological findings additional to zopiclone in all types of blood were categorized into substance groups on the basis of their pharmacological effects. The Anatomic Therapeutic Chemical (ATC) classification system was used in cases where pharmaceutical drugs were detected. Some exceptions to the ATC-classification system were made. Hypnotics were defined as the following ATC codes: N05BB, N05BE, N05CM, N05CH, R06AD, and R06AA02 (hydroxyzine, promethazine, propiomazine, alimemazine, buspirone, clomethiazole, melatonin, and diphenhydramine ) . Benzodiazepines were defined as ATC codes N05CD and N05BA (alprazolam, diazepam, flunitrazepam, lorazepam, nitrazepam, temazepam, oxazepam, and bromazepam) and Z-drugs as ATC code N05CF (zolpidem and zaleplon). Substances with ATC codes N02A, N07BC02, and R05DA01 (fentanyl, codeine, morphine, oxycodone, tramadol, methadone, buprenorphine, hydrocodone, tapentadol, dextropropoxyphene, and ethylmorphine) were categorized as opioids. Findings of ethanol were included if the femoral blood ethanol concentration was ≥ 0.2%. Fatal toxicity index (FTI) is a measure that can be applied when investigating relative drug toxicity . In this study, the FTI for zopiclone was calculated by relating the number of autopsied zopiclone fatalities to the sales of zopiclone measured in defined daily dose (DDD) dispensed during a set time period. DDD is the assumed average maintenance dose per day for a drug used for its main indication in adults (7.5 mg for zopiclone) . The Swedish eHealth agency compiled data on the dispensed DDD for zopiclone during 2012–2020 in Sweden, which was utilized in this study. Descriptive statistics, including frequencies, median, and percentiles, were used to describe the demographics of the study material and the concentrations of zopiclone. Chi-squared tests were used to compare the distribution of categorical variables between groups. For group comparisons of the median value, Mood’s median test was used, and Bonferroni corrections of the p -values were applied to counteract the multiple-testing problem. Possible time trends were investigated using linear regression with bootstrap-based confidence intervals. The analysis was weighted against the yearly number of performed forensic autopsies. The significance level was set to 5%, with corresponding 95% confidence intervals (CI). All data were analyzed in IBM SPSS® (IBM, Armonk, NY, USA) versions 27.0 and 28.0. Out of the 1539 cases of intoxication where zopiclone was detected in femoral blood, 573 zopiclone-caused fatalities were identified among forensic autopsy cases in Sweden between 2012 and 2020 (Fig. ). During the study period, zopiclone contributed to approximately 8% of fatal drug intoxications (573 out of 7320 cases) and about 17% of all intoxication suicides (354 out of 2118 cases; Table ). The yearly number of autopsied intoxications with zopiclone decreased during the study period (Fig. ) after a plateau between 2012 and 2016. The lowest number was seen in 2020 with 42 deaths. The total sales of zopiclone (measured in dispensed DDD) increased between 2012 and 2016 and decreased between 2016 and 2020. The decrease of the number of fatalities was 0.76 cases per 1000 forensic autopsies and year (95% CI − 0.42 to − 1.14). Population Demographics Women constituted 51% (291 cases) of zopiclone intoxications (Table ). Cases of suicide made up approximately 62% of the fatalities, and unclear and accidental intoxications constituted 21% and 17% of cases, respectively. As shown in Table , the median age among intoxications with zopiclone (55 years) was higher compared with the median age of all intoxication fatalities in Sweden (44 years). Among zopiclone suicides, the median age (58 years) was significantly higher ( p < 0.01) compared with intoxications where the manner of death was unclear (51 years) or accidental (49 years). There was no significant difference in median age between accidents and unclear cases. As presented in Table , women were significantly overrepresented in suicides with zopiclone, comprising 56% of cases ( p < 0.01). Men were significantly overrepresented in both unclear and accidental intoxications, constituting 57% and 58% of fatalities, respectively ( p < 0.01). Among the total number of intoxication fatalities in Sweden, men constituted 65% of deaths (Table ). They comprised 79% of accidental and 63% of unclear fatalities, although women accounted for 55% of intoxication suicides (Table ). The largest number of zopiclone fatalities for both men and women occurred between the ages of 46 and 65 years (Fig. ). In the age category 18–30 years, 71% of cases were men. Women were slightly overrepresented in the remaining age categories, most prominently among individuals aged > 80, where they constituted 55% of deaths (Fig. ) . Men were overrepresented among accidental fatalities in all age categories except 66–80 years, where women were implicated in more cases. Suicide was the most common manner of death in all age categories for women. Almost 30% ( n = 156) of all fatal zopiclone intoxications and 34% of all suicides with zopiclone ( n = 119) afflicted individuals > 65 years of age. Among zopiclone intoxications in the elderly (> 65 years), 77% (120 out of 156 cases) committed suicide. Intoxications with Zopiclone In total, 8% ( n = 43) of all zopiclone fatalities were monointoxications, among which 86% were suicides. Out of the 43 monointoxications, 35% (15 cases) were monointoxications with no other findings in blood (Table ). Individuals aged > 65 years comprised 65% of all monointoxications, and the eldest (> 80 years) constituted 34% of them. Out of the 15 monointoxications with no other findings, 80% (12 cases) involved individuals aged > 65 years. The intoxications with zopiclone related to sales measured in DDD ×10 −6 during 2012–2020 resulted in an FTI of 0.79 in total (Table ), and 0.06 for monointoxications. No obvious time trends in FTI for zopiclone could be observed during the study period. Data were available for 571 of the 573 cases in the Swedish prescribed drug register; among them 87% ( n = 494) were prescribed users of zopiclone. Only small variations of the proportion of prescriptions could be seen during the study period (Table ). The single substance most often detected along with zopiclone was ethanol (with a femoral blood concentration ≥ 0.2%). Ethanol was present in 213 cases, and it was the most common additional finding in both accidental and unclear zopiclone intoxications (found in 41% and 44% of the cases, respectively). For suicides, the most frequent additional substance in blood (from all sites) was propiomazine, found in 35% of the fatalities. Among the additional findings of all zopiclone intoxications, the most common substance group was hypnotics, found in 50% of fatalities, followed by antidepressants (48%) and opioids (43%). Other Z-drugs (zolpidem and zaleplon) were found in 7% (42 cases) of cases. As presented in Table , hypnotics were the most common substance group found in suicides and unclear deaths, detected in 51% and 55% of the cases, respectively. In the suicide category, antidepressant drugs ranked second and were found in 47% of the fatalities. Amongst the accidental intoxications, 70% of cases had findings of opioids, and 55% had findings of benzodiazepines. The median zopiclone concentration of all 573 cases was 0.47 µg/g in femoral blood (Fig. ). The median concentration of zopiclone in suicides (0.66 µg/g) was significantly higher ( p < 0.01) compared with the concentration in unclear cases (0.34 µg/g) and accidents (0.15 µg/g). The comparison was adjusted with Bonferroni corrections. The median concentration of zopiclone in monointoxications (0.79 µg/g; Table ) was significantly higher ( p < 0.01) compared with the median concentration of the remaining 530 fatalities (0.45 µg/g). The highest measured concentration was 12.0 µg/g (Fig. ). Women constituted 51% (291 cases) of zopiclone intoxications (Table ). Cases of suicide made up approximately 62% of the fatalities, and unclear and accidental intoxications constituted 21% and 17% of cases, respectively. As shown in Table , the median age among intoxications with zopiclone (55 years) was higher compared with the median age of all intoxication fatalities in Sweden (44 years). Among zopiclone suicides, the median age (58 years) was significantly higher ( p < 0.01) compared with intoxications where the manner of death was unclear (51 years) or accidental (49 years). There was no significant difference in median age between accidents and unclear cases. As presented in Table , women were significantly overrepresented in suicides with zopiclone, comprising 56% of cases ( p < 0.01). Men were significantly overrepresented in both unclear and accidental intoxications, constituting 57% and 58% of fatalities, respectively ( p < 0.01). Among the total number of intoxication fatalities in Sweden, men constituted 65% of deaths (Table ). They comprised 79% of accidental and 63% of unclear fatalities, although women accounted for 55% of intoxication suicides (Table ). The largest number of zopiclone fatalities for both men and women occurred between the ages of 46 and 65 years (Fig. ). In the age category 18–30 years, 71% of cases were men. Women were slightly overrepresented in the remaining age categories, most prominently among individuals aged > 80, where they constituted 55% of deaths (Fig. ) . Men were overrepresented among accidental fatalities in all age categories except 66–80 years, where women were implicated in more cases. Suicide was the most common manner of death in all age categories for women. Almost 30% ( n = 156) of all fatal zopiclone intoxications and 34% of all suicides with zopiclone ( n = 119) afflicted individuals > 65 years of age. Among zopiclone intoxications in the elderly (> 65 years), 77% (120 out of 156 cases) committed suicide. In total, 8% ( n = 43) of all zopiclone fatalities were monointoxications, among which 86% were suicides. Out of the 43 monointoxications, 35% (15 cases) were monointoxications with no other findings in blood (Table ). Individuals aged > 65 years comprised 65% of all monointoxications, and the eldest (> 80 years) constituted 34% of them. Out of the 15 monointoxications with no other findings, 80% (12 cases) involved individuals aged > 65 years. The intoxications with zopiclone related to sales measured in DDD ×10 −6 during 2012–2020 resulted in an FTI of 0.79 in total (Table ), and 0.06 for monointoxications. No obvious time trends in FTI for zopiclone could be observed during the study period. Data were available for 571 of the 573 cases in the Swedish prescribed drug register; among them 87% ( n = 494) were prescribed users of zopiclone. Only small variations of the proportion of prescriptions could be seen during the study period (Table ). The single substance most often detected along with zopiclone was ethanol (with a femoral blood concentration ≥ 0.2%). Ethanol was present in 213 cases, and it was the most common additional finding in both accidental and unclear zopiclone intoxications (found in 41% and 44% of the cases, respectively). For suicides, the most frequent additional substance in blood (from all sites) was propiomazine, found in 35% of the fatalities. Among the additional findings of all zopiclone intoxications, the most common substance group was hypnotics, found in 50% of fatalities, followed by antidepressants (48%) and opioids (43%). Other Z-drugs (zolpidem and zaleplon) were found in 7% (42 cases) of cases. As presented in Table , hypnotics were the most common substance group found in suicides and unclear deaths, detected in 51% and 55% of the cases, respectively. In the suicide category, antidepressant drugs ranked second and were found in 47% of the fatalities. Amongst the accidental intoxications, 70% of cases had findings of opioids, and 55% had findings of benzodiazepines. The median zopiclone concentration of all 573 cases was 0.47 µg/g in femoral blood (Fig. ). The median concentration of zopiclone in suicides (0.66 µg/g) was significantly higher ( p < 0.01) compared with the concentration in unclear cases (0.34 µg/g) and accidents (0.15 µg/g). The comparison was adjusted with Bonferroni corrections. The median concentration of zopiclone in monointoxications (0.79 µg/g; Table ) was significantly higher ( p < 0.01) compared with the median concentration of the remaining 530 fatalities (0.45 µg/g). The highest measured concentration was 12.0 µg/g (Fig. ). Main Findings This study shows that zopiclone contributed to 17% of all intoxication suicides autopsied in Sweden between 2012 and 2020. The 8% of monointoxications found in this study indicates that zopiclone is a substance with the potential of being lethal on its own. Although zopiclone fatalities are common in intoxication deaths in Sweden, they decreased at the end of the study period. Time Trends The declining number of zopiclone intoxications is in line with Swedish data on intoxication deaths in general . The present study also found that the sales (measured in dispensed DDD) of zopiclone decreased between 2016 and 2020 in Sweden. A potential explanation for the reduction of zopiclone fatalities could be that medical professionals are more restrictive in prescribing the drug; there is evidence suggesting that limiting the access to lethal means is effective in the prevention of suicide . Demographics Among all intoxication fatalities in Sweden, men constituted 65% of the deaths, which is in line with results from a Swedish publication on 6894 intoxication fatalities between 1998 and 2007 . Interestingly, our study found that women and men were equally represented in fatal intoxications with zopiclone. Previous research has found women to be predisposed to insomnia ; in Sweden, women are prescribed more zopiclone, and drugs in general, compared with men, which could partially explain this finding . We found that the proportion of suicides in intoxications with zopiclone (62%) was larger compared with the proportion in all intoxication fatalities (29%). The majority of suicides with zopiclone (56%) and suicides through intoxication in general (55%) found in this study were committed by women. The large portion of suicides in zopiclone fatalities and the overrepresentation of women in this group could potentially explain the equal representation of sexes in zopiclone deaths. A speculative explanation for the large proportion of suicides in zopiclone deaths could be the correlation between sleep disturbances and depression. Insomnia is a common issue among individuals suffering from depressive symptoms , and sleep disturbances are important risk factors for suicide, even when adjusted for mental disorders . This study found that 48% of zopiclone fatalities also had findings of antidepressant drugs, and therefore, it is likely that a prominent proportion of the individuals had been diagnosed with depression. Since zopiclone is prescribed to patients with sleep disturbances, it could be speculated that the patient group suffers an increased risk for suicide, which could potentially explain the findings of this study. A randomized controlled trial found a greater incidence of depression among patients receiving treatment with hypnotic drugs compared with placebo . It could be speculated that the treatment with zopiclone potentially increased depressive symptoms among the patients. As mentioned, women were overrepresented in suicides both among all intoxications (55%) and in intoxications with zopiclone (56%). This result contrasts previous research on completed suicides, where men commit almost twice as many compared with women . Evidence suggests that women tend to choose less violent methods of suicide , and intoxication with drugs is the most common suicide method for women in Sweden . Women are considerably overrepresented in suicide attempts, which are more frequent than completed suicides . When attempting suicide, intoxication with drugs is a common method, which could partially explain the large finding of women among intoxication suicides seen in this study. When specifically investigating intoxication suicides, there are previous studies finding women to be equally represented and overrepresented , supporting the results of this study. Individuals dying in zopiclone fatalities were older compared with all fatal intoxications in Sweden; the median age was 55 and 44 years, respectively (Table ). This study found that women dying in the case of zopiclone intoxications was associated with older age, which has been seen in previous research of intoxication deaths . Therefore, it could be speculated that the large representation of women among the zopiclone fatalities could explain the higher median age seen in this study. Among individuals aged > 65 years, 76% of deaths were suicides, and in total they constituted about one-third of all suicides with zopiclone. The large representation of the elderly in suicides is in line with previous research , and a Swedish study found that intoxication with drugs constituted about 40% of female and 16% of male suicides in the elderly population . According to data published by the Swedish National Board of Health and Welfare, the largest group of patients receiving a prescription for zopiclone were > 84 years of age. In 2020, women constituted 65% of the patients aged > 64 years and prescribed zopiclone . It could be speculated that the large prescription to the elderly and elderly women is a contributing factor to their representation in zopiclone suicides. Monointoxications In this study, 8% of the fatalities with zopiclone were monointoxications. Early clinical trials failed to show major morbidity or mortality in connection with zopiclone , and details regarding its toxicity have remained unclear. The present findings indicate that the use of zopiclone alone can have fatal consequences, especially among the elderly. Some previous studies on intoxication deaths have found fatalities with zopiclone as the sole toxicological finding, supporting the thesis that zopiclone can be lethal on its own . Acute toxicity from lone use of both Z-drugs and benzodiazepines has been shown to be common among intoxications presented at emergency departments throughout Europe . The elderly (aged > 65 years) constituted 65% of all monointoxications and 80% of monointoxications, with no additional findings in this study. Among the monointoxications, 86% of deaths were suicides, and an explanation for the overrepresentation of the elderly could be that they apply more lethal means in their attempts to commit suicide , and therefore might have ingested higher dosages. Another theory could be that the frailty as well as comorbidities and polypharmacy of the elderly made them more susceptible to the toxicity of zopiclone. Toxicology The postmortem concentrations of zopiclone found in this study were in line with the results of previous research . A Swedish study on data between 1992 and 2006 found the median concentration of zopiclone in intoxications caused by one substance (0.80 µg/g) to be similar to the concentrations of the monointoxications in this study . The same study also investigated the concentrations of zopiclone in fatal intoxications caused by multiple substances. They found the median concentration to be 0.70 µg/g, and the upper 90th percentile was 1.90 µg/g, which is slightly higher compared with the corresponding concentrations in the present study comprising all manners of deaths (median 0.47 µg/g and upper 90th percentile 1.6 µg/g). The majority of zopiclone fatalities were caused by more than one substance. This phenomenon is seen when studying fatal intoxications in general where most deaths are caused by the synergic effects of multiple substances . Ethanol was the most common substance found, which is in line with previous data . For suicides and fatalities with an undetermined manner of death, the most common additional findings were hypnotics. Hypnotic and sedative drugs have previously been shown to be common toxicological findings in intoxication fatalities . Our study found that 70% of all accidental zopiclone intoxications also had findings of opioids in the toxicological analysis. Previous studies have found opioids to be common findings among accidental intoxications . Fatal Toxicity Index and Prescribed Zopiclone Use This study found the FTI to be 0.79 for zopiclone, and 0.06 for monointoxications, which corresponds with the findings of previous publications and can be considered quite low. Ojanperä et al. reasoned that substances with an FTI > 1 had “an especially high toxicity” in relation to sales. Our interpretation of this result is that, although it is a common substance used in fatal intoxications, the number of zopiclone fatalities are somewhat low in relation to sales. Jönsson et al. found other sedatives/hypnotics, such as propiomazine (FTI 1.49), flunitrazepam (FTI 1.43), and hydroxyzine (FTI 2.02), with higher FTI’s compared with zopiclone. A publication by Geulayov et al. utilized FTI to compare relative toxicity of substances in fatal self-poisonings and found zopiclone/zolpidem to be nine times more toxic compared with diazepam (odds ratio 9.14, 95% CI 5.01–16.65). An interesting result of this study was that 87% of the fatalities had a prescription for zopiclone, indicating that most individuals received the substance from the Swedish healthcare system. The proportion of prescribed users remained relatively unchanged throughout the years, even when the sales of zopiclone started to decrease by the end of the study period. To our knowledge, the prevalence of prescribed use of zopiclone in fatal zopiclone intoxications has not been reported previously. However, Haukka et al. investigated zolpidem (another Z-drug) within this context and found that 88% were prescribed users, a result similar to the findings of this study. In comparison with previous publications investigating other substances, such as tramadol or oxycodone, the proportion of prescribed users was lower compared with the 87% seen in this study . Tjäderborn et al. also found that the prevalence of prescribed zopiclone (70%) and zaleplon (79%) use among impaired drivers was higher compared with other substances, supporting the results of this study. The high proportion of prescribed zopiclone use potentially indicates that a more restrictive prescribing rate could serve as a preventive measure for intoxication deaths, especially when caring for patients with an increased suicide risk. However, sleep disturbances are known risk factors for suicide , and it could be speculated that treatment with sedatives is an important factor for suicide prevention. Prescribing potentially harmful substances to patients with an increased risk for suicide is a balancing act for medical professionals. Through identifying individuals with an increased risk for misuse as well as examining the potential harm of zopiclone, medical professionals can make more informed assessments when prescribing the substance. Strengths and Limitations A major strength of this study is the national standardization of forensic autopsies in Sweden. All autopsies are performed by one governmental institution, and the toxicological analysis is performed at one central laboratory. Another strength is that each death was reviewed individually to conclude whether zopiclone contributed to the lethality of the poisoning or not. When uncertainties appeared, the autopsy reports were scrutinized. This method enabled an understanding of the role of zopiclone in fatal intoxications and prevented inclusion of incidental zopiclone findings. One limitation of this study is the risk for circular reasoning when utilizing postmortem concentrations of substances to investigate the cause of death in potential intoxications. A high concentration of a substance could potentially make the forensic pathologist more inclined to assume that the death was caused by an intoxication and vice versa. Another limitation of this study is the instability of zopiclone in vitro. If a sample is stored in suboptimal conditions, zopiclone can be degraded, resulting in lower concentrations or even undetectable levels . A lower concentration of zopiclone could potentially make the forensic pathologist less inclined to consider zopiclone as a contributor to the lethality of the intoxication, which could have resulted in an underestimation of zopiclone intoxications. This study only included cases with detection of zopiclone in femoral blood. This is a limitation since fatalities without access to femoral blood were excluded, which could have resulted in an underestimation of cases. However, femoral blood is the site least susceptible for postmortem changes and therefore optimal for studying concentrations of xenobiotics after death . A prescription for zopiclone was defined as valid if it was dispensed within 1 year before the date of death in our study. A sensitivity analysis was carried out prolonging and shortening the time interval between the day for the last dispense and the death date, none of which had a relevant impact on the results in this study. When shortening the time interval to 6 months, the proportion of prescribed users of zopiclone was 84%; when prolonging the period to 1 year and 6 months, 88% of zopiclone fatalities were prescribed users. This study shows that zopiclone contributed to 17% of all intoxication suicides autopsied in Sweden between 2012 and 2020. The 8% of monointoxications found in this study indicates that zopiclone is a substance with the potential of being lethal on its own. Although zopiclone fatalities are common in intoxication deaths in Sweden, they decreased at the end of the study period. The declining number of zopiclone intoxications is in line with Swedish data on intoxication deaths in general . The present study also found that the sales (measured in dispensed DDD) of zopiclone decreased between 2016 and 2020 in Sweden. A potential explanation for the reduction of zopiclone fatalities could be that medical professionals are more restrictive in prescribing the drug; there is evidence suggesting that limiting the access to lethal means is effective in the prevention of suicide . Among all intoxication fatalities in Sweden, men constituted 65% of the deaths, which is in line with results from a Swedish publication on 6894 intoxication fatalities between 1998 and 2007 . Interestingly, our study found that women and men were equally represented in fatal intoxications with zopiclone. Previous research has found women to be predisposed to insomnia ; in Sweden, women are prescribed more zopiclone, and drugs in general, compared with men, which could partially explain this finding . We found that the proportion of suicides in intoxications with zopiclone (62%) was larger compared with the proportion in all intoxication fatalities (29%). The majority of suicides with zopiclone (56%) and suicides through intoxication in general (55%) found in this study were committed by women. The large portion of suicides in zopiclone fatalities and the overrepresentation of women in this group could potentially explain the equal representation of sexes in zopiclone deaths. A speculative explanation for the large proportion of suicides in zopiclone deaths could be the correlation between sleep disturbances and depression. Insomnia is a common issue among individuals suffering from depressive symptoms , and sleep disturbances are important risk factors for suicide, even when adjusted for mental disorders . This study found that 48% of zopiclone fatalities also had findings of antidepressant drugs, and therefore, it is likely that a prominent proportion of the individuals had been diagnosed with depression. Since zopiclone is prescribed to patients with sleep disturbances, it could be speculated that the patient group suffers an increased risk for suicide, which could potentially explain the findings of this study. A randomized controlled trial found a greater incidence of depression among patients receiving treatment with hypnotic drugs compared with placebo . It could be speculated that the treatment with zopiclone potentially increased depressive symptoms among the patients. As mentioned, women were overrepresented in suicides both among all intoxications (55%) and in intoxications with zopiclone (56%). This result contrasts previous research on completed suicides, where men commit almost twice as many compared with women . Evidence suggests that women tend to choose less violent methods of suicide , and intoxication with drugs is the most common suicide method for women in Sweden . Women are considerably overrepresented in suicide attempts, which are more frequent than completed suicides . When attempting suicide, intoxication with drugs is a common method, which could partially explain the large finding of women among intoxication suicides seen in this study. When specifically investigating intoxication suicides, there are previous studies finding women to be equally represented and overrepresented , supporting the results of this study. Individuals dying in zopiclone fatalities were older compared with all fatal intoxications in Sweden; the median age was 55 and 44 years, respectively (Table ). This study found that women dying in the case of zopiclone intoxications was associated with older age, which has been seen in previous research of intoxication deaths . Therefore, it could be speculated that the large representation of women among the zopiclone fatalities could explain the higher median age seen in this study. Among individuals aged > 65 years, 76% of deaths were suicides, and in total they constituted about one-third of all suicides with zopiclone. The large representation of the elderly in suicides is in line with previous research , and a Swedish study found that intoxication with drugs constituted about 40% of female and 16% of male suicides in the elderly population . According to data published by the Swedish National Board of Health and Welfare, the largest group of patients receiving a prescription for zopiclone were > 84 years of age. In 2020, women constituted 65% of the patients aged > 64 years and prescribed zopiclone . It could be speculated that the large prescription to the elderly and elderly women is a contributing factor to their representation in zopiclone suicides. In this study, 8% of the fatalities with zopiclone were monointoxications. Early clinical trials failed to show major morbidity or mortality in connection with zopiclone , and details regarding its toxicity have remained unclear. The present findings indicate that the use of zopiclone alone can have fatal consequences, especially among the elderly. Some previous studies on intoxication deaths have found fatalities with zopiclone as the sole toxicological finding, supporting the thesis that zopiclone can be lethal on its own . Acute toxicity from lone use of both Z-drugs and benzodiazepines has been shown to be common among intoxications presented at emergency departments throughout Europe . The elderly (aged > 65 years) constituted 65% of all monointoxications and 80% of monointoxications, with no additional findings in this study. Among the monointoxications, 86% of deaths were suicides, and an explanation for the overrepresentation of the elderly could be that they apply more lethal means in their attempts to commit suicide , and therefore might have ingested higher dosages. Another theory could be that the frailty as well as comorbidities and polypharmacy of the elderly made them more susceptible to the toxicity of zopiclone. The postmortem concentrations of zopiclone found in this study were in line with the results of previous research . A Swedish study on data between 1992 and 2006 found the median concentration of zopiclone in intoxications caused by one substance (0.80 µg/g) to be similar to the concentrations of the monointoxications in this study . The same study also investigated the concentrations of zopiclone in fatal intoxications caused by multiple substances. They found the median concentration to be 0.70 µg/g, and the upper 90th percentile was 1.90 µg/g, which is slightly higher compared with the corresponding concentrations in the present study comprising all manners of deaths (median 0.47 µg/g and upper 90th percentile 1.6 µg/g). The majority of zopiclone fatalities were caused by more than one substance. This phenomenon is seen when studying fatal intoxications in general where most deaths are caused by the synergic effects of multiple substances . Ethanol was the most common substance found, which is in line with previous data . For suicides and fatalities with an undetermined manner of death, the most common additional findings were hypnotics. Hypnotic and sedative drugs have previously been shown to be common toxicological findings in intoxication fatalities . Our study found that 70% of all accidental zopiclone intoxications also had findings of opioids in the toxicological analysis. Previous studies have found opioids to be common findings among accidental intoxications . This study found the FTI to be 0.79 for zopiclone, and 0.06 for monointoxications, which corresponds with the findings of previous publications and can be considered quite low. Ojanperä et al. reasoned that substances with an FTI > 1 had “an especially high toxicity” in relation to sales. Our interpretation of this result is that, although it is a common substance used in fatal intoxications, the number of zopiclone fatalities are somewhat low in relation to sales. Jönsson et al. found other sedatives/hypnotics, such as propiomazine (FTI 1.49), flunitrazepam (FTI 1.43), and hydroxyzine (FTI 2.02), with higher FTI’s compared with zopiclone. A publication by Geulayov et al. utilized FTI to compare relative toxicity of substances in fatal self-poisonings and found zopiclone/zolpidem to be nine times more toxic compared with diazepam (odds ratio 9.14, 95% CI 5.01–16.65). An interesting result of this study was that 87% of the fatalities had a prescription for zopiclone, indicating that most individuals received the substance from the Swedish healthcare system. The proportion of prescribed users remained relatively unchanged throughout the years, even when the sales of zopiclone started to decrease by the end of the study period. To our knowledge, the prevalence of prescribed use of zopiclone in fatal zopiclone intoxications has not been reported previously. However, Haukka et al. investigated zolpidem (another Z-drug) within this context and found that 88% were prescribed users, a result similar to the findings of this study. In comparison with previous publications investigating other substances, such as tramadol or oxycodone, the proportion of prescribed users was lower compared with the 87% seen in this study . Tjäderborn et al. also found that the prevalence of prescribed zopiclone (70%) and zaleplon (79%) use among impaired drivers was higher compared with other substances, supporting the results of this study. The high proportion of prescribed zopiclone use potentially indicates that a more restrictive prescribing rate could serve as a preventive measure for intoxication deaths, especially when caring for patients with an increased suicide risk. However, sleep disturbances are known risk factors for suicide , and it could be speculated that treatment with sedatives is an important factor for suicide prevention. Prescribing potentially harmful substances to patients with an increased risk for suicide is a balancing act for medical professionals. Through identifying individuals with an increased risk for misuse as well as examining the potential harm of zopiclone, medical professionals can make more informed assessments when prescribing the substance. A major strength of this study is the national standardization of forensic autopsies in Sweden. All autopsies are performed by one governmental institution, and the toxicological analysis is performed at one central laboratory. Another strength is that each death was reviewed individually to conclude whether zopiclone contributed to the lethality of the poisoning or not. When uncertainties appeared, the autopsy reports were scrutinized. This method enabled an understanding of the role of zopiclone in fatal intoxications and prevented inclusion of incidental zopiclone findings. One limitation of this study is the risk for circular reasoning when utilizing postmortem concentrations of substances to investigate the cause of death in potential intoxications. A high concentration of a substance could potentially make the forensic pathologist more inclined to assume that the death was caused by an intoxication and vice versa. Another limitation of this study is the instability of zopiclone in vitro. If a sample is stored in suboptimal conditions, zopiclone can be degraded, resulting in lower concentrations or even undetectable levels . A lower concentration of zopiclone could potentially make the forensic pathologist less inclined to consider zopiclone as a contributor to the lethality of the intoxication, which could have resulted in an underestimation of zopiclone intoxications. This study only included cases with detection of zopiclone in femoral blood. This is a limitation since fatalities without access to femoral blood were excluded, which could have resulted in an underestimation of cases. However, femoral blood is the site least susceptible for postmortem changes and therefore optimal for studying concentrations of xenobiotics after death . A prescription for zopiclone was defined as valid if it was dispensed within 1 year before the date of death in our study. A sensitivity analysis was carried out prolonging and shortening the time interval between the day for the last dispense and the death date, none of which had a relevant impact on the results in this study. When shortening the time interval to 6 months, the proportion of prescribed users of zopiclone was 84%; when prolonging the period to 1 year and 6 months, 88% of zopiclone fatalities were prescribed users. The present study demonstrates that the toxicity of zopiclone can be fatal both on its own and in combination with other substances. Being a widely prescribed drug, zopiclone may serve as an accessible means for suicide. Most cases were prescribed zopiclone, which potentially indicates that restrictions in the prescribing rate could serve as a preventive measure for intoxication deaths, especially when caring for patients with an increased suicide risk. |
Otolaryngology in the COVID-19 pandemic era: the impact on our clinical practice | 42108a9c-bc9b-4f42-830d-1a269232e23b | 7310591 | Otolaryngology[mh] | The SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus-2) is rapidly expanding around the globe and the World Health Organization (WHO) declared COVID-19 (coronavirus disease) outbreak a global pandemic on March 11, 2020 . SARS-CoV-2 virus is mainly transmitted between people through respiratory droplets and contact routes. Infected respiratory droplets enter the human body through the nose and mouth. Conjunctiva is also considered to be a potential entrance point, although clear data proving this are not sufficient. Contact transmission by hands occurs through surfaces on which the virus is deposited. Aerosol transmission of the virus is plausible as well; however, doubtful evidence of this is still lacking. For healthcare workers, attention must be paid to all possible modes of transmission by taking appropriate protective and hygiene measures [ – ]. Otolaryngologists and surrounding staff are a high-risk group for COVID-19 infection, since they are particularly exposed to viral transmission directly through mucus and aerosolized particles during clinical examination, surgeries, or other interventions in the head and neck area. Evidence from China, Italy, and Iran and recently from the United Kingdom suggests that otolaryngologists are among the highest risk group of contracting the SARS-CoV-2 virus, especially when their examinations and procedures are performed without using appropriate personal protective equipment (PPE). Unfortunately, many of our ΕΝΤ colleagues worldwide are victims of the pandemic [ – ]. The rapid evolution of the pandemic adds new data on the virus and its action almost daily. Our knowledge has initially derived from anecdotal reports and subjective or empirical assessments, but has gradually evolved and now is based on reliable scientific data. Numerous online scientific publications are coming out, whereas scientific societies publish their recommendations about the otolaryngology practice in the COVID-19 era. This paper aims to give a brief overview of the current knowledge about the impact of COVID-19 pandemic on otolaryngology using the best available evidence. Special focus is given on how this knowledge has changed or should change our daily medical practice. As our knowledge about the virus is rapidly increased, it is more than likely that these recommendations will be reviewed in the future.
Over the last 3 months, there have been increasing reports that anosmia and to a lesser extent dysgeusia are significantly linked to COVID-19 disease. In April 2020, WHO added loss of smell and taste to the official lists of COVID-19 symptoms . In particular, anosmia rates in SARS-COV-2 positive patients vary significantly among studies and are in the order of 30–70%, while in some of the patients anosmia may be the only present symptom [ – ]. For example, new data arrive from a recently conducted European multicenter study in which patients with laboratory-confirmed COVID-19 infection completed olfactory and gustatory questionnaires. The results showed that 85.6% and 88.0% of patients reported olfactory and gustatory dysfunctions, respectively. Olfactory dysfunction (OD) appeared before the other symptoms in 11.8% of cases, whereas the early olfactory recovery rate was 44.0% . In addition, results from the first 237 entries of the COVID-19 Anosmia Reporting Tool for Clinicians, developed by the American Academy of Otolaryngology-Head and Neck Surgery, revealed that anosmia was noted in 73% of patients prior to COVID-19 diagnosis and was the initial symptom in 26.6% . There is a very high heteterogeneity among studies, with proportions ranging from 5 to 98% . Differences in clinical work-up, specific regional patient characteristics or viral strains might be possible explanations for these rate variations . The COVID-19-related anosmia is reported to be different from the well-known post-viral loss of smell, which follows rhinitis or other upper respiratory tract infections. Interestingly, most patients report a sudden and almost complete loss of smell i.e. anosmia, which is rarely accompanied by other nasal symptoms, such as nasal obstruction, secretions, or rhinorrhea . Impact on otolaryngology practice Anosmia (and dysgeusia) in the absence of other diseases of the upper respiratory tract (e.g. allergic rhinitis, acute and chronic rhinosinusitis) should raise the suspicion of COVID-19 infection. This should lead medical and paramedical staff to take the necessary measures for personal protection and warrant consideration for testing and self-isolation of these patients [ – , , , ]. Regarding changes on the therapy of anosmia during the pandemic see below at the “Medical treatment with steroid” section.
Anosmia (and dysgeusia) in the absence of other diseases of the upper respiratory tract (e.g. allergic rhinitis, acute and chronic rhinosinusitis) should raise the suspicion of COVID-19 infection. This should lead medical and paramedical staff to take the necessary measures for personal protection and warrant consideration for testing and self-isolation of these patients [ – , , , ]. Regarding changes on the therapy of anosmia during the pandemic see below at the “Medical treatment with steroid” section.
ENT clinical examination is considered a high-risk medical procedure for the transmission of the SARS-CoV-2 virus [ , , – ]. Particularly endoscopic examinations of the nose, sinuses, pharynx, and larynx are considered aerosol-generating procedures . The virus appears to be present in the upper aerodigestive tract, with very high concentrations in the nasal cavity and nasopharynx compared to the rest of the pharynx . It has also been shown that viral aerosol particles may remain in the air for three, if not more, hours . Therefore, it is recommended that the precautions adopted for endoscopic examinations of the head and neck should be the same as for other aerosol-generating procedures . Impact on otolaryngology practice Depending on the local circumstances, routine, nonurgent appointments should be postponed to limit the chance of virus infection of patients or healthcare professionals. Hence, otolaryngologists should limit their medical care activities to patients with time-sensitive, urgent, and emergent medical conditions such as head and neck cancers, airway emergencies, head and neck abscesses, acute otitis media, acute mastoiditis, complicated sinusitis, sudden hearing loss, facial paralysis or facial trauma . In any case, the clinical examination should be limited to the absolute necessary diagnostic procedures . Endoscopic examinations should be avoided if possible and should only be indicated if absolutely needed (e.g. increased suspicion or risk of malignancy, airway obstruction) [ , , , ]. Regarding rhinologic examination, not only endoscopy but even anterior rhinoscopy should be performed only when absolutely indicated, according to a recommendation . The use of high level PPE is mandatory when examining a patient confirmed or suspected for COVID-19, in particular during nasal and laryngeal endoscopy (Table ). The appropriate PPE in such cases should include high protection mask (FFP2 or FFP3/N95, depending on the source of recommendation), goggles or face shield, gown, surgical cap, and (double) gloves [ , , , , , , ]. Physicians are also advised to wear theater clothes (scrubs) , whereas a full protection suit is less commonly suggested . The patient himself should wear a mask in such cases [ , , ]. Local decongestants and anesthetics in form of sprays should be avoided, to avoid sneezing and coughing. Instead carefully placed pledgets should be used [ , , ]. In addition, endoscopy should be performed by video monitoring rather than use of eyepiece, to keep the patient’s and health care worker’s faces apart . Additional recommendations indicate that the examination should be performed by the most experienced professional and that the examination should take place in a negative pressure room and only the necessary personnel should be present . If a negative pressure isolation room is not available, endoscopic procedures can be performed in a designated room equipped with a high-performance air cleaning system .
Depending on the local circumstances, routine, nonurgent appointments should be postponed to limit the chance of virus infection of patients or healthcare professionals. Hence, otolaryngologists should limit their medical care activities to patients with time-sensitive, urgent, and emergent medical conditions such as head and neck cancers, airway emergencies, head and neck abscesses, acute otitis media, acute mastoiditis, complicated sinusitis, sudden hearing loss, facial paralysis or facial trauma . In any case, the clinical examination should be limited to the absolute necessary diagnostic procedures . Endoscopic examinations should be avoided if possible and should only be indicated if absolutely needed (e.g. increased suspicion or risk of malignancy, airway obstruction) [ , , , ]. Regarding rhinologic examination, not only endoscopy but even anterior rhinoscopy should be performed only when absolutely indicated, according to a recommendation . The use of high level PPE is mandatory when examining a patient confirmed or suspected for COVID-19, in particular during nasal and laryngeal endoscopy (Table ). The appropriate PPE in such cases should include high protection mask (FFP2 or FFP3/N95, depending on the source of recommendation), goggles or face shield, gown, surgical cap, and (double) gloves [ , , , , , , ]. Physicians are also advised to wear theater clothes (scrubs) , whereas a full protection suit is less commonly suggested . The patient himself should wear a mask in such cases [ , , ]. Local decongestants and anesthetics in form of sprays should be avoided, to avoid sneezing and coughing. Instead carefully placed pledgets should be used [ , , ]. In addition, endoscopy should be performed by video monitoring rather than use of eyepiece, to keep the patient’s and health care worker’s faces apart . Additional recommendations indicate that the examination should be performed by the most experienced professional and that the examination should take place in a negative pressure room and only the necessary personnel should be present . If a negative pressure isolation room is not available, endoscopic procedures can be performed in a designated room equipped with a high-performance air cleaning system .
For the reasons analysed in the previous section, many ENT procedures are considered high risk due to the exposure of airway and mucosal surfaces that could generate contaminating droplets and aerosols. Impact on otolaryngology practice Procedures in the examination room A variety of emergency or not avoidable procedures performed in the ENT examination room are considered high risk and are summarized in Table [ , , – , ]. During these procedures, the rules described above about staff protection (e.g. PPE) must be followed. Procedures in the operating room There is broad international consensus that not urgent/emergent and not time-sensitive (e.g. concerning malignancies) surgeries should be avoided during the pandemic [ , , , , ]. Particularly, endonasal endoscopic sinonasal surgery and laryngological surgery (especially jet ventilated) appear to be the riskiest procedures . Ideally, COVID-19 status should be determined preoperatively . In case of an elective but time-sensitive surgery, advice should be given to all COVID-19-negative patients for social distancing and hand hygiene between the testing time and the time of surgery . During the pandemic, all recommended staff protection measures described in Table must be implemented. In particular, full PPE should be used not only in COVID-19 positive or high suspicious patients, but in COVID-19 negative or asymptomatic patients as well. In some reports, PAPR system (powered air purifying respirators) is recommended . High-risk operations or operations in COVID-19-positive patients should be performed in a designated operating room with negative pressures , in which the smallest possible surgical team should be used both for reasons of safety and to preserve PPE (Table ). When performing the surgery, the use of powered devises (eg., drills, microdebriders) or ultrasonic shears should be avoided, since they may cause aerosolization of blood and other tissues . Even the use of electrocautery may be a risk factor for transmitting the virus via surgical smoke, although the infectiousness of aerosolized blood with SARS-CoV-2 is not yet known. Hence, it is advisable to keep the power settings of electrocautery as low as possible .
Procedures in the examination room A variety of emergency or not avoidable procedures performed in the ENT examination room are considered high risk and are summarized in Table [ , , – , ]. During these procedures, the rules described above about staff protection (e.g. PPE) must be followed. Procedures in the operating room There is broad international consensus that not urgent/emergent and not time-sensitive (e.g. concerning malignancies) surgeries should be avoided during the pandemic [ , , , , ]. Particularly, endonasal endoscopic sinonasal surgery and laryngological surgery (especially jet ventilated) appear to be the riskiest procedures . Ideally, COVID-19 status should be determined preoperatively . In case of an elective but time-sensitive surgery, advice should be given to all COVID-19-negative patients for social distancing and hand hygiene between the testing time and the time of surgery . During the pandemic, all recommended staff protection measures described in Table must be implemented. In particular, full PPE should be used not only in COVID-19 positive or high suspicious patients, but in COVID-19 negative or asymptomatic patients as well. In some reports, PAPR system (powered air purifying respirators) is recommended . High-risk operations or operations in COVID-19-positive patients should be performed in a designated operating room with negative pressures , in which the smallest possible surgical team should be used both for reasons of safety and to preserve PPE (Table ). When performing the surgery, the use of powered devises (eg., drills, microdebriders) or ultrasonic shears should be avoided, since they may cause aerosolization of blood and other tissues . Even the use of electrocautery may be a risk factor for transmitting the virus via surgical smoke, although the infectiousness of aerosolized blood with SARS-CoV-2 is not yet known. Hence, it is advisable to keep the power settings of electrocautery as low as possible .
A variety of emergency or not avoidable procedures performed in the ENT examination room are considered high risk and are summarized in Table [ , , – , ]. During these procedures, the rules described above about staff protection (e.g. PPE) must be followed.
There is broad international consensus that not urgent/emergent and not time-sensitive (e.g. concerning malignancies) surgeries should be avoided during the pandemic [ , , , , ]. Particularly, endonasal endoscopic sinonasal surgery and laryngological surgery (especially jet ventilated) appear to be the riskiest procedures . Ideally, COVID-19 status should be determined preoperatively . In case of an elective but time-sensitive surgery, advice should be given to all COVID-19-negative patients for social distancing and hand hygiene between the testing time and the time of surgery . During the pandemic, all recommended staff protection measures described in Table must be implemented. In particular, full PPE should be used not only in COVID-19 positive or high suspicious patients, but in COVID-19 negative or asymptomatic patients as well. In some reports, PAPR system (powered air purifying respirators) is recommended . High-risk operations or operations in COVID-19-positive patients should be performed in a designated operating room with negative pressures , in which the smallest possible surgical team should be used both for reasons of safety and to preserve PPE (Table ). When performing the surgery, the use of powered devises (eg., drills, microdebriders) or ultrasonic shears should be avoided, since they may cause aerosolization of blood and other tissues . Even the use of electrocautery may be a risk factor for transmitting the virus via surgical smoke, although the infectiousness of aerosolized blood with SARS-CoV-2 is not yet known. Hence, it is advisable to keep the power settings of electrocautery as low as possible .
Nasal and transnasal endoscopic operations are very high-risk procedures for SARS-CoV-2 transmission, because of the high viral titers in nasal and nasopharyngeal mucosa. In addition, the use of powered instruments (eg., drill, microdebrider) and the frequent rinsing of the endoscope during the procedure may be a source of droplets and aerosolized viral particles [ – , , , ]. Recent experimental data suggest that cold surgical instrumentation and microdebrider use pose significantly less aerosolization risk than a high-speed drill . Impact on otolaryngology practice In patients positive to COVID-19, the surgery should be postponed . In case that the surgery cannot be postponed, then the use of PAPR (Powered Air Purifying Respirators) additional to the appropriate PPE (Table ) by all the surgery room staff is recommended. Alternatively, an external approach is chosen if possible . If the patient is COVID-19 negative, the appropriate staff protection measures are needed (Table ) . The same applies to the surgical management of epistaxis . The use of powered instruments like shaver and/or drill should be limited or even avoided whenever possible .
In patients positive to COVID-19, the surgery should be postponed . In case that the surgery cannot be postponed, then the use of PAPR (Powered Air Purifying Respirators) additional to the appropriate PPE (Table ) by all the surgery room staff is recommended. Alternatively, an external approach is chosen if possible . If the patient is COVID-19 negative, the appropriate staff protection measures are needed (Table ) . The same applies to the surgical management of epistaxis . The use of powered instruments like shaver and/or drill should be limited or even avoided whenever possible .
Patients with head and neck cancer are obviously “time-sensitive’’ cases. Therefore, head and neck surgery will still be imperative and indicated in the care of these patients . The importance of surgical manipulation on mucosa surfaces is analyzed in the ENT examination section. Procedures without exposure of the mucosa, like neck or thyroid surgery, are lower risk. However, the use of electrocautery can result in aerosolization of the virus from the bloodstream and caution is needed, e.g. by keeping the power settings of electrocautery as low as possible .
Although not yet known whether the middle ear and mastoid are involved in COVID-19, it appears likely that the mucosa of the Eustachian tube, middle ear, and mastoid cells are contaminated. The involvement of the adjacent epithelium of the nose and nasopharynx in the disease and the fact that the middle ear mucosa is affected in other viral respiratory infections of the upper respiratory tract (including infections by other coronaviruses) makes this scenario possible. The surgical step that significantly increases the risk of virus transmission is drilling through the mastoid. During mastoidectomy, viral particles spread in the air in the form of droplets and aerosols and may be present there for several hours. Therefore, mastoidectomy is considered a high-risk procedure for all the operating room staff [ , , ]. Impact on otolaryngology practice As with every ENT surgery during the pandemic, any patient undergoing any otologic surgery should be tested for COVID-19 preoperatively. In case of a positive result, surgery should be postponed until the patient has cleared the disease . In COVID-19-negative patients, it is imperative that not only the surgeon but all operating room staff takes protection measures as described above. According to the British Society of Otology, life-threatening urgent otological situations in which surgery cannot be delayed include acute mastoiditis, otogenic intracranial sepsis, and operable temporal bone malignancy. Moreover, a vestibular schwannoma with life-threatening brainstem compression should be regarded as urgent as well. Surgery for cholesteatoma and implantation of auditory devices, adult and pediatric, should not be regarded as urgent . An unavoidable mastoidectomy should be kept to a minimum or even be carried out with curettage rather than with drilling if possible (e.g., subperiosteal abscess). If drilling cannot be avoided tips for reducing aerosolization include drill speed and irrigation volume reduction, effective suctioning and good hypotension to minimize bleeding . Moreover, various techniques of covering the surgical field and performing the drilling procedure under a drape have been described .
As with every ENT surgery during the pandemic, any patient undergoing any otologic surgery should be tested for COVID-19 preoperatively. In case of a positive result, surgery should be postponed until the patient has cleared the disease . In COVID-19-negative patients, it is imperative that not only the surgeon but all operating room staff takes protection measures as described above. According to the British Society of Otology, life-threatening urgent otological situations in which surgery cannot be delayed include acute mastoiditis, otogenic intracranial sepsis, and operable temporal bone malignancy. Moreover, a vestibular schwannoma with life-threatening brainstem compression should be regarded as urgent as well. Surgery for cholesteatoma and implantation of auditory devices, adult and pediatric, should not be regarded as urgent . An unavoidable mastoidectomy should be kept to a minimum or even be carried out with curettage rather than with drilling if possible (e.g., subperiosteal abscess). If drilling cannot be avoided tips for reducing aerosolization include drill speed and irrigation volume reduction, effective suctioning and good hypotension to minimize bleeding . Moreover, various techniques of covering the surgical field and performing the drilling procedure under a drape have been described .
Due to the amount of droplets and aerosols produced, tracheostomy and tracheostomy postoperative care (tracheostomy evaluation, suctioning, wound and tube changes, etc.) in COVID-19 patients is associated with a very high transmission risk to the entire health care team [ , , ]. Except in extremely urgent cases, it is essential to determine the COVID-19 status of the patient preoperatively . Comparing surgical with percutaneous tracheostomy, no concrete evidence exists about the less aerosol-generating procedure . It is reported that percutaneous tracheostomy is associated with higher aerosolization risks compared with open tracheostomy, because of more extensive airway manipulation, such as bronchoscopy and/or serial dilations during trachea entry. Moreover, patients with high ventilatory settings may also require repeated connection and disconnection from the ventilatory circuit . Impact on otolaryngology practice In COVID-19 patients, tracheostomy should be indicated by a multidisciplinary team and only if absolutely necessary [ , , , ]. Based on the available data, the advantages of an early tracheostomy in severe COVID-19 patients have not been clarified . The nature of the COVID-19 disease is such that tracheostomy in ICU COVID-19 patients is of less importance. This is first due to the interstitial pneumonia caused with few secretions and second due to the fact that COVID-19 rarely leads to actual long-term intubations . The possibility of tracheostomy may be considered in patients with stable lung condition; however, it should not occur earlier than 2–3 weeks after intubation and preferably with negative COVID-19 testing. On the other hand, it should be avoided during periods of respiratory instability or high respiratory dependence . When planning for open tracheostomy in an infected patient, there are several important perioperative considerations that should be taken into account, as widely recommended [ , – ]: Use of appropriate PPE: Table . Location of the surgery: perform at the bedside in the ICU in negative-pressure rooms, the presence of adjacent anterooms is ideal. If performed in the operating room (OR), preferably in negative pressure ORs in special areas within the OR complex. Use of suitable tracheostomy tube: nonfenestrated, cuffed. Minimization of time of exposure to aerosolized secretions intraoperatively: ensure complete patient paralysis throughout the procedure to prevent coughing, stop mechanical ventilation just before entering into the trachea, reduce the use of suction, if suction needed this should be within a closed system with a viral filter. Dedicated and experienced tracheostomy team, with preestablished communication plans. Careful waste disposal and decontamination of equipment after the procedure. Postoperatively, important considerations that should be taken into account include [ , – ]: The tracheal tube cuff should be kept inflated and care should be taken to avoid leaks. Tracheostomy tube changes should be delayed until COVID-19 testing is negative or until viral load is as low as possible. Subsequent scheduled tracheostomy tube changes should be also delayed. Tracheostomy suctioning should be performed using a closed suction system with a viral filter. Circuit disconnection must be generally avoided. During weaning, a heat moisture exchanger (HME) should be used to prevent virus spread or reinfection of patients.
In COVID-19 patients, tracheostomy should be indicated by a multidisciplinary team and only if absolutely necessary [ , , , ]. Based on the available data, the advantages of an early tracheostomy in severe COVID-19 patients have not been clarified . The nature of the COVID-19 disease is such that tracheostomy in ICU COVID-19 patients is of less importance. This is first due to the interstitial pneumonia caused with few secretions and second due to the fact that COVID-19 rarely leads to actual long-term intubations . The possibility of tracheostomy may be considered in patients with stable lung condition; however, it should not occur earlier than 2–3 weeks after intubation and preferably with negative COVID-19 testing. On the other hand, it should be avoided during periods of respiratory instability or high respiratory dependence . When planning for open tracheostomy in an infected patient, there are several important perioperative considerations that should be taken into account, as widely recommended [ , – ]: Use of appropriate PPE: Table . Location of the surgery: perform at the bedside in the ICU in negative-pressure rooms, the presence of adjacent anterooms is ideal. If performed in the operating room (OR), preferably in negative pressure ORs in special areas within the OR complex. Use of suitable tracheostomy tube: nonfenestrated, cuffed. Minimization of time of exposure to aerosolized secretions intraoperatively: ensure complete patient paralysis throughout the procedure to prevent coughing, stop mechanical ventilation just before entering into the trachea, reduce the use of suction, if suction needed this should be within a closed system with a viral filter. Dedicated and experienced tracheostomy team, with preestablished communication plans. Careful waste disposal and decontamination of equipment after the procedure. Postoperatively, important considerations that should be taken into account include [ , – ]: The tracheal tube cuff should be kept inflated and care should be taken to avoid leaks. Tracheostomy tube changes should be delayed until COVID-19 testing is negative or until viral load is as low as possible. Subsequent scheduled tracheostomy tube changes should be also delayed. Tracheostomy suctioning should be performed using a closed suction system with a viral filter. Circuit disconnection must be generally avoided. During weaning, a heat moisture exchanger (HME) should be used to prevent virus spread or reinfection of patients.
Crying and/or coughing is very common during pediatric ENT examination. Therefore, pediatric airway procedures or even simple examinations are considered highly likely to generate droplets or aerosols and health professionals should maintain a high level of precaution using appropriate PPE . As in adult otolaryngology, all planned surgeries including operations on the adenoids and tonsils should be postponed unless there are extremely special indications. Indications for performing a pediatric ENT surgery during the COVID-19 pandemic include not only life-threatening emergencies, but also procedures that may reduce the need for visiting the physician or prevent complications (eg., ear tubes in young children with raging infections) . During the pandemic, newborn hearing screening, diagnosis, and treatment of hearing loss should be continued. ABR and/or other diagnostic audiological testing should be considered essential patient care. However, genetic testing, eye exam, or other testing could be delayed unless they directly impact patient management in the short-term .
According to the present knowledge, high doses of steroids are associated with worse outcome of the COVID-19 infection . This information should be taken into account when we manage patients with conditions requiring steroid administration as a treatment option during the pandemic. Neurootological disorders It is advisable to avoid high doses of corticosteroids for the treatment of Meniere's disease or sudden hearing loss in a COVID-positive patient. Intratympanic steroid injection could be an alternative management approach, although no data exist to support this . Bell’s facial palsy For COVID-19-positive patients, it is reasonable to avoid steroids, since Bell's facial palsy has a high rate of spontaneous recovery . Rhinologic diseases A reasonable consideration concerns the use of topical nasal corticosteroids for the treatment of allergic rhinitis (AR) and chronic rhinosinusitis (CRS). So far there is no indication that their use may be a risk factor for SARS-Cov-2 virus infection or that they may negatively affect an existing COVID-19 infection. Therefore, adults and children undergoing treatment with nasal corticosteroids should continue their treatment and not modify or discontinue the therapy without consulting their doctor. Ceasing intranasal steroids could lead to more sneezing and thus easier transmission of the virus. Systemic steroids in patients with AR or CRS should be administered with caution and only in the absence or failure of other alternative therapies (eg., patients with CRS in whom surgical therapy is not possible due to the pandemic, or patients with CRS with polyps in whom biological therapy with Dupilumab was not effective) [ , , ]. Anosmia During the pandemic oral corticosteroids should be avoided in new cases of anosmia in the absence of an obvious cause (e.g., head trauma, nasal polyps), since recovery can occur in the first weeks after onset [ , , , ]. Topical nasal corticosteroid application is controversial. Oral corticosteroids could be optionally recommended for patients with loss of smell more than 2 weeks as an isolated symptom or following resolution of any other COVID symptoms . Despite existing recommendations against their use in patients with olfactory and gustatory dysfunction without nasal obstruction , the use of intranasal corticosteroids can be considered, in the form of spray formulation with a long applicator so the olfactory cleft can be reached to minimize potential viral spill. The controversy about corticosteroids brings attention to other treatment options for smell disorders, such as olfactory training, omega 3 supplements, topical vitamin A, and zinc .
It is advisable to avoid high doses of corticosteroids for the treatment of Meniere's disease or sudden hearing loss in a COVID-positive patient. Intratympanic steroid injection could be an alternative management approach, although no data exist to support this .
For COVID-19-positive patients, it is reasonable to avoid steroids, since Bell's facial palsy has a high rate of spontaneous recovery .
A reasonable consideration concerns the use of topical nasal corticosteroids for the treatment of allergic rhinitis (AR) and chronic rhinosinusitis (CRS). So far there is no indication that their use may be a risk factor for SARS-Cov-2 virus infection or that they may negatively affect an existing COVID-19 infection. Therefore, adults and children undergoing treatment with nasal corticosteroids should continue their treatment and not modify or discontinue the therapy without consulting their doctor. Ceasing intranasal steroids could lead to more sneezing and thus easier transmission of the virus. Systemic steroids in patients with AR or CRS should be administered with caution and only in the absence or failure of other alternative therapies (eg., patients with CRS in whom surgical therapy is not possible due to the pandemic, or patients with CRS with polyps in whom biological therapy with Dupilumab was not effective) [ , , ].
During the pandemic oral corticosteroids should be avoided in new cases of anosmia in the absence of an obvious cause (e.g., head trauma, nasal polyps), since recovery can occur in the first weeks after onset [ , , , ]. Topical nasal corticosteroid application is controversial. Oral corticosteroids could be optionally recommended for patients with loss of smell more than 2 weeks as an isolated symptom or following resolution of any other COVID symptoms . Despite existing recommendations against their use in patients with olfactory and gustatory dysfunction without nasal obstruction , the use of intranasal corticosteroids can be considered, in the form of spray formulation with a long applicator so the olfactory cleft can be reached to minimize potential viral spill. The controversy about corticosteroids brings attention to other treatment options for smell disorders, such as olfactory training, omega 3 supplements, topical vitamin A, and zinc .
Given the recommendation that as long as the pandemic lasts, the smallest possible surgical team should be used, the presence of trainees and observers in the OR should be avoided. Training could be enhanced by recording the procedure digitally and share it with trainees at a later time .
The COVID-19 pandemic is an extraordinary challenge for the medical community. Since the SARS-CoV-2 virus has already expanded in the community in many countries of the world, each patient in which COVID-19 status cannot be confirmed should be managed as positive. Even if in many countries the pandemic is slowing down and medical practice is been adapted to new normality, a new pandemic wave in the upcoming winter is a possibility. Therefore, the way we practice medicine during the present or a new COVID-19 pandemic has to be based on scientific data and evidence. Otolaryngologists and surrounding staff are particularly at risk for COVID-19 infection. As with all health care professionals, their protection is essential for avoiding collapse of the health care system. As knowledge about COVID-19 infection rapidly evolves, we need to keep ourselves up to date and follow the respective recommendations. The need for future revisions of these recommendations based on more data and randomized controlled trials is imperative.
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Enhancing xylose-fermentation capacity of engineered | 3d90c9fd-179b-4126-9099-4f70f36bd64f | 11062418 | Microbiology[mh] | The bioethanol industry has contributed significantly to reduction of greenhouse gases, increasing energy security, and also supported economic development in many countries. Ethanol produced from biomass accounts for the largest fermentation product by volume (Meyer Hans-Peter ). It is among the most promising green fuel alternatives to fossil fuels in the short term. Currently, ethanol is produced mainly from feedstocks such as corn and sugar cane, known as first-generation (1 G) bioethanol. 1 G bioethanol production has greatly optimized fermentation processes and has grown to an economically highly competitive industry. 1 G bioethanol is currently the only transportation fuel alternative that can be produced in an economically viable manner (Mizik ). However, feedstock competition with the food supply has drawn considerable attention, especially because of the impact on developing countries. Additionally, the increased demand for 1 G feedstock might have contributed to deforestation when forest land was converted into agricultural land. This is claimed to have resulted, at least in some cases, in low or even no net greenhouse gas savings by the 1 G bioethanol production process (Jeswani et al. ). On the other hand, second generation (2 G) ethanol production utilizes lignocellulosic feedstocks such as agricultural and forest residues, as well as the organic fraction of municipal solid waste. Ethanol produced from such waste biomass is considered to be a near carbon-neutral or even carbon-negative renewable fuel alternative. However, until now, economically feasible industrial-scale production of bioethanol from waste biomass has remained a major challenge, with only limited industries advancing to commercial scale and their economic viability remaining unclear (Devi et al. , Raj et al. ). The main hurdle for economically sustainable 2 G ethanol production lies in the recalcitrant nature of lignocellulosic biomass. Complete hydrolysis of lignocellulosic biomass into fermentable sugars in an economically viable manner has not been achieved because of its complex structure and composition (Vasic et al. ). Lignocellulose materials are composed of polymers of cellulose, hemicellulose, and lignin. These polymers provide rigidity to the biomass, are structurally complex and are resistant to chemical, physical, and enzymatic hydrolysis. The most effective hydrolysis processes to date implement harsh chemical and physical pretreatment conditions before enzymatic hydrolysis. Such harsh pretreatment steps release inhibitory chemicals such as weak acids, furan, and phenolic compounds (Palmqvist Eva , Soares et al. , Seidel et al. ). These chemicals significantly reduce the efficiency of fermentation by inhibiting the metabolism of the fermenting microorganisms. In addition, the industry is confronted with the difficulty of finding robust microorganisms that are able to completely convert all the hydrolyzed sugars derived from the cellulose and hemicellulose into bioethanol under industrial conditions. Since the biomass is a major contributor to the production cost, a high overall ethanol yield, utilizing all available sugars from the biomass, is an essential condition for the industrial process. The sugars include hexose sugars such as glucose and mannose, and pentose sugars, mainly xylose and arabinose. On top of that, minimum water usage is important to reduce operational costs. As a result, there is a need to use biomass hydrolysates with a high solids load. High solid content, however, implies high concentrations of inhibitors, of which the toxicity is further enhanced by the ethanol produced (Koppram et al. ). As a consequence, an organism that can ferment both hexose and pentose sugars and displays high inhibitor tolerance is a prerequisite for economically viable industrial production of bioethanol from lignocellulosic biomass. Saccharomyces cerevisiae is the dominant microorganism in 1 G bioethanol production because it produces the highest ethanol titer from hexose sugars at nearly stochiometric yield and is tolerant to ethanol and a wide range of inhibitors. The major bottleneck for the use of S. cerevisiae in cellulosic ethanol production is its inability to utilize pentose sugars. However, in recent years, recombinant S. cerevisiae strains that can efficiently ferment xylose have been developed by metabolic and evolutionary engineering (Jeffries , Hahn-Hagerdal et al. , Brat et al. , Demeke et al. ). Yet, the efficiency of hexose and especially pentose fermentation by the engineered strains is greatly hampered by the inhibitors present in lignocellulosic hydrolysates. Though glucose utilization is reasonably maintained in the presence of moderate to high concentrations of inhibitors, xylose fermentation is much more sensitive and severely reduced or even eliminated already at low inhibitor concentrations (Bellissimi et al. , Vanmarcke et al. ). This forced the industry to use low density lignocellulose hydrolysates to achieve good ethanol yields and productivity. However, this results in the use of excessive amounts of water, and also results in a low final ethanol titer. As a consequence, the downstream processing becomes less cost effective. Therefore, yeast strains able to ferment all sugars in hydrolysates at high solids loads and inhibitor concentrations are necessary for economically viable cellulosic ethanol production. Evolutionary engineering has been applied widely for improvement of industrial properties in S. cerevisiae . In evolutionary engineering, a cultivation condition with a selective pressure to industrially relevant traits is applied and spontaneous or induced mutant strains with a selective advantage under the condition used are selected (Mans et al. ). To enhance the mutation frequency, chemical or physical mutagens can be applied, followed by selection for the specific trait of interest (Smith et al. , Inokuma et al. ). However, the large number of mutations generated by such mutagens frequently results in side effects that compromise other important industrial traits, such as the proliferation rate under conditions used for industrial yeast production and the general robustness under varying, stressful industrial conditions (Cakar et al. , Demeke et al. ). In this work, we have developed a robust industrial S. cerevisiae strain with efficient xylose-fermentation capacity in nondetoxified lignocellulose hydrolysates at high solids loading. For that purpose, we developed and employed a novel evolutionary engineering strategy that can be applied for industrial strain development with selectable traits such as efficient substrate utilization and high inhibitor tolerance. The resulting strain, MDS130, demonstrated complete conversion of both glucose and xylose to ethanol with a high yield and overall productivity, and reaching ethanol titers >7% (v/v) in concentrated undetoxified cellulosic hydrolysates.
Strains and growth conditions The yeast strains used and developed in this study are listed in Table . Yeast extract peptone (YP) medium composed of 10 g/l yeast extract and 20 g/l bacteriological peptone supplemented with glucose or xylose was used for yeast propagation. For solid medium, 15 g/l bacteriological agar was added. The sugars were autoclaved separately at 400 g/l concentration. The appropriate antibiotics were added to the medium for selection of yeast strains transformed with plasmids carrying a resistance marker. All yeast strains were maintained at −80°C in storage medium (YP with 25% glycerol). Propagation in molasses Yeast strains were pregrown overnight in YPD (2% glucose) medium. The culture was transferred into 50 ml of 10% sugarcane molasses medium at an initial OD 600 of 1. The 10% molasses medium was prepared by diluting the original concentrated molasses, containing 60% w/v sucrose, with deionized water, resulting in a concentration of 6% sucrose in the 10% molasses medium. Media for evolutionary adaptation Pretreated spruce biomass was obtained from SEKAB, Sweden. The biomass was pretreated with SO 2 -impregnated steam explosion (Demeke et al. ) and had 22% total solids fraction. A xylose enriched and inhibitor rich pretreated biomass medium (XIPB) was prepared by adding xylose powder to the liquid fraction of the pretreated spruce biomass and shaking the media at 35°C until the sugar was completely dissolved. To prepare glucose depleted XIPB named XIPB-G, a nonxylose utilizing S. cerevisiae strain, Ethanol Red, was inoculated in the XIPB at a starting OD 600 of 5. The mixture was incubated at 30°C in a shaking incubator for 48 h. A sample was then taken for HPLC analysis to check whether the glucose was completely consumed. After the glucose was used up, the culture was incubated in a shaking incubator at 70°C to inactivate the yeast. Complete yeast inactivation was confirmed by spreading 200 µl of the culture on a YPD plate and checking that no yeast colonies were formed after 72 h. Small-scale fermentations For the evolutionary adaptation experiments, small-scale semianaerobic fermentations were performed in 50 ml using cylindrical tubes with magnetic stirrers (Demeke et al. ). The tubes were closed with a rubber stopper containing a glass tube plugged with cotton. For screening purposes, fermentations were carried out either in 50 ml scale as in the evolutionary adaptation experiment or in 10 ml working volume using glass vials with 20 ml capacity. Cultures were incubated at 35°C with continuous stirring using a magnetic stirrer at 150–350 rpm. The fermentations were followed by measuring the weight at the start and after several time intervals using a precision balance. The weight loss during fermentation is directly related to CO 2 production (Demeke et al. ). For evaluation of selected segregants, fermentations were performed in 120 ml working volume using 250 ml glass bottles. Strains were pregrown for 24 h in 50 ml YPD or 10% sugarcane molasses medium in 300 ml capacity shake flasks. The molasses medium used for the propagation was prepared by diluting the original molasses, with initial sugar content of 60% w/v sucrose, to 10% resulting in a final sucrose level of 6% w/v). The medium was incubated for about 20 h in a shaking incubator at 30°C. Cells were pelleted by centrifugation at 2000 × g for 1 min. The cell pellets were inoculated in the fermentation medium at 1 g DW/l. Samples for HPLC analysis were withdrawn at time zero and at subsequent time intervals. Molecular biology techniques Transformation of yeast strains with plasmid DNA was performed using the standard lithium acetate method (Gietz et al. ). Polymerase chain reaction (PCR) for mating-type determination was done using standard Taq Polymerase (New England Biolabs). A primer at the MAT locus was used in combination with a MATα or MATa specific primers (Huxley et al. ). Genomic DNA for PCR amplification was extracted by breaking cells with glass beads using a Fast Prep homogenizer in PCI (phenol/chloroform/isoamyl-alcohol) solution according to Thompson et al. . Sporulation and tetrad analysis Diploid or tetraploid strains were sporulated as follows. First, the strains were grown in YPD medium till early stationary phase. Then the cell pellets were transferred onto a sporulation plate (1% potassium acetate, pH 6 and 1.5% agar). The plate was incubated at 23°C for 7–10 days, until most of the cells had formed tetrads. Spore isolation was done by tetrad dissection using a Sanger MSM micromanipulator (Sanger instruments, Somerset, UK). Mating type switch The mating type of the diploid industrial strains was switched according to Haber . Briefly, the yeast HO gene was transiently expressed under a galactose inducible promoter by transforming the plasmid pFL39Gal1HO carrying the HPH selection marker into the strains. Transformants carrying the HO plasmid were grown overnight in YPD + hygromycin. The cells were pelleted and cell pellets were inoculated into YP + 2% galactose for 1 h at 30°C. The galactose induction was then stopped by adding 2% glucose. Afterwards, samples were taken every hour for 5 h and spread for single colonies on YPD plates. After 2 days, the colonies formed were evaluated for mating type by PCR. Colonies with the correct mating type were allowed to lose the pFL39Gal1HO plasmid by growth in liquid YPD medium without selection. Hybridization A small amount of cells from the two strains with opposite mating type, GSE16-T18- MAT α/α and strain HDY.GUF5- MAT a/a, were mixed on a YPD plate and incubated for 24 h. A sample from the mix was spread on a YPD plate for single colonies. Colonies were then evaluated for mating type by PCR. Possible hybrid strains with MAT a/α mating type were verified by flow cytometry for correct ploidy. Determination of ploidy The DNA content was analyzed for determination of ploidy by flow cytometry according to Popolo et al. Briefly, cells were grown to exponential phase, washed with ice-cold sterile water and fixed with 70% ethanol. Ethanol-fixed cells were then treated with RNase (1 mg/ml) for 1 h to remove the RNA. The DNA was subsequently stained with propidium iodide (0.046 M) in a solution of 50 mM Tris, pH 7.7 and 15 mM MgCl 2 , at 4°C for 72 h. A FACScan instrument (Becton Dickinson) was then used to measure the fluorescence intensity in the DNA sample. HPLC analysis Substrate sugars and metabolites produced in the fermentations were analyzed with a Shimadzu Nexera X2 HPLC system (Shimadzu corporation) using 5 mM H 2 SO 4 as mobile phase at a flow rate of 0.65 ml/min. An ion-exchange MetaCarb 87H column (Agilent Technologies) was used to separate the compounds at 60°C and detection was done with a refractive index detector. Samples were prepared by performing twice a centrifugation at 20 000 g for 10 min, after which the supernatant was injected into the HPLC system.
The yeast strains used and developed in this study are listed in Table . Yeast extract peptone (YP) medium composed of 10 g/l yeast extract and 20 g/l bacteriological peptone supplemented with glucose or xylose was used for yeast propagation. For solid medium, 15 g/l bacteriological agar was added. The sugars were autoclaved separately at 400 g/l concentration. The appropriate antibiotics were added to the medium for selection of yeast strains transformed with plasmids carrying a resistance marker. All yeast strains were maintained at −80°C in storage medium (YP with 25% glycerol).
Yeast strains were pregrown overnight in YPD (2% glucose) medium. The culture was transferred into 50 ml of 10% sugarcane molasses medium at an initial OD 600 of 1. The 10% molasses medium was prepared by diluting the original concentrated molasses, containing 60% w/v sucrose, with deionized water, resulting in a concentration of 6% sucrose in the 10% molasses medium.
Pretreated spruce biomass was obtained from SEKAB, Sweden. The biomass was pretreated with SO 2 -impregnated steam explosion (Demeke et al. ) and had 22% total solids fraction. A xylose enriched and inhibitor rich pretreated biomass medium (XIPB) was prepared by adding xylose powder to the liquid fraction of the pretreated spruce biomass and shaking the media at 35°C until the sugar was completely dissolved. To prepare glucose depleted XIPB named XIPB-G, a nonxylose utilizing S. cerevisiae strain, Ethanol Red, was inoculated in the XIPB at a starting OD 600 of 5. The mixture was incubated at 30°C in a shaking incubator for 48 h. A sample was then taken for HPLC analysis to check whether the glucose was completely consumed. After the glucose was used up, the culture was incubated in a shaking incubator at 70°C to inactivate the yeast. Complete yeast inactivation was confirmed by spreading 200 µl of the culture on a YPD plate and checking that no yeast colonies were formed after 72 h.
For the evolutionary adaptation experiments, small-scale semianaerobic fermentations were performed in 50 ml using cylindrical tubes with magnetic stirrers (Demeke et al. ). The tubes were closed with a rubber stopper containing a glass tube plugged with cotton. For screening purposes, fermentations were carried out either in 50 ml scale as in the evolutionary adaptation experiment or in 10 ml working volume using glass vials with 20 ml capacity. Cultures were incubated at 35°C with continuous stirring using a magnetic stirrer at 150–350 rpm. The fermentations were followed by measuring the weight at the start and after several time intervals using a precision balance. The weight loss during fermentation is directly related to CO 2 production (Demeke et al. ). For evaluation of selected segregants, fermentations were performed in 120 ml working volume using 250 ml glass bottles. Strains were pregrown for 24 h in 50 ml YPD or 10% sugarcane molasses medium in 300 ml capacity shake flasks. The molasses medium used for the propagation was prepared by diluting the original molasses, with initial sugar content of 60% w/v sucrose, to 10% resulting in a final sucrose level of 6% w/v). The medium was incubated for about 20 h in a shaking incubator at 30°C. Cells were pelleted by centrifugation at 2000 × g for 1 min. The cell pellets were inoculated in the fermentation medium at 1 g DW/l. Samples for HPLC analysis were withdrawn at time zero and at subsequent time intervals.
Transformation of yeast strains with plasmid DNA was performed using the standard lithium acetate method (Gietz et al. ). Polymerase chain reaction (PCR) for mating-type determination was done using standard Taq Polymerase (New England Biolabs). A primer at the MAT locus was used in combination with a MATα or MATa specific primers (Huxley et al. ). Genomic DNA for PCR amplification was extracted by breaking cells with glass beads using a Fast Prep homogenizer in PCI (phenol/chloroform/isoamyl-alcohol) solution according to Thompson et al. .
Diploid or tetraploid strains were sporulated as follows. First, the strains were grown in YPD medium till early stationary phase. Then the cell pellets were transferred onto a sporulation plate (1% potassium acetate, pH 6 and 1.5% agar). The plate was incubated at 23°C for 7–10 days, until most of the cells had formed tetrads. Spore isolation was done by tetrad dissection using a Sanger MSM micromanipulator (Sanger instruments, Somerset, UK).
The mating type of the diploid industrial strains was switched according to Haber . Briefly, the yeast HO gene was transiently expressed under a galactose inducible promoter by transforming the plasmid pFL39Gal1HO carrying the HPH selection marker into the strains. Transformants carrying the HO plasmid were grown overnight in YPD + hygromycin. The cells were pelleted and cell pellets were inoculated into YP + 2% galactose for 1 h at 30°C. The galactose induction was then stopped by adding 2% glucose. Afterwards, samples were taken every hour for 5 h and spread for single colonies on YPD plates. After 2 days, the colonies formed were evaluated for mating type by PCR. Colonies with the correct mating type were allowed to lose the pFL39Gal1HO plasmid by growth in liquid YPD medium without selection.
A small amount of cells from the two strains with opposite mating type, GSE16-T18- MAT α/α and strain HDY.GUF5- MAT a/a, were mixed on a YPD plate and incubated for 24 h. A sample from the mix was spread on a YPD plate for single colonies. Colonies were then evaluated for mating type by PCR. Possible hybrid strains with MAT a/α mating type were verified by flow cytometry for correct ploidy.
The DNA content was analyzed for determination of ploidy by flow cytometry according to Popolo et al. Briefly, cells were grown to exponential phase, washed with ice-cold sterile water and fixed with 70% ethanol. Ethanol-fixed cells were then treated with RNase (1 mg/ml) for 1 h to remove the RNA. The DNA was subsequently stained with propidium iodide (0.046 M) in a solution of 50 mM Tris, pH 7.7 and 15 mM MgCl 2 , at 4°C for 72 h. A FACScan instrument (Becton Dickinson) was then used to measure the fluorescence intensity in the DNA sample.
Substrate sugars and metabolites produced in the fermentations were analyzed with a Shimadzu Nexera X2 HPLC system (Shimadzu corporation) using 5 mM H 2 SO 4 as mobile phase at a flow rate of 0.65 ml/min. An ion-exchange MetaCarb 87H column (Agilent Technologies) was used to separate the compounds at 60°C and detection was done with a refractive index detector. Samples were prepared by performing twice a centrifugation at 20 000 g for 10 min, after which the supernatant was injected into the HPLC system.
We have constructed a robust yeast strain with efficient xylose utilization capacity in the presence of high concentrations of fermentation inhibitors in lignocellulose hydrolysates. For that purpose, we developed and implemented a multistep evolutionary engineering approach, consisting of the generation of tetraploid hybrid strains from 1 G and 2 G industrial strains, a two-step adaptive evolution of the tetraploid hybrid strains in xylose-rich, high-ethanol, nondetoxified pretreated biomass, selection of a superior evolved tetraploid hybrid strain, sporulation of the evolved tetraploid strain, and selection of diploid segregants with superior xylose-fermentation capacity in the presence of inhibitors. Generation of a tetraploid hybrid from a 1 G and a 2 G industrial strain In the first step, we aimed at combining the superior genetic elements of a 2 G strain GSE16-T18 and a 1 G strain Ethanol Red. GSE16-T18 was previously developed by metabolic and evolutionary engineering for rapid xylose-fermentation capacity and enhanced inhibitor tolerance (Demeke et al. , ). However, its xylose-fermentation capacity in the presence of inhibitors was still too slow and incomplete, its growth rate in glucose was significantly compromised during the evolutionary adaptation, and it flocculated during propagation and fermentation, a property that is undesirable in 2 G industrial bioethanol production (Vanmarcke et al. ). The second strain, Ethanol Red, is a rapid hexose-fermenting and temperature-tolerant industrial yeast strain with high ethanol accumulation capacity (Leaf-Lesaffre, Lille, https://leaf-lesaffre.com/ ). Ethanol Red is widely used in the starch-based ethanol production industry. In order not to lose any possibly relevant genetic information through sporulation of the industrial parent strains, we decided to generate a tetraploid hybrid strain from the two parent strains. For that purpose, we first generated mating-competent strains from each of the two diploid parent strains by switching the mating types of each strain from the original MAT a/α to either MAT α/α or MAT a/a. We then crossed GSE16-T18- MAT α/α with Ethanol Red- MAT a/a to generate tetraploid hybrid strains. Two independent tetraploid hybrid strains, named TH8 and TH9, were subsequently used for further strain development by adaptive evolution. First round of adaptive evolution Using the two equivalent hybrid strains TH8 and TH9, we started the evolutionary adaptation in xylose enriched, inhibitor-rich pretreated lignocellulose biomass, using serial batch fermentation cycles to enhance xylose-fermentation capacity in the presence of inhibitors in lignocellulosic hydrolysate. The original xylose-fermenting strain GSE16-T18 and the mating type switched counterpart GSE16-T18- MAT α/α were used for comparison, each in duplicate cultures. The xylose-enriched and inhibitor-rich pretreated biomass, named XIPB, was prepared using pretreated spruce biomass without enzymatic saccharification. The pretreated spruce biomass contained a high concentration of inhibitors including acetic acid (7 g/l), 5-hydroxymethylfurfural (HMF) (5 g/l), and furfural (3 g/l), but a low concentration of sugars (13 g/l glucose and 18 g/l xylose). XIPB was made by enriching the pretreated spruce biomass with pure xylose to reach 70 g/l. The low level of available glucose was useful for initiation of growth during the first hours of each fermentation cycle, and to avoid loss of the strain's high glucose-fermentation capacity due to unwanted mutations. The evolutionary adaptation cycles were started in 100% XIPB with the aim of exposing the cells to stressful conditions without completely inhibiting fermentation and proliferation capacity. However, after a rapid fermentation phase in the first 48 h, the fermentation rate dropped significantly in the xylose phase, probably due to the high inhibitor concentration (Fig. ). The first fermentation cycle was followed for 12 days but after 2–3 days the fermentation progressed further at a slow rate for all the cultures. After 12 days of cycle 1, the cultures were transferred to new XIPB medium diluted to 67% with YP medium to reduce the inhibitor concentration. However, none of the strains showed any fermentation even of the glucose for 72 h, probably due to complete inhibition and partial loss of viability in the first fermentation cycle. After 72 h of cycle 2, each culture was therefore diluted further to 52% using YP medium without sugar, to further reduce the inhibitor concentration and revive any cells that had maintained viability. All the cultures regained rapid fermentation capacity, albeit with different fermentation rates within 3–7 days (cycle 3). The two tetraploid hybrid strains TH8 and TH9 showed a faster fermentation rate and higher CO 2 production compared to the diploid parent strains. We then started the usual evolutionary adaptation procedure with slowly increasing stressful conditions. First, we increased the concentration of the XIPB to 80% in cycle 4. All the cultures, except one of the T18 cultures, maintained their fermentation capacity with moderate to rapid fermentation rates. When these cultures were transferred to new 80% XIPB (cycle 5), none of the cultures except TH8 and TH9 were able to ferment, even after prolonged incubation time. The fermentation capacity could not be recovered when the two cultures of the T18 strain were transferred to new 50% XIPB medium. On the other hand, the fermentation rate increased for the hybrid strains, especially for TH9 until the seventh cycle in 80% XIPB. TH8 dropped out at cycle 6 because of its slow fermentation rate and loss of fermentation capacity, while TH9 showed a consistently high fermentation rate in 80% XIPB up to cycle 10. Subsequently, the fermentation rate slightly dropped in the following two cycles. Evaluation of single colonies isolated after the sixth cycle Because of the sudden rapid increase in fermentation rate of the TH9 culture at the sixth cycle, a sample was withdrawn and spread for single colonies on a YPD agar plate to obtain possible superior isolates. We selected 63 colonies based on colony size on the YPD plate. Only large colonies were selected to avoid strains with a slow growth rate on glucose, since slow growth in glucose is a common tradeoff during adaptation for improved xylose utilization. It can result in poor propagation capacity on molasses and other substrates and in a reduced glucose-fermentation rate (Demeke et al. ). The 63 colonies were replated onto a YPX plate (YP agar containing xylose) to exclude colonies that were not growing on xylose. Nine of the 63 colonies showed growth on the YPX plate after 24 h. These nine colonies were then evaluated for fermentation rate in 80% XIPB medium in 10 ml scale. For comparison, two other colonies with poor growth in YPX plate, one of the tetraploid hybrids TH9, and the two original parent strains GSE16-T18 and Ethanol Red were included. Of the 11 single isolates tested, G610 showed an exceptionally better fermentation profile compared to the other colonies and the control parent strains (Fig. ). As expected, strain Ethanol Red utilized only the available glucose but no xylose. Its overall fermentation rate was also much slower compared to the other strains tested in XIPB. Strains GSE16-T18 and TH9 showed a better fermentation profile compared to Ethanol Red, yet xylose was also poorly utilized, as estimated from the expected CO 2 production. Two single isolates, G660 and G663, displayed similar poor fermentation profiles as Ethanol Red, with slightly faster rate at the beginning of the fermentation. These are the two poor xylose-growing colonies included in the experiment for comparison. When the fermentation was repeated for the nine xylose growing single isolates in 50 ml scale in the same medium (80% XIPB), a comparable fermentation profile was obtained as in the 10 ml scale (Fig. ). Strain G610 showed again an exceptionally better performance as observed in the 10 ml scale and produced about 87% of the expected CO 2 release upon complete sugar utilization. All other strains tested produced only about 1/3 of the expected CO 2 . We also tested the xylose-fermentation capacity of the nine xylose growing single isolates in YPX medium without any inhibitors. All the single isolates as well as the original hybrid strain TH9 showed a slower xylose-fermentation profile compared to GSE16-T18 (Fig. ). The slower xylose-fermentation rate of the original hybrid strain TH9 compared to its parent GSE16-T18 is probably due to the presence of positive recessive alleles in GSE16-T18, which are masked by negative dominant alleles of Ethanol Red. On the other hand, three evolved strains including G610 showed a better fermentation profile compared to TH9, indicating improved xylose fermentation in these three evolved strains, but not to the level of GSE16-T18. Colony G610 starts slower but overtakes TH9 in the later fermentation phase. Of the three strains performing better than the tetraploid parent strain in YPX, only G610 showed better fermentation than GSE16-T18 in pretreated biomass medium indicating improvement of inhibitor tolerance in the strain G610. Second round of adaptive evolution To further enhance xylose-fermentation capacity in the presence of inhibitors, we started a new adaptation phase using the best isolate G610, and in parallel the whole evolved culture of TH9 from the previous round at cycle 10, named G10. The culture from cycle 10 (G10) was used instead of that from cycles 11 or 12, since the cultures in these subsequent cycles showed slower and incomplete fermentation, and thus might have lost better-performing isolates (Fig. ). Duplicate cultures were used for each G610 (G610-1 and G610-2) and G10 (G10-3 and G10-4) new evolutionary adaptation cycle. In these cases, we have used glucose-depleted xylose enriched pretreated biomass, named XIPB-G, which contains xylose as the only sugar source. The glucose was depleted by growing a nonxylose consuming yeast strain for 48 h in XIPB and inactivating the yeast at 70°C for 4 h. Depletion of glucose was done because S. cerevisiae prefers glucose over xylose in medium containing a mixture of glucose and xylose (Zaldivar et al. ). As a result, new strains with high glucose-fermentation capacity could rapidly outgrow new strains with high xylose-fermentation capacity, while the latter were the main goal of the evolutionary adaptation experiment. The biomass medium concentration was slightly reduced to 75% to lower the concentration of inhibitors since xylose-fermentation is more sensitive to inhibitor stress than glucose utilization, and since there is no glucose in the medium to support initiation of the fermentation (Ask et al. , Deparis et al. ). To initiate the first cycle, the four cultures were first pregrown in YPX medium for 24 h. Fermentation was then started at 1gDW/l in 50 ml scale. Serial transfer was subsequently performed by transferring 10% of the volume to new medium when the fermentation rate started to drop. Interestingly, both cultures from the single colony isolate G610 performed much better than the mixed G10 cultures in the first fermentation cycle (Fig. ). The G610 cultures produced 1.1 g CO 2 in less than 72 h, which is about 67% of the maximum of 1.7 g CO 2 in case xylose would be completely utilized. The G10 cultures reached about the same level of CO 2 output but only after 144 h. The next three fermentation cycles also showed a more rapid fermentation and higher CO 2 production for the two G610 cultures. After five successive cycles, the concentration of XIPB-G was increased to 80%, but this caused the fermentation performance to drop significantly for all the cultures. In the very first round of the evolutionary adaptation cycles, 80% XIPB was not completely inhibitory. The absence of glucose in the XIPB-G medium used in the last round might have attributed to the poor performance despite the same 80% concentration used. Therefore, we reduced the medium concentration back to 75% for an additional five cycles (Fig. ). After about 48 h lag phase, the fermentation rate at cycle number 7 drastically increased, and more CO 2 was produced compared to the previous six cycles, reaching close to the theoretical maximum of CO 2 production in the G610-2 culture. Subsequent cycles in the same 75% XIPB-G, up to cycle 11, all show no significant lag phase. The biomass medium concentration was increased again to 80% at cycle 12. This time, the fermentation continued, though at a slower rate. The transfers were always done before the fermentation rate dropped, to avoid loss of viability. Increasing the medium concentration to 85% and then to 90% gradually reduced somewhat the fermentation rate in subsequent cycles, but did not arrest the fermentation. With successive cycles at 90% concentration, the G610-2 and G10-4 cultures stood out from the rest of the cultures starting from cycle 16. Selection of superior evolved hybrid strains At the end of the 17th cycle, we isolated 57 single colonies on YPD agar plates from the G610-2 and G10-4 cultures. Only large colonies were selected to avoid strains with poor growth in glucose. When these colonies were grown in liquid YPD medium, all except one colony were able to grow up to higher OD 600 values in 20 h, compared to the original 2 G strain GSE16-T18 (Fig. ). We next tested the fermentation performance of all 57 colonies in 90% XIPB at 10 ml scale (Fig. and ). Interestingly, all except two colonies isolated from these cultures showed better fermentation profile compared to GSE16-T18. Most colonies isolated from the G610-2 culture performed much better than the original G610 strain, the best isolate from the first round evolutionary adaptation. We selected the five best performing single isolates from the G610-2 culture, including the very best single isolate MD104, and one colony from the G10-4 culture. These were evaluated in a concentrated hydrolysate medium prepared from sugarcane bagasse. Due to the strong inhibitory nature of the medium used, only a fraction of the sugars ranging from 15% to 30%, as estimated from the CO 2 produced, was consumed by the strains even after 8 days (Fig. ). MD104 showed slightly better performance than the other strains. However, two of the single isolates, G2-14 and G2-13, started to gain a rapid fermentation rate after day 5 and day 7, respectively. We transferred these two cultures to the same concentration of biomass medium for three additional cycles to enrich for possible improved mutant strains. Only the G2-13 culture continued to ferment, while the G2-14 culture showed no further CO 2 production anymore (data no shown). Afterwards, we spread the G2-13 culture for single cell colonies and evaluated nine of these single isolates in the same concentrated sugar cane bagasse hydrolysate medium (Fig. ). Interestingly, one of the nine single isolates named MD4, showed superior performance compared to the other single isolates and to the control strains G610 and GSE16T18. Therefore, MD4 and MD104 (the best strain from the evaluation shown in Fig. ) were selected for further analysis. The two superior strains MD104 and MD4 were then evaluated in hydrolysate from sugarcane bagasse and corn cob. As expected, the evolved strains showed improved fermentation performance compared to GSE16-T18 in both types of hydrolysates (Fig. ). In sugarcane bagasse hydrolysate, the MD4 and MD104 produced 77% and 75% of the maximum theoretical ethanol yield, respectively, compared to 69% for GSE16-T18. The ethanol yield was better in corn cob hydrolysate for all the strains, which is 85%, 86%, and 81% for MD4, MD104, and GSE16-T18, respectively. Since we performed the adaptive evolution in medium with only xylose as a carbon source, the improved performance by the evolved strains was due to improved xylose utilization in the presence of inhibitors, and we noticed that the glucose-fermentation rate was unaffected. Overall, the two evolved strains showed much better fermentation performance in the lignocellulose hydrolysates tested compared to GSE16T18. Although this constitutes a significant improvement, xylose was not completely utilized in these inhibitor rich hydrolysates. Sporulation and selection of a diploid segregant from the evolved tetraploid strains Considering the slow xylose utilization rate by the original tetraploid strains compared to GSE16-T18 (Fig. ), we speculated that one or more superior recessive alleles might be responsible for the rapid xylose-fermentation rate in the diploid segregant, while being masked by one or more inferior wild type alleles in the tetraploid strain. Sporulation and selection of diploid segregants with superior performance would lead to gain of recessive alleles when the dominating inferior allele is lost during segregation. For that reason and because diploid strains are more stable than tetraploid strains, we decided to sporulate the two selected evolved strains MD104 and MD4 to screen for superior diploid segregants. MD4 showed good sporulation capacity while MD104 not. When the DNA content was measured, MD104 showed a triploid-size genome, while MD4 maintained its tetraploid size. The triploid-size genome in MD104 might have resulted from loss of chromosomes during the evolutionary adaptation cycles. Ploidy reduction even over a low number of generations has previously been shown in S. cerevisiae (Gerstein et al. ). Therefore, we continued our work with strain MD4. Initially we dissected eight tetrads from MD4 to evaluate xylose utilization performance of the segregants. From the expected 32 spores, only 10 were able to grow on a YPD plate indicating a spore viability of about 31%. When the 10 segregants were evaluated for fermentation performance in YPX medium, two segregants showed similar or better fermentation performance than MD4 and MD104, while five others showed a slower xylose-utilization rate (Fig. ). The remaining three showed a loss of xylose-fermentation capacity, at least in the first 48 h. The loss of xylose utilization capacity in these three segregants might be due to the loss of the xylose metabolism gene cassette and/or other important genetic elements during chromosome segregation. The presence of multiple copies of the XylA gene has been shown to be necessary for efficient xylose utilization (Demeke et al. ). The tetraploid strain MD4 should have multiple copies of CpXI in only one of the four chromosomes of chromosome XV. This is because one of the diploid parent strains of GSE16-T18 carried multiple copies of CpXI in tandem in one of the two alleles of chromosome XV, while the other allele had no CpXI gene copies. The second parent strain Ethanol Red has no CpXI in the genome. Therefore, the three segregants that lost xylose-fermentation capacity might have inherited the chromosome from Ethanol Red or the allele that has no CpXI from MD4. The two best segregants of MD4, named MDS2 and MDS7 were evaluated in inhibitor rich sugar cane bagasse hydrolysate. Interestingly, MDS4 showed significantly better performance in xylose-fermentation rate compared to the tetraploid parent MD4 (Fig. ). It consumed about 90% of the xylose present in the medium in less than 72 h when fermentation was started at 1gDW/l. For comparison, its parent strain MD4 consumed 79% of xylose at the end of 72 h. The range of xylose-fermentation performance in the 10 segregants tested indicates that the trait is determined by multiple genetic factors. This increases the likelihood of finding even better strains than MDS4. With that consideration, we further analyzed an additional 200 segregants of MD4. All the segregants were first screened for fermentation performance in YPX at 10 ml scale (data not shown). The best 62 segregants that showed good xylose fermentation were tested again in YPX at 50 ml scale in three different batches (Fig. ). From the 56 segregants tested, 28 segregants showed similar or better xylose-fermentation performance compared to MDS4. The best 23 among the 28 segregants were subsequently evaluated in spruce hydrolysate medium in 10 ml scale (Fig. ). Three segregants MDS96, MDS34, and MDS130 showed a better fermentation profile than MDS4. These three strains were further evaluated in sugarcane bagasse hydrolysate after propagation in YPD or molasses/hydrolysate mixture. Propagation in molasses/hydrolysate mixture was done to preadapt the strains to the hydrolysate medium. In both conditions MDS130 showed better performance compared to the other two strains (Fig. and ). Since strain MDS130 showed a consistently better xylose-fermentation profile in two different lignocellulose hydrolysates, propagated well in YPD and in molasses medium and showed no flocculation during growth or fermentation, it was selected for further evaluation. Evaluation of MDS130 in lignocellulose hydrolysate Finally, the best strain MDS130 was evaluated in corn cob hydrolysate medium. This medium was obtained from Praj industries (Pune, India) ( https://www.praj.net/ ). The hydrolysate material was prepared under industrially relevant conditions and contained high concentrations of glucose and xylose (72 g/l and 46 g/l, respectively). This is important to obtain an ethanol titer that is economically feasible for the downstream distillation process. On the other hand, the high sugar content was accompanied by a high concentration of inhibitory compounds, such as acetic acid (6 g/l), HMF (0.2 g/l), and furfural (0.2 g/l). Despite the high inhibitor content of the hydrolysate, MDS130 completely utilized all the glucose and more than 94% of the xylose in less than 48 h (Fig. ). For comparison GSE16-T18 utilized only 67% of the xylose, even at the end of 76 h. Glucose fermentation was slightly slower in MDS130, but this had no effect on the overall fermentation time. Interestingly, xylose was to some extent already coconsumed before glucose was depleted. Generally, 56 g/l ethanol was produced by MDS130, which is about 20% higher compared to that of GSE16-T18, which produced 47 g/l. The high ethanol yield (91% of the maximum theoretical yield) and overall productivity of 1.22 g/l/h at 44 h from the initial fermentable sugars by MDS130 is excellent. In contrast, GSE16-T18 produced only 81% of the maximum theoretical ethanol yield and overall ethanol productivity of 0.64 g/l/h at the end of the fermentation. The slow xylose utilization rate and low ethanol yield by GSE16-T18 is likely due to the high inhibitor content of the hydrolysate, resulting in xylose left-over at the end of the fermentation. MDS130 has acquired apparently a much higher inhibitor tolerance resulting in the near-complete utilization of xylose within 48 h.
In the first step, we aimed at combining the superior genetic elements of a 2 G strain GSE16-T18 and a 1 G strain Ethanol Red. GSE16-T18 was previously developed by metabolic and evolutionary engineering for rapid xylose-fermentation capacity and enhanced inhibitor tolerance (Demeke et al. , ). However, its xylose-fermentation capacity in the presence of inhibitors was still too slow and incomplete, its growth rate in glucose was significantly compromised during the evolutionary adaptation, and it flocculated during propagation and fermentation, a property that is undesirable in 2 G industrial bioethanol production (Vanmarcke et al. ). The second strain, Ethanol Red, is a rapid hexose-fermenting and temperature-tolerant industrial yeast strain with high ethanol accumulation capacity (Leaf-Lesaffre, Lille, https://leaf-lesaffre.com/ ). Ethanol Red is widely used in the starch-based ethanol production industry. In order not to lose any possibly relevant genetic information through sporulation of the industrial parent strains, we decided to generate a tetraploid hybrid strain from the two parent strains. For that purpose, we first generated mating-competent strains from each of the two diploid parent strains by switching the mating types of each strain from the original MAT a/α to either MAT α/α or MAT a/a. We then crossed GSE16-T18- MAT α/α with Ethanol Red- MAT a/a to generate tetraploid hybrid strains. Two independent tetraploid hybrid strains, named TH8 and TH9, were subsequently used for further strain development by adaptive evolution.
Using the two equivalent hybrid strains TH8 and TH9, we started the evolutionary adaptation in xylose enriched, inhibitor-rich pretreated lignocellulose biomass, using serial batch fermentation cycles to enhance xylose-fermentation capacity in the presence of inhibitors in lignocellulosic hydrolysate. The original xylose-fermenting strain GSE16-T18 and the mating type switched counterpart GSE16-T18- MAT α/α were used for comparison, each in duplicate cultures. The xylose-enriched and inhibitor-rich pretreated biomass, named XIPB, was prepared using pretreated spruce biomass without enzymatic saccharification. The pretreated spruce biomass contained a high concentration of inhibitors including acetic acid (7 g/l), 5-hydroxymethylfurfural (HMF) (5 g/l), and furfural (3 g/l), but a low concentration of sugars (13 g/l glucose and 18 g/l xylose). XIPB was made by enriching the pretreated spruce biomass with pure xylose to reach 70 g/l. The low level of available glucose was useful for initiation of growth during the first hours of each fermentation cycle, and to avoid loss of the strain's high glucose-fermentation capacity due to unwanted mutations. The evolutionary adaptation cycles were started in 100% XIPB with the aim of exposing the cells to stressful conditions without completely inhibiting fermentation and proliferation capacity. However, after a rapid fermentation phase in the first 48 h, the fermentation rate dropped significantly in the xylose phase, probably due to the high inhibitor concentration (Fig. ). The first fermentation cycle was followed for 12 days but after 2–3 days the fermentation progressed further at a slow rate for all the cultures. After 12 days of cycle 1, the cultures were transferred to new XIPB medium diluted to 67% with YP medium to reduce the inhibitor concentration. However, none of the strains showed any fermentation even of the glucose for 72 h, probably due to complete inhibition and partial loss of viability in the first fermentation cycle. After 72 h of cycle 2, each culture was therefore diluted further to 52% using YP medium without sugar, to further reduce the inhibitor concentration and revive any cells that had maintained viability. All the cultures regained rapid fermentation capacity, albeit with different fermentation rates within 3–7 days (cycle 3). The two tetraploid hybrid strains TH8 and TH9 showed a faster fermentation rate and higher CO 2 production compared to the diploid parent strains. We then started the usual evolutionary adaptation procedure with slowly increasing stressful conditions. First, we increased the concentration of the XIPB to 80% in cycle 4. All the cultures, except one of the T18 cultures, maintained their fermentation capacity with moderate to rapid fermentation rates. When these cultures were transferred to new 80% XIPB (cycle 5), none of the cultures except TH8 and TH9 were able to ferment, even after prolonged incubation time. The fermentation capacity could not be recovered when the two cultures of the T18 strain were transferred to new 50% XIPB medium. On the other hand, the fermentation rate increased for the hybrid strains, especially for TH9 until the seventh cycle in 80% XIPB. TH8 dropped out at cycle 6 because of its slow fermentation rate and loss of fermentation capacity, while TH9 showed a consistently high fermentation rate in 80% XIPB up to cycle 10. Subsequently, the fermentation rate slightly dropped in the following two cycles.
Because of the sudden rapid increase in fermentation rate of the TH9 culture at the sixth cycle, a sample was withdrawn and spread for single colonies on a YPD agar plate to obtain possible superior isolates. We selected 63 colonies based on colony size on the YPD plate. Only large colonies were selected to avoid strains with a slow growth rate on glucose, since slow growth in glucose is a common tradeoff during adaptation for improved xylose utilization. It can result in poor propagation capacity on molasses and other substrates and in a reduced glucose-fermentation rate (Demeke et al. ). The 63 colonies were replated onto a YPX plate (YP agar containing xylose) to exclude colonies that were not growing on xylose. Nine of the 63 colonies showed growth on the YPX plate after 24 h. These nine colonies were then evaluated for fermentation rate in 80% XIPB medium in 10 ml scale. For comparison, two other colonies with poor growth in YPX plate, one of the tetraploid hybrids TH9, and the two original parent strains GSE16-T18 and Ethanol Red were included. Of the 11 single isolates tested, G610 showed an exceptionally better fermentation profile compared to the other colonies and the control parent strains (Fig. ). As expected, strain Ethanol Red utilized only the available glucose but no xylose. Its overall fermentation rate was also much slower compared to the other strains tested in XIPB. Strains GSE16-T18 and TH9 showed a better fermentation profile compared to Ethanol Red, yet xylose was also poorly utilized, as estimated from the expected CO 2 production. Two single isolates, G660 and G663, displayed similar poor fermentation profiles as Ethanol Red, with slightly faster rate at the beginning of the fermentation. These are the two poor xylose-growing colonies included in the experiment for comparison. When the fermentation was repeated for the nine xylose growing single isolates in 50 ml scale in the same medium (80% XIPB), a comparable fermentation profile was obtained as in the 10 ml scale (Fig. ). Strain G610 showed again an exceptionally better performance as observed in the 10 ml scale and produced about 87% of the expected CO 2 release upon complete sugar utilization. All other strains tested produced only about 1/3 of the expected CO 2 . We also tested the xylose-fermentation capacity of the nine xylose growing single isolates in YPX medium without any inhibitors. All the single isolates as well as the original hybrid strain TH9 showed a slower xylose-fermentation profile compared to GSE16-T18 (Fig. ). The slower xylose-fermentation rate of the original hybrid strain TH9 compared to its parent GSE16-T18 is probably due to the presence of positive recessive alleles in GSE16-T18, which are masked by negative dominant alleles of Ethanol Red. On the other hand, three evolved strains including G610 showed a better fermentation profile compared to TH9, indicating improved xylose fermentation in these three evolved strains, but not to the level of GSE16-T18. Colony G610 starts slower but overtakes TH9 in the later fermentation phase. Of the three strains performing better than the tetraploid parent strain in YPX, only G610 showed better fermentation than GSE16-T18 in pretreated biomass medium indicating improvement of inhibitor tolerance in the strain G610.
To further enhance xylose-fermentation capacity in the presence of inhibitors, we started a new adaptation phase using the best isolate G610, and in parallel the whole evolved culture of TH9 from the previous round at cycle 10, named G10. The culture from cycle 10 (G10) was used instead of that from cycles 11 or 12, since the cultures in these subsequent cycles showed slower and incomplete fermentation, and thus might have lost better-performing isolates (Fig. ). Duplicate cultures were used for each G610 (G610-1 and G610-2) and G10 (G10-3 and G10-4) new evolutionary adaptation cycle. In these cases, we have used glucose-depleted xylose enriched pretreated biomass, named XIPB-G, which contains xylose as the only sugar source. The glucose was depleted by growing a nonxylose consuming yeast strain for 48 h in XIPB and inactivating the yeast at 70°C for 4 h. Depletion of glucose was done because S. cerevisiae prefers glucose over xylose in medium containing a mixture of glucose and xylose (Zaldivar et al. ). As a result, new strains with high glucose-fermentation capacity could rapidly outgrow new strains with high xylose-fermentation capacity, while the latter were the main goal of the evolutionary adaptation experiment. The biomass medium concentration was slightly reduced to 75% to lower the concentration of inhibitors since xylose-fermentation is more sensitive to inhibitor stress than glucose utilization, and since there is no glucose in the medium to support initiation of the fermentation (Ask et al. , Deparis et al. ). To initiate the first cycle, the four cultures were first pregrown in YPX medium for 24 h. Fermentation was then started at 1gDW/l in 50 ml scale. Serial transfer was subsequently performed by transferring 10% of the volume to new medium when the fermentation rate started to drop. Interestingly, both cultures from the single colony isolate G610 performed much better than the mixed G10 cultures in the first fermentation cycle (Fig. ). The G610 cultures produced 1.1 g CO 2 in less than 72 h, which is about 67% of the maximum of 1.7 g CO 2 in case xylose would be completely utilized. The G10 cultures reached about the same level of CO 2 output but only after 144 h. The next three fermentation cycles also showed a more rapid fermentation and higher CO 2 production for the two G610 cultures. After five successive cycles, the concentration of XIPB-G was increased to 80%, but this caused the fermentation performance to drop significantly for all the cultures. In the very first round of the evolutionary adaptation cycles, 80% XIPB was not completely inhibitory. The absence of glucose in the XIPB-G medium used in the last round might have attributed to the poor performance despite the same 80% concentration used. Therefore, we reduced the medium concentration back to 75% for an additional five cycles (Fig. ). After about 48 h lag phase, the fermentation rate at cycle number 7 drastically increased, and more CO 2 was produced compared to the previous six cycles, reaching close to the theoretical maximum of CO 2 production in the G610-2 culture. Subsequent cycles in the same 75% XIPB-G, up to cycle 11, all show no significant lag phase. The biomass medium concentration was increased again to 80% at cycle 12. This time, the fermentation continued, though at a slower rate. The transfers were always done before the fermentation rate dropped, to avoid loss of viability. Increasing the medium concentration to 85% and then to 90% gradually reduced somewhat the fermentation rate in subsequent cycles, but did not arrest the fermentation. With successive cycles at 90% concentration, the G610-2 and G10-4 cultures stood out from the rest of the cultures starting from cycle 16.
At the end of the 17th cycle, we isolated 57 single colonies on YPD agar plates from the G610-2 and G10-4 cultures. Only large colonies were selected to avoid strains with poor growth in glucose. When these colonies were grown in liquid YPD medium, all except one colony were able to grow up to higher OD 600 values in 20 h, compared to the original 2 G strain GSE16-T18 (Fig. ). We next tested the fermentation performance of all 57 colonies in 90% XIPB at 10 ml scale (Fig. and ). Interestingly, all except two colonies isolated from these cultures showed better fermentation profile compared to GSE16-T18. Most colonies isolated from the G610-2 culture performed much better than the original G610 strain, the best isolate from the first round evolutionary adaptation. We selected the five best performing single isolates from the G610-2 culture, including the very best single isolate MD104, and one colony from the G10-4 culture. These were evaluated in a concentrated hydrolysate medium prepared from sugarcane bagasse. Due to the strong inhibitory nature of the medium used, only a fraction of the sugars ranging from 15% to 30%, as estimated from the CO 2 produced, was consumed by the strains even after 8 days (Fig. ). MD104 showed slightly better performance than the other strains. However, two of the single isolates, G2-14 and G2-13, started to gain a rapid fermentation rate after day 5 and day 7, respectively. We transferred these two cultures to the same concentration of biomass medium for three additional cycles to enrich for possible improved mutant strains. Only the G2-13 culture continued to ferment, while the G2-14 culture showed no further CO 2 production anymore (data no shown). Afterwards, we spread the G2-13 culture for single cell colonies and evaluated nine of these single isolates in the same concentrated sugar cane bagasse hydrolysate medium (Fig. ). Interestingly, one of the nine single isolates named MD4, showed superior performance compared to the other single isolates and to the control strains G610 and GSE16T18. Therefore, MD4 and MD104 (the best strain from the evaluation shown in Fig. ) were selected for further analysis. The two superior strains MD104 and MD4 were then evaluated in hydrolysate from sugarcane bagasse and corn cob. As expected, the evolved strains showed improved fermentation performance compared to GSE16-T18 in both types of hydrolysates (Fig. ). In sugarcane bagasse hydrolysate, the MD4 and MD104 produced 77% and 75% of the maximum theoretical ethanol yield, respectively, compared to 69% for GSE16-T18. The ethanol yield was better in corn cob hydrolysate for all the strains, which is 85%, 86%, and 81% for MD4, MD104, and GSE16-T18, respectively. Since we performed the adaptive evolution in medium with only xylose as a carbon source, the improved performance by the evolved strains was due to improved xylose utilization in the presence of inhibitors, and we noticed that the glucose-fermentation rate was unaffected. Overall, the two evolved strains showed much better fermentation performance in the lignocellulose hydrolysates tested compared to GSE16T18. Although this constitutes a significant improvement, xylose was not completely utilized in these inhibitor rich hydrolysates.
Considering the slow xylose utilization rate by the original tetraploid strains compared to GSE16-T18 (Fig. ), we speculated that one or more superior recessive alleles might be responsible for the rapid xylose-fermentation rate in the diploid segregant, while being masked by one or more inferior wild type alleles in the tetraploid strain. Sporulation and selection of diploid segregants with superior performance would lead to gain of recessive alleles when the dominating inferior allele is lost during segregation. For that reason and because diploid strains are more stable than tetraploid strains, we decided to sporulate the two selected evolved strains MD104 and MD4 to screen for superior diploid segregants. MD4 showed good sporulation capacity while MD104 not. When the DNA content was measured, MD104 showed a triploid-size genome, while MD4 maintained its tetraploid size. The triploid-size genome in MD104 might have resulted from loss of chromosomes during the evolutionary adaptation cycles. Ploidy reduction even over a low number of generations has previously been shown in S. cerevisiae (Gerstein et al. ). Therefore, we continued our work with strain MD4. Initially we dissected eight tetrads from MD4 to evaluate xylose utilization performance of the segregants. From the expected 32 spores, only 10 were able to grow on a YPD plate indicating a spore viability of about 31%. When the 10 segregants were evaluated for fermentation performance in YPX medium, two segregants showed similar or better fermentation performance than MD4 and MD104, while five others showed a slower xylose-utilization rate (Fig. ). The remaining three showed a loss of xylose-fermentation capacity, at least in the first 48 h. The loss of xylose utilization capacity in these three segregants might be due to the loss of the xylose metabolism gene cassette and/or other important genetic elements during chromosome segregation. The presence of multiple copies of the XylA gene has been shown to be necessary for efficient xylose utilization (Demeke et al. ). The tetraploid strain MD4 should have multiple copies of CpXI in only one of the four chromosomes of chromosome XV. This is because one of the diploid parent strains of GSE16-T18 carried multiple copies of CpXI in tandem in one of the two alleles of chromosome XV, while the other allele had no CpXI gene copies. The second parent strain Ethanol Red has no CpXI in the genome. Therefore, the three segregants that lost xylose-fermentation capacity might have inherited the chromosome from Ethanol Red or the allele that has no CpXI from MD4. The two best segregants of MD4, named MDS2 and MDS7 were evaluated in inhibitor rich sugar cane bagasse hydrolysate. Interestingly, MDS4 showed significantly better performance in xylose-fermentation rate compared to the tetraploid parent MD4 (Fig. ). It consumed about 90% of the xylose present in the medium in less than 72 h when fermentation was started at 1gDW/l. For comparison, its parent strain MD4 consumed 79% of xylose at the end of 72 h. The range of xylose-fermentation performance in the 10 segregants tested indicates that the trait is determined by multiple genetic factors. This increases the likelihood of finding even better strains than MDS4. With that consideration, we further analyzed an additional 200 segregants of MD4. All the segregants were first screened for fermentation performance in YPX at 10 ml scale (data not shown). The best 62 segregants that showed good xylose fermentation were tested again in YPX at 50 ml scale in three different batches (Fig. ). From the 56 segregants tested, 28 segregants showed similar or better xylose-fermentation performance compared to MDS4. The best 23 among the 28 segregants were subsequently evaluated in spruce hydrolysate medium in 10 ml scale (Fig. ). Three segregants MDS96, MDS34, and MDS130 showed a better fermentation profile than MDS4. These three strains were further evaluated in sugarcane bagasse hydrolysate after propagation in YPD or molasses/hydrolysate mixture. Propagation in molasses/hydrolysate mixture was done to preadapt the strains to the hydrolysate medium. In both conditions MDS130 showed better performance compared to the other two strains (Fig. and ). Since strain MDS130 showed a consistently better xylose-fermentation profile in two different lignocellulose hydrolysates, propagated well in YPD and in molasses medium and showed no flocculation during growth or fermentation, it was selected for further evaluation.
Finally, the best strain MDS130 was evaluated in corn cob hydrolysate medium. This medium was obtained from Praj industries (Pune, India) ( https://www.praj.net/ ). The hydrolysate material was prepared under industrially relevant conditions and contained high concentrations of glucose and xylose (72 g/l and 46 g/l, respectively). This is important to obtain an ethanol titer that is economically feasible for the downstream distillation process. On the other hand, the high sugar content was accompanied by a high concentration of inhibitory compounds, such as acetic acid (6 g/l), HMF (0.2 g/l), and furfural (0.2 g/l). Despite the high inhibitor content of the hydrolysate, MDS130 completely utilized all the glucose and more than 94% of the xylose in less than 48 h (Fig. ). For comparison GSE16-T18 utilized only 67% of the xylose, even at the end of 76 h. Glucose fermentation was slightly slower in MDS130, but this had no effect on the overall fermentation time. Interestingly, xylose was to some extent already coconsumed before glucose was depleted. Generally, 56 g/l ethanol was produced by MDS130, which is about 20% higher compared to that of GSE16-T18, which produced 47 g/l. The high ethanol yield (91% of the maximum theoretical yield) and overall productivity of 1.22 g/l/h at 44 h from the initial fermentable sugars by MDS130 is excellent. In contrast, GSE16-T18 produced only 81% of the maximum theoretical ethanol yield and overall ethanol productivity of 0.64 g/l/h at the end of the fermentation. The slow xylose utilization rate and low ethanol yield by GSE16-T18 is likely due to the high inhibitor content of the hydrolysate, resulting in xylose left-over at the end of the fermentation. MDS130 has acquired apparently a much higher inhibitor tolerance resulting in the near-complete utilization of xylose within 48 h.
Impressive progress has been achieved in the past decades for the development of superior S. cerevisiae strains with very good xylose-fermentation capacity. However, strains that show rapid and complete xylose utilization in synthetic medium were found to have much slower and incomplete xylose utilization in lignocellulose hydrolysates (Demeke et al. , Li et al. , Costa et al. ). Though glucose utilization is not severely affected in lignocellulose hydrolysate fermentations, xylose utilization is hindered even at lower inhibitor concentrations. This could be due to the fact that xylose is not a natural substrate for S. cerevisiae , with its metabolism as a result not being well-integrated into the regulatory network of cellular metabolism, such as the response to stressful conditions (Deparis et al. ). The slow and incomplete xylose utilization observed when the strains are used in fermentations of concentrated undetoxified lignocellulose hydrolysates, which are notoriously rich in fermentation inhibitors, has forced the industry to introduce a costly washing step or to use more diluted hydrolysate to reduce the inhibitor concentration. However, cost competitive lignocellulose based ethanol production requires the use of concentrated hydrolysates to achieve a minimum ethanol concentration of at least 4% v/v (Palmqvist Eva , Koppram et al. ). In this work, we have developed using a novel evolutionary engineering method an industrial yeast strain able to efficiently utilize xylose in nondetoxified concentrated lignocellulose hydrolysates. We have employed an evolutionary engineering approach that combined the superior industrial properties of a robust 1 G strain, Ethanol Red, and a 2 G strain GSE16-T18. We used a tetraploid hybrid, rather than a regular diploid hybrid strain generated from two haploid derivative strains, in the adaptive evolution cycles for two main reasons. First, to obtain a diploid hybrid strain, one must isolate haploid segregants from each diploid parent strain with the same industrial trait as the diploid parent. Isolation of haploid segregants carrying all the superior properties of its diploid parent strain is cumbersome and sometimes impossible (Kim et al. ). Instead, by using a tetraploid hybrid, we maintain all the genetic factors of both parent strains that determine important industrial traits. In our case, the main industrial traits are the rapid xylose-fermentation capacity and good inhibitor tolerance of the 2 G strain GSE16-T18, and the very good propagation capacity, high temperature tolerance and absent flocculation of the 1 G strain Ethanol Red. Second, considering a limited rate of random mutations for a certain genome size per generation, we anticipated that tetraploid strains that carry double the genome of diploid strains generate more mutations per generation than diploid strains during adaptive evolution (Selmecki et al. ). This would facilitate the generation of beneficial mutations that could be selected with the applied selective pressure. Indeed, all four cultures containing diploid strains dropped out due to the loss of fermentation capacity in the first five cycles of the adaptive evolution step. One of the two tetraploid hybrids maintained higher fermentation capacity, probably due to the rapid generation of mutants able to tolerate the high level of inhibitors. However, the better performance by the tetraploid hybrid strains could also be due to their inherent genetic fitness since they carry all genetic elements coming from each diploid parent. Acid pretreated spruce material is among the most inhibitory lignocellulose material. It contains high concentrations of acetic acid, HMF and furfural (Demeke et al. , Vanmarcke et al. ). We used a spruce hydrolysate with a high concentration of inhibitors for the adaptive evolution steps. Improvement of inhibitor tolerance to this high concentration of inhibitors should in principle also result in better performance in other relatively less inhibitory hydrolysates. As expected, the best isolate MDS130 showed significant improvement in spruce hydrolysate as well as in two other hydrolysates originating from sugar cane bagasse and corn cob. Adaptive evolution in inhibitor-rich hydrolysate has been used previously to improve fermentation performance of 2 G yeast strains. Nevertheless, enhanced fermentation is often associated with improved glucose utilization, while xylose utilization usually shows much less or even no improvement at all (Zhu et al. , Liu 2017 et al. ). This is probably because most hydrolysate media contain much more glucose than xylose, and S. cerevisiae prefers glucose over xylose (Zaldivar et al. ). The yeast’s innate preference for glucose would therefore hamper xylose metabolism and its adaptation in the presence of inhibitors. For that reason, improvement of xylose utilization in inhibitor-rich hydrolysates was found to be difficult (Liu et al. ). To address this problem, we have first used xylose-enriched hydrolysate and second, hydrolysate in which all glucose was converted with a regular yeast strain into ethanol. In the first hydrolysate, the yeast had to improve its xylose-utilization capacity in the inhibitor-rich hydrolysate to proliferate faster. The same was true in the second hydrolysate, which however, had the additional challenge of the presence of high ethanol, which exacerbates the toxicity of the lignocellulose-derived inhibitors. Encouraging results have been obtained with rational metabolic engineering for improvement of inhibitor tolerance in 2 G yeast strains. However, similar to the results with evolutionary engineering approaches, the inhibitor tolerance was often only improved for glucose utilization while xylose-fermentation capacity was sometimes even reduced (Wallace-Salinas et al. , Jayakody et al. , Brandt et al. ). Targeted genetic modifications to improve inhibitor tolerance possibly only work well for glucose utilization because the genetic factors were originally also identified for fermentation in glucose medium. In that sense, evolutionary engineering for improved xylose utilization and inhibitor tolerance in the absence of glucose, and especially in the presence of high ethanol, is an interesting alternative. In our study, we performed the evolutionary adaptation in glucose-depleted and xylose-enriched hydrolysate to facilitate development of inhibitor tolerance of xylose fermentation by overcoming the effect of glucose repression on xylose utilization. In the first-round adaptation, there was still a small amount of glucose in the medium to help initiate growth. Once the strains were adapted to the presence of the inhibitors, the second-round adaptive evolution was subsequently done using the best isolate from the first round in glucose-depleted medium in the presence of only xylose as a carbon source and also high ethanol. As a result of the two consecutive approaches, significant improvement in the xylose-fermentation rate was observed over the course of the adaptive evolution cycles, indicating improvement of xylose-fermentation tolerance to higher concentrations of inhibitors. This was clearly demonstrated by the significant improvement of the xylose-utilization rate in the presence of inhibitors by one of the evolved single cell isolates, MD4, compared to GSE16-T18, without much difference in the glucose utilization rate (Fig. ). Unraveling the genetic modifications responsible for the simultaneous improvement of xylose fermentation and inhibitor tolerance could reveal targets for further improvement by targeted metabolic engineering, though that is beyond the scope of this work. Simultaneous improvement of xylose fermentation and inhibitor tolerance has been achieved previously in lignocellulose hydrolysates (Smith et al. ) and also specifically to weak acid and high temperature (Inokuma et al. ). While those studies used chemical or physical mutagenesis to create population diversity, no mutagenesis step was used in our study to avoid negative effects by background mutations. Reduced growth rate, for instance, was manifested in previous studies (Demeke et al. , Smith et al. ). Instead, adaptive evolution of tetraploid hybrid strains followed by sporulation, generated a very diverse population of diploid strains carrying different combinations of genetic elements from the two parent strains as well as new combinations of mutations generated during the adaptive evolution. The evolved tetraploid strain MD4 itself showed significant improvement in xylose fermentation in corn cob and sugarcane bagasse hydrolysates (Fig. ). However, xylose fermentation by MD4 was not complete, even after 90 h of fermentation. Since generation of heterozygous mutations is more common during evolutionary adaptation than generation of homozygous mutations (Sellis et al. ), we envisaged that the effect of recessive mutations masked by the wild type allele could be manifested when the wild type allele was lost during subsequent chromosome segregation. This could further improve the xylose-fermentation performance and inhibitor tolerance upon selection for these traits. Additionally, genetically diverse diploid populations of strains could be generated by sporulation, and with an efficient selection step, further improved superior strains could be obtained. Indeed, after sporulation and screening of more than 200 segregants in inhibitor-rich hydrolysate, several diploid strains showed better fermentation performance in lignocellulose hydrolysates (Figs and ). The best diploid isolate, MDS130, showed a stable superior fermentation profile in three different lignocellulose hydrolysates. MDS130 showed very good xylose utilization in nondetoxified, concentrated lignocellulose hydrolysates. The very high ethanol yield of 91% in such very inhibitory medium appears to be unprecedented. The ethanol yield by the control strain GSE16-T18 was 81%, which is comparable to that of most engineered 2 G strains in previous reports (Jansen et al. ). Additionally, the almost complete xylose utilization by MDS130 within 48 h resulting in an ethanol titer of 5.6% w/v (about 7% v/v) in such highly challenging lignocellulose hydrolysates is unprecedented and might already meet industrial requirements. Nonetheless, compared to glucose utilization, xylose utilization is still much slower resulting in a prolonged overall fermentation time. Hence, further improvement of the xylose utilization rate in the presence of inhibitors would further reduce the overall fermentation time to make industrial 2 G ethanol production more economically feasible. The fermentation temperature employed in this study was 35°C, which is higher than the regular 30°C–32°C fermentation temperatures for S. cerevisiae . Though 35°C is optimum for the first generation strain Ethanol Red, fermentation of lignocellulosic material is sensitive to higher temperatures (Zhu et al. ). We used 35°C during the evolutionary adaptation, which resulted in superior performance by MDS130 at this temperature. We chose 35°C for two main reasons. First, higher temperature is more relevant for the simultaneous saccharification and fermentation (SSF) process (Mutturi and Lidén ). SSF is an interesting process option for bioethanol production that uses enzymatic hydrolysis together with fermentation. It is preferred for higher product yield and requires less investment. Though SSF is not yet fully practical, partial saccharification could be possible during fermentation even in a separate hydrolysis and fermentation process, when the enzymes used at the saccharification step are not inactivated. In that respect, fermentation at higher temperature will have an advantage because it is closer to the optimum saccharification temperature. On top of that, fermentation at higher temperature reduces the cost of cooling fermentation tanks (Prado et al. ). In conclusion, we have developed a robust industrial strain MDS130, that can completely utilize xylose in undetoxified lignocellulose hydrolysate with high ethanol yield and titer. To achieve this, we devised a new evolutionary engineering method that allows to combine and select the superior industrial properties from two diploid industrial strains into a single diploid strain, and also resulted in more rapid evolution without external mutagenesis step. The method can be applied for development of industrial strains with selectable traits without introducing chemical or physical mutagenesis steps, which are known to frequently introduce undesired genetic changes. MDS130 is a promising strain for direct industrial application of cellulosic ethanol production.
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Oral health in patients with cleft lip and palate: a systematic literature review and meta-analysis of periodontal and dental disease and oral microbiota (part 1) | c9e5e988-9e53-4f9e-ab48-14e49bb58f21 | 11776186 | Dentistry[mh] | Rationale Orofacial cleft, the most common congenital malformation in humans, results from disruption of growth and fusion of the frontonasal and the maxillary processes . Its incidence is one in every 700 live births . Its etiology is unclear but is thought to be the final outcome of complex events involving environmental and genetic factors . Malformation can manifest with cleft lip and/or cleft palate and can be unilateral or bilateral; it can be isolated or part of a clinical syndrome (e.g., Pierre Robin syndrome, George syndrome, Treacher Collins syndrome) . Orofacial cleft impacts the development and functionality of the jaw and the teeth, with serious implications for oral health. Optimal oral hygiene can be difficult to maintain due to anatomical defects associated with the cleft itself or alterations following surgery and orthodontic treatment, prosthetic implantation, postsurgical complications, e.g., oronasal fistula and/or residual scar tissue, and dental anomalies . Such alterations of the oral cavity can promote colonization by microbial strains seldom found in healthy individuals and can disturb the homeostatic equilibrium between microorganisms and host . Dysbiosis of the oral microbiota raises the risk for local infection besides the development of dental caries, periodontal disease , candidiasis, oral cancer , and airway disease, such as sinusitis and bronchiolitis . Scope and Objectives For this two-part systematic review and meta-analysis of the literature we reviewed studies on oral health in persons with cleft lip or palate. All types of cleft lip and palate were included in the review (cleft lip, cleft palate, cleft lip and palate with/without cleft alveolo, unilateral/bilateral clefts and other types). The research was not limited to a specific age group or the presence of any syndromes or surgical/orthodontic status. However, in cases where this information was not specified within the study, attempts were made to contact the authors to possibly carry out more specific analyses. Studies concerning oral health in patients with cleft lip and plate were selected, for which the following data were described: Quantitative data on caries experience in deciduous, mixed and permanent dentition (dmft, DMFT, dmfs, DMFS) Quantitative data on periodontal parameters (plaque indices, gingival inflammation indices, probing depth index, clinical attachment level index) Quantitative and/or qualitative data on the microbiota (bacteria, fungi). The study objectives were to: Analyze the oral microflora of persons with cleft lip or palate and compare periodontal clinical parameters between persons with cleft lip or palate and healthy controls (Part 1). Compare differences in the prevalence of caries in deciduous, mixed, and permanent teeth between persons with cleft lip and palate and healthy controls as measured with epidemiological indices of caries; compare caries rating between different kinds of orofacial cleft (Part 2, upcoming manuscript). Orofacial cleft, the most common congenital malformation in humans, results from disruption of growth and fusion of the frontonasal and the maxillary processes . Its incidence is one in every 700 live births . Its etiology is unclear but is thought to be the final outcome of complex events involving environmental and genetic factors . Malformation can manifest with cleft lip and/or cleft palate and can be unilateral or bilateral; it can be isolated or part of a clinical syndrome (e.g., Pierre Robin syndrome, George syndrome, Treacher Collins syndrome) . Orofacial cleft impacts the development and functionality of the jaw and the teeth, with serious implications for oral health. Optimal oral hygiene can be difficult to maintain due to anatomical defects associated with the cleft itself or alterations following surgery and orthodontic treatment, prosthetic implantation, postsurgical complications, e.g., oronasal fistula and/or residual scar tissue, and dental anomalies . Such alterations of the oral cavity can promote colonization by microbial strains seldom found in healthy individuals and can disturb the homeostatic equilibrium between microorganisms and host . Dysbiosis of the oral microbiota raises the risk for local infection besides the development of dental caries, periodontal disease , candidiasis, oral cancer , and airway disease, such as sinusitis and bronchiolitis . For this two-part systematic review and meta-analysis of the literature we reviewed studies on oral health in persons with cleft lip or palate. All types of cleft lip and palate were included in the review (cleft lip, cleft palate, cleft lip and palate with/without cleft alveolo, unilateral/bilateral clefts and other types). The research was not limited to a specific age group or the presence of any syndromes or surgical/orthodontic status. However, in cases where this information was not specified within the study, attempts were made to contact the authors to possibly carry out more specific analyses. Studies concerning oral health in patients with cleft lip and plate were selected, for which the following data were described: Quantitative data on caries experience in deciduous, mixed and permanent dentition (dmft, DMFT, dmfs, DMFS) Quantitative data on periodontal parameters (plaque indices, gingival inflammation indices, probing depth index, clinical attachment level index) Quantitative and/or qualitative data on the microbiota (bacteria, fungi). The study objectives were to: Analyze the oral microflora of persons with cleft lip or palate and compare periodontal clinical parameters between persons with cleft lip or palate and healthy controls (Part 1). Compare differences in the prevalence of caries in deciduous, mixed, and permanent teeth between persons with cleft lip and palate and healthy controls as measured with epidemiological indices of caries; compare caries rating between different kinds of orofacial cleft (Part 2, upcoming manuscript). Inclusion Criteria Inclusion criteria were: full-text articles published in English involving human subjects, diagnosis of cleft lip or palate, description of oral health factors; quantitative data on dental caries in deciduous, mixed, and permanent teeth expressed as: DMFT (decayed, missing, filled teeth) and DMFS (decayed, missing, filled surfaces); quantitative data on periodontal parameters: plaque index, index of gum inflammation, index of depth of periodontal sounding, loss of clinical attachment level; quantitative or qualitative data on oral microbiota. Exclusion criteria were: full text unavailable, publication in a language other than English, samples involving animals or in vitro, samples involving only subjects with apparatus for nasoalveolar molding, subjects undergoing presurgical orthopedic treatment, prosthesis wearers; case reports, letters, editorials, interviews, systemic reviews and meta-analysis of the literature. Information sources and search strategy Four electronic databases were searched: PubMed, Scopus, Web of Science, Cochrane Library. The search was conducted during the time interval from March 2023 to January 2024. The following terms were used for the search strings: “cleft lip,” "cleft palate,” "oral microbiology,” "oral colonization,” " Candida albicans ,” "DMFT,” "dental caries,” "plaque index,” "dental plaque,” "gingival index,” "bleeding on probing,” "gingivitis,” "periodontal disease,” "periodontal index.”. The Boolean operators “AND” and “OR” were used to connect the terms to limit the search and make it more efficient. For all databases the following string was used: “Cleft lip" OR "Cleft palate" AND "Oral microbiology" OR "Oral colonization" OR "Candida Albicans" OR "DMFT" OR "dental caries" OR "plaque index" OR "Dental plaque" OR "gingival Index” OR "Bleeding on probing" OR "gingivitis" OR "periodontal disease" OR "periodontal index". Studies that may have been initially missed were manually searched. For the present review, all types of labiopalatoschisis were included (labioschisis, palatoschisis, labiopalatoschisis with or without alveolar schisis, unilateral and bilateral schisis, and other types). The study was not limited to any specific age group, symptoms, or surgical/orthodontic state. Screening, selection and data collection The screening and selection of studies were performed by two independent operators Two (AP, VV), and included: the removal of duplicates, the elimination of not accessible articles, manuscripts published in languages other than English. The titles and abstracts assessed as suitable from the records obtained were analyzed, excluding those not in line to the inclusion criteria. The full text of medical and/or orthodontic studies considered as relevant from the previous steps was read to assess their final inclusion in the review. In case of disagreement between the two reviewers, a third party (FL) intervened in the decision-making process. Data collection from the included reports was performed by the same first two reviewers (AP, AS), who independently worked on an Excel spreadsheet to identify parameters referring to general article information (title, author, year of publication, journal, volume, and pages), study design, the population included, type of intervention, control used, and outcomes. No data extraction software was used. Data parameters According to the objectives, primary outcomes assessed in the studies were: the following periodontal indices: Plaque Index (PI), Plaque Index Score (PIS), Visible Plaque Index (VPI), Quigley-Hein Index (QHI), Gingival Index (GI), Bleeding Index (BI), Bleeding on Probing (BoP) Probing Pocket Depth (PPD) and Clinical Attachment Level (CAL); the following caries indices: decayed missing filling teeth (dmft), decayed missing filled surfaces (dmfs), DECAYED MISSING FILLED TEETH (DMFT) and DECAYED MISSING FILLED SURFACES (DMFS). Secondary outcomes concerned the analysis of the oral microbiota, to compare the main microorganisms between patients with schisis and healthy controls. Risk of bias assessment Two reviewers independently applied the Newcastle-Ottawa scale (NOS) and the Joanna Briggs Institute (JBI) checklist to determine and classify study quality. Disagreement was resolved by discussion. The Newcastle-Ottawa scale (NOS) is a tool for assessing the quality of non-randomized studies. The evaluation includes questions on three domains: selection of study groups, comparability of groups, assessment of exposure or outcome of interest. Each question, based on the answers, can be assigned one star (with a maximum of 4 stars for selection, with a maximum of two stars for comparability, with a maximum of three stars for the result). The quality of a study is calculated based on the sum of the stars for a maximum of 9 stars. Higher scores indicate lower risk of bias. Studies are considered of high quality when the overall score is >=7, they are considered of moderate quality when the score is between 4 and 6, and they are considered of low quality when the score is <=3. The Joanna Briggs Institute (JBI) is a tool used for cross-sectional, case-control and cohort studies, with a collection of different questions focused on the appropriateness of the statistical analysis used (Y yes, N no, UC unclear). Effect measures Continuous outcomes were identified for the meta-analysis. The number of samples, mean, and standard deviation were defined for each outcome. Statistical analysis Statistical analysis was conducted on studies with comparable outcomes, while microbiological analysis was not included in the meta-analysis because data comparison would have been practically impossible. Statistical analysis of periodontal parameters and caries indices was performed. Review Manager Web software (Cochrane Collaboration) was used for analyzing the quantitative data. Meta-analysis was performed using a fixed-effects model, inverse-variance method, average differences, or standardized average differences according to the studies and parameters. A 95% confidence interval was calculated for the primary results. Finally, forest plots were created and heterogeneity and overall effect tests were performed. Subgroup analysis explored the causes of statistical heterogeneity and to differentiate studies involving different age groups. Method to quantify statistical heterogeneity was I 2 . Certainty assessment The assessment of confidence was conducted using GRADEpro Guideline Development Tool (GDT). The two reviewers evaluated the level of confidence in the evidence based on the following factors: risk of bias, inconsistency, indirectness, imprecision, publication bias, large effect, plausible confounding, and dose-response gradient. In the event of a disagreement between the two reviewers, additional discussion was used to reach a consensus. Inclusion criteria were: full-text articles published in English involving human subjects, diagnosis of cleft lip or palate, description of oral health factors; quantitative data on dental caries in deciduous, mixed, and permanent teeth expressed as: DMFT (decayed, missing, filled teeth) and DMFS (decayed, missing, filled surfaces); quantitative data on periodontal parameters: plaque index, index of gum inflammation, index of depth of periodontal sounding, loss of clinical attachment level; quantitative or qualitative data on oral microbiota. Exclusion criteria were: full text unavailable, publication in a language other than English, samples involving animals or in vitro, samples involving only subjects with apparatus for nasoalveolar molding, subjects undergoing presurgical orthopedic treatment, prosthesis wearers; case reports, letters, editorials, interviews, systemic reviews and meta-analysis of the literature. Four electronic databases were searched: PubMed, Scopus, Web of Science, Cochrane Library. The search was conducted during the time interval from March 2023 to January 2024. The following terms were used for the search strings: “cleft lip,” "cleft palate,” "oral microbiology,” "oral colonization,” " Candida albicans ,” "DMFT,” "dental caries,” "plaque index,” "dental plaque,” "gingival index,” "bleeding on probing,” "gingivitis,” "periodontal disease,” "periodontal index.”. The Boolean operators “AND” and “OR” were used to connect the terms to limit the search and make it more efficient. For all databases the following string was used: “Cleft lip" OR "Cleft palate" AND "Oral microbiology" OR "Oral colonization" OR "Candida Albicans" OR "DMFT" OR "dental caries" OR "plaque index" OR "Dental plaque" OR "gingival Index” OR "Bleeding on probing" OR "gingivitis" OR "periodontal disease" OR "periodontal index". Studies that may have been initially missed were manually searched. For the present review, all types of labiopalatoschisis were included (labioschisis, palatoschisis, labiopalatoschisis with or without alveolar schisis, unilateral and bilateral schisis, and other types). The study was not limited to any specific age group, symptoms, or surgical/orthodontic state. The screening and selection of studies were performed by two independent operators Two (AP, VV), and included: the removal of duplicates, the elimination of not accessible articles, manuscripts published in languages other than English. The titles and abstracts assessed as suitable from the records obtained were analyzed, excluding those not in line to the inclusion criteria. The full text of medical and/or orthodontic studies considered as relevant from the previous steps was read to assess their final inclusion in the review. In case of disagreement between the two reviewers, a third party (FL) intervened in the decision-making process. Data collection from the included reports was performed by the same first two reviewers (AP, AS), who independently worked on an Excel spreadsheet to identify parameters referring to general article information (title, author, year of publication, journal, volume, and pages), study design, the population included, type of intervention, control used, and outcomes. No data extraction software was used. According to the objectives, primary outcomes assessed in the studies were: the following periodontal indices: Plaque Index (PI), Plaque Index Score (PIS), Visible Plaque Index (VPI), Quigley-Hein Index (QHI), Gingival Index (GI), Bleeding Index (BI), Bleeding on Probing (BoP) Probing Pocket Depth (PPD) and Clinical Attachment Level (CAL); the following caries indices: decayed missing filling teeth (dmft), decayed missing filled surfaces (dmfs), DECAYED MISSING FILLED TEETH (DMFT) and DECAYED MISSING FILLED SURFACES (DMFS). Secondary outcomes concerned the analysis of the oral microbiota, to compare the main microorganisms between patients with schisis and healthy controls. Two reviewers independently applied the Newcastle-Ottawa scale (NOS) and the Joanna Briggs Institute (JBI) checklist to determine and classify study quality. Disagreement was resolved by discussion. The Newcastle-Ottawa scale (NOS) is a tool for assessing the quality of non-randomized studies. The evaluation includes questions on three domains: selection of study groups, comparability of groups, assessment of exposure or outcome of interest. Each question, based on the answers, can be assigned one star (with a maximum of 4 stars for selection, with a maximum of two stars for comparability, with a maximum of three stars for the result). The quality of a study is calculated based on the sum of the stars for a maximum of 9 stars. Higher scores indicate lower risk of bias. Studies are considered of high quality when the overall score is >=7, they are considered of moderate quality when the score is between 4 and 6, and they are considered of low quality when the score is <=3. The Joanna Briggs Institute (JBI) is a tool used for cross-sectional, case-control and cohort studies, with a collection of different questions focused on the appropriateness of the statistical analysis used (Y yes, N no, UC unclear). Continuous outcomes were identified for the meta-analysis. The number of samples, mean, and standard deviation were defined for each outcome. Statistical analysis was conducted on studies with comparable outcomes, while microbiological analysis was not included in the meta-analysis because data comparison would have been practically impossible. Statistical analysis of periodontal parameters and caries indices was performed. Review Manager Web software (Cochrane Collaboration) was used for analyzing the quantitative data. Meta-analysis was performed using a fixed-effects model, inverse-variance method, average differences, or standardized average differences according to the studies and parameters. A 95% confidence interval was calculated for the primary results. Finally, forest plots were created and heterogeneity and overall effect tests were performed. Subgroup analysis explored the causes of statistical heterogeneity and to differentiate studies involving different age groups. Method to quantify statistical heterogeneity was I 2 . The assessment of confidence was conducted using GRADEpro Guideline Development Tool (GDT). The two reviewers evaluated the level of confidence in the evidence based on the following factors: risk of bias, inconsistency, indirectness, imprecision, publication bias, large effect, plausible confounding, and dose-response gradient. In the event of a disagreement between the two reviewers, additional discussion was used to reach a consensus. Study selection The search was conducted during the time interval from March 2023 to January 2024. The search retrieved 1350 records: 308 from PubMed, 581 from Scopus, 58 from Cochrane 403 from Web of Science. A manual search yielded four additional studies. A total of 163 duplicates and 12 studies published in languages other than English were removed. 918 studies were excluded using filters: 753 before 2013 (as deemed not complete for the variables considered and to provide an updated overview of the oral health of these patients), 5 not full text, 29 not conducted on humans, 114 reviews or meta-analyses and 17 chapters, conference papers and notes. 273 studies were assessed for eligibility, and 204 of these were excluded after reading the title/abstract. Of the 69 articles to be analyzed, 4 were excluded because they were not reachable. 65 studies were examined. After text analysis, 14 irrelevant articles and 15 articles that did not meet the inclusion criteria were excluded. Finally, a total of 24 studies underwent qualitative review and subsequent metanalysis: these were full-text published in English after 1 January 2013, deemed as complete for the variables considered according to the inclusion criteria (involving human subjects, diagnosis of cleft lip or palate, description of oral health factors). Figure presents the study flow chart according to PRISMA criteria, with number of articles retrieved and included. Study characteristics Ten of the 24 studies (five case-control , four cross-sectional , one cohort ) evaluated clinical periodontal measurements in 1619 subjects (643 with lip cleft palate and 976 healthy controls) aged >2 years and three were conducted in Brazil , two in India , two in Sweden , one study each in China and in Thailand (Table ). All defined the type of cleft. Four studies involved subjects who underwent surgery , five did not state whether they did , one study reported that 16 out of 50 subjects with cleft lip and palate did not undergo surgery, 18 subjects underwent surgery twice, nine underwent surgery once, and seven underwent surgery three times . Seven studies excluded patients with lip cleft and palate associated with history of a syndrome . Two studies included subjects with syndromes and one did not specify . Two studies included subjects (cases and controls) undergoing orthodontic treatment , one study excluded subjects undergoing orthodontic treatment , and seven studies did not specify . Eight observational studies analyzed oral microflora . The studies included a mixed age group of patients with lip cleft and a healthy controls group. All reported on the type of cleft. Four reported that subjects underwent surgery , while four did not specify . Two studies included symptomatic subjects , four excluded subjects with symptoms , and two did not specify . Five studies did not specify whether the subjects were receiving orthodontic treatment and three excluded subjects who were . Risk of bias The studies were evaluated and classified for quality according to the Newcastle–Ottawa scale (NOS) and the Joanna Briggs Institute (JBI) checklist (Figs. , , and ). Meta-analysis PI (Plaque Index) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the PI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated in the total observations is centered at 0.29 (with values of 0.24–0.34). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:0.0002; p -value: < 0.00001). The forest plot (Fig. ) showed a higher PI for the cleft group. PI (Plaque index) in patients with unilateral and with bilateral cleft lip and palate A statistical analysis was conducted on the PI parameter between subjects affected by unilateral cleft lip and palate and subjects affected by bilateral cleft lip and palate using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at -0.13 (with values of -0.38; 0.12). The heterogeneity test is not statistically significant ( p -value:0.49). The overall effect test is not statistically significant ( p -value:0.32). Comparison between unilateral and bilateral cleft lip and palate showed no statistically significant difference (Fig. ). GI (Gingival Index) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the GI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at 0.15 (with values of 0.11-0.19). The heterogeneity test is not statistically significant ( p -value:0.07), while the overall effect test is statistically significant ( p -value:<0.0001). The gingival index (Fig. ) was higher for the cleft group. PPD (Probing pocket depth) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the PPD parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval on the total observations is centered at 0.88 (with values of 0.82-0.95). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:<0.00001; p -value:<0.00001). The probing pocket depth (Fig. ) was higher for the cleft group. Certainty assessment The estimated risk of bias displayed Low certainty evidence, with comparisons between the two intervention tests and controls, for PI, GI and PPD (Table ). The search was conducted during the time interval from March 2023 to January 2024. The search retrieved 1350 records: 308 from PubMed, 581 from Scopus, 58 from Cochrane 403 from Web of Science. A manual search yielded four additional studies. A total of 163 duplicates and 12 studies published in languages other than English were removed. 918 studies were excluded using filters: 753 before 2013 (as deemed not complete for the variables considered and to provide an updated overview of the oral health of these patients), 5 not full text, 29 not conducted on humans, 114 reviews or meta-analyses and 17 chapters, conference papers and notes. 273 studies were assessed for eligibility, and 204 of these were excluded after reading the title/abstract. Of the 69 articles to be analyzed, 4 were excluded because they were not reachable. 65 studies were examined. After text analysis, 14 irrelevant articles and 15 articles that did not meet the inclusion criteria were excluded. Finally, a total of 24 studies underwent qualitative review and subsequent metanalysis: these were full-text published in English after 1 January 2013, deemed as complete for the variables considered according to the inclusion criteria (involving human subjects, diagnosis of cleft lip or palate, description of oral health factors). Figure presents the study flow chart according to PRISMA criteria, with number of articles retrieved and included. Ten of the 24 studies (five case-control , four cross-sectional , one cohort ) evaluated clinical periodontal measurements in 1619 subjects (643 with lip cleft palate and 976 healthy controls) aged >2 years and three were conducted in Brazil , two in India , two in Sweden , one study each in China and in Thailand (Table ). All defined the type of cleft. Four studies involved subjects who underwent surgery , five did not state whether they did , one study reported that 16 out of 50 subjects with cleft lip and palate did not undergo surgery, 18 subjects underwent surgery twice, nine underwent surgery once, and seven underwent surgery three times . Seven studies excluded patients with lip cleft and palate associated with history of a syndrome . Two studies included subjects with syndromes and one did not specify . Two studies included subjects (cases and controls) undergoing orthodontic treatment , one study excluded subjects undergoing orthodontic treatment , and seven studies did not specify . Eight observational studies analyzed oral microflora . The studies included a mixed age group of patients with lip cleft and a healthy controls group. All reported on the type of cleft. Four reported that subjects underwent surgery , while four did not specify . Two studies included symptomatic subjects , four excluded subjects with symptoms , and two did not specify . Five studies did not specify whether the subjects were receiving orthodontic treatment and three excluded subjects who were . The studies were evaluated and classified for quality according to the Newcastle–Ottawa scale (NOS) and the Joanna Briggs Institute (JBI) checklist (Figs. , , and ). PI (Plaque Index) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the PI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated in the total observations is centered at 0.29 (with values of 0.24–0.34). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:0.0002; p -value: < 0.00001). The forest plot (Fig. ) showed a higher PI for the cleft group. PI (Plaque index) in patients with unilateral and with bilateral cleft lip and palate A statistical analysis was conducted on the PI parameter between subjects affected by unilateral cleft lip and palate and subjects affected by bilateral cleft lip and palate using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at -0.13 (with values of -0.38; 0.12). The heterogeneity test is not statistically significant ( p -value:0.49). The overall effect test is not statistically significant ( p -value:0.32). Comparison between unilateral and bilateral cleft lip and palate showed no statistically significant difference (Fig. ). GI (Gingival Index) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the GI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at 0.15 (with values of 0.11-0.19). The heterogeneity test is not statistically significant ( p -value:0.07), while the overall effect test is statistically significant ( p -value:<0.0001). The gingival index (Fig. ) was higher for the cleft group. PPD (Probing pocket depth) in patients with orofacial cleft and healthy controls A statistical analysis was conducted on the PPD parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval on the total observations is centered at 0.88 (with values of 0.82-0.95). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:<0.00001; p -value:<0.00001). The probing pocket depth (Fig. ) was higher for the cleft group. A statistical analysis was conducted on the PI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated in the total observations is centered at 0.29 (with values of 0.24–0.34). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:0.0002; p -value: < 0.00001). The forest plot (Fig. ) showed a higher PI for the cleft group. A statistical analysis was conducted on the PI parameter between subjects affected by unilateral cleft lip and palate and subjects affected by bilateral cleft lip and palate using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at -0.13 (with values of -0.38; 0.12). The heterogeneity test is not statistically significant ( p -value:0.49). The overall effect test is not statistically significant ( p -value:0.32). Comparison between unilateral and bilateral cleft lip and palate showed no statistically significant difference (Fig. ). A statistical analysis was conducted on the GI parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval calculated across the total observations is centered at 0.15 (with values of 0.11-0.19). The heterogeneity test is not statistically significant ( p -value:0.07), while the overall effect test is statistically significant ( p -value:<0.0001). The gingival index (Fig. ) was higher for the cleft group. A statistical analysis was conducted on the PPD parameter between subjects affected by cleft lip and palate and healthy subjects using the fixed effects model and mean differences. The 95% confidence interval on the total observations is centered at 0.88 (with values of 0.82-0.95). Both the heterogeneity test and the overall effect test are statistically significant ( p -value:<0.00001; p -value:<0.00001). The probing pocket depth (Fig. ) was higher for the cleft group. The estimated risk of bias displayed Low certainty evidence, with comparisons between the two intervention tests and controls, for PI, GI and PPD (Table ). This first part of systematic review and meta-analysis provides an overview of oral health in patients with cleft lip and/or palate. We wanted to determine the effect of cleft lip and/or palate on periodontal health. To do this, we reviewed 24 studies on periodontal parameters and oral microflora, 18 of which underwent meta-analysis. Of note, the studies by Sundel (2018) and Sundel/Nilsson (2016) involved the same sample; therefore, the results of the meta-analysis were considered only once. Healthy periodontal tissue is essential for successful treatment outcome, especially since each step in cleft treatment can have negative consequences for periodontal health . In recent years, oral health monitoring has played a key role in the management of various systemic diseases and maintaining good oral hygiene practices and addressing dental problems promptly can help prevent the exacerbation of existing systemic diseases . This integrated approach to health care emphasizes the interconnectedness of oral and overall health, highlighting the need for collaborative efforts between dental and medical professionals to ensure comprehensive patient care. Achieving optimal oral hygiene can be difficult due to schisis, soft tissue folds, poorly developed bone, malocclusion, inadequate vestibule depth, and retention area. The potential habitat for bacteria and other microorganisms raises the risk of intraoral translocation of pathogens and periodontal illness. Moreover, patients often undergo multiple surgeries (medical, prosthetic, orthodontic), which pose added risk for periodontal disease . Residual scar tissue after defect closure and postsurgical complications (e.g., oronasal fistula) can make oral hygiene difficult to achieve and maintain, leading to poor oronasal health and a higher risk of dental caries, halitosis, and periodontal disease . Meta-analysis of the gingival index (GI) and the bleeding index (BI) showed significantly higher values for subjects with cleft lip and/or palate (GI p < 0.00001; BI p < 0.0001). One study was included in the qualitative but not the meta-analyses because it applied parameters (bleeding on probing) that cannot be compared with those entered in the statistical analyses. The study suggested that the difference in scores between patients with orofacial cleft and healthy controls was not statistically significant . In a split-mouth study, Plakwicz (2017) observed gingival inflammation more often involving the teeth on the cleft side than on the healthy side, with statistically higher scores for the distovestibular surface of the central incisor (58.8% vs 26.5%), vestibular surface of the canines (38.5% vs 9.7%), and mesiopalatal surface of the canines (50% vs 16.1%) . Patients with cleft lip and/or palate are disposed to a higher risk of gingival inflammation because of the anatomical peculiarity of the cleft area and surgical repair. During the first years of life, the parents of patients with orofacial cleft understandably direct enormous attention to surgical repair, psychological health, and phonetic and phonological development of their children but they tend to neglect teaching them the basics of oral health care, the lack of which can promote inflammation of the superficial periodontium . Furthermore, Plakwicz (2017) found a deeper probing depth for the teeth on the schisis side than on the healthy side, with significantly higher scores ( p < 0.05) on the vestibular, distopalatal, palatal, and mesiopalatal surfaces of the canines and on the mesiopalatal surfaces of the lateral incisors . The meta-analysis showed higher GI scores for the subjects without labiopalatalschisis ( p < 0.0000). This observation is shared by Marzouk (2022) . The loss of clinical attachment level (CAL) is greater in patients with cleft lip and palate than in healthy controls ( p < 0.00001). Mutthineni (2010) found that periodontal status is influenced by schisis type . A split-mouth study (2017) by Plakwicz reported that loss of CAL was greater for teeth on the cleft side than on the healthy side . Mutthineni (2010) compared the sites of teeth adjacent to an alveolar cleft with control sites (not on the cleft side) and found a long supracrestal connective tissue attachment (SCTA) at the sites close to the cleft. Despite the lower bone level, the resistance to periodontal disease seemed to be the same for all teeth . While periodontal disease is usually rare in younger patients, even a minor loss of CAL can signal the initial onset of disease . Evaluation of the development of periodontal disease was reported by prospective studies with long-term follow-up. Salvi (2003) and Huynh-Ba (2009) evaluated the progression of periodontal disease in subjects with orofacial cleft lip and palate not undergoing support periodontal therapy and found an increase in PPD (0.09–0.57 mm) and CAL (1.52–1.85 mm). Periodontal therapy is fundamental for maintaining a low probing depth and preventing loss of CAL after active therapy . The two studies did not include a control group, however. The relationship between cleft lip and palate, periodontal parameters, and the microbiota has been recently revised. The focus of the present study, which differs from that of other reviews, was directed at studies published in the last 10 years, so as to provide an updated overview of the oral health of these patients. We noted that the case–control studies involving patients with orofacial cleft lip and palate and their oral health are few but the revisions on the topic are plentiful. Furthermore, the literature is highly heterogeneous in quality, age group, number of samples, schisis typology, association-exclusion of syndrome history (not always specified), treatment stage, socioeconomic status, geographic area, and types of parameters considered. Study limitations Many studies were unclear about the type, number, and timeframe of the surgical procedures. The subgroups should take into consideration multiple factors, such as the different types of clefts, associated syndromic pictures, non-syndromic cleft lip and palate, groups of subjects who have/have not undergone surgery, groups of subjects who have not/are having/have already undergone an orthodontic treatment. In addition, few studies mentioned orthodontic treatment, though it may be assumed that only the group with schisis underwent treatment or was planned to. These factors, which are associated with the scarcity of the available literature, are a limitation of the present study. Most studies do not carry out separate analyses, which does not allow for a precise assessment. For example, both the presence of malocclusion and orthodontic treatment, which plays a key role in the multidisciplinary treatment of subjects affected by clefts, can modify the oral environment the periodontal apparatus, the oral microbiota, the composition and biochemical properties of saliva. A further limitation is that only studies published in English were included and this may have reduced the sample size. The paper includes studies carried out in several countries, including developing ones, and this represents a strength of this review because it allows us to provide a representative analysis at a global level. However, due to the nature of the studies, the influence of the socio-economic data is not well distinguishable from the other parameters and could have produced an altered result which underestimates the risk of incidence of caries pathology in the poorest areas and overestimates it compared to the richest areas. Given the paucity of studies in this area, standardized studies using the most recent classification of periodontal illness, with control groups, long-term follow-up, larger sample size, and more homogeneous age groups are warranted. Future research directions To deepen the topic of caries pathology in subjects affected by clefts, standardized case–control studies would be necessary that use the same caries evaluation system, while to deepen the topic of periodontal disease in subjects with clefts, standardized studies using the most recent classification of periodontal disease, with control groups and long-term follow-up, would be necessary. It may be speculated that children with cleft, who are colonized early by periodontium pathogenic species, are at greater risk for periodontal disease. This makes prevention protocols necessary, with regular follow-up visits starting at an early age. Further research is recommended which includes a greater number of patients, more homogeneous samples, and which takes into consideration more factors, such as types of cleft, orthodontics and surgery. Furthermore, it would be desirable to introduce a standardized method for measuring the microbiota in order to be able to perform a meta-analysis of the microflora in the future. Many studies were unclear about the type, number, and timeframe of the surgical procedures. The subgroups should take into consideration multiple factors, such as the different types of clefts, associated syndromic pictures, non-syndromic cleft lip and palate, groups of subjects who have/have not undergone surgery, groups of subjects who have not/are having/have already undergone an orthodontic treatment. In addition, few studies mentioned orthodontic treatment, though it may be assumed that only the group with schisis underwent treatment or was planned to. These factors, which are associated with the scarcity of the available literature, are a limitation of the present study. Most studies do not carry out separate analyses, which does not allow for a precise assessment. For example, both the presence of malocclusion and orthodontic treatment, which plays a key role in the multidisciplinary treatment of subjects affected by clefts, can modify the oral environment the periodontal apparatus, the oral microbiota, the composition and biochemical properties of saliva. A further limitation is that only studies published in English were included and this may have reduced the sample size. The paper includes studies carried out in several countries, including developing ones, and this represents a strength of this review because it allows us to provide a representative analysis at a global level. However, due to the nature of the studies, the influence of the socio-economic data is not well distinguishable from the other parameters and could have produced an altered result which underestimates the risk of incidence of caries pathology in the poorest areas and overestimates it compared to the richest areas. Given the paucity of studies in this area, standardized studies using the most recent classification of periodontal illness, with control groups, long-term follow-up, larger sample size, and more homogeneous age groups are warranted. To deepen the topic of caries pathology in subjects affected by clefts, standardized case–control studies would be necessary that use the same caries evaluation system, while to deepen the topic of periodontal disease in subjects with clefts, standardized studies using the most recent classification of periodontal disease, with control groups and long-term follow-up, would be necessary. It may be speculated that children with cleft, who are colonized early by periodontium pathogenic species, are at greater risk for periodontal disease. This makes prevention protocols necessary, with regular follow-up visits starting at an early age. Further research is recommended which includes a greater number of patients, more homogeneous samples, and which takes into consideration more factors, such as types of cleft, orthodontics and surgery. Furthermore, it would be desirable to introduce a standardized method for measuring the microbiota in order to be able to perform a meta-analysis of the microflora in the future. The findings of this first part of systemic review and meta-analysis are shared by previous studies that reported that persons with orofacial schisis are at higher risk for poor oral health and dental and periodontal disease. Optimal oral hygiene is often difficult to achieve and maintain. Multiple factors contribute to the risk of dental-periodontal infection. Controversy surrounds the extent to which these risk factors, either singularly or combined, promote co-infection by pathogenic strains and dysbiosis of the oral microbiota, dental caries and periodontal disease. Given that persons with orofacial cleft lip and palate are at risk of dental-periodontal disease, the implementation is warranted of primary prevention strategies to promote oral health in children with cleft lip and palate starting from a very early age. There is a need for more research with larger and more homogeneous samples, global analyses, and subgroups. It would also be desirable to develop a standardized method to measure oral microbiota and conduct a meta-analysis of the findings of future studies. |
A bibliometric insight into neoadjuvant chemotherapy in bladder cancer: trends, collaborations, and future avenues | caa08fb4-b7e3-41e8-84fe-cf94ebfc4c16 | 10912866 | Internal Medicine[mh] | Bladder cancer ranks as the 10th most prevalent cancer globally and represents the most frequently diagnosed malignancy within the urinary system . According to the latest global cancer statistics, bladder cancer accounts for approximately 3% of all cancer cases worldwide, emphasizing its significant impact on global health . It is categorized, based on pathological or radiological evaluations, into Non-Muscle Invasive Bladder Cancer (NMIBC) and Muscle Invasive Bladder Cancer (MIBC). MIBC patients exhibit a markedly heightened risk of recurrence and lymphatic metastasis relative to those with NMIBC. Sole reliance on surgical resection for treatment is associated with suboptimal therapeutic outcomes, with recurrence rates in lymph node-positive patients reaching up to 76% . To address this clinical challenge, perioperative treatments, including neoadjuvant and adjuvant therapies, have been rigorously explored to enhance patient outcomes. Introduced in the 1980s, neoadjuvant chemotherapy has been integrated into modern clinical paradigms . This regimen seeks to reduce primary tumor size, mitigate remote micro-metastasis, and bolster curative potential preceding surgery. Contemporary recommendations endorse cisplatin-based combination regimens for eligible patients, delivering a modest but notable 5-8% uptick in overall survival (OS) . Nevertheless, the broader application of chemotherapy is hindered by its toxicity profile and the diverse nature of bladder cancer. The advent of high-throughput genomic sequencing technologies, such as next-generation sequencing (NGS), has revolutionized bladder cancer research . These advancements have enabled a detailed understanding of the genetic landscape of bladder cancer, identifying critical mutations in genes like FGFR3, TP53, and RB1. Such discoveries are instrumental in developing targeted therapies and predicting patient responses to treatments like neoadjuvant chemotherapy . Furthermore, genomic sequencing has facilitated the identification of molecular subtypes of bladder cancer, providing insights into their distinct prognostic and therapeutic implications. For instance, recent studies have shown that certain genomic alterations are associated with a better response to cisplatin-based chemotherapy, guiding treatment decisions and improving patient outcomes . Recent advances in immunotherapeutic interventions have been remarkable, with several agents undergoing clinical evaluation and manifesting encouraging therapeutic profiles. Immune checkpoint inhibitors (ICIs), particularly those targeting PD-1 or PD-L1 pathways, such as pembrolizumab, have demonstrated significant efficacy in advanced bladder cancer, especially when combined with chemotherapy . The integration of genomic data with immunotherapy research is poised to further revolutionize the therapeutic landscape of bladder cancer, offering more personalized and effective treatment options . In the contemporary landscape of bladder cancer research, characterized by an ever-expanding corpus of scholarly articles. Conventional review methodologies, while undeniably valuable, often grapple with the formidable challenge of comprehensively elucidating the swiftly evolving sphere of neoadjuvant chemotherapy for bladder cancer. Bibliometrics, a statistical approach, furnishes an analytical perspective on publications, presenting a methodical depiction of research trajectories and emphases. Through mathematical techniques, it illuminates various facets of scholarly contributions, including affiliations, journals, authors, citations, and keywords . The advent of visualization platforms, like CiteSpace and VOSviewer, has facilitated the intuitive exploration and visualization of interrelationships based on publication, citation, and collaboration metrics sourced from open databases . In this study, we will utilize advanced bibliometric techniques to assess the current landscape of neoadjuvant chemotherapy research for bladder cancer. By doing so, we seek to illuminate the most influential works, prominent research clusters, and emerging trends in the field. Furthermore, our analysis aims to provide researchers and clinicians with a clear roadmap of the domain’s evolution and to pinpoint areas that warrant further exploration. Data source and acquisition We searched the Clarivate Analytics Web of Science Core Collection database (WoSCC), which is one of the most commonly used repositories for bibliometric analysis, to identify and collect related publications on neoadjuvant chemotherapy of bladder cancer. To refine our search, we included articles that specifically mentioned “neoadjuvant chemotherapy” in the title, abstract, or keywords, and were related to bladder cancer, ensuring focused relevance. We excluded conference abstracts, editorials, and letters, aiming for a comprehensive collection of original research articles and reviews. In an effort to mitigate potential biases associated with updates to articles, the search was jointly executed by two independent researchers and was finalized on June 16, 2023. Search strategy The employed search algorithm was delineated as: topic = (neoadjuvant or NAC) NEAR/1 (therapy* OR treatment* OR chemotherapy*) AND topic = (bladder) NEAR/1 (cancer* OR tumor* OR tumour* OR oncology OR neoplasm* OR carcinoma*) with a publication year constraint of 1999-2022. This query yielded 2549 articles within the WoSCC database. To ensure relevance and quality, we manually reviewed the titles and abstracts of these articles, selecting those that directly addressed neoadjuvant chemotherapy in the context of bladder cancer. Articles that were not focused on this specific topic or did not provide significant insights into the field were excluded. We further refined our selection to English-language articles and reviews from the specified date range, culminating in 1836 publications for subsequent analysis. Ethical approval was deemed non-essential for this study. Bibliometric analysis tools For our bibliometric analyses, we utilized SCImago Graphica (Beta 1.0.35), Citespace (version 5.8.R2), and VOSviewer (version 1.6.16). Visualization and data presentation In our bibliometric analysis, we employed several mathematical techniques to extract meaningful patterns and trends from the data. One key technique was the use of frequency and co-occurrence analysis, which helped in identifying the most frequently addressed topics and the relationships between different concepts within the literature. We also applied cluster analysis to group related articles, authors, or keywords into distinct clusters, revealing thematic concentrations and patterns of research activity. Network analysis was another pivotal technique, where we constructed and analyzed networks of citations and co-authorships to uncover the most influential authors and publications, as well as to visualize the collaborative landscape. We incorporated temporal analysis to trace the evolution of research themes over time, thereby identifying both historical and emerging trends . To assist readers in interpreting these visualizations, we have added a brief tutorial. For instance, in CiteSpace, each node represents an article, author, or keyword, with the size of the node corresponding to its citation count or occurrence frequency. The lines between nodes represent co-citations or co-occurrences, indicating thematic or collaborative connections . Similarly, in VOSviewer, network maps display clusters of related items, with different colors representing different clusters. The distance between nodes in these maps reflects the strength of the relationship, with closer nodes indicating stronger connections. Furthermore, we present illustrative examples to demonstrate the practical application of our findings. For example, one of our network maps highlights a significant cluster of research focused on the role of PD-1/PD-L1 inhibitors in neoadjuvant chemotherapy for bladder cancer. This cluster includes key publications and influential authors, illustrating the growing interest and pivotal research in this area. Another example is our temporal analysis graph, which shows the evolution of research themes over time, highlighting the shift from traditional chemotherapy approaches to combined chemo-immunotherapy regimens in recent years. Citespace facilitated the extraction of annual publication and citation graphs, country collaboration diagrams, dual-map journal overlays, and the 25 most salient keywords based on citation bursts. Both VOSviewer and SCImago Graphica were instrumental in generating graphs depicting collaborative ties between nations, institutions, and authors, in addition to keyword analyses. Microsoft Office Excel 2019 (Microsoft, Redmond, WA, USA) was employed to illustrate publication trends and project anticipated publication counts for the ensuing year. Within our bibliometric analysis, the H-index of journals was calculated following the method proposed by Hirsch JE . This index is determined by arranging the published articles of a journal in descending order of their citation counts, and identifying the number “H”, where at least “H” articles have received “H” or more citations each. We searched the Clarivate Analytics Web of Science Core Collection database (WoSCC), which is one of the most commonly used repositories for bibliometric analysis, to identify and collect related publications on neoadjuvant chemotherapy of bladder cancer. To refine our search, we included articles that specifically mentioned “neoadjuvant chemotherapy” in the title, abstract, or keywords, and were related to bladder cancer, ensuring focused relevance. We excluded conference abstracts, editorials, and letters, aiming for a comprehensive collection of original research articles and reviews. In an effort to mitigate potential biases associated with updates to articles, the search was jointly executed by two independent researchers and was finalized on June 16, 2023. The employed search algorithm was delineated as: topic = (neoadjuvant or NAC) NEAR/1 (therapy* OR treatment* OR chemotherapy*) AND topic = (bladder) NEAR/1 (cancer* OR tumor* OR tumour* OR oncology OR neoplasm* OR carcinoma*) with a publication year constraint of 1999-2022. This query yielded 2549 articles within the WoSCC database. To ensure relevance and quality, we manually reviewed the titles and abstracts of these articles, selecting those that directly addressed neoadjuvant chemotherapy in the context of bladder cancer. Articles that were not focused on this specific topic or did not provide significant insights into the field were excluded. We further refined our selection to English-language articles and reviews from the specified date range, culminating in 1836 publications for subsequent analysis. Ethical approval was deemed non-essential for this study. For our bibliometric analyses, we utilized SCImago Graphica (Beta 1.0.35), Citespace (version 5.8.R2), and VOSviewer (version 1.6.16). In our bibliometric analysis, we employed several mathematical techniques to extract meaningful patterns and trends from the data. One key technique was the use of frequency and co-occurrence analysis, which helped in identifying the most frequently addressed topics and the relationships between different concepts within the literature. We also applied cluster analysis to group related articles, authors, or keywords into distinct clusters, revealing thematic concentrations and patterns of research activity. Network analysis was another pivotal technique, where we constructed and analyzed networks of citations and co-authorships to uncover the most influential authors and publications, as well as to visualize the collaborative landscape. We incorporated temporal analysis to trace the evolution of research themes over time, thereby identifying both historical and emerging trends . To assist readers in interpreting these visualizations, we have added a brief tutorial. For instance, in CiteSpace, each node represents an article, author, or keyword, with the size of the node corresponding to its citation count or occurrence frequency. The lines between nodes represent co-citations or co-occurrences, indicating thematic or collaborative connections . Similarly, in VOSviewer, network maps display clusters of related items, with different colors representing different clusters. The distance between nodes in these maps reflects the strength of the relationship, with closer nodes indicating stronger connections. Furthermore, we present illustrative examples to demonstrate the practical application of our findings. For example, one of our network maps highlights a significant cluster of research focused on the role of PD-1/PD-L1 inhibitors in neoadjuvant chemotherapy for bladder cancer. This cluster includes key publications and influential authors, illustrating the growing interest and pivotal research in this area. Another example is our temporal analysis graph, which shows the evolution of research themes over time, highlighting the shift from traditional chemotherapy approaches to combined chemo-immunotherapy regimens in recent years. Citespace facilitated the extraction of annual publication and citation graphs, country collaboration diagrams, dual-map journal overlays, and the 25 most salient keywords based on citation bursts. Both VOSviewer and SCImago Graphica were instrumental in generating graphs depicting collaborative ties between nations, institutions, and authors, in addition to keyword analyses. Microsoft Office Excel 2019 (Microsoft, Redmond, WA, USA) was employed to illustrate publication trends and project anticipated publication counts for the ensuing year. Within our bibliometric analysis, the H-index of journals was calculated following the method proposed by Hirsch JE . This index is determined by arranging the published articles of a journal in descending order of their citation counts, and identifying the number “H”, where at least “H” articles have received “H” or more citations each. Annual publications trend Our bibliometric analysis encompassed 1,836 publications from 1999 to 2022. Original research articles constituted 78% of these, and comprehensive reviews, 22%. Yearly publication output and citations showed a consistent increase, with a zenith in 2021 . From 2012 to 2022, annual publication output doubled. A polynomial fitting curve was employed to elucidate this trend. The analysis rendered a coefficient of determination (R²=0.9868), emphasizing the trend’s statistical significance. Projections suggest approximately 230 publications in 2023. These data highlight the escalating interest in NAC for bladder cancer. Countries/regions Researcher from 57 countries or regions participated in the study of NAC for bladder cancer in total. provides a comprehensive overview of the top 10 most productive nations in this research field. Notably, Europe emerges as a dominant contributor, with six countries, while North America and Asia each account for two. The United States stands out prominently, boasting the highest number of publications, total citations, and an impressive H-index of 98, which indicates academic output and quality. This conveys the United States’ indisputable leadership in the study of NAC for bladder cancer . Furthermore, the United Kingdom garners distinction by achieving the highest average citation per paper, indicative of the nation’s production of high-quality studies with a notable influence on average. It is noteworthy that China, the sole developing country among the top 10, has demonstrated remarkable growth. Over the past five years, China has witnessed a two-fold increase in the quantity of publications . A collaboration map depicts the US as the nexus of international collaborations, with North America and Europe as major participants. Institutes As shown in , a detailed analysis of the top 10 prolific institutes in NAC research for bladder cancer highlights a significant presence of institutions from North America and Europe. Specifically, five of these top institutes are based in the United States, two in Canada, and the remaining three in Austria, Germany, and Italy. Within this competitive landscape, the University of Texas emerges as the most prolific institution, contributing a substantial number of papers to this field. Meanwhile, Memorial Sloan-Kettering Cancer Center stands out by accruing the highest number of total citations, indicative of its significant impact on the research domain. A visual representation of institutional collaborations, as depicted in , gives the noteworthy observation that collaborations are predominantly fostered between American and European institutions. This intercontinental collaborative endeavor reflects the global nature of research in NAC for bladder cancer, with North American and European institutions playing pivotal roles in facilitating these cooperative relationships. Journals and co-cited journals In , we present a comprehensive overview of the top 10 journals pertinent to NAC for bladder cancer. Strikingly, five of these journals originate from the United States, while two are affiliated with institutions in the Netherlands. The journals’ impact factors vary, ranging from a peak of 23.4 to a minimum of 1.1. European Urology claims the distinction of the highest impact factor, standing at 23.4, and additionally boasts the most total citations, tallying an impressive 12,137. This underscores the journal’s remarkable academic influence within the domain of NAC for bladder cancer. Intriguingly, despite Urologic Oncology-Seminars and Original Investigations publishing the highest volume of papers, it garners 2,231 total citations and possesses an influence factor of 2.7. This delineates a crucial point that in academic impact, both quantity and quality of publications wield significance. Also we calculated the H-indices of key journals in the field of urologic oncology. Notably, “The Journal of Urology” and “Cancer” emerged as leading publications with H-indices of 236 and 277, respectively. This contrasts with “Bladder Cancer”, a relatively newer journal, which currently has an H-index of 0. These indices reflect the varying levels of citation impact and scholarly influence among these publications in the field. Furthermore, eight out of the top 10 journals are specialized in urology, while the remaining two predominantly focus on oncology. A visualization graph depicting collaboration relationships among journals reveals that, at present, there is no significant collaborative interaction between these academic publications. This suggests that the independent and distinct contributions are made by these journals in advancing the field of NAC for bladder cancer, with each journal fostering its own unique academic impact. In the dual-map overlay of journals and citing journals in , there were 2 main citation lines suggesting that the papers published on the journals of Medicine/Medical/Clinical could be cited by the papers on Health/Nursing/Medicine or Molecular/Biology/Genetic journals. Authors and co-cited authors presents the top 10 prolific authors and the top 10 co-cited authors with the highest citations in the domain of neoadjuvant chemotherapy (NAC) for bladder cancer. Shariat Shahrokh F, affiliated with the University of Vienna, distinguishes himself as the foremost contributor in this field. He claims the top position in the number of publications, total citations, and total link strength. This multifaceted achievement underscores his remarkable productivity, high-quality research output, and cooperative engagement with fellow authors. offers a visualized representation of co-author relationships, indicating the collaborative networks among authors. In our analysis, we did not discern any clear co-authored relationships, signifying that research contributions in this field have primarily been characterized by independent efforts. By means of co-cited author analysis, we gain insight into the interconnections between authors who share similar research interests. Among these, Grossman HB, Sternberg CN, and Herr HW emerge as the top three co-cited authors. visually represents these relationships, with the number of lines connected to each author’s bubble corresponding to the extent of their co-cited connections. This visually highlights the considerable influence exerted by these authors within the field of NAC for bladder cancer. Co-cited references provides a listing of the top 10 co-cited papers in the field of neoadjuvant chemotherapy (NAC) for bladder cancer. A noteworthy observation is that seven out of these top 10 co-cited papers were published during the period spanning 2000 to 2005. These papers reflect seminal contributions to the literature that continue to exert a significant influence. These top 10 co-cited references encompass a diverse range of publications, comprising three meta-analyses, five clinical trial articles, and a paper focusing on molecular subtypes of bladder cancer and guideline updates. Among them, the article titled “Neoadjuvant chemotherapy plus cystectomy compared with cystectomy alone for locally advanced bladder cancer”, published in the New England Journal of Medicine in 2003, emerges as the top co-cited reference, accumulating more than nine hundred citations. To further explore the relationships between these co-cited references, we employed a visualized graph of co-cited references analysis . Intriguingly, while the graph provides a holistic view of the interconnectedness of these references, it does not reveal any significant cluster trends, suggesting a broad and diverse body of literature with varying influences and interconnections. Keywords As depicted in , the visual representation generated using VOSviewer provides insight into the occurrence frequency and correlations among keywords. Among the top 5 keywords with the highest occurrence, “Bladder cancer”, “Neoadjuvant chemotherapy”, “Cystectomy”, “Chemotherapy” and “Radical cystectomy” are central to the discourse in this research domain, reflecting the core themes of investigation. Furthermore, showcases the top 25 keywords characterized by the strongest citation bursts, effectively representing the evolving trends and hotspots within the field of NAC for bladder cancer over time. “Transitional cell carcinoma”, which represents the most common histopathological type in bladder cancer, demonstrates the highest citation strength and the longest duration, with a burst period spanning from 1999 to 2013 and a strength of 57.71. This extended burst period highlights the enduring significance of this keyword within the literature. Additionally, keywords such as “Bladder neoplasms”, “Prognostic factors”, “Phase II trial”, “Randomized trial”, “MVAC” and “Muscle-invasive bladder cancer” exhibit burst strengths exceeding 10, signifying their dynamic and influential roles as research topics and focal points in the field of NAC for bladder cancer. These burst keywords underscore the evolving nature of research interests and the emergence of new themes and research directions over time. Our bibliometric analysis encompassed 1,836 publications from 1999 to 2022. Original research articles constituted 78% of these, and comprehensive reviews, 22%. Yearly publication output and citations showed a consistent increase, with a zenith in 2021 . From 2012 to 2022, annual publication output doubled. A polynomial fitting curve was employed to elucidate this trend. The analysis rendered a coefficient of determination (R²=0.9868), emphasizing the trend’s statistical significance. Projections suggest approximately 230 publications in 2023. These data highlight the escalating interest in NAC for bladder cancer. Researcher from 57 countries or regions participated in the study of NAC for bladder cancer in total. provides a comprehensive overview of the top 10 most productive nations in this research field. Notably, Europe emerges as a dominant contributor, with six countries, while North America and Asia each account for two. The United States stands out prominently, boasting the highest number of publications, total citations, and an impressive H-index of 98, which indicates academic output and quality. This conveys the United States’ indisputable leadership in the study of NAC for bladder cancer . Furthermore, the United Kingdom garners distinction by achieving the highest average citation per paper, indicative of the nation’s production of high-quality studies with a notable influence on average. It is noteworthy that China, the sole developing country among the top 10, has demonstrated remarkable growth. Over the past five years, China has witnessed a two-fold increase in the quantity of publications . A collaboration map depicts the US as the nexus of international collaborations, with North America and Europe as major participants. As shown in , a detailed analysis of the top 10 prolific institutes in NAC research for bladder cancer highlights a significant presence of institutions from North America and Europe. Specifically, five of these top institutes are based in the United States, two in Canada, and the remaining three in Austria, Germany, and Italy. Within this competitive landscape, the University of Texas emerges as the most prolific institution, contributing a substantial number of papers to this field. Meanwhile, Memorial Sloan-Kettering Cancer Center stands out by accruing the highest number of total citations, indicative of its significant impact on the research domain. A visual representation of institutional collaborations, as depicted in , gives the noteworthy observation that collaborations are predominantly fostered between American and European institutions. This intercontinental collaborative endeavor reflects the global nature of research in NAC for bladder cancer, with North American and European institutions playing pivotal roles in facilitating these cooperative relationships. In , we present a comprehensive overview of the top 10 journals pertinent to NAC for bladder cancer. Strikingly, five of these journals originate from the United States, while two are affiliated with institutions in the Netherlands. The journals’ impact factors vary, ranging from a peak of 23.4 to a minimum of 1.1. European Urology claims the distinction of the highest impact factor, standing at 23.4, and additionally boasts the most total citations, tallying an impressive 12,137. This underscores the journal’s remarkable academic influence within the domain of NAC for bladder cancer. Intriguingly, despite Urologic Oncology-Seminars and Original Investigations publishing the highest volume of papers, it garners 2,231 total citations and possesses an influence factor of 2.7. This delineates a crucial point that in academic impact, both quantity and quality of publications wield significance. Also we calculated the H-indices of key journals in the field of urologic oncology. Notably, “The Journal of Urology” and “Cancer” emerged as leading publications with H-indices of 236 and 277, respectively. This contrasts with “Bladder Cancer”, a relatively newer journal, which currently has an H-index of 0. These indices reflect the varying levels of citation impact and scholarly influence among these publications in the field. Furthermore, eight out of the top 10 journals are specialized in urology, while the remaining two predominantly focus on oncology. A visualization graph depicting collaboration relationships among journals reveals that, at present, there is no significant collaborative interaction between these academic publications. This suggests that the independent and distinct contributions are made by these journals in advancing the field of NAC for bladder cancer, with each journal fostering its own unique academic impact. In the dual-map overlay of journals and citing journals in , there were 2 main citation lines suggesting that the papers published on the journals of Medicine/Medical/Clinical could be cited by the papers on Health/Nursing/Medicine or Molecular/Biology/Genetic journals. presents the top 10 prolific authors and the top 10 co-cited authors with the highest citations in the domain of neoadjuvant chemotherapy (NAC) for bladder cancer. Shariat Shahrokh F, affiliated with the University of Vienna, distinguishes himself as the foremost contributor in this field. He claims the top position in the number of publications, total citations, and total link strength. This multifaceted achievement underscores his remarkable productivity, high-quality research output, and cooperative engagement with fellow authors. offers a visualized representation of co-author relationships, indicating the collaborative networks among authors. In our analysis, we did not discern any clear co-authored relationships, signifying that research contributions in this field have primarily been characterized by independent efforts. By means of co-cited author analysis, we gain insight into the interconnections between authors who share similar research interests. Among these, Grossman HB, Sternberg CN, and Herr HW emerge as the top three co-cited authors. visually represents these relationships, with the number of lines connected to each author’s bubble corresponding to the extent of their co-cited connections. This visually highlights the considerable influence exerted by these authors within the field of NAC for bladder cancer. provides a listing of the top 10 co-cited papers in the field of neoadjuvant chemotherapy (NAC) for bladder cancer. A noteworthy observation is that seven out of these top 10 co-cited papers were published during the period spanning 2000 to 2005. These papers reflect seminal contributions to the literature that continue to exert a significant influence. These top 10 co-cited references encompass a diverse range of publications, comprising three meta-analyses, five clinical trial articles, and a paper focusing on molecular subtypes of bladder cancer and guideline updates. Among them, the article titled “Neoadjuvant chemotherapy plus cystectomy compared with cystectomy alone for locally advanced bladder cancer”, published in the New England Journal of Medicine in 2003, emerges as the top co-cited reference, accumulating more than nine hundred citations. To further explore the relationships between these co-cited references, we employed a visualized graph of co-cited references analysis . Intriguingly, while the graph provides a holistic view of the interconnectedness of these references, it does not reveal any significant cluster trends, suggesting a broad and diverse body of literature with varying influences and interconnections. As depicted in , the visual representation generated using VOSviewer provides insight into the occurrence frequency and correlations among keywords. Among the top 5 keywords with the highest occurrence, “Bladder cancer”, “Neoadjuvant chemotherapy”, “Cystectomy”, “Chemotherapy” and “Radical cystectomy” are central to the discourse in this research domain, reflecting the core themes of investigation. Furthermore, showcases the top 25 keywords characterized by the strongest citation bursts, effectively representing the evolving trends and hotspots within the field of NAC for bladder cancer over time. “Transitional cell carcinoma”, which represents the most common histopathological type in bladder cancer, demonstrates the highest citation strength and the longest duration, with a burst period spanning from 1999 to 2013 and a strength of 57.71. This extended burst period highlights the enduring significance of this keyword within the literature. Additionally, keywords such as “Bladder neoplasms”, “Prognostic factors”, “Phase II trial”, “Randomized trial”, “MVAC” and “Muscle-invasive bladder cancer” exhibit burst strengths exceeding 10, signifying their dynamic and influential roles as research topics and focal points in the field of NAC for bladder cancer. These burst keywords underscore the evolving nature of research interests and the emergence of new themes and research directions over time. General information Multiple clinical trials indicate that exclusive reliance on surgery provides limited therapeutic advantages for MIBC patients. Conversely, neoadjuvant chemotherapy (NAC), especially those grounded in cisplatin-based regimens, is gaining prominence as a primary strategy, enhancing overall survival rates and mitigating recurrence and metastasis risks. Recent advances in NAC, including the integration of immunotherapy and targeted therapy, are transforming the treatment landscape for bladder cancer. This reflects a shift from traditional chemotherapy approaches to more personalized and effective strategies. The field of neoadjuvant chemotherapy for bladder cancer has witnessed significant shifts in research focus over the years. Initially, studies predominantly focused on the efficacy and safety of platinum-based chemotherapy regimens. However, recent research has progressively embraced genetic markers and precision medicine, culminating in the latest trend towards immunochemotherapy approaches. These transitions reflect the dynamic adaptation of the field to emerging scientific insights and underline the critical importance of evolving treatment paradigms in response to these advances. With the advent of innovative therapeutic agents, NAC research for bladder cancer has seen significant growth, substantially influencing MIBC patient management and prognosis. This growth is characterized by an expanded focus on molecular profiling and precision medicine, aiming to tailor treatments to individual patient needs and tumor characteristics. The surge in clinical trials aiming to ascertain the optimal NAC strategies and predictive indicators for patient outcomes has resulted in a plethora of publications. These trials underscore the necessity for ongoing research to refine NAC protocols and improve patient selection criteria.An in-depth analysis of the contributions from 57 countries or regions reveals a diverse research landscape. For instance, the United States, leading in publication volume, has fostered pioneering research in genomic predictors of NAC response. In contrast, European countries, with a focus on translational research, have contributed significantly to understanding the molecular mechanisms underlying bladder cancer. Institutions like the University of Texas and Memorial Sloan-Kettering Cancer Center have been instrumental in integrating clinical and translational research, demonstrating a holistic approach to NAC for bladder cancer. Regarding global contributions, the United States is at the vanguard of NAC research for bladder cancer, evidenced by its prolific publications, citations, and international collaborations. In contrast, European countries and China are emerging as significant contributors, each bringing unique perspectives and strengths to NAC research. Notably, six out of the ten leading contributors are European countries: Italy, Germany, the United Kingdom, France, Netherlands, and Austria. Although China, the sole developing country among the top ten, has exhibited exponential publication growth, it ranks second in the 2022 publication count. Yet, China’s citation metrics trail, suggesting a need for a more focused approach to enhance the quality and impact of its research contributions. Prominent institutions, such as the University of Texas, Memorial Sloan-Kettering Cancer Center, and the University of Vienna, have garnered significant recognition. Their contributions, particularly in pioneering clinical trials and developing novel therapeutic approaches, have been instrumental in advancing NAC research. In the journal spectrum, “European Urology” stands preeminent, boasting the superior Impact Factor among top-tier journals and underscoring its role as a primary conduit for NAC research dissemination. This prominence reflects the journal’s commitment to publishing pioneering studies that have significantly influenced the course of NAC treatment. Shahrokh F. Shariat of the University of Vienna has an exemplary publication record, notably eclipsing the second-ranked author, Ashish M. Kamat. Shahrokh F. Shariat’s research found in a phase 3, multicenter, double-blind, randomized, controlled trial that adjuvant nivolumab prolonged disease-free survival in patients with high-risk muscle-invasive urothelial carcinoma who had undergone radical surgery compared to placebo . This critical finding is dissected to showcase the evolving landscape of NAC where immunotherapeutic agents are becoming increasingly significant. The potential implications of these findings for future therapeutic strategies are also discussed. Furthermore, HB Grossman’s research highlights the significance of cisplatin-based chemotherapy (M-VAC), which exhibits a superior median survival of 44 months in comparison to 37.5 months in the surgery group alone, and an overall 3-year survival rate improvement .These results emphasize the continued importance of traditional chemotherapy in NAC, while also highlighting the need for ongoing research to enhance efficacy and reduce toxicity. Keyword analysis offers invaluable insights into predominant research foci, particularly evidenced by the surge in citations for terms like “Prognostic factors” and “Gene expression”. As therapeutic innovations emerge, clinical trials are increasingly pivotal, bridging foundational research and clinical application. While neoadjuvant immunotherapy presents promising potential, the keyword “Pembrolizumab” gained traction in 2020. Given the ongoing clinical trials, a surge in related keyword citations is anticipated. This anticipation is framed within the broader context of rapidly evolving NAC research, indicating a dynamic field that is responsive to new discoveries and treatment modalities. The potential for these trials to bring about significant shifts in the treatment landscape is explored, along with their implications for future research directions and clinical practice. In summation, this exhaustive review elucidates the landscape of NAC research for bladder cancer, emphasizing global contributions, influential institutions, authors, journals, and emerging trends. Such insights empower researchers to adeptly navigate the domain, shaping future inquiries and enhancing bladder cancer patient outcomes. Following this bibliometric analysis, several pivotal subtopics in neoadjuvant chemotherapy for bladder cancer have been discerned: Regimens of platin-based chemotherapy Since the 1980s, cisplatin-based neoadjuvant chemotherapy has been utilized with the primary objective of improving surgical resection outcomes and overall survival . The prescription of this neoadjuvant chemotherapy to medically eligible MIBC patients has achieved broad clinical agreement . With time, the paradigm of chemotherapy regimens has dynamically transformed, reflecting the advent of innovative chemotherapeutic agents and becoming a focal point of comprehensive research and publications. A seminal clinical trial aimed to contrast the therapeutic effectiveness of neoadjuvant methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) chemotherapy combined with cystectomy against cystectomy as a standalone treatment. The study showcased favorable outcomes, delineating a marked advantage in complete pathological response rates for patients undergoing neoadjuvant chemotherapy (38% vs. 15%, P < 0.001) . This noteworthy outcome underscored the preeminence of NAC, marking a significant milestone in the realm of NAC studies, as evidenced by its top-ranking in co-cited reference analysis presented in . Furthermore, alternative regimens, including cisplatin with methotrexate (CM), cisplatin with Adriamycin (CA), cisplatin combined with methotrexate and vinblastine (CMV), and the combination of gemcitabine and cisplatin (GC), have all affirmed their therapeutic potency . Building on the foundational contributions of urologists, numerous meta-analyses have furnished compelling evidence underscoring the advantages of neoadjuvant chemotherapy for patient prognosis, thereby cementing its role in clinical practice . The recent VESPER trial insights have enriched our comprehension of neoadjuvant chemotherapy, elucidating that dose-dense MVAC (dd-MVAC) surpasses the commonly adopted GC regimen in local tumor management and achieving superior three-year progression-free survival rates . In summation, the domain of neoadjuvant chemotherapy for bladder cancer is poised for further evolution, with prospective research endeavors targeting the formulation of holistic protocols that promise enhanced therapeutic outcomes, expansive applicability, and economic efficiency. Prognostic factors and biomarkers Bladder cancer, characterized by its pronounced heterogeneity, presents clinical challenges, especially when implementing NAC for patients resistant to chemotherapy. The identification of prognostic factors, biomarkers, and appropriate patient cohorts remains paramount. The advent of advanced sequencing technologies and bioinformatics tools, notably the TCGA database, facilitates a comprehensive analysis of expansive genetic datasets spanning various bladder cancer subtypes. The predictive function of molecular subtypes in relation to response rates remains unclear owing to the absence of a standardized approach in molecular categorization and the mechanism by which they do so remains unknown . As our understanding of the fundamental mechanisms of carcinogenesis expands, the link between gene mutations and resistance to chemotherapeutic agents becomes clearer, paving the way for the identification of new biomarkers. Several gene mutations, including ERCC2 , ERBB2 , and BRCA1 , are strongly correlated with NAC outcomes. In ATM/RB1/FANCC mutant research, patients receiving cisplatin-based neoadjuvant chemotherapy for Muscle-invasive Bladder Cancer who possessed one or more ATM/RB1/FANCC mutations had 5-year survival rates that were higher for both OS (85% mutant vs. 46% wild) and DSS (90% mutant vs. 49% wild), respectively, than those without such mutations. Likewise, recent studies have indicated a positive correlation between deleterious mutations in ERCC2 and the pathological response to neoadjuvant chemotherapy based on Cisplatin. Patients who had ERCC2 mutations had a 5-year overall survival rate of 75%, while those who did not had that rate at 52% . Molecular pathology classifications further elucidate NAC responses. Utilizing immunohistochemical profiling to identify specific gene expressions, researchers have classified muscle-invasive bladder cancer into distinct molecular subtypes. Echoing molecular subtypes found in breast cancer, Choi et al. identified three unique bladder cancer subtypes, emphasizing the p53-like MIBC, known for its pronounced NAC resistance . This seminal study underscores the relationship between molecular subtypes and NAC responses. Building on the TCGA dataset, Robertson et al. identified five MIBC molecular subtypes: luminal-papillary, luminal-infiltrated, luminal, basal/squamous, and neuronal . While basal/squamous MIBC might respond positively to NAC, it could also be associated with an unfavorable prognosis. Several methods, including circulating tumor DNA (ctDNA) , urine tumor DNA (utDNA) and clinical factors , have been explored to predict NAC responses. However, a substantial divide persists between experimental techniques and tools suitable for clinical application. Emerging trends in neoadjuvant chemotherapy for bladder cancer Recent breakthroughs in immunotherapy have revolutionized the approach to neoadjuvant chemotherapy in bladder cancer .The introduction of immune checkpoint inhibitors (ICIs) such as pembrolizumab and atezolizumab has paved the way for new therapeutic combinations. Studies are increasingly focusing on the efficacy of combining ICIs with traditional cisplatin-based chemotherapy, revealing potential synergies that enhance response rates and improve survival outcomes compared to chemotherapy alone . This innovative approach presents a promising advancement in the treatment of bladder cancer, offering more personalized and effective therapeutic strategies. Recent studies have also highlighted the potential of integrating genomic profiling into the NAC paradigm, offering a more personalized approach to treatment. For instance, research identifying specific molecular subtypes of bladder cancer that respond favorably to NAC opens new avenues for patient-specific therapy optimization. Additionally, ongoing trials exploring the combination of immunotherapy with NAC underscore the evolving nature of bladder cancer treatment and the necessity to adapt to these advancements. The integration of precision medicine into bladder cancer treatment is an emerging trend that warrants further exploration. Advances in genomic profiling and biomarker identification are enabling the development of targeted therapies tailored to individual patient profiles. Research into molecular biomarkers to predict response to neoadjuvant chemotherapy and immunotherapy is particularly promising . This direction may lead to the formulation of more effective and less toxic treatment regimens, optimizing patient care.Looking to the future, understanding the mechanisms of resistance to chemotherapy and immunotherapy in bladder cancer is a crucial research area. Investigating the genetic and molecular basis of resistance can uncover new therapeutic targets. Another burgeoning area of interest is the role of the tumor microenvironment in influencing bladder cancer progression and treatment response. Studies exploring the interactions between tumor cells, immune cells, and other microenvironment components could unveil novel methods to enhance the efficacy of neoadjuvant chemotherapy. This perspective is further reinforced by the findings of Zhou et al. , who explored temozolomide-based sonodynamic therapy and its role in inducing immunogenic cell death in glioma, an approach that might offer insights for bladder cancer treatment strategies . Their work exemplifies the kind of innovative approaches that could be pivotal in advancing neoadjuvant chemotherapy techniques. In addition, exploring the potential of novel agents and combination therapies, especially in the context of drug resistance, is a critical area for future research. The development of therapies targeting specific molecular pathways implicated in bladder cancer progression, such as FGFR3 inhibitors and PARP inhibitors, holds promise for improving treatment outcomes . Future prospects Patients who were administered neoadjuvant camrelizumab, in conjunction with gemcitabine and cisplatin, demonstrated a pathological response rate of 43.3% and a pathologic downstaging rate of 53.3% . These findings underscore the potential of incorporating novel ICIs into NAC regimens, potentially redefining treatment standards for bladder cancer. In contrast, the combination of rapamycin with gemcitabine-cisplatin did not show improved efficacy in treating muscle-invasive bladder cancer, as evidenced by a relatively low complete response rate of 23%, despite the inhibition of mTOR in tumor cells . This underscores the importance of ongoing clinical trials and research in identifying the most effective treatment combinations. The exploration of these novel therapies is critical to advancing our understanding of bladder cancer treatment and improving patient outcomes. When patients receiving neoadjuvant platinum-based combination immune ICIs (ipilimumab plus nivolumab) for locally advanced urothelial cancer were compared with neoadjuvant platinum-based combination chemotherapy, the results indicated that patients receiving platinum-based combination ICIs achieved a greater degree of pathological complete pathological response rate . Although platinum-based regimens have shown benefits in tumor downstaging and improved long-term survival for certain patients, they also pose considerable risks and challenges. These include the potential for non-responsiveness in a subset of patients, significant toxicities, and the exclusion of patients with renal impairment. Understanding and mitigating these challenges are critical for maximizing the therapeutic potential of NAC in MIBC. Furthermore, initially employed as a second-line treatment for advanced urothelial cancer, immunotherapy has shown significant therapeutic efficacy as a standalone neoadjuvant treatment, boasting an acceptable tolerability profile . The success of immunotherapy in these contexts highlights its potential as a transformative approach in NAC, offering new hope for patients with advanced bladder cancer. Patients who have been diagnosed with metastatic urothelial carcinoma and are having chemotherapy that is based on platinum have a greater overall survival rate (median 12.8 months) in comparison to patients who are receiving immunotherapy (median 6.3 months) . In addition, a large-scale, randomized, international, multicenter Phase III Study was carried out in order to compare the efficacy of gemcitabine plus cisplatin (GC) with methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) for locally advanced or metastatic transitional-cell carcinoma patients. The findings revealed that overall survival was comparable between GC and MVAC, and the toxic mortality rate was 1% on the GC group as opposed to 3% on the MVAC group. Thus, GC gives a similar survival benefit to MVAC with a higher safety profile and tolerability . In our bibliometric analysis, we spotlight the increasing prominence of the keyword “Pembrolizumab” an “ICI”, which has seen a significant citation surge since 2020. This reflects a growing interest in the combination of immunotherapy with chemotherapy, especially considering the potential of cisplatin-based agents to potentiate the anti-cancer effects of ICIs by enhancing intratumoral T-cell activity . Recent studies suggest that ICIs, in conjunction with gemcitabine and cisplatin, yield positive results in terms of complete response rate and event-free survival . Ongoing trials, including EV304 and KEYNOTE-866, aim to ascertain the efficacy and safety of this combined approach. In recent years, artificial intelligence (AI) has showcased its potential in predicting NAC outcomes in colorectal, breast, and gastric cancer . The application of AI in NAC for bladder cancer is still nascent, but significant strides have been made. For instance, predictive models for NAC responses have been formulated using machine-learning techniques based on biopsy pathology images . Similarly, Hepburn et al. utilized machine learning to pinpoint novel NAC predictive biomarkers . While literature on AI’s role in NAC for bladder cancer remains sparse in our analysis, the future likely holds a significant role for AI in advancing NAC research, propelled by advancements in computational capabilities, algorithms, and clinical databases. In conclusion, the integration of these clinical and translational breakthroughs into standard clinical protocols is imperative. It involves tailoring treatments to individual patients, enhancing the likelihood of complete responses, and championing bladder preservation strategies. The future of NAC in bladder cancer treatment is poised at an exciting juncture, with the potential to significantly improve patient outcomes through innovative, personalized, and multidisciplinary approaches. Limitations This analysis is not without limitations, primarily stemming from the exclusive reliance on the WOSCC database and the constraint to English-language publications. Additionally, we acknowledge that our analysis did not differentiate between subtypes of bladder cancer, such as urothelial and non-urothelial carcinomas, or between muscle invasive and non-muscle invasive forms. This broad approach may overlook specific trends within these distinct subgroups. Future endeavors should contemplate a more holistic approach, incorporating diverse data sources and languages. Multiple clinical trials indicate that exclusive reliance on surgery provides limited therapeutic advantages for MIBC patients. Conversely, neoadjuvant chemotherapy (NAC), especially those grounded in cisplatin-based regimens, is gaining prominence as a primary strategy, enhancing overall survival rates and mitigating recurrence and metastasis risks. Recent advances in NAC, including the integration of immunotherapy and targeted therapy, are transforming the treatment landscape for bladder cancer. This reflects a shift from traditional chemotherapy approaches to more personalized and effective strategies. The field of neoadjuvant chemotherapy for bladder cancer has witnessed significant shifts in research focus over the years. Initially, studies predominantly focused on the efficacy and safety of platinum-based chemotherapy regimens. However, recent research has progressively embraced genetic markers and precision medicine, culminating in the latest trend towards immunochemotherapy approaches. These transitions reflect the dynamic adaptation of the field to emerging scientific insights and underline the critical importance of evolving treatment paradigms in response to these advances. With the advent of innovative therapeutic agents, NAC research for bladder cancer has seen significant growth, substantially influencing MIBC patient management and prognosis. This growth is characterized by an expanded focus on molecular profiling and precision medicine, aiming to tailor treatments to individual patient needs and tumor characteristics. The surge in clinical trials aiming to ascertain the optimal NAC strategies and predictive indicators for patient outcomes has resulted in a plethora of publications. These trials underscore the necessity for ongoing research to refine NAC protocols and improve patient selection criteria.An in-depth analysis of the contributions from 57 countries or regions reveals a diverse research landscape. For instance, the United States, leading in publication volume, has fostered pioneering research in genomic predictors of NAC response. In contrast, European countries, with a focus on translational research, have contributed significantly to understanding the molecular mechanisms underlying bladder cancer. Institutions like the University of Texas and Memorial Sloan-Kettering Cancer Center have been instrumental in integrating clinical and translational research, demonstrating a holistic approach to NAC for bladder cancer. Regarding global contributions, the United States is at the vanguard of NAC research for bladder cancer, evidenced by its prolific publications, citations, and international collaborations. In contrast, European countries and China are emerging as significant contributors, each bringing unique perspectives and strengths to NAC research. Notably, six out of the ten leading contributors are European countries: Italy, Germany, the United Kingdom, France, Netherlands, and Austria. Although China, the sole developing country among the top ten, has exhibited exponential publication growth, it ranks second in the 2022 publication count. Yet, China’s citation metrics trail, suggesting a need for a more focused approach to enhance the quality and impact of its research contributions. Prominent institutions, such as the University of Texas, Memorial Sloan-Kettering Cancer Center, and the University of Vienna, have garnered significant recognition. Their contributions, particularly in pioneering clinical trials and developing novel therapeutic approaches, have been instrumental in advancing NAC research. In the journal spectrum, “European Urology” stands preeminent, boasting the superior Impact Factor among top-tier journals and underscoring its role as a primary conduit for NAC research dissemination. This prominence reflects the journal’s commitment to publishing pioneering studies that have significantly influenced the course of NAC treatment. Shahrokh F. Shariat of the University of Vienna has an exemplary publication record, notably eclipsing the second-ranked author, Ashish M. Kamat. Shahrokh F. Shariat’s research found in a phase 3, multicenter, double-blind, randomized, controlled trial that adjuvant nivolumab prolonged disease-free survival in patients with high-risk muscle-invasive urothelial carcinoma who had undergone radical surgery compared to placebo . This critical finding is dissected to showcase the evolving landscape of NAC where immunotherapeutic agents are becoming increasingly significant. The potential implications of these findings for future therapeutic strategies are also discussed. Furthermore, HB Grossman’s research highlights the significance of cisplatin-based chemotherapy (M-VAC), which exhibits a superior median survival of 44 months in comparison to 37.5 months in the surgery group alone, and an overall 3-year survival rate improvement .These results emphasize the continued importance of traditional chemotherapy in NAC, while also highlighting the need for ongoing research to enhance efficacy and reduce toxicity. Keyword analysis offers invaluable insights into predominant research foci, particularly evidenced by the surge in citations for terms like “Prognostic factors” and “Gene expression”. As therapeutic innovations emerge, clinical trials are increasingly pivotal, bridging foundational research and clinical application. While neoadjuvant immunotherapy presents promising potential, the keyword “Pembrolizumab” gained traction in 2020. Given the ongoing clinical trials, a surge in related keyword citations is anticipated. This anticipation is framed within the broader context of rapidly evolving NAC research, indicating a dynamic field that is responsive to new discoveries and treatment modalities. The potential for these trials to bring about significant shifts in the treatment landscape is explored, along with their implications for future research directions and clinical practice. In summation, this exhaustive review elucidates the landscape of NAC research for bladder cancer, emphasizing global contributions, influential institutions, authors, journals, and emerging trends. Such insights empower researchers to adeptly navigate the domain, shaping future inquiries and enhancing bladder cancer patient outcomes. Following this bibliometric analysis, several pivotal subtopics in neoadjuvant chemotherapy for bladder cancer have been discerned: Since the 1980s, cisplatin-based neoadjuvant chemotherapy has been utilized with the primary objective of improving surgical resection outcomes and overall survival . The prescription of this neoadjuvant chemotherapy to medically eligible MIBC patients has achieved broad clinical agreement . With time, the paradigm of chemotherapy regimens has dynamically transformed, reflecting the advent of innovative chemotherapeutic agents and becoming a focal point of comprehensive research and publications. A seminal clinical trial aimed to contrast the therapeutic effectiveness of neoadjuvant methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) chemotherapy combined with cystectomy against cystectomy as a standalone treatment. The study showcased favorable outcomes, delineating a marked advantage in complete pathological response rates for patients undergoing neoadjuvant chemotherapy (38% vs. 15%, P < 0.001) . This noteworthy outcome underscored the preeminence of NAC, marking a significant milestone in the realm of NAC studies, as evidenced by its top-ranking in co-cited reference analysis presented in . Furthermore, alternative regimens, including cisplatin with methotrexate (CM), cisplatin with Adriamycin (CA), cisplatin combined with methotrexate and vinblastine (CMV), and the combination of gemcitabine and cisplatin (GC), have all affirmed their therapeutic potency . Building on the foundational contributions of urologists, numerous meta-analyses have furnished compelling evidence underscoring the advantages of neoadjuvant chemotherapy for patient prognosis, thereby cementing its role in clinical practice . The recent VESPER trial insights have enriched our comprehension of neoadjuvant chemotherapy, elucidating that dose-dense MVAC (dd-MVAC) surpasses the commonly adopted GC regimen in local tumor management and achieving superior three-year progression-free survival rates . In summation, the domain of neoadjuvant chemotherapy for bladder cancer is poised for further evolution, with prospective research endeavors targeting the formulation of holistic protocols that promise enhanced therapeutic outcomes, expansive applicability, and economic efficiency. Bladder cancer, characterized by its pronounced heterogeneity, presents clinical challenges, especially when implementing NAC for patients resistant to chemotherapy. The identification of prognostic factors, biomarkers, and appropriate patient cohorts remains paramount. The advent of advanced sequencing technologies and bioinformatics tools, notably the TCGA database, facilitates a comprehensive analysis of expansive genetic datasets spanning various bladder cancer subtypes. The predictive function of molecular subtypes in relation to response rates remains unclear owing to the absence of a standardized approach in molecular categorization and the mechanism by which they do so remains unknown . As our understanding of the fundamental mechanisms of carcinogenesis expands, the link between gene mutations and resistance to chemotherapeutic agents becomes clearer, paving the way for the identification of new biomarkers. Several gene mutations, including ERCC2 , ERBB2 , and BRCA1 , are strongly correlated with NAC outcomes. In ATM/RB1/FANCC mutant research, patients receiving cisplatin-based neoadjuvant chemotherapy for Muscle-invasive Bladder Cancer who possessed one or more ATM/RB1/FANCC mutations had 5-year survival rates that were higher for both OS (85% mutant vs. 46% wild) and DSS (90% mutant vs. 49% wild), respectively, than those without such mutations. Likewise, recent studies have indicated a positive correlation between deleterious mutations in ERCC2 and the pathological response to neoadjuvant chemotherapy based on Cisplatin. Patients who had ERCC2 mutations had a 5-year overall survival rate of 75%, while those who did not had that rate at 52% . Molecular pathology classifications further elucidate NAC responses. Utilizing immunohistochemical profiling to identify specific gene expressions, researchers have classified muscle-invasive bladder cancer into distinct molecular subtypes. Echoing molecular subtypes found in breast cancer, Choi et al. identified three unique bladder cancer subtypes, emphasizing the p53-like MIBC, known for its pronounced NAC resistance . This seminal study underscores the relationship between molecular subtypes and NAC responses. Building on the TCGA dataset, Robertson et al. identified five MIBC molecular subtypes: luminal-papillary, luminal-infiltrated, luminal, basal/squamous, and neuronal . While basal/squamous MIBC might respond positively to NAC, it could also be associated with an unfavorable prognosis. Several methods, including circulating tumor DNA (ctDNA) , urine tumor DNA (utDNA) and clinical factors , have been explored to predict NAC responses. However, a substantial divide persists between experimental techniques and tools suitable for clinical application. Recent breakthroughs in immunotherapy have revolutionized the approach to neoadjuvant chemotherapy in bladder cancer .The introduction of immune checkpoint inhibitors (ICIs) such as pembrolizumab and atezolizumab has paved the way for new therapeutic combinations. Studies are increasingly focusing on the efficacy of combining ICIs with traditional cisplatin-based chemotherapy, revealing potential synergies that enhance response rates and improve survival outcomes compared to chemotherapy alone . This innovative approach presents a promising advancement in the treatment of bladder cancer, offering more personalized and effective therapeutic strategies. Recent studies have also highlighted the potential of integrating genomic profiling into the NAC paradigm, offering a more personalized approach to treatment. For instance, research identifying specific molecular subtypes of bladder cancer that respond favorably to NAC opens new avenues for patient-specific therapy optimization. Additionally, ongoing trials exploring the combination of immunotherapy with NAC underscore the evolving nature of bladder cancer treatment and the necessity to adapt to these advancements. The integration of precision medicine into bladder cancer treatment is an emerging trend that warrants further exploration. Advances in genomic profiling and biomarker identification are enabling the development of targeted therapies tailored to individual patient profiles. Research into molecular biomarkers to predict response to neoadjuvant chemotherapy and immunotherapy is particularly promising . This direction may lead to the formulation of more effective and less toxic treatment regimens, optimizing patient care.Looking to the future, understanding the mechanisms of resistance to chemotherapy and immunotherapy in bladder cancer is a crucial research area. Investigating the genetic and molecular basis of resistance can uncover new therapeutic targets. Another burgeoning area of interest is the role of the tumor microenvironment in influencing bladder cancer progression and treatment response. Studies exploring the interactions between tumor cells, immune cells, and other microenvironment components could unveil novel methods to enhance the efficacy of neoadjuvant chemotherapy. This perspective is further reinforced by the findings of Zhou et al. , who explored temozolomide-based sonodynamic therapy and its role in inducing immunogenic cell death in glioma, an approach that might offer insights for bladder cancer treatment strategies . Their work exemplifies the kind of innovative approaches that could be pivotal in advancing neoadjuvant chemotherapy techniques. In addition, exploring the potential of novel agents and combination therapies, especially in the context of drug resistance, is a critical area for future research. The development of therapies targeting specific molecular pathways implicated in bladder cancer progression, such as FGFR3 inhibitors and PARP inhibitors, holds promise for improving treatment outcomes . Patients who were administered neoadjuvant camrelizumab, in conjunction with gemcitabine and cisplatin, demonstrated a pathological response rate of 43.3% and a pathologic downstaging rate of 53.3% . These findings underscore the potential of incorporating novel ICIs into NAC regimens, potentially redefining treatment standards for bladder cancer. In contrast, the combination of rapamycin with gemcitabine-cisplatin did not show improved efficacy in treating muscle-invasive bladder cancer, as evidenced by a relatively low complete response rate of 23%, despite the inhibition of mTOR in tumor cells . This underscores the importance of ongoing clinical trials and research in identifying the most effective treatment combinations. The exploration of these novel therapies is critical to advancing our understanding of bladder cancer treatment and improving patient outcomes. When patients receiving neoadjuvant platinum-based combination immune ICIs (ipilimumab plus nivolumab) for locally advanced urothelial cancer were compared with neoadjuvant platinum-based combination chemotherapy, the results indicated that patients receiving platinum-based combination ICIs achieved a greater degree of pathological complete pathological response rate . Although platinum-based regimens have shown benefits in tumor downstaging and improved long-term survival for certain patients, they also pose considerable risks and challenges. These include the potential for non-responsiveness in a subset of patients, significant toxicities, and the exclusion of patients with renal impairment. Understanding and mitigating these challenges are critical for maximizing the therapeutic potential of NAC in MIBC. Furthermore, initially employed as a second-line treatment for advanced urothelial cancer, immunotherapy has shown significant therapeutic efficacy as a standalone neoadjuvant treatment, boasting an acceptable tolerability profile . The success of immunotherapy in these contexts highlights its potential as a transformative approach in NAC, offering new hope for patients with advanced bladder cancer. Patients who have been diagnosed with metastatic urothelial carcinoma and are having chemotherapy that is based on platinum have a greater overall survival rate (median 12.8 months) in comparison to patients who are receiving immunotherapy (median 6.3 months) . In addition, a large-scale, randomized, international, multicenter Phase III Study was carried out in order to compare the efficacy of gemcitabine plus cisplatin (GC) with methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC) for locally advanced or metastatic transitional-cell carcinoma patients. The findings revealed that overall survival was comparable between GC and MVAC, and the toxic mortality rate was 1% on the GC group as opposed to 3% on the MVAC group. Thus, GC gives a similar survival benefit to MVAC with a higher safety profile and tolerability . In our bibliometric analysis, we spotlight the increasing prominence of the keyword “Pembrolizumab” an “ICI”, which has seen a significant citation surge since 2020. This reflects a growing interest in the combination of immunotherapy with chemotherapy, especially considering the potential of cisplatin-based agents to potentiate the anti-cancer effects of ICIs by enhancing intratumoral T-cell activity . Recent studies suggest that ICIs, in conjunction with gemcitabine and cisplatin, yield positive results in terms of complete response rate and event-free survival . Ongoing trials, including EV304 and KEYNOTE-866, aim to ascertain the efficacy and safety of this combined approach. In recent years, artificial intelligence (AI) has showcased its potential in predicting NAC outcomes in colorectal, breast, and gastric cancer . The application of AI in NAC for bladder cancer is still nascent, but significant strides have been made. For instance, predictive models for NAC responses have been formulated using machine-learning techniques based on biopsy pathology images . Similarly, Hepburn et al. utilized machine learning to pinpoint novel NAC predictive biomarkers . While literature on AI’s role in NAC for bladder cancer remains sparse in our analysis, the future likely holds a significant role for AI in advancing NAC research, propelled by advancements in computational capabilities, algorithms, and clinical databases. In conclusion, the integration of these clinical and translational breakthroughs into standard clinical protocols is imperative. It involves tailoring treatments to individual patients, enhancing the likelihood of complete responses, and championing bladder preservation strategies. The future of NAC in bladder cancer treatment is poised at an exciting juncture, with the potential to significantly improve patient outcomes through innovative, personalized, and multidisciplinary approaches. This analysis is not without limitations, primarily stemming from the exclusive reliance on the WOSCC database and the constraint to English-language publications. Additionally, we acknowledge that our analysis did not differentiate between subtypes of bladder cancer, such as urothelial and non-urothelial carcinomas, or between muscle invasive and non-muscle invasive forms. This broad approach may overlook specific trends within these distinct subgroups. Future endeavors should contemplate a more holistic approach, incorporating diverse data sources and languages. This bibliometric analysis has provided a comprehensive overview of NAC research in bladder cancer from 1999 to 2022, revealing the pivotal role of the United States and other regions in advancing the field. Importantly, this study highlights not just the evolution of chemotherapy regimens and the role of prognostic biomarkers, but also the emerging complexity within NAC treatment strategies. The findings underscore the growing importance of integrating immunochemotherapy and leveraging artificial intelligence (AI) to address the multifaceted challenges in bladder cancer treatment. Our analysis suggests a trend towards more integrated, personalized approaches, driven by a deeper understanding of the molecular and clinical complexities of bladder cancer. Future research should focus on further unraveling these complexities, particularly in optimizing immunochemotherapy strategies and utilizing AI for advanced patient stratification and treatment personalization. Such avenues are crucial for the continued advancement of bladder cancer treatment and improving patient outcomes, reflecting a deeper comprehension of the intricate interplay of various therapeutic modalities in NAC. The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors. YH: Conceptualization, Writing – original draft, Formal analysis, Investigation, Methodology. CL: Software, Writing – original draft, Formal analysis. ZS: Investigation, Conceptualization, Writing – review & editing. YZ: Data curation, Methodology, Writing – review & editing. WX: Conceptualization, Methodology, Writing – review & editing. QG: Formal analysis, Investigation, Software, Writing – review & editing. YY: Data curation, Investigation, Software, Writing – review & editing. JZ: Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing. JK: Formal analysis, Methodology, Software, Supervision, Validation, Writing – original draft, Writing – review & editing. |
Modifiable predictors of mental health literacy in the educational context: a systematic review and meta-analysis | dab61032-f13b-4edb-b26a-c5eb709eb130 | 11225224 | Health Literacy[mh] | Mental health literacy (MHL), introduced by Australian researcher Anthony Jorm and colleagues in their influential 1997 work, is defined as ‘knowledge and beliefs about mental disorders that facilitate their recognition, management, or prevention . This concept includes various components: (1) the ability to recognize specific disorders or types of psychological distress; (2) knowledge and beliefs about risk factors and causes; (3) knowledge and beliefs about self-help interventions; (4) knowledge and beliefs about available professional help; (5) attitudes that facilitate recognition and appropriate help-seeking; and (6) knowledge of how to seek mental health information . MHL extends beyond mere conceptual comprehension of mental health issues; it involves knowledge aimed at increasing the likelihood of taking action to improve one’s own mental health or that of others . This includes knowing how to attain and sustain good mental health, understanding mental disorders and their treatments, reducing associated stigma, and promoting effective help-seeking abilities, including knowing when, where, and how to access quality mental health care and developing competencies for self-care . Robust population-based research on MHL is actively progressing, offering valuable insights for mental healthcare systems and professionals as they adapt their practices to serve better individuals facing mental health challenges . Furthermore, it’s essential to emphasize that MHL is contextually situated, often involving numerous stakeholders and is particularly relevant in developmental contexts , especially within educational settings where young people and school staff represent primary targets. In educational settings, where the cultivation and dissemination of knowledge take center stage, nurturing MHL assumes critical significance . It not only provides individuals, whether they are students, educators, or staff members, with essential tools for recognizing and addressing mental health challenges within themselves but also empowers them to be better prepared to offer support to their peers or students who may be grappling with mental health issues . This interconnected support system not only alleviates feelings of isolation but also fosters an environment conducive to open dialogues surrounding mental health concerns . As a result, it fosters a culture marked by empathy and understanding within educational environments, thus facilitating the ability to assist others and the creation of a more inclusive, safe, and supportive learning atmosphere . Previous research on MHL has primarily centered on individuals, including students, teachers, educators, and various community members . While this body of work has significantly contributed to our understanding of how individuals perceive and engage with mental health issues, it has often overlooked a crucial aspect—the MHL within the broader educational environment itself, which has faced unprecedented challenges due to the COVID-19 pandemic. Educational settings, whether schools, colleges, or universities, serve as multifaceted ecosystems where myriad interactions unfold daily. They are not merely places of academic learning but dynamic environments where social, emotional, and intellectual development intersect . In the wake of COVID-19, the significance of addressing mental health literacy within educational institutions has become even more pronounced, given the additional stressors and uncertainties faced by students, teachers, and the entire educational community . Therefore, examining and enhancing MHL within the educational context is imperative. This investigation addresses a noticeable void in current research, specifically the lack of focus on modifiable factors related to MHL that can be influenced through targeted educational interventions. While previous studies have delved into non-modifiable factors such as age, gender, and prior exposure to mental health issues , there is a significant research gap when it comes to comprehensively analyzing factors that can be modified and improved through intentional educational strategies. By addressing this research gap, this systematic review aims to identify potentially modifiable predictors of MHL in the educational context. It emphasizes the critical importance of these modifiable predictors, providing actionable insights to guide the design of educational interventions aimed at enhancing MHL within educational institutions. By clarifying these modifiable predictors, this research provides a roadmap for educational institutions to customize interventions that address areas of MHL deficiency among students and faculty. These interventions have the potential to nurture a culture of understanding, empathy, and support for mental health issues within educational environments. In doing so, this research aims to make a meaningful contribution to the cultivation of healthier and more mentally literate educational environments.
Search strategy In accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) , an extensive search was carried out to identify relevant articles published between 2019 and October 2023. A systematic search was conducted across global databases (PubMed, SCOPUS, PsycINFO and ERIC), as well as regional databases (TCI and Vietnamese Database), to capture a diverse range of studies relevant to MHL within educational contexts. This approach ensures comprehensive coverage while considering the specific geographical and cultural context of the research. These search terms included a combination of terms related to predictors, factors, associations, or relationships, along with terms related to MHL, which were developed following the conceptualization by Jorm and educational contexts. Once the search terms were established, they were adapted to suit the specific search language of each respective database. The search criteria included the following terms: (predictors OR factors OR association OR relationship) AND (mental health literacy) AND (education OR school OR university OR students OR teacher OR professor). Eligibility criteria and study selection The inclusion criteria were: (1) studies involving populations within an educational context, including but not limited to students (from primary to higher education levels), teachers, lecturers, professors, school administrators, counselors, and similar educational personnel; (2) studies containing quantitative data investigating potentially modifiable predictors related to MHL; (3) studies assessing MHL as an outcome measure using validated instruments or measures; and (4) studies published in peer-reviewed journals, available in English, Thai, or Vietnamese languages. The exclusion criteria were: (1) studies adopting a qualitative research design which may not provide suitable data for inclusion in a meta-analysis; (2) studies utilizing an experimental research design, which focuses on the intervention to enhance MHL; (3) studies with insufficient statistical data for meta-analysis, including missing and incomplete data on key variables relevant to the study’s objectives; or (4) studies omitting information about the educational institution of the participants, including details regarding the type of educational setting (e.g., primary school, university). Two authors (CS & PP) independently assessed the relevance of the study titles and abstracts to determine eligibility, and any disagreements were resolved through team discussion. Data extraction Information retrieval during data extraction included details such as the first author’s name, year of publication, country of origin, study participants, sample size, the instruments used to assess MHL, and the main findings. Two authors (CS & AJ) independently conducted the data extraction process, and their findings were cross-checked and harmonized through discussions. Consensus was achieved through ongoing discussion within the research team. Quality assessment The assessment of the quality of the included studies was conducted using the Appraisal tool for Cross-Sectional Studies (AXIS tool) . This tool comprises 20 questions that address various aspects of study design, reporting quality, and the risk of bias in cross-sectional studies. A score of 1 was assigned for each ‘yes’ response to a question, while a score of 0 was given for ‘no’ or ‘don’t know’ responses. Based on the total score represented as a percentage, the studies were categorized into one of three groups: high quality (above 80%), moderate quality (between 60% and 80%), or low quality (below 60%). The quality assessment for each study was independently evaluated by two authors (CS & UI). In cases where discrepancies arose in the ratings between the two authors, these differences were resolved through team discussions. Statistical analysis We conducted meta-analyses using effect sizes based on correlation coefficients between two continuous variables measuring MHL and the respective factor. The majority of the studies provided direct correlation coefficients (r). For those that presented different metrics, such as odds ratios, t-values, F-values, or standardized regression coefficient (β), we converted them into correlation coefficients. For this purpose, correlation coefficients are transformed into Fisher’s Z and estimated with 95% confidence intervals (CIs) using a random-effects model. To assess heterogeneity among the studies, we employed Cochrane’s Q test and I 2 statistics . Egger’s test was employed to assess the presence of publication bias. All statistical analyses were performed using RStudio software (v. 4.3.1), and the packages metafor .
In accordance with the guidelines outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) , an extensive search was carried out to identify relevant articles published between 2019 and October 2023. A systematic search was conducted across global databases (PubMed, SCOPUS, PsycINFO and ERIC), as well as regional databases (TCI and Vietnamese Database), to capture a diverse range of studies relevant to MHL within educational contexts. This approach ensures comprehensive coverage while considering the specific geographical and cultural context of the research. These search terms included a combination of terms related to predictors, factors, associations, or relationships, along with terms related to MHL, which were developed following the conceptualization by Jorm and educational contexts. Once the search terms were established, they were adapted to suit the specific search language of each respective database. The search criteria included the following terms: (predictors OR factors OR association OR relationship) AND (mental health literacy) AND (education OR school OR university OR students OR teacher OR professor).
The inclusion criteria were: (1) studies involving populations within an educational context, including but not limited to students (from primary to higher education levels), teachers, lecturers, professors, school administrators, counselors, and similar educational personnel; (2) studies containing quantitative data investigating potentially modifiable predictors related to MHL; (3) studies assessing MHL as an outcome measure using validated instruments or measures; and (4) studies published in peer-reviewed journals, available in English, Thai, or Vietnamese languages. The exclusion criteria were: (1) studies adopting a qualitative research design which may not provide suitable data for inclusion in a meta-analysis; (2) studies utilizing an experimental research design, which focuses on the intervention to enhance MHL; (3) studies with insufficient statistical data for meta-analysis, including missing and incomplete data on key variables relevant to the study’s objectives; or (4) studies omitting information about the educational institution of the participants, including details regarding the type of educational setting (e.g., primary school, university). Two authors (CS & PP) independently assessed the relevance of the study titles and abstracts to determine eligibility, and any disagreements were resolved through team discussion.
Information retrieval during data extraction included details such as the first author’s name, year of publication, country of origin, study participants, sample size, the instruments used to assess MHL, and the main findings. Two authors (CS & AJ) independently conducted the data extraction process, and their findings were cross-checked and harmonized through discussions. Consensus was achieved through ongoing discussion within the research team.
The assessment of the quality of the included studies was conducted using the Appraisal tool for Cross-Sectional Studies (AXIS tool) . This tool comprises 20 questions that address various aspects of study design, reporting quality, and the risk of bias in cross-sectional studies. A score of 1 was assigned for each ‘yes’ response to a question, while a score of 0 was given for ‘no’ or ‘don’t know’ responses. Based on the total score represented as a percentage, the studies were categorized into one of three groups: high quality (above 80%), moderate quality (between 60% and 80%), or low quality (below 60%). The quality assessment for each study was independently evaluated by two authors (CS & UI). In cases where discrepancies arose in the ratings between the two authors, these differences were resolved through team discussions.
We conducted meta-analyses using effect sizes based on correlation coefficients between two continuous variables measuring MHL and the respective factor. The majority of the studies provided direct correlation coefficients (r). For those that presented different metrics, such as odds ratios, t-values, F-values, or standardized regression coefficient (β), we converted them into correlation coefficients. For this purpose, correlation coefficients are transformed into Fisher’s Z and estimated with 95% confidence intervals (CIs) using a random-effects model. To assess heterogeneity among the studies, we employed Cochrane’s Q test and I 2 statistics . Egger’s test was employed to assess the presence of publication bias. All statistical analyses were performed using RStudio software (v. 4.3.1), and the packages metafor .
Characteristics of included studies In this systematic review, database searches were performed, revealing a total of 3747 articles. After removing duplicates, 2224 articles underwent screening, and 60 were subjected to full-text review. Finally, 21 studies met the eligibility criteria. Primary reasons for exclusion included studies not conducted in educational settings, inadequate statistical data, and non-modifiable variables. This process is summarized in Fig. . The studies involved a diverse range of participants, including university students ( n = 12), teachers ( n = 5), secondary and high school students ( n = 3), and a mix of university and secondary school students ( n = 1). The majority of participants were female. Most studies utilized mental health literacy scale as outcomes. The majority of the research ( n = 18) was conducted in middle-income countries like China, Malaysia, Taiwan, Thailand, and others. A small number of studies ( n = 3) were carried out in both low- and high-income countries. Primary research settings included universities ( n = 12), followed by secondary and high schools ( n = 5), among others. All included studies underwent peer review, and their quality was assessed using the AXIS tool. Rating indicated high quality for 7 studies, moderate for 11 studies, and low for 3 studies. A summary of study characteristics is presented in Table . Modifiable predictors of MHL In total of 21 studies, we identified more than 20 potentially modifiable predictors of MHL in an educational context. However, we specifically conducted random-effects meta-analyses for those potentially modifiable predictors reported in more than two studies to assess the strength of the association between these predictors and MHL. Any predictor mentioned in only one study was excluded from the pooled effect size analysis in this study, or if the reported data could not be converted to the effect size ( r ). Consequently, we performed eight meta-analyses to explore the association between modifiable predictors (Stigma toward professional help, stigma toward mental illness, self-efficacy, seeking help from mental health professionals, attitudes toward help-seeking, social support, positive psychological states, receiving mental health training, and psychological distress) and MHL within educational contexts (Table ). Stigma toward professional help Three studies investigated the correlation between stigma toward professional help and MHL (Fig. ). The pooled correlation resulted in a significant negative finding, with r = -0.33 [95% CI : -0.45, -0.19]. The Q -test revealed substantial heterogeneity among the studies ( Q (2) = 8.98, p = 0.011, I 2 = 77.7%). Nevertheless, Egger’s test did not show significance, indicating no presence of publication bias. Stigma toward mental illness Three studies investigated the correlation between stigma toward mental illness and MHL (Fig. ). The pooled correlation produced a non-significant outcome, with r = 0.00 [95% CI : -0.13, 0.14]. The Q -test revealed significant heterogeneity among the studies ( Q (2) = 10.30, p = 0.006, I 2 = 80.6%). However, Egger’s test did not show significance, indicating no presence of publication bias. Self-efficacy Four studies investigated the correlation between self-efficacy and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.24 [95% CI : 0.18, 0.30]. The Q -test showed no heterogeneity among the studies ( Q (3) = 6.64, p = 0.085, I 2 = 54.8%). However, Egger’s test indicated significance, suggesting the potential presence of publication bias. Seeking help from mental health professionals Four studies investigated the correlation between seeking help from mental health professionals and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.29 [95% CI : 0.25, 0.34]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 0.27, p = 0.966, I 2 = 0.0%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias. Attitudes toward help-seeking Four studies investigated the correlation between attitudes toward help-seeking and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.30 [95% CI : 0.00, 0.55]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 120.29, p = 0.000, I 2 = 97.5%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias. Social support Five studies investigated the correlation between social support and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.41 [95% CI : 0.05, 0.68]. The Q -test indicated substantial heterogeneity among the studies ( Q (4) = 748.26, p = 0.000, I 2 = 99.5%). However, Egger’s test did not show significance, indicating no presence of publication bias. Positive psychological states Four studies investigated the correlation between positive psychological states and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.37 [95% CI : 0.30, 0.43]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 9.75, p = 0.021, I 2 = 69.2%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias. Receiving mental health training Four studies investigated the correlation between receiving mental health training and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.33 [95% CI : 0.18, 0.47]. The Q -test indicated substantial heterogeneity among the studies ( Q (3) = 31.57, p = 0.000, I 2 = 90.5%). However, Egger’s test did not show significance, suggesting no presence of publication bias. Psychological distress Four studies investigated the correlation between psychological distress and MHL (Fig. ). The pooled correlation resulted in a significant negative outcome, with r = -0.39 [95% CI : -0.47, -0.30]. The Q -test indicated substantial heterogeneity among the studies ( Q (3) = 45.56, p = 0.000, I 2 = 93.4%). However, Egger’s test did not show significance, suggesting no presence of publication bias. Impact of modifiable predictors on MHL The effect size for each modifiable predictor varied between − 0.39 and 0.41. Social support emerged as the most influential predictor, positively impacting MHL, followed by positive psychological states, received mental health training, attitudes towards help seeking, seeking help from mental health professionals, and self-efficacy. In contrast, psychological distress was identified as the most significant predictor with a negative impact on MHL, followed by stigma towards professional help. However, the effect size for stigma towards mental illness was not statistically significant.
In this systematic review, database searches were performed, revealing a total of 3747 articles. After removing duplicates, 2224 articles underwent screening, and 60 were subjected to full-text review. Finally, 21 studies met the eligibility criteria. Primary reasons for exclusion included studies not conducted in educational settings, inadequate statistical data, and non-modifiable variables. This process is summarized in Fig. . The studies involved a diverse range of participants, including university students ( n = 12), teachers ( n = 5), secondary and high school students ( n = 3), and a mix of university and secondary school students ( n = 1). The majority of participants were female. Most studies utilized mental health literacy scale as outcomes. The majority of the research ( n = 18) was conducted in middle-income countries like China, Malaysia, Taiwan, Thailand, and others. A small number of studies ( n = 3) were carried out in both low- and high-income countries. Primary research settings included universities ( n = 12), followed by secondary and high schools ( n = 5), among others. All included studies underwent peer review, and their quality was assessed using the AXIS tool. Rating indicated high quality for 7 studies, moderate for 11 studies, and low for 3 studies. A summary of study characteristics is presented in Table .
In total of 21 studies, we identified more than 20 potentially modifiable predictors of MHL in an educational context. However, we specifically conducted random-effects meta-analyses for those potentially modifiable predictors reported in more than two studies to assess the strength of the association between these predictors and MHL. Any predictor mentioned in only one study was excluded from the pooled effect size analysis in this study, or if the reported data could not be converted to the effect size ( r ). Consequently, we performed eight meta-analyses to explore the association between modifiable predictors (Stigma toward professional help, stigma toward mental illness, self-efficacy, seeking help from mental health professionals, attitudes toward help-seeking, social support, positive psychological states, receiving mental health training, and psychological distress) and MHL within educational contexts (Table ).
Three studies investigated the correlation between stigma toward professional help and MHL (Fig. ). The pooled correlation resulted in a significant negative finding, with r = -0.33 [95% CI : -0.45, -0.19]. The Q -test revealed substantial heterogeneity among the studies ( Q (2) = 8.98, p = 0.011, I 2 = 77.7%). Nevertheless, Egger’s test did not show significance, indicating no presence of publication bias.
Three studies investigated the correlation between stigma toward mental illness and MHL (Fig. ). The pooled correlation produced a non-significant outcome, with r = 0.00 [95% CI : -0.13, 0.14]. The Q -test revealed significant heterogeneity among the studies ( Q (2) = 10.30, p = 0.006, I 2 = 80.6%). However, Egger’s test did not show significance, indicating no presence of publication bias.
Four studies investigated the correlation between self-efficacy and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.24 [95% CI : 0.18, 0.30]. The Q -test showed no heterogeneity among the studies ( Q (3) = 6.64, p = 0.085, I 2 = 54.8%). However, Egger’s test indicated significance, suggesting the potential presence of publication bias.
Four studies investigated the correlation between seeking help from mental health professionals and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.29 [95% CI : 0.25, 0.34]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 0.27, p = 0.966, I 2 = 0.0%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias.
Four studies investigated the correlation between attitudes toward help-seeking and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.30 [95% CI : 0.00, 0.55]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 120.29, p = 0.000, I 2 = 97.5%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias.
Five studies investigated the correlation between social support and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.41 [95% CI : 0.05, 0.68]. The Q -test indicated substantial heterogeneity among the studies ( Q (4) = 748.26, p = 0.000, I 2 = 99.5%). However, Egger’s test did not show significance, indicating no presence of publication bias.
Four studies investigated the correlation between positive psychological states and MHL (Fig. ). The pooled correlation resulted in a significant positive outcome, with r = 0.37 [95% CI : 0.30, 0.43]. The Q -test indicated considerable heterogeneity among the studies ( Q (3) = 9.75, p = 0.021, I 2 = 69.2%). Nevertheless, Egger’s test did not show significance, suggesting no presence of publication bias.
Four studies investigated the correlation between receiving mental health training and MHL (Fig. ). The pooled correlation resulted in a significant positive finding, with r = 0.33 [95% CI : 0.18, 0.47]. The Q -test indicated substantial heterogeneity among the studies ( Q (3) = 31.57, p = 0.000, I 2 = 90.5%). However, Egger’s test did not show significance, suggesting no presence of publication bias.
Four studies investigated the correlation between psychological distress and MHL (Fig. ). The pooled correlation resulted in a significant negative outcome, with r = -0.39 [95% CI : -0.47, -0.30]. The Q -test indicated substantial heterogeneity among the studies ( Q (3) = 45.56, p = 0.000, I 2 = 93.4%). However, Egger’s test did not show significance, suggesting no presence of publication bias.
The effect size for each modifiable predictor varied between − 0.39 and 0.41. Social support emerged as the most influential predictor, positively impacting MHL, followed by positive psychological states, received mental health training, attitudes towards help seeking, seeking help from mental health professionals, and self-efficacy. In contrast, psychological distress was identified as the most significant predictor with a negative impact on MHL, followed by stigma towards professional help. However, the effect size for stigma towards mental illness was not statistically significant.
In this systematic review, we meticulously examined existing quantitative evidence on modifiable predictors influencing MHL in educational settings. Our primary goal was to identify areas for improvement and lay the foundation for robust early interventions in mental health within educational contexts. Our findings highlighted consistent associations between MHL and various factors, including stigma toward professional help, self-efficacy, attitudes toward help-seeking, social support, positive psychological states, receiving mental health training, and psychological distress. Importantly, no significant association was found between stigma toward mental illness and MHL. Stigma toward professional help Our analysis confirmed a negative association between stigma toward professional help and MHL, aligning with prior research . Individuals with stigmatizing views on seeking support from mental health professionals exhibited lower MHL in educational contexts. This resistance to seeking professional health assistance highlights the necessity for tailored interventions within educational institutions aimed at enhancing MHL and destigmatize professional help-seeking behaviors. Anti-stigma interventions, such as psychoeducation and contact-based learning, have proven effective in reducing stigma and enhancing MHL in educational environments . By implementing targeted interventions that address stigma toward professional help, educational institutions can play a pivotal role in creating an atmosphere where mental health is prioritized. These interventions should go beyond merely providing information; they should actively work to change perceptions and attitudes related to mental health support. Through comprehensive mental health education covering various mental health conditions, symptoms, and available treatments, as well as the launch of stigma reduction campaigns that challenge negative stereotypes surrounding mental health issues, institutions can contribute to breaking down barriers to seeking professional help, ultimately fostering a more mentally health-literate community. Self-efficacy The significant positive relationship between self-efficacy and MHL highlights the importance of self-efficacy in seeking help within educational settings. Individuals with higher self-efficacy are more likely to possess improved MHL, especially in seeking assistance for mental health-related issues. Nurturing self-efficacy in seeking help becomes a crucial aspect of comprehensive mental health education in educational environments . Self-efficacy refers to an individual’s belief in their capacity to execute actions necessary to achieve specific goals . In the context of mental health, fostering self-efficacy involves instilling confidence in individuals to take proactive steps in addressing their mental health needs. When individuals feel capable and confident in their ability to seek assistance, they are more likely to take proactive steps to address mental health challenges. However, barriers like lack of self-efficacy may impede individuals from seeking help, hindering progress towards MHL and well-being. Integrating self-efficacy-focused interventions into mental health education curricula empowers individuals to actively engage with mental health resources, contributing to a supportive and mentally health-literate educational community. This cultivates an environment where mental health is openly discussed, reducing stigma and promoting a culture of support and understanding. Seeking help from mental health professionals The significant positive correlation between seeking help from mental health professionals emphasizes the importance of encouraging help-seeking behaviors in comprehensive mental health education. Consistent with previous studies , individuals who actively seek assistance from mental health professionals are more likely to possess a better understanding of mental health issues, their own mental well-being, and the available avenues for support and treatment. Encouraging help-seeking behaviors can take various forms within the educational environment. Educational programs and interventions aimed at supporting students and staff in reaching out to mental health professionals play a crucial role in fostering proactive engagement with mental health. One potential barrier to implementing these changes is individuals’ reluctance to seek assistance from mental health professionals, often due to stigma, fear of judgment, or lack of awareness about available resources. These initiatives may involve workshops covering topics such as recognizing mental health concerns, understanding available resources, and navigating the mental health support system. Additionally, providing easily accessible resources on mental health support services and self-help materials through online platforms and educational support centers ensure individuals have the necessary information to seek assistance when facing mental health challenges. Such programs contribute not only to individual well-being but also to the broader goal of developing a more mentally health-literate educational community . Attitudes toward help seeking The significant positive correlation between attitudes toward help-seeking and MHL reveals insights into the dynamics of MHL within educational contexts. Consistent with previous studies , positive attitudes toward seeking help are associated with higher levels of MHL. Understanding and cultivating these positive attitudes within educational institutions can play a pivotal role in shaping a more mentally health-literate community . Educational interventions and programs play a crucial role in cultivating positive attitudes toward help-seeking. One potential barrier in this scenario revolves around individuals who already possess positive attitudes toward help-seeking. They might not see the immediate need to actively engage in seeking further assistance or resources, as they perceived themselves as already well-informed about mental health issues. Initiatives that aim to reduce stigma, dispel myths surrounding mental health, and promote positive beliefs about seeking assistance are integral components of mental health education. These efforts contribute to the creation of a supportive and understanding environment, encouraging individuals to actively engage with mental health resources and seek help when needed. Social support Our analysis uncovered a significant positive correlation between social support and MHL, highlighting the influential role of interpersonal relationships in shaping individuals’ mental health awareness. Consistent with previous studies , individuals receiving social support tend to have higher levels of MHL. Understanding the positive impact of social support on MHL opens avenues for educators and policymakers to consider targeted interventions that foster a supportive social environment within educational contexts. Potential barriers include a lack of resources; educational institutions may encounter limitations in terms of funding, staffing, or infrastructure to develop and sustain programs. Additionally, there may be resistance from certain stakeholders within the educational community, such as administrators, teachers, or students, who may resist changes in policies or practices. One effective strategy involves enhancing peer relationships through structured programs and activities. Peer support initiatives, mentorship programs, and community-building activities create opportunities for students to connect with one another, share experiences, and offer mutual support. These initiatives not only contribute to students’ overall well-being but also play a crucial role in fostering a mentally health-literate educational community . Positive psychological states The significant positive correlation between positive psychological states and MHL emphasizes the substantial contribution of these characteristics to the development of a more mentally health-literate educational community. Consistent with previous studies, individuals with positive psychological states tend to have higher levels of MHL . The recognition of the positive impact of these states provides educational institutions with valuable insights to advocate for the integration of mental health education into curricula. Emphasizing the cultivation of positive psychological states becomes a key aspect of a comprehensive approach to MHL . Designing curriculum modules focused on a positive psychology approach represents a proactive and empowering strategy for enhancing MHL in educational contexts. These modules provide an opportunity for students to explore and develop positive psychological states such as resilience, mindfulness, and enthusiasm. By participating in engaging activities such as group projects, role-playing scenarios, and case studies, along with reflective exercises like journaling and self-assessments, and through fostering open discussions in class, students can enhance their understanding of these states and apply them in real-life situations. This not only contributes to improved MHL but also equips students with valuable life skills that extend beyond the educational setting. One potential barrier is the resistance to adopting new teaching methodologies or content. Educators or institutions may be accustomed to traditional approaches to mental health education and may be hesitant to embrace newer, positive psychology-focused methods. Overcoming these barriers may require comprehensive training and professional development for educators, clear communication about the benefits of positive psychology approaches, and collaboration with relevant stakeholders to ensure buy-in and support for implementation. Receiving mental health training The significant positive correlation between receiving mental health training and MHL highlights the pivotal role of training programs in fostering a mentally health-literate community. Advocating for structured mental health training programs in educational settings, covering topics such as mental health awareness, coping strategies, and destigmatization, can equip students and staff with the knowledge and skills to navigate mental health challenges effectively . Advocating for the integration of mental health training into educational curricula recognizes the transformative impact these programs can have on the overall well-being of the community. It aligns with a proactive approach to mental health, emphasizing prevention, early intervention, and the cultivation of a supportive culture. One potential barrier is the challenge of prioritizing mental health education among competing academic and institutional priorities. Educational institutions may face pressure to allocate resources and time to other areas of study, potentially relegating mental health training to a lower priority. Additionally, there may be resistance from stakeholders who perceive mental health training as unnecessary or unrelated to academic achievement. Addressing this barrier requires effective advocacy efforts to demonstrate the importance of mental health training in promoting overall well-being and academic success. This may involve providing evidence-based research on the benefits of mental health education, engaging with decision-makers to gain their support, and fostering a culture that values mental health and wellness within the educational community. Acknowledging the role of training in curricula signals a commitment to creating an informed, empathetic, and mentally health-literate educational environment. Psychological distress The significant negative correlation between psychological distress and MHL sheds light on the intricate relationship between psychological distress and the ability to comprehend and respond to mental health issues. Previous studies suggest that students experiencing higher levels of psychological distress may face challenges in understanding and addressing mental health concerns. Integrating mental health support services, coping mechanisms, and stress management strategies into educational programs contributes to a comprehensive approach to fostering MHL, emphasizing sensitivity to students’ mental well-being. For example, students facing elevated psychological distress may encounter barriers to engaging with and comprehending mental health information . The emotional and cognitive burden associated with distress can impede the capacity to absorb and apply concepts related to mental health, potentially leading to a reduced ability to recognize signs of distress in oneself or others. Furthermore, individuals experiencing psychological distress may be less inclined to seek help or participate in mental health programs due to feelings of shame, embarrassment, or stigma surrounding their mental health challenges. They may also fear judgment from peers or staff, leading them to withdraw or avoid seeking support altogether. This emphasizes the need for educational institutions to be proactive in addressing the mental health needs of students, especially during periods of heightened psychological distress. Each modifiable predictor identified can be theoretically grounded in the Ecological Systems Theory , which explores the dynamic interplay between individuals and their social, cultural, and environmental surroundings. Within this theoretical framework, modifiable predictors of MHL in educational contexts––such as social support networks, institutional policies, and cultural attitudes toward mental health––can be analyzed. This perspective allows for an examination of how these factors shape individuals’ MHL within educational settings. By adopting this approach, researchers and educators can gain a comprehensive understanding of the factors influencing MHL in educational contexts., facilitating the development of interventions that target modifiable predictors across multiple levels of the ecological system. Ultimately, this approach aims to foster positive mental health outcomes among students and enhance the overall well-being of the educational community.
Our analysis confirmed a negative association between stigma toward professional help and MHL, aligning with prior research . Individuals with stigmatizing views on seeking support from mental health professionals exhibited lower MHL in educational contexts. This resistance to seeking professional health assistance highlights the necessity for tailored interventions within educational institutions aimed at enhancing MHL and destigmatize professional help-seeking behaviors. Anti-stigma interventions, such as psychoeducation and contact-based learning, have proven effective in reducing stigma and enhancing MHL in educational environments . By implementing targeted interventions that address stigma toward professional help, educational institutions can play a pivotal role in creating an atmosphere where mental health is prioritized. These interventions should go beyond merely providing information; they should actively work to change perceptions and attitudes related to mental health support. Through comprehensive mental health education covering various mental health conditions, symptoms, and available treatments, as well as the launch of stigma reduction campaigns that challenge negative stereotypes surrounding mental health issues, institutions can contribute to breaking down barriers to seeking professional help, ultimately fostering a more mentally health-literate community.
The significant positive relationship between self-efficacy and MHL highlights the importance of self-efficacy in seeking help within educational settings. Individuals with higher self-efficacy are more likely to possess improved MHL, especially in seeking assistance for mental health-related issues. Nurturing self-efficacy in seeking help becomes a crucial aspect of comprehensive mental health education in educational environments . Self-efficacy refers to an individual’s belief in their capacity to execute actions necessary to achieve specific goals . In the context of mental health, fostering self-efficacy involves instilling confidence in individuals to take proactive steps in addressing their mental health needs. When individuals feel capable and confident in their ability to seek assistance, they are more likely to take proactive steps to address mental health challenges. However, barriers like lack of self-efficacy may impede individuals from seeking help, hindering progress towards MHL and well-being. Integrating self-efficacy-focused interventions into mental health education curricula empowers individuals to actively engage with mental health resources, contributing to a supportive and mentally health-literate educational community. This cultivates an environment where mental health is openly discussed, reducing stigma and promoting a culture of support and understanding.
The significant positive correlation between seeking help from mental health professionals emphasizes the importance of encouraging help-seeking behaviors in comprehensive mental health education. Consistent with previous studies , individuals who actively seek assistance from mental health professionals are more likely to possess a better understanding of mental health issues, their own mental well-being, and the available avenues for support and treatment. Encouraging help-seeking behaviors can take various forms within the educational environment. Educational programs and interventions aimed at supporting students and staff in reaching out to mental health professionals play a crucial role in fostering proactive engagement with mental health. One potential barrier to implementing these changes is individuals’ reluctance to seek assistance from mental health professionals, often due to stigma, fear of judgment, or lack of awareness about available resources. These initiatives may involve workshops covering topics such as recognizing mental health concerns, understanding available resources, and navigating the mental health support system. Additionally, providing easily accessible resources on mental health support services and self-help materials through online platforms and educational support centers ensure individuals have the necessary information to seek assistance when facing mental health challenges. Such programs contribute not only to individual well-being but also to the broader goal of developing a more mentally health-literate educational community .
The significant positive correlation between attitudes toward help-seeking and MHL reveals insights into the dynamics of MHL within educational contexts. Consistent with previous studies , positive attitudes toward seeking help are associated with higher levels of MHL. Understanding and cultivating these positive attitudes within educational institutions can play a pivotal role in shaping a more mentally health-literate community . Educational interventions and programs play a crucial role in cultivating positive attitudes toward help-seeking. One potential barrier in this scenario revolves around individuals who already possess positive attitudes toward help-seeking. They might not see the immediate need to actively engage in seeking further assistance or resources, as they perceived themselves as already well-informed about mental health issues. Initiatives that aim to reduce stigma, dispel myths surrounding mental health, and promote positive beliefs about seeking assistance are integral components of mental health education. These efforts contribute to the creation of a supportive and understanding environment, encouraging individuals to actively engage with mental health resources and seek help when needed.
Our analysis uncovered a significant positive correlation between social support and MHL, highlighting the influential role of interpersonal relationships in shaping individuals’ mental health awareness. Consistent with previous studies , individuals receiving social support tend to have higher levels of MHL. Understanding the positive impact of social support on MHL opens avenues for educators and policymakers to consider targeted interventions that foster a supportive social environment within educational contexts. Potential barriers include a lack of resources; educational institutions may encounter limitations in terms of funding, staffing, or infrastructure to develop and sustain programs. Additionally, there may be resistance from certain stakeholders within the educational community, such as administrators, teachers, or students, who may resist changes in policies or practices. One effective strategy involves enhancing peer relationships through structured programs and activities. Peer support initiatives, mentorship programs, and community-building activities create opportunities for students to connect with one another, share experiences, and offer mutual support. These initiatives not only contribute to students’ overall well-being but also play a crucial role in fostering a mentally health-literate educational community .
The significant positive correlation between positive psychological states and MHL emphasizes the substantial contribution of these characteristics to the development of a more mentally health-literate educational community. Consistent with previous studies, individuals with positive psychological states tend to have higher levels of MHL . The recognition of the positive impact of these states provides educational institutions with valuable insights to advocate for the integration of mental health education into curricula. Emphasizing the cultivation of positive psychological states becomes a key aspect of a comprehensive approach to MHL . Designing curriculum modules focused on a positive psychology approach represents a proactive and empowering strategy for enhancing MHL in educational contexts. These modules provide an opportunity for students to explore and develop positive psychological states such as resilience, mindfulness, and enthusiasm. By participating in engaging activities such as group projects, role-playing scenarios, and case studies, along with reflective exercises like journaling and self-assessments, and through fostering open discussions in class, students can enhance their understanding of these states and apply them in real-life situations. This not only contributes to improved MHL but also equips students with valuable life skills that extend beyond the educational setting. One potential barrier is the resistance to adopting new teaching methodologies or content. Educators or institutions may be accustomed to traditional approaches to mental health education and may be hesitant to embrace newer, positive psychology-focused methods. Overcoming these barriers may require comprehensive training and professional development for educators, clear communication about the benefits of positive psychology approaches, and collaboration with relevant stakeholders to ensure buy-in and support for implementation.
The significant positive correlation between receiving mental health training and MHL highlights the pivotal role of training programs in fostering a mentally health-literate community. Advocating for structured mental health training programs in educational settings, covering topics such as mental health awareness, coping strategies, and destigmatization, can equip students and staff with the knowledge and skills to navigate mental health challenges effectively . Advocating for the integration of mental health training into educational curricula recognizes the transformative impact these programs can have on the overall well-being of the community. It aligns with a proactive approach to mental health, emphasizing prevention, early intervention, and the cultivation of a supportive culture. One potential barrier is the challenge of prioritizing mental health education among competing academic and institutional priorities. Educational institutions may face pressure to allocate resources and time to other areas of study, potentially relegating mental health training to a lower priority. Additionally, there may be resistance from stakeholders who perceive mental health training as unnecessary or unrelated to academic achievement. Addressing this barrier requires effective advocacy efforts to demonstrate the importance of mental health training in promoting overall well-being and academic success. This may involve providing evidence-based research on the benefits of mental health education, engaging with decision-makers to gain their support, and fostering a culture that values mental health and wellness within the educational community. Acknowledging the role of training in curricula signals a commitment to creating an informed, empathetic, and mentally health-literate educational environment.
The significant negative correlation between psychological distress and MHL sheds light on the intricate relationship between psychological distress and the ability to comprehend and respond to mental health issues. Previous studies suggest that students experiencing higher levels of psychological distress may face challenges in understanding and addressing mental health concerns. Integrating mental health support services, coping mechanisms, and stress management strategies into educational programs contributes to a comprehensive approach to fostering MHL, emphasizing sensitivity to students’ mental well-being. For example, students facing elevated psychological distress may encounter barriers to engaging with and comprehending mental health information . The emotional and cognitive burden associated with distress can impede the capacity to absorb and apply concepts related to mental health, potentially leading to a reduced ability to recognize signs of distress in oneself or others. Furthermore, individuals experiencing psychological distress may be less inclined to seek help or participate in mental health programs due to feelings of shame, embarrassment, or stigma surrounding their mental health challenges. They may also fear judgment from peers or staff, leading them to withdraw or avoid seeking support altogether. This emphasizes the need for educational institutions to be proactive in addressing the mental health needs of students, especially during periods of heightened psychological distress. Each modifiable predictor identified can be theoretically grounded in the Ecological Systems Theory , which explores the dynamic interplay between individuals and their social, cultural, and environmental surroundings. Within this theoretical framework, modifiable predictors of MHL in educational contexts––such as social support networks, institutional policies, and cultural attitudes toward mental health––can be analyzed. This perspective allows for an examination of how these factors shape individuals’ MHL within educational settings. By adopting this approach, researchers and educators can gain a comprehensive understanding of the factors influencing MHL in educational contexts., facilitating the development of interventions that target modifiable predictors across multiple levels of the ecological system. Ultimately, this approach aims to foster positive mental health outcomes among students and enhance the overall well-being of the educational community.
The study highlights the contextual relevance of MHL within educational settings, acknowledging the intricate interplay of social, emotional, and intellectual development in schools, colleges, and universities. This contextualization not only enriches the analysis but also provides actionable insights for educational interventions, addressing a research gap by specifically focusing on modifiable factors related to MHL within educational environments. Despite these valuable contributions, several limitations warrant consideration. First, certain factors exhibited high heterogeneity, potentially influencing the robustness and generalizability of the meta-analysis findings. The diverse nature of educational contexts, including variations in cultural norms, educational systems, and demographic characteristics, may contribute to this heterogeneity. The study refrained from conducting a subgroup analysis due to the limited number of original studies, highlighting the need for future research to explore how contextual differences impact the associations between predictors and MHL. Second, the heterogeneity of the study population, encompassing a diverse range of participants from college students to teachers, emerges as a noteworthy limitation. While this diversity mirrors the intricate tapestry of educational environments, it introduces potential sources of variability that could impact the precision and generalizability of the study’s findings. Third, the majority of studies were conducted in middle-income countries, posing a challenge to the broad applicability of the findings across different socioeconomic contexts. Educational systems, cultural attitudes toward mental health, and the availability of mental health resources can vary significantly between countries and regions. Future research should strive for a more globally representative sample to enhance the external validity of the study’s conclusions. Fourth, potential biases in study selection might have influenced the overall bias, particularly if certain studies were omitted due to specific characteristics like educational contexts. Future research should consider broader criteria for selecting studies, including a wider array of educational settings and populations. This would help ensure that the results are more inclusive and applicable to diverse populations. Fifth, there is significant variability in how MHL is measured within educational contexts. Different studies employ diverse assessment tools, resulting in inconsistencies and challenges in synthesizing findings across studies. Future research should prioritize the development and validation of standardized measurement tools tailored specifically for assessing MHL in educational contexts. Finally, the study is based on correlational data, emphasizing the need for prudence when deducing a cause-and-effect connection between modifiable predictors and MHL. To characterize this association as causal, more robust research methodologies are needed, incorporating longitudinal or repeated assessment of MHL alongside potentially modifiable predictors. Additionally, longitudinal studies to assess the impact of interventions derived from modifiable predictors on MHL over time are also essential.
This systematic review aimed to fill the existing research gap concerning modifiable predictors influencing MHL in educational settings. The study identified and examined potential predictors associated with MHL, including stigma toward professional help, self-efficacy, attitudes toward help seeking, social support, positive psychological states, receiving mental health training, and psychological distress. By addressing these factors, educational institutions can strive to cultivate communities that are adept in mental health, fostering an environment characterized by empathy, understanding, and proactive engagement in addressing mental health issues. The implications extend beyond individual well-being, reaching into the establishment of inclusive, safe, and supportive learning environments within educational institutions. The study’s findings serve as a foundation for future research, policy development, and the implementation of practical strategies aimed at enhancing MHL in diverse educational settings.
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Developing intervention fidelity strategies for a behaviour change intervention delivered in primary care dental practices: the RETURN fidelity strategy | dec20632-7507-42f2-ba14-d8ce6942773e | 11831780 | Dentistry[mh] | Monitoring the implementation of behaviour change interventions (BCIs) according to their intended protocols is essential for the accurate interpretation of healthcare trial results . Failure to prevent unintended deviations from BCI protocols increases the risk of methodological errors, leading to uncertainties in the interpretation of results . Specifically, poor monitoring of BCI implementation can result in Type I errors, where trial results falsely indicate an intervention’s effectiveness due to unauthorised additions or omissions of key components. Type II errors occur when a genuine effect is not detected for similar reasons, and Type III errors arise when incorrect conclusions about BCI effectiveness are drawn due to discrepancies between the intended and delivered interventions . To mitigate unintended outcomes in trials testing BCIs, it is crucial to implement strategies that enhance both internal and external validity . This ensures that conclusions drawn are unequivocally attributable to the BCI rather than extraneous factors . The complexity and multi-component nature of BCIs present specific challenges in achieving scientific rigour, as isolating the effect of each component and ensuring consistent implementation across various contexts is difficult . Intervention fidelity, also known as treatment fidelity, is a critical methodological tool in addressing these challenges within randomised controlled trials (RCTs) . One conceptualisation of intervention fidelity tailored to BCIs is the National Institutes of Health Behavior Change Consortium (BCC) treatment fidelity framework . The BCC defines intervention fidelity as “the methodological strategies and practices used to enhance and monitor the reliability and validity of behavioural interventions” . The framework provides a structured set of strategies for researchers to enhance fidelity practices during the development and testing of BCIs, particularly when these interventions are delivered in real-world environments by healthcare professionals . This approach ensures consistent and effective implementation across different settings. The BCC fidelity framework encompasses five domains: design, training, delivery, receipt, and enactment, with each domain offering specific strategies to enhance fidelity within that area . Table provides an overview of how the strategies recommended by the BCC enhance intervention fidelity within each domain. The recent iteration of the Medical Research Council’s (MRC) guidance on the development and evaluation of complex interventions underscores the necessity for a flexible, iterative, and context-dependent approach to ensure that research findings are applicable and beneficial to real-world settings . The framework specifically emphasises the value of transitioning between research phases, allowing for the integration of new insights and the refinement of interventions to optimise outcomes . Feasibility studies play a crucial role in this iterative process, enabling researchers to identify and address potential implementation challenges, assess recruitment and retention rates, and test the practicality of procedures on a smaller scale before advancing to full-scale evaluations . Accordingly, it is essential that the refinement of intervention fidelity strategies is embedded within the outcomes of feasibility studies, with a particular focus on context-dependent factors and the incorporation of relevant stakeholder perspectives . The primary dental care setting poses distinct challenges for implementing BCI trials, and dental trials often lack methodological rigor, resulting in ambiguous findings . Several factors contribute to these challenges. The decentralised nature of primary care dental practices, which often function as independent business entities, complicates the standardisation and coordination necessary across multiple study sites . Additionally, the significant variability in patient populations within dental practices hampers the development of uniform research protocols . The busy and high-demand environment of dental practices also restricts the time available for dental teams to participate in research activities , thereby affecting the feasibility of conducting methodologically rigorous studies. Whilst many of these challenges could apply to other primary care settings (i.e. General Practice), the primary dental care setting within the United Kingdom (UK) is also an untapped research setting suggesting dental personnel are relatively inexperienced in research delivery further adding to the challenges of delivering robust research. To address these issues, enhancing intervention fidelity strategies in trials testing BCIs within primary dental care settings may be a viable solution. However, a recent scoping review revealed that little emphasis has been placed on the development and implementation of robust fidelity strategies in this field to date . Implementing these strategies could potentially improve the reliability and consistency of outcomes in BCI trials conducted in primary dental care settings. Accordingly, this paper aims to describe the development of a comprehensive intervention fidelity strategy for implementation in a RCT (inteRventions to rEduce inequaliTies in the Uptake of Routine deNtal care RCT – the RETURN main trial) which assesses a BCI delivered within primary dental care settings. Drawing upon principles outlined in the BCC framework, the strategy’s development has been informed by insights gathered from the RETURN feasibility study. Ethics Ethical approval was obtained from Bromley Research Ethics Committee (19/LO/1510). Research governance approvals were obtained from the Health Research Authority (reference 265789), and sponsorship was provided by the University of Liverpool (reference UoL001354). All data used were accessed only by authorised study members and were stored in a secure location in accordance with ethical requirements. Procedures The RETURN intervention The RETURN intervention is a single-session, brief psychological intervention delivered by dental nurses in urgent dental care settings. Its primary objective is to support patients who only use dental services when they have an urgent problem. By assisting patients in identifying and overcoming barriers to routine dental visits, the intervention aims to promote regular, planned dental care, thereby improving oral health outcomes. The intervention is multifaceted and comprises several components delivered opportunistically to patients attending an urgent dental appointment. It leverages a “teachable moment” approach . A comprehensive description of the intervention has been detailed elsewhere . Briefly the intervention comprises two elements: A “patient pack” with behaviour change techniques embedded within the materials. The pack comprises: Six booklets addressing common barriers to routine dental visiting (cost, time constraints, not thinking to go when not in pain, distrust of dentists, embarrassment, and anxiety). Corresponding barrier videos featuring dental patients sharing their experiences of overcoming barriers, augmented with engaging animations. These videos were created specifically to resonate with the trial population. A written goal and action plan completed during the intervention session, targeting one barrier. Additional materials and booklets intended for post-appointment use at home, encouraging routine dental visiting. These include practical aids such as breathing exercises for anxious patients, contact information for dental services, and an “employer card” endorsing routine dental attendance. Access to a study website via a personal login where all intervention materials can be viewed. 2) A structured conversation facilitated by trained dental nurses . The conversation guides patients through the intervention process, utilising empathetic listening, non-judgmental, and non-directive dialogue. Its dual purpose is to enhance participant engagement by tailoring discussions to individual experiences whilst ensuring interaction with key intervention components. The RETURN feasibility study The RETURN feasibility study was a parallel group, two-arm, RCT that aimed to recruit 60 patients. Its primary objective was to assess the feasibility of conducting a larger RCT (the RETURN main trial) within urgent dental care settings to evaluate the RETURN intervention. Patients were allocated to either receive no intervention (usual care at the recruiting urgent dental care site) or the RETURN intervention. The study was conducted in Merseyside, North-West England in the UK in three site types: (1) an urgent clinic in a Teaching Dental Hospital (2), an out-of-hours urgent dental care service, and (3) an urgent clinic in an in-hours dental practice. Each site put forward dental nurses to be trained for one hour in Good Clinical Practice principles and for two hours in study procedures and intervention delivery. Training sessions were didactic, with opportunities to role play intervention deliveries and were conducted either at the University of Liverpool or at site. During the recruitment period (January 2020 to March 2020), routine dental care appointments for new National Health Service (NHS) patients were readily available in the region. Recruitment ceased abruptly due to the COVID-19 pandemic, resulting in the enrolment of 28 patients, approximately halfway to the target. Follow-up was achieved for 82% of the patients via telephone, email, or post, four months post-recruitment. Feasibility measures included primary outcome data completion rates, recruitment rates, and fidelity. A comprehensive study description and results have been published elsewhere . Briefly, despite premature termination, the results were considered sufficient to warrant proceeding to a full-scale RCT, with the addition of an internal pilot to monitor progress. Developing the fidelity strategies In alignment with MRC guidance on intervention refinement and Borrelli’s recommendation to pilot test interventions and incorporate feedback from participants and providers, the RETURN feasibility study provided an opportunity to develop fidelity strategies for the RETURN main trial. A total of 58 h of observations were conducted, covering the recruitment of 24 patients and 11 intervention delivery sessions (the remaining 13 patients were allocated to the control arm, and therefore, no intervention delivery was observed). Observation time also encompassed site set-up, informal discussions with dental nurses, and additional ad hoc training conversations throughout the study period. Field notes were recorded at the end of each day. Additionally, telephone semi-structured interviews were conducted with two dental nurses involved in delivering the feasibility study and 17 study patients. All dental nurses who were both trained and delivered the intervention were invited to be interviewed. This meant that numbers of dental nurses participating in interviews were limited because the onset of the COVID pandemic meant a refocusing of the dental workforce on purely clinical activity and so fewer nurses ( n = 2) delivered the intervention than were trained ( n = 9). This also resulted in a researcher recruiting patients at one site instead of dental nurses, but they were not approached to take part in this study. For pragmatic reasons, the 17 patients who responded to the RETURN feasibility study follow-up by telephone were invited to be interviewed ( n = 9 intervention & n = 8 control), all of whom agreed to take part. Interviews were audio-recorded and transcribed. Employing the Framework Method guided by the BCC recommendations and using a deductive approach to structure the coding framework in accordance with the components of the intervention, field notes and interview transcripts were analysed to pinpoint areas where fidelity could be strengthened for the RETURN man trial. Data underwent coding, charting, mapping, and verification across the entire dataset to inform the development of a robust fidelity strategy. In addition to the logic model which sets out the underlying mechanisms of the intervention materials as described in the intervention development publication , and recognising the two separate elements of the intervention (the “patient pack” and conversational element), we have produced an ‘operational model’ , to facilitate a complete assessment of intervention fidelity within the RETURN main trial . This can be found at Table . This operational model provides a scaffold for the intervention fidelity strategy and helped inform its design, by outlining which intervention activities should be present in an intervention conversation for it to be considered delivered as intended. From this model, many of the strategies contained in this manuscript were developed (for example, it guided the components featured in the RETURN fidelity checklist developed to monitor training and assess delivery fidelity, discussed within the ‘delivery’ section below). Ethical approval was obtained from Bromley Research Ethics Committee (19/LO/1510). Research governance approvals were obtained from the Health Research Authority (reference 265789), and sponsorship was provided by the University of Liverpool (reference UoL001354). All data used were accessed only by authorised study members and were stored in a secure location in accordance with ethical requirements. The RETURN intervention The RETURN intervention is a single-session, brief psychological intervention delivered by dental nurses in urgent dental care settings. Its primary objective is to support patients who only use dental services when they have an urgent problem. By assisting patients in identifying and overcoming barriers to routine dental visits, the intervention aims to promote regular, planned dental care, thereby improving oral health outcomes. The intervention is multifaceted and comprises several components delivered opportunistically to patients attending an urgent dental appointment. It leverages a “teachable moment” approach . A comprehensive description of the intervention has been detailed elsewhere . Briefly the intervention comprises two elements: A “patient pack” with behaviour change techniques embedded within the materials. The pack comprises: Six booklets addressing common barriers to routine dental visiting (cost, time constraints, not thinking to go when not in pain, distrust of dentists, embarrassment, and anxiety). Corresponding barrier videos featuring dental patients sharing their experiences of overcoming barriers, augmented with engaging animations. These videos were created specifically to resonate with the trial population. A written goal and action plan completed during the intervention session, targeting one barrier. Additional materials and booklets intended for post-appointment use at home, encouraging routine dental visiting. These include practical aids such as breathing exercises for anxious patients, contact information for dental services, and an “employer card” endorsing routine dental attendance. Access to a study website via a personal login where all intervention materials can be viewed. 2) A structured conversation facilitated by trained dental nurses . The conversation guides patients through the intervention process, utilising empathetic listening, non-judgmental, and non-directive dialogue. Its dual purpose is to enhance participant engagement by tailoring discussions to individual experiences whilst ensuring interaction with key intervention components. The RETURN feasibility study The RETURN feasibility study was a parallel group, two-arm, RCT that aimed to recruit 60 patients. Its primary objective was to assess the feasibility of conducting a larger RCT (the RETURN main trial) within urgent dental care settings to evaluate the RETURN intervention. Patients were allocated to either receive no intervention (usual care at the recruiting urgent dental care site) or the RETURN intervention. The study was conducted in Merseyside, North-West England in the UK in three site types: (1) an urgent clinic in a Teaching Dental Hospital (2), an out-of-hours urgent dental care service, and (3) an urgent clinic in an in-hours dental practice. Each site put forward dental nurses to be trained for one hour in Good Clinical Practice principles and for two hours in study procedures and intervention delivery. Training sessions were didactic, with opportunities to role play intervention deliveries and were conducted either at the University of Liverpool or at site. During the recruitment period (January 2020 to March 2020), routine dental care appointments for new National Health Service (NHS) patients were readily available in the region. Recruitment ceased abruptly due to the COVID-19 pandemic, resulting in the enrolment of 28 patients, approximately halfway to the target. Follow-up was achieved for 82% of the patients via telephone, email, or post, four months post-recruitment. Feasibility measures included primary outcome data completion rates, recruitment rates, and fidelity. A comprehensive study description and results have been published elsewhere . Briefly, despite premature termination, the results were considered sufficient to warrant proceeding to a full-scale RCT, with the addition of an internal pilot to monitor progress. Developing the fidelity strategies In alignment with MRC guidance on intervention refinement and Borrelli’s recommendation to pilot test interventions and incorporate feedback from participants and providers, the RETURN feasibility study provided an opportunity to develop fidelity strategies for the RETURN main trial. A total of 58 h of observations were conducted, covering the recruitment of 24 patients and 11 intervention delivery sessions (the remaining 13 patients were allocated to the control arm, and therefore, no intervention delivery was observed). Observation time also encompassed site set-up, informal discussions with dental nurses, and additional ad hoc training conversations throughout the study period. Field notes were recorded at the end of each day. Additionally, telephone semi-structured interviews were conducted with two dental nurses involved in delivering the feasibility study and 17 study patients. All dental nurses who were both trained and delivered the intervention were invited to be interviewed. This meant that numbers of dental nurses participating in interviews were limited because the onset of the COVID pandemic meant a refocusing of the dental workforce on purely clinical activity and so fewer nurses ( n = 2) delivered the intervention than were trained ( n = 9). This also resulted in a researcher recruiting patients at one site instead of dental nurses, but they were not approached to take part in this study. For pragmatic reasons, the 17 patients who responded to the RETURN feasibility study follow-up by telephone were invited to be interviewed ( n = 9 intervention & n = 8 control), all of whom agreed to take part. Interviews were audio-recorded and transcribed. Employing the Framework Method guided by the BCC recommendations and using a deductive approach to structure the coding framework in accordance with the components of the intervention, field notes and interview transcripts were analysed to pinpoint areas where fidelity could be strengthened for the RETURN man trial. Data underwent coding, charting, mapping, and verification across the entire dataset to inform the development of a robust fidelity strategy. In addition to the logic model which sets out the underlying mechanisms of the intervention materials as described in the intervention development publication , and recognising the two separate elements of the intervention (the “patient pack” and conversational element), we have produced an ‘operational model’ , to facilitate a complete assessment of intervention fidelity within the RETURN main trial . This can be found at Table . This operational model provides a scaffold for the intervention fidelity strategy and helped inform its design, by outlining which intervention activities should be present in an intervention conversation for it to be considered delivered as intended. From this model, many of the strategies contained in this manuscript were developed (for example, it guided the components featured in the RETURN fidelity checklist developed to monitor training and assess delivery fidelity, discussed within the ‘delivery’ section below). The RETURN intervention is a single-session, brief psychological intervention delivered by dental nurses in urgent dental care settings. Its primary objective is to support patients who only use dental services when they have an urgent problem. By assisting patients in identifying and overcoming barriers to routine dental visits, the intervention aims to promote regular, planned dental care, thereby improving oral health outcomes. The intervention is multifaceted and comprises several components delivered opportunistically to patients attending an urgent dental appointment. It leverages a “teachable moment” approach . A comprehensive description of the intervention has been detailed elsewhere . Briefly the intervention comprises two elements: A “patient pack” with behaviour change techniques embedded within the materials. The pack comprises: Six booklets addressing common barriers to routine dental visiting (cost, time constraints, not thinking to go when not in pain, distrust of dentists, embarrassment, and anxiety). Corresponding barrier videos featuring dental patients sharing their experiences of overcoming barriers, augmented with engaging animations. These videos were created specifically to resonate with the trial population. A written goal and action plan completed during the intervention session, targeting one barrier. Additional materials and booklets intended for post-appointment use at home, encouraging routine dental visiting. These include practical aids such as breathing exercises for anxious patients, contact information for dental services, and an “employer card” endorsing routine dental attendance. Access to a study website via a personal login where all intervention materials can be viewed. 2) A structured conversation facilitated by trained dental nurses . The conversation guides patients through the intervention process, utilising empathetic listening, non-judgmental, and non-directive dialogue. Its dual purpose is to enhance participant engagement by tailoring discussions to individual experiences whilst ensuring interaction with key intervention components. The RETURN feasibility study was a parallel group, two-arm, RCT that aimed to recruit 60 patients. Its primary objective was to assess the feasibility of conducting a larger RCT (the RETURN main trial) within urgent dental care settings to evaluate the RETURN intervention. Patients were allocated to either receive no intervention (usual care at the recruiting urgent dental care site) or the RETURN intervention. The study was conducted in Merseyside, North-West England in the UK in three site types: (1) an urgent clinic in a Teaching Dental Hospital (2), an out-of-hours urgent dental care service, and (3) an urgent clinic in an in-hours dental practice. Each site put forward dental nurses to be trained for one hour in Good Clinical Practice principles and for two hours in study procedures and intervention delivery. Training sessions were didactic, with opportunities to role play intervention deliveries and were conducted either at the University of Liverpool or at site. During the recruitment period (January 2020 to March 2020), routine dental care appointments for new National Health Service (NHS) patients were readily available in the region. Recruitment ceased abruptly due to the COVID-19 pandemic, resulting in the enrolment of 28 patients, approximately halfway to the target. Follow-up was achieved for 82% of the patients via telephone, email, or post, four months post-recruitment. Feasibility measures included primary outcome data completion rates, recruitment rates, and fidelity. A comprehensive study description and results have been published elsewhere . Briefly, despite premature termination, the results were considered sufficient to warrant proceeding to a full-scale RCT, with the addition of an internal pilot to monitor progress. In alignment with MRC guidance on intervention refinement and Borrelli’s recommendation to pilot test interventions and incorporate feedback from participants and providers, the RETURN feasibility study provided an opportunity to develop fidelity strategies for the RETURN main trial. A total of 58 h of observations were conducted, covering the recruitment of 24 patients and 11 intervention delivery sessions (the remaining 13 patients were allocated to the control arm, and therefore, no intervention delivery was observed). Observation time also encompassed site set-up, informal discussions with dental nurses, and additional ad hoc training conversations throughout the study period. Field notes were recorded at the end of each day. Additionally, telephone semi-structured interviews were conducted with two dental nurses involved in delivering the feasibility study and 17 study patients. All dental nurses who were both trained and delivered the intervention were invited to be interviewed. This meant that numbers of dental nurses participating in interviews were limited because the onset of the COVID pandemic meant a refocusing of the dental workforce on purely clinical activity and so fewer nurses ( n = 2) delivered the intervention than were trained ( n = 9). This also resulted in a researcher recruiting patients at one site instead of dental nurses, but they were not approached to take part in this study. For pragmatic reasons, the 17 patients who responded to the RETURN feasibility study follow-up by telephone were invited to be interviewed ( n = 9 intervention & n = 8 control), all of whom agreed to take part. Interviews were audio-recorded and transcribed. Employing the Framework Method guided by the BCC recommendations and using a deductive approach to structure the coding framework in accordance with the components of the intervention, field notes and interview transcripts were analysed to pinpoint areas where fidelity could be strengthened for the RETURN man trial. Data underwent coding, charting, mapping, and verification across the entire dataset to inform the development of a robust fidelity strategy. In addition to the logic model which sets out the underlying mechanisms of the intervention materials as described in the intervention development publication , and recognising the two separate elements of the intervention (the “patient pack” and conversational element), we have produced an ‘operational model’ , to facilitate a complete assessment of intervention fidelity within the RETURN main trial . This can be found at Table . This operational model provides a scaffold for the intervention fidelity strategy and helped inform its design, by outlining which intervention activities should be present in an intervention conversation for it to be considered delivered as intended. From this model, many of the strategies contained in this manuscript were developed (for example, it guided the components featured in the RETURN fidelity checklist developed to monitor training and assess delivery fidelity, discussed within the ‘delivery’ section below). The BCC recommendations were used as a guide to develop a comprehensive fidelity strategy for the RETURN trial, addressing the lessons learned from the conduct of the feasibility study. This article now sets out the strategy following the 5 domains ( in bold ) and goals ( in bold italics ) of the BCC framework , adapted by Borrelli . Design Explicitly identify and use a theoretical model as a basis for the intervention and ensure the intervention components and measures are reflective of underlying theory The theoretical underpinnings guiding the intervention have been detailed in a publication outlining the intervention’s development process, which includes a comprehensive logic model . Briefly, the intervention draws from multiple theoretical frameworks, incorporating elements of Protection Motivation Theory and Identity-based Motivation Theory . During the feasibility study, it became evident that the conversational aspect of the intervention required a structured approach to enhance standardisation across intervention sessions. Accordingly, Motivational Interviewing (MI) ‘spirit’ was introduced as a framework to provide structure to these conversations in the RETURN main trial, while bolstering the theoretical coherence of intervention deliveries. Ensure consistent intervention dose and develop a monitoring plan to maintain consistency Variations in intervention ‘dose’ were noted during the feasibility study, with session durations ranging from 10 to 37 min, Mean (Standard Deviation (SD)) = 21 minutes. Observations revealed this was primarily influenced by patient engagement and confidence levels of the interventionist. Whilst an intervention duration target of around 15 min was set for pragmatic reasons as part of the intervention design goals for the feasibility study, for the RETURN main trial, a larger emphasis on dose standardisation will be implemented through training. Additionally, to underscore the importance of regulating dose, specific guidance on the duration for each intervention component for the main trial will be given: Barrier discussion – 4 min. Motivation enhancement: video and discussion – 3 min. Knowledge enhancement (guided discussion using booklet materials) – 3 min. Setting Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals and action plan – 4 min. Setting intentions at the session’s conclusion – 1 min. However, as a patient-centred approach is inherent in MI techniques where discussions are led by patients, variations in intervention dose will be deemed an acceptable intervention adaptation in the RETURN main trial. This decision is supported by the understanding that patients facing multiple barriers may have longer ‘barrier discussions’ leading to variations in intervention duration. Monitoring of dose will be achieved through audio-recordings, although no corrective measures will be taken to standardise dose in the main trial. Patients also take intervention materials home, and accordingly, questions about additional engagement with the materials will form part of the RETURN main trial follow-ups. Likewise, metadata from the study website will be reviewed to assess whether patients viewed intervention materials at home. This comprehensive approach to dose monitoring aims to enrich the interpretation of the RETURN main trial findings, and dose variations will be considered in the analysis of study outcomes (i.e. is there an optimum amount of ‘dose’ to elucidate behaviour change? ). Develop a plan for how adherence to the protocol will be monitored. Monitor both intervention delivery and assessment administration Adherence to the intervention protocol was identified as a concern during the feasibility study. Based on observations, only 5/11 (45%) intervention patients received the intended discussion. The following feasibility observation illustrates poor adherence to the prescribed approach: DN02: “ This is the pack; they have spoken to lots of people to make the pack. There are 6 barriers that people told to them. These are common and lots of people said them ”. Observation: DN02 was showing the ‘What Next Booklet’ to the participant but kept it in front of them so the participant was unable to read it. DN02 flashed the booklet and pointed to the barriers. Moving the booklet away again, they read the barriers out one by one. DA0201: “ So we have cost , time , I don’t think I have any problems , trust , embarrassment , anxiety”. The nurse turned the booklet over, and said “and there is also a plan , that is from psychological theory , and there are other materials ”. All the while DA02 kept hold of the booklet. Observation: DN02 then went back to the barrier page, showing the participant and asked: “ Which of these do you relate to? ” I felt this was quite a closed question. There was no conversation about what was stopping them from going. The participant was simply asked to choose which one from the list. Observation 06: Site 02, DN02. To address this in the RETURN main trial, adherence monitoring will be strengthened by considering the challenges of the research context. Indeed, findings from a recent scoping review of fidelity reporting in primary care dental settings suggests the onus/burden of intervention protocol adherence and competency monitoring should sit with research teams. Therefore, in the RETURN main trial, dental nurses will be asked to audio-record 100% of their intervention sessions, rather than alternative monitoring techniques such as asking them to complete checklists after each intervention delivery. Adherence and competency during the RETURN main trial will be monitored by selecting at least one intervention recording per dental nurse each month which the research team will score using pre-determined criteria contained within an intervention specific fidelity checklist (the RETURN checklist, see Table ). The RETURN checklist comprises 6 essential intervention components: overarching communication skills (MI derived), barrier discussion, motivation enhancement through a video, knowledge enhancement through a barrier booklet, goal and action plan setting, intention setting. Each component comprises a combination of theoretical components designed to increase behaviour change capacity (i.e. encouraging the use of SMART principles for goal setting) and practical requirements (i.e. showing the video relevant to the selected barrier). The scoring system takes the form of a Likert-scale: 0 = not implemented, 1 = partially implemented, 2 = substantially implemented, 3 = fully implemented, to give an indication of both adherence and competency. There are no guidelines to inform the optimum ‘level’ of fidelity that should be present in a BCI delivered within dental practices. However, Durlak and DuPre found outcomes were effective in educational interventions if they were delivered with 60-80% fidelity , and a 90% threshold is frequently used in clinical interventions involving psychological therapies . Therefore, a cautious approach will be adopted in the RETURN main trial and a threshold of 80% within each intervention component will be set for a delivery session to be considered to have achieved high fidelity. To provide guidance and to ensure consistency in intervention scoring, a scoring guidance manual was created (see Additional File ). This was developed collaboratively by RETURN researchers using an iterative approach to ensure that the descriptions contained within the manual were understood consistently across the team. The manual was both created and tested using a method whereby audio-recordings of the feasibility intervention sessions were scored independently, results compared, and discrepancies discussed until consensus was achieved (> 80% agreement rate). The development of the fidelity checklist and the scoring guidance manual followed steps three to five as suggested by Walton and colleagues , with an iterative approach utilising feedback from the RETURN researchers to refine the items and scoring guidance. An example of the scoring guidance for the domain of ‘overarching communication skills’ for the demonstration of ‘priorities, beliefs and challenges acknowledged’ is illustrated below: Patient’s priorities, beliefs and challenges acknowledged patients should not be challenged on their beliefs, priorities or challenges experienced previously, even if they are in direct conflict with the principles of the delivery nurse. These should simply be acknowledged as an experience that occurred. Score 0 if patient’s priorities/beliefs are challenged by the nurse e.g. Patient: “I couldn’t get a dentist because there weren’t any” Nurse “There was loads of NHS availability a year ago so that can’t be true”. Score 1 if some attempt is made to acknowledge but the patient’s priorities/beliefs are also challenged e.g. Patient “I couldn’t get a dentist because there weren’t any” Nurse “It sounds like it was really difficult for you to get yourself into the dentist, but there were dentists available”. Score 2 if patient’s priorities/beliefs and challenges are acknowledged during most of the session, but once or twice the nurse challenged the patients on these. Score 3 if acknowledgments rather than challenges are present. Patient: “I couldn’t get a dentist” Nurse: “Sounds like it was really tricky for you to get into a dentist in the past”. Evaluation procedures to support scoring throughout the RETURN main trial will also include the consistent use of the same scoring team and the employment of interrater reliability methods. Where an agreement rate of less than 60% is found between team members responsible for scoring throughout the course of the trial, additional scoring training will take place, again using inter-rater reliability to determine agreement rates. The RETURN checklist has been designed as a multi-functional tool for the implementation of fidelity strategies. Its functions are to act as a standardised training aide, a method to set competency expectations, a means of leveraging feedback to interventionists, a means of monitoring protocol adherence and competency levels throughout the main trial, and to assess the level of fidelity achieved in intervention deliveries at the end of the trial. Develop a plan to record intervention protocol deviations and a method for providing timely feedback to interventionists Several strategies were developed to document and address protocol deviations in the RETURN main trial: A coaching culture will be integrated into the training methodology to promote open communication and rapport between trainers and dental nurses. This aims to facilitate an environment where protocol deviations would be more likely to be reported, and where feedback would be enacted. This will take the form of regular, personalised, and constructive feedback designed to encourage confidence and build both communication and intervention skills. Additionally, monthly, each nurse will have at least one intervention audio-recording evaluated using the RETURN checklist with strengths and any areas for improvement noted. Checklists will be provided to the dental nurses once completed. Where low scores are found, additional intervention sessions will be scored, supplemented with a support site visit. Booster training will trigger where necessary through consistent low scores using the RETURN checklist. The protocol deviation plan will be clearly communicated to dental nurses at the outset of the RETURN main trial set-up phase. This transparent approach aims to cultivate an environment where protocol deviations are viewed as opportunities for learning rather than punitive measures. Develop a user-friendly scripted intervention manual to ensure consistency of delivery and adherence to active ingredients of the treatment Learning from the feasibility study suggested that using scripted approaches to intervention delivery were unsuccessful, as is demonstrated in the following observation: The nurse opened the pack and put it on the table. They read through the patient pack introduction information printed on the materials very quietly, not making eye contact with the patient as they did this. The patient was listening intently, leaning forward slightly to be able to hear what the nurse was saying. I felt some of the meaning was lost during this explanation, as the nurse was so quiet and stilted, it was difficult to hear. The nurse came across as very unconfident and reliant on the written materials. This created no room for the patient discussion. Observation 02: Site 02, DN02. For the RETURN main trial therefore, there will be a conscious move away from scripted materials, and instead, training intensity will be increased. In addition, an easy-to-follow intervention crib sheet was developed (see Additional File ), alongside a written intervention training manual, designed to support intervention delivery beyond training (see Additional File ). Plan for implementation setbacks During the feasibility study, limited resources at sites resulted in just one nurse from each of the two sites taking part in research activities, despite delivering training to multiple nurses in all three sites. As research activities were intended to integrate into nurses’ regular duties within urgent dental care settings, this constraint contributed to recruitment delays, exacerbated by factors such as COVID-19, staff sickness or holiday leave. To address these challenges in the RETURN main trial, additional ‘float’ dental nurses will be employed as part of the core research team to carry our research duties across sites, utilising funds earmarked for reimbursing dental practices for staff time spent on research activities. Furthermore, efforts will be made to train multiple dental nurses at each site, where feasible. These strategies will form part of the early site communications. Minimize contamination between conditions Contamination was not found to be an issue within the feasibility study. Nonetheless, in the RETURN main trial, training will be provided around the importance of allocation adherence. In addition, portable research activity flow charts detailing the specific actions to follow within each study arm will be provided, supported by regular site visits from the research team. Questions will be included in the RETURN trial follow-up pertaining to contamination (i.e. control group question: ‘Did you receive any materials at your urgent care appointment to help you to find a dentist? If so, what did that look like? ). Training Training was identified as an area for improvement during the feasibility study. ‘Hiring’ dental nurses to deliver the RETURN intervention Confidence was found to be a major contributing factor to intervention delivery success, detailed in the feasibility observation below: I passed the booklet back to the nurse, and they started going through the booklet. They didn’t explain what the booklet was for. They read out the title on each page loudly, but the rest of the information on the pages was said very quietly and sound a little muddled. The walk through of the booklet didn’t flow, and it’s more like they were reading it to them themselves under their breath to familiarise themselves with the content. DN02: (page 2) “ For healthy teeth do I need to go? ” “ This is Megan , you can see about her story on the video ”. Page 3 is skipped. Page 4 “ Keeping on top of it ” “ It’s important to go all the time ” Page 5 “ This is a picture of a tooth that only the dentist could see , it shows the decay ”. It is very difficult to hear what DN02 was saying, and the overall feeling is someone who lacks confidence. I felt harsh making them deliver when clearly, they didn’t feel ready with any confidence. Observation 05, Site 01: DN02. At the setup phase of the feasibility study, it was stipulated that effective delivery of the intervention would require experienced nurses with proficient communication skills. This expectation was based on the belief that such traits would facilitate the skills required to successfully deliver the intervention. However, implementation revealed challenges to this ideal. Informal discussions with dental staff at sites, recorded in field notes, noted that dental teams could use trial participation as an opportunity to enhance the communication skills of their staff involved in the research. This experience highlights the existence of conflicting priorities when conducting research. As we found dental nurse attributes cannot be guaranteed, the RETURN main trial training will include elements specifically designed to increase confidence and communication skills, including enhanced role-play and a coaching style training approach. In addition, training sessions will not be fixed in length, and instead provision will be based on individualised need. This will be achievable as shadowing training is planned to occur concurrently with patient recruitment, so as not to hamper trial progress. Standardise training The BCC framework recommends training all interventionists together. In the primary dental care setting, this would require inviting dental teams to converge in a mutually convenient location, and taking staff members out of clinic was found to be problematic during the feasibility study. Instead, in the RETURN main trial, a model will be used where site personnel are trained together. As this method could affect the standardisation of the training delivered, multiple strategies were designed to mitigate that risk: Implementation of a ‘train the trainers’ training model led by a clinical psychologist. Using the same team of trainers throughout the trial. Using identical training materials for each site. Using the same role play tasks with all teams trained. Using a training manual and training videos. The development of a central website to house all training materials, as well as providing hard copies of all materials to all trainees. Use a training content checklist to ensure all training components were delivered to all dental teams (see Additional File ). Ensure dental nurse skill acquisition Skill acquisition was not measured as part of the feasibility study. However, observations demonstrated variation in competency between dental nurses. Therefore, a plan was developed for the RETURN main trial to test skill acquisition during the different phases of training: Training phase 1 Good Clinical Practice Training – A one-hour online module. Skill acquisition measured through an online quiz, with a pass mark of 80%. Training phase 2 Intervention training – three hours, face to face delivery with a mixture of didactic learning, open discussions, and role plays. Skill acquisition measured through discussion and observations by a RETURN trainer through an intervention delivery skill acquisition checklist (see Additional File ). Training phase 3 On the job shadowing training – the amount will depend on demonstration of competencies. Skill acquisition will be measured through in vitro observations using the RETURN checklist. Each interventionist will need to achieve a score of 80% within each intervention component in a single session to be signed off as competent to deliver the intervention independently. Scoring will be conducted by the RETURN trainers and scoring decisions will be supported by the guidance manual. Minimise ‘drift’ in dental nurse skills Skills drift was not explicitly monitored during the feasibility study. However, from feasibility observations, it was discovered that intervention skills needed to be practiced regularly to be maintained. Therefore, a strategy to reduce skills drift was developed for the RETURN main trial: Frequent (at least one per month, per nurse) scoring and feedback of audio-recorded interventions using the scoring checklist, including elaborating strengths and areas for development. Triggered site visits to provide additional booster training and support in the event of low scoring (< 60% in any one component). Triggered (by consistent low scores) or requested reflective practice sessions, wherein a selected audio-recording will be discussed with the dental team at site, focusing on intervention elements that went well, and things that could be improved or done differently. Maintaining a collaborative coaching style approach to all feedback provision, booster training and reflective practice sessions to maintain relationships between the trainers and the dental nurses. Accommodate dental nurse differences Stark differences between the skills and experience levels of the feasibility dental nurses were found. The dental nurses involved in the delivery of the RETURN intervention study were not selected by the research team, they were volunteered by the dental practice owners / managers due to their availability and expression of interest in taking part. DN02 had less than 2 years’ experience of dental nursing and lacked confidence with patient communication. DN01 had more than 10 years’ experience, demonstrated good communication skills and overall was more confident in their approach to the intervention. This quotation from DN02 describes this: Yeah. I don’t know it might be easy for other nurses but for my range of vocabulary to like GCSE, maybe some words I found difficult, and how it works, like the way it’s [training materials] worded was difficult. If it was more informal, like ‘What are we going to do?’ ‘We’re going to do this’. Like a chatty kind of presentation maybe. Interview with DN02 There were also differences in day-to-day responsibilities within their respective dental practices, with DN01 taking a more patient engaged role than DN02. These contrasting quotations demonstrate this: It’s very difficult, you know, especially for nurses because they do not have a lot of contact with patients. It’s only the dentist that takes over everything. So we do our own bit in surgery, cleaning, helping, but we don’t have conversations like that with patients. Interview with DN02 I like talking to patients and I like the interaction and chatting with them and, you know, talking to different people as well and finding out their barriers. I think we seem a bit more human to them as well when we sit down and have a chat with them and we’re not just the scary people who work in the dentist. Interview with DN01. An additional challenge identified during the feasibility study was the need for training to encompass multiple methods, accommodating a wide range of baseline research skill levels. This was highlighted by the following observation on the first day of recruitment at site 02: The nurse [DN02] told me that during the feasibility study training, they didn’t know what the word feasibility meant. They described that this word was in big letters on the very first training slide and all they could think about was wanting to Google what that word meant, so found it difficult to keep up with the rest of the training. Observation 01, Site 02: DN02 To maintain training standardisation whilst also acknowledging the challenge of variation between nurses likely be experienced in the main trial, an ‘on-the-job shadowing’ training element was developed. Shadowing training will involve a RETURN team member ‘chaperoning’ a dental nurse whilst they deliver interventions. Tailored support will be provided alongside real-time verbal and written feedback. This training is not time limited. Training will continue until the nurse both demonstrates competency through the scoring checklist and articulates to the trainers that they feel they have achieved a level of confidence sufficient to deliver the intervention independently. This style of ‘on-the-job’ shadowing training was developed for its ability to be highly individualised, and because it reflects the stye of training routinely undertaken by dental nurses in primary care. Enhance buy-in from dental nurses Enhancement of dental nurse buy-in was considered a priority for the upcoming RETURN trial. Within the dental practice setting, a practice owner often acts as the gatekeeper to research conduct. Those carrying out the research become involved later in the process, with vital opportunities to increase buy-in often missed. Accordingly, a series of dental nurse buy-in strategies were developed for implementation in the RETURN main trial: Continuing Professional Development (CPD) accreditation for all training. Training components designed to explain the purpose of the research, paying particular attention to patient benefit. An early interactive information session including dental nurses, highlighting the opportunities presented by the trial for enhanced patient interaction and training. Inclusion of communication skills training targeted to dental nurses. Monthly newsletters aimed at dental nurses and wider practice staff, with the addition of real dental nurse stories about their involvement in the trial and a quiz and prize element. Engagement lunches for dental nurses as a reward for participation. Use of communication modes congruent with dental nurse preferences i.e. WhatsApp messages rather than emails. Regular site visits to increase self-efficacy and confidence with research activities. Dental nurse awards evening to celebrate trial achievements (i.e. best recruiter etc.) Delivery Use a scripted curriculum or treatment manual Based on feasibility observations, scripts will not be utilised in the RETURN main trial. Instead, a selection of prompts will be provided to the nurses to ensure the intervention’s essential components are delivered. These prompts will take the form of the training manual (including intervention delivery cheat sheets), the intervention crib sheet, and videos demonstrating intervention delivery. Some components however, are ‘scripted’ within the intervention materials themselves, such as the goal and action planning section (see Additional File ). Assess non-specific effects through multiple methods and on an ongoing basis Non-specific factors (such as empathy and components that lend themselves to the target communication style) will be assessed as a stand-alone domain within the RETURN checklist. Nonspecific effects will also specifically be discussed during shadowing training. Ensure both adherence to the protocol and competency of intervention delivery Adherence and competency of intervention deliveries will be assessed through the application of the RETURN checklist throughout the main trial. In addition, 100% of all available recordings will be assessed at the end of the main trial to provide a comprehensive overview of the adherence and competency of intervention deliveries. A fidelity threshold of 80% in every domain per intervention delivery will be applied when scoring the recordings. Receipt Ensure participants’ understanding of the intervention Although data collected from the patients during the feasibility study suggested that patients overwhelmingly found the intervention useful, understandable and relevant, it is helpful to outline here the steps taken to enhance participants’ understanding of the intervention during its development: The RETURN intervention is designed to be engaging, specifically targeted to the trial population. An extensive patient and public involvement (PPI) work stream fed into its design (full details have been published elsewhere ), with the aim of ensuring the materials were culturally relevant, containing congruent messages and images to the trial population. A design company and a professional illustrator were employed to embed these strategies. To account for different learning styles, information was presented and repeated using multiple formats - verbal, written, pictorial and videography. The intervention materials were written to a reading age of 8 years to ensure health literacy inclusivity. Intervention delivery sessions are formatted as reciprocal conversations, and therefore by design, mutual understanding between the patient and dental nurse is embedded. During training and throughout the recruitment period, intervention deliveries will be scored, and feedback provided to ensure that ‘reciprocity’ and patient understanding is embedded, with these criteria factored into the RETURN checklist. Ensure participants’ ability to perform behavioural skills The RETURN intervention seeks to target the behaviour of routine dental appointment visiting. To ensure patients’ ability to perform the behavioural skills required, the intervention was designed to be tailored, considering obstacles unique to individuals’ lives. The intervention culminates in a goal setting and action planning exercise, where participants think through their individual circumstances, and write out SMART (specific, measurable, achievable, relevant and time-bound) goals and plans to help them to overcome their barriers. In this way the target behavioural skills were articulated, discussed and broken down into small actions. From the feasibility observations, this element of the intervention needed improvement, specifically around patient engagement. The nurse put the booklet to one side, and then took the planning booklet from their knee. “We know that writing plans helps”. I felt this introduction didn’t really explain to the participant what the nurse was asking them to do – The nurse looked at me to help as they were getting their words muddled…The nurse devised the plan for the participant, rather than letting the participant make the plan for themselves. The patient set their goal themselves, but they did not put in much detail. They wrote down 3 words and didn’t discuss this with the nurse at all. DN02, Observation 11 For the RETURN main trial, several strategies will therefore be implemented to improve how assessment of behavioural skills were conducted during the intervention delivery sessions: Training will include a dedicated component on how to facilitate goal setting and action planning, emphasising the importance of facilitating and not leading the task, and how to encourage patients to think through and articulate their own mechanisms. Goal setting and action planning have been included on the RETURN checklist, and timely feedback will be provided. A follow-up text message will be sent to participants a week post-intervention including the participants’ own wording from their goals and plans set within the intervention sessions to reinforce behavioural skills and build self-efficacy. The 6-month follow-up telephone call to patients will explore their comprehension of the intervention and how meaningful they found it to track receipt. A component of the intervention conversation will encourage discussion around what was achieved during the intervention session. This has been designed to improve participant receipt of the intervention by setting intentions. This element is also included in the RETURN checklist assessment. Enactment Participant performance of the intervention skills will be assessed in settings in which the intervention might be applied Data was collected from patients of the feasibility study amid the first COVID lockdown restrictions (May – September 2020), and accordingly it was not possible to assess enactment at that time. Therefore, as part of the RETURN main trial telephone follow-up at three time points, questions will be included about whether and how the intervention materials and associated intervention skills had been used since leaving the urgent care dental setting. Questions will focus on which parts of the intervention had been used, whether the intervention skills had been enacted (i.e. phoning for a dental appointment, exploring which dental practice they may like to contact, attending a dental appointment) and how the intervention supported any actions taken to attend a routine dental appointment. Additionally, enactment strategies are embedded within the intervention materials themselves. Some materials are labelled ‘to look at at home’, providing encouragement and support in locating a dentist, making an appointment and thereafter attending an appointment – the behaviours targeted by the intervention. The full RETURN fidelity strategy is summarised in Table . The strategies presented there show the tangible actions taken to attend to the various intervention fidelity recommendations, which may help other researchers to think through the strategies that will apply to their studies (i.e. using audio recordings to monitor skills drift). Explicitly identify and use a theoretical model as a basis for the intervention and ensure the intervention components and measures are reflective of underlying theory The theoretical underpinnings guiding the intervention have been detailed in a publication outlining the intervention’s development process, which includes a comprehensive logic model . Briefly, the intervention draws from multiple theoretical frameworks, incorporating elements of Protection Motivation Theory and Identity-based Motivation Theory . During the feasibility study, it became evident that the conversational aspect of the intervention required a structured approach to enhance standardisation across intervention sessions. Accordingly, Motivational Interviewing (MI) ‘spirit’ was introduced as a framework to provide structure to these conversations in the RETURN main trial, while bolstering the theoretical coherence of intervention deliveries. Ensure consistent intervention dose and develop a monitoring plan to maintain consistency Variations in intervention ‘dose’ were noted during the feasibility study, with session durations ranging from 10 to 37 min, Mean (Standard Deviation (SD)) = 21 minutes. Observations revealed this was primarily influenced by patient engagement and confidence levels of the interventionist. Whilst an intervention duration target of around 15 min was set for pragmatic reasons as part of the intervention design goals for the feasibility study, for the RETURN main trial, a larger emphasis on dose standardisation will be implemented through training. Additionally, to underscore the importance of regulating dose, specific guidance on the duration for each intervention component for the main trial will be given: Barrier discussion – 4 min. Motivation enhancement: video and discussion – 3 min. Knowledge enhancement (guided discussion using booklet materials) – 3 min. Setting Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals and action plan – 4 min. Setting intentions at the session’s conclusion – 1 min. However, as a patient-centred approach is inherent in MI techniques where discussions are led by patients, variations in intervention dose will be deemed an acceptable intervention adaptation in the RETURN main trial. This decision is supported by the understanding that patients facing multiple barriers may have longer ‘barrier discussions’ leading to variations in intervention duration. Monitoring of dose will be achieved through audio-recordings, although no corrective measures will be taken to standardise dose in the main trial. Patients also take intervention materials home, and accordingly, questions about additional engagement with the materials will form part of the RETURN main trial follow-ups. Likewise, metadata from the study website will be reviewed to assess whether patients viewed intervention materials at home. This comprehensive approach to dose monitoring aims to enrich the interpretation of the RETURN main trial findings, and dose variations will be considered in the analysis of study outcomes (i.e. is there an optimum amount of ‘dose’ to elucidate behaviour change? ). Develop a plan for how adherence to the protocol will be monitored. Monitor both intervention delivery and assessment administration Adherence to the intervention protocol was identified as a concern during the feasibility study. Based on observations, only 5/11 (45%) intervention patients received the intended discussion. The following feasibility observation illustrates poor adherence to the prescribed approach: DN02: “ This is the pack; they have spoken to lots of people to make the pack. There are 6 barriers that people told to them. These are common and lots of people said them ”. Observation: DN02 was showing the ‘What Next Booklet’ to the participant but kept it in front of them so the participant was unable to read it. DN02 flashed the booklet and pointed to the barriers. Moving the booklet away again, they read the barriers out one by one. DA0201: “ So we have cost , time , I don’t think I have any problems , trust , embarrassment , anxiety”. The nurse turned the booklet over, and said “and there is also a plan , that is from psychological theory , and there are other materials ”. All the while DA02 kept hold of the booklet. Observation: DN02 then went back to the barrier page, showing the participant and asked: “ Which of these do you relate to? ” I felt this was quite a closed question. There was no conversation about what was stopping them from going. The participant was simply asked to choose which one from the list. Observation 06: Site 02, DN02. To address this in the RETURN main trial, adherence monitoring will be strengthened by considering the challenges of the research context. Indeed, findings from a recent scoping review of fidelity reporting in primary care dental settings suggests the onus/burden of intervention protocol adherence and competency monitoring should sit with research teams. Therefore, in the RETURN main trial, dental nurses will be asked to audio-record 100% of their intervention sessions, rather than alternative monitoring techniques such as asking them to complete checklists after each intervention delivery. Adherence and competency during the RETURN main trial will be monitored by selecting at least one intervention recording per dental nurse each month which the research team will score using pre-determined criteria contained within an intervention specific fidelity checklist (the RETURN checklist, see Table ). The RETURN checklist comprises 6 essential intervention components: overarching communication skills (MI derived), barrier discussion, motivation enhancement through a video, knowledge enhancement through a barrier booklet, goal and action plan setting, intention setting. Each component comprises a combination of theoretical components designed to increase behaviour change capacity (i.e. encouraging the use of SMART principles for goal setting) and practical requirements (i.e. showing the video relevant to the selected barrier). The scoring system takes the form of a Likert-scale: 0 = not implemented, 1 = partially implemented, 2 = substantially implemented, 3 = fully implemented, to give an indication of both adherence and competency. There are no guidelines to inform the optimum ‘level’ of fidelity that should be present in a BCI delivered within dental practices. However, Durlak and DuPre found outcomes were effective in educational interventions if they were delivered with 60-80% fidelity , and a 90% threshold is frequently used in clinical interventions involving psychological therapies . Therefore, a cautious approach will be adopted in the RETURN main trial and a threshold of 80% within each intervention component will be set for a delivery session to be considered to have achieved high fidelity. To provide guidance and to ensure consistency in intervention scoring, a scoring guidance manual was created (see Additional File ). This was developed collaboratively by RETURN researchers using an iterative approach to ensure that the descriptions contained within the manual were understood consistently across the team. The manual was both created and tested using a method whereby audio-recordings of the feasibility intervention sessions were scored independently, results compared, and discrepancies discussed until consensus was achieved (> 80% agreement rate). The development of the fidelity checklist and the scoring guidance manual followed steps three to five as suggested by Walton and colleagues , with an iterative approach utilising feedback from the RETURN researchers to refine the items and scoring guidance. An example of the scoring guidance for the domain of ‘overarching communication skills’ for the demonstration of ‘priorities, beliefs and challenges acknowledged’ is illustrated below: Patient’s priorities, beliefs and challenges acknowledged patients should not be challenged on their beliefs, priorities or challenges experienced previously, even if they are in direct conflict with the principles of the delivery nurse. These should simply be acknowledged as an experience that occurred. Score 0 if patient’s priorities/beliefs are challenged by the nurse e.g. Patient: “I couldn’t get a dentist because there weren’t any” Nurse “There was loads of NHS availability a year ago so that can’t be true”. Score 1 if some attempt is made to acknowledge but the patient’s priorities/beliefs are also challenged e.g. Patient “I couldn’t get a dentist because there weren’t any” Nurse “It sounds like it was really difficult for you to get yourself into the dentist, but there were dentists available”. Score 2 if patient’s priorities/beliefs and challenges are acknowledged during most of the session, but once or twice the nurse challenged the patients on these. Score 3 if acknowledgments rather than challenges are present. Patient: “I couldn’t get a dentist” Nurse: “Sounds like it was really tricky for you to get into a dentist in the past”. Evaluation procedures to support scoring throughout the RETURN main trial will also include the consistent use of the same scoring team and the employment of interrater reliability methods. Where an agreement rate of less than 60% is found between team members responsible for scoring throughout the course of the trial, additional scoring training will take place, again using inter-rater reliability to determine agreement rates. The RETURN checklist has been designed as a multi-functional tool for the implementation of fidelity strategies. Its functions are to act as a standardised training aide, a method to set competency expectations, a means of leveraging feedback to interventionists, a means of monitoring protocol adherence and competency levels throughout the main trial, and to assess the level of fidelity achieved in intervention deliveries at the end of the trial. Develop a plan to record intervention protocol deviations and a method for providing timely feedback to interventionists Several strategies were developed to document and address protocol deviations in the RETURN main trial: A coaching culture will be integrated into the training methodology to promote open communication and rapport between trainers and dental nurses. This aims to facilitate an environment where protocol deviations would be more likely to be reported, and where feedback would be enacted. This will take the form of regular, personalised, and constructive feedback designed to encourage confidence and build both communication and intervention skills. Additionally, monthly, each nurse will have at least one intervention audio-recording evaluated using the RETURN checklist with strengths and any areas for improvement noted. Checklists will be provided to the dental nurses once completed. Where low scores are found, additional intervention sessions will be scored, supplemented with a support site visit. Booster training will trigger where necessary through consistent low scores using the RETURN checklist. The protocol deviation plan will be clearly communicated to dental nurses at the outset of the RETURN main trial set-up phase. This transparent approach aims to cultivate an environment where protocol deviations are viewed as opportunities for learning rather than punitive measures. Develop a user-friendly scripted intervention manual to ensure consistency of delivery and adherence to active ingredients of the treatment Learning from the feasibility study suggested that using scripted approaches to intervention delivery were unsuccessful, as is demonstrated in the following observation: The nurse opened the pack and put it on the table. They read through the patient pack introduction information printed on the materials very quietly, not making eye contact with the patient as they did this. The patient was listening intently, leaning forward slightly to be able to hear what the nurse was saying. I felt some of the meaning was lost during this explanation, as the nurse was so quiet and stilted, it was difficult to hear. The nurse came across as very unconfident and reliant on the written materials. This created no room for the patient discussion. Observation 02: Site 02, DN02. For the RETURN main trial therefore, there will be a conscious move away from scripted materials, and instead, training intensity will be increased. In addition, an easy-to-follow intervention crib sheet was developed (see Additional File ), alongside a written intervention training manual, designed to support intervention delivery beyond training (see Additional File ). Plan for implementation setbacks During the feasibility study, limited resources at sites resulted in just one nurse from each of the two sites taking part in research activities, despite delivering training to multiple nurses in all three sites. As research activities were intended to integrate into nurses’ regular duties within urgent dental care settings, this constraint contributed to recruitment delays, exacerbated by factors such as COVID-19, staff sickness or holiday leave. To address these challenges in the RETURN main trial, additional ‘float’ dental nurses will be employed as part of the core research team to carry our research duties across sites, utilising funds earmarked for reimbursing dental practices for staff time spent on research activities. Furthermore, efforts will be made to train multiple dental nurses at each site, where feasible. These strategies will form part of the early site communications. Minimize contamination between conditions Contamination was not found to be an issue within the feasibility study. Nonetheless, in the RETURN main trial, training will be provided around the importance of allocation adherence. In addition, portable research activity flow charts detailing the specific actions to follow within each study arm will be provided, supported by regular site visits from the research team. Questions will be included in the RETURN trial follow-up pertaining to contamination (i.e. control group question: ‘Did you receive any materials at your urgent care appointment to help you to find a dentist? If so, what did that look like? ). The theoretical underpinnings guiding the intervention have been detailed in a publication outlining the intervention’s development process, which includes a comprehensive logic model . Briefly, the intervention draws from multiple theoretical frameworks, incorporating elements of Protection Motivation Theory and Identity-based Motivation Theory . During the feasibility study, it became evident that the conversational aspect of the intervention required a structured approach to enhance standardisation across intervention sessions. Accordingly, Motivational Interviewing (MI) ‘spirit’ was introduced as a framework to provide structure to these conversations in the RETURN main trial, while bolstering the theoretical coherence of intervention deliveries. Variations in intervention ‘dose’ were noted during the feasibility study, with session durations ranging from 10 to 37 min, Mean (Standard Deviation (SD)) = 21 minutes. Observations revealed this was primarily influenced by patient engagement and confidence levels of the interventionist. Whilst an intervention duration target of around 15 min was set for pragmatic reasons as part of the intervention design goals for the feasibility study, for the RETURN main trial, a larger emphasis on dose standardisation will be implemented through training. Additionally, to underscore the importance of regulating dose, specific guidance on the duration for each intervention component for the main trial will be given: Barrier discussion – 4 min. Motivation enhancement: video and discussion – 3 min. Knowledge enhancement (guided discussion using booklet materials) – 3 min. Setting Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals and action plan – 4 min. Setting intentions at the session’s conclusion – 1 min. However, as a patient-centred approach is inherent in MI techniques where discussions are led by patients, variations in intervention dose will be deemed an acceptable intervention adaptation in the RETURN main trial. This decision is supported by the understanding that patients facing multiple barriers may have longer ‘barrier discussions’ leading to variations in intervention duration. Monitoring of dose will be achieved through audio-recordings, although no corrective measures will be taken to standardise dose in the main trial. Patients also take intervention materials home, and accordingly, questions about additional engagement with the materials will form part of the RETURN main trial follow-ups. Likewise, metadata from the study website will be reviewed to assess whether patients viewed intervention materials at home. This comprehensive approach to dose monitoring aims to enrich the interpretation of the RETURN main trial findings, and dose variations will be considered in the analysis of study outcomes (i.e. is there an optimum amount of ‘dose’ to elucidate behaviour change? ). Adherence to the intervention protocol was identified as a concern during the feasibility study. Based on observations, only 5/11 (45%) intervention patients received the intended discussion. The following feasibility observation illustrates poor adherence to the prescribed approach: DN02: “ This is the pack; they have spoken to lots of people to make the pack. There are 6 barriers that people told to them. These are common and lots of people said them ”. Observation: DN02 was showing the ‘What Next Booklet’ to the participant but kept it in front of them so the participant was unable to read it. DN02 flashed the booklet and pointed to the barriers. Moving the booklet away again, they read the barriers out one by one. DA0201: “ So we have cost , time , I don’t think I have any problems , trust , embarrassment , anxiety”. The nurse turned the booklet over, and said “and there is also a plan , that is from psychological theory , and there are other materials ”. All the while DA02 kept hold of the booklet. Observation: DN02 then went back to the barrier page, showing the participant and asked: “ Which of these do you relate to? ” I felt this was quite a closed question. There was no conversation about what was stopping them from going. The participant was simply asked to choose which one from the list. Observation 06: Site 02, DN02. To address this in the RETURN main trial, adherence monitoring will be strengthened by considering the challenges of the research context. Indeed, findings from a recent scoping review of fidelity reporting in primary care dental settings suggests the onus/burden of intervention protocol adherence and competency monitoring should sit with research teams. Therefore, in the RETURN main trial, dental nurses will be asked to audio-record 100% of their intervention sessions, rather than alternative monitoring techniques such as asking them to complete checklists after each intervention delivery. Adherence and competency during the RETURN main trial will be monitored by selecting at least one intervention recording per dental nurse each month which the research team will score using pre-determined criteria contained within an intervention specific fidelity checklist (the RETURN checklist, see Table ). The RETURN checklist comprises 6 essential intervention components: overarching communication skills (MI derived), barrier discussion, motivation enhancement through a video, knowledge enhancement through a barrier booklet, goal and action plan setting, intention setting. Each component comprises a combination of theoretical components designed to increase behaviour change capacity (i.e. encouraging the use of SMART principles for goal setting) and practical requirements (i.e. showing the video relevant to the selected barrier). The scoring system takes the form of a Likert-scale: 0 = not implemented, 1 = partially implemented, 2 = substantially implemented, 3 = fully implemented, to give an indication of both adherence and competency. There are no guidelines to inform the optimum ‘level’ of fidelity that should be present in a BCI delivered within dental practices. However, Durlak and DuPre found outcomes were effective in educational interventions if they were delivered with 60-80% fidelity , and a 90% threshold is frequently used in clinical interventions involving psychological therapies . Therefore, a cautious approach will be adopted in the RETURN main trial and a threshold of 80% within each intervention component will be set for a delivery session to be considered to have achieved high fidelity. To provide guidance and to ensure consistency in intervention scoring, a scoring guidance manual was created (see Additional File ). This was developed collaboratively by RETURN researchers using an iterative approach to ensure that the descriptions contained within the manual were understood consistently across the team. The manual was both created and tested using a method whereby audio-recordings of the feasibility intervention sessions were scored independently, results compared, and discrepancies discussed until consensus was achieved (> 80% agreement rate). The development of the fidelity checklist and the scoring guidance manual followed steps three to five as suggested by Walton and colleagues , with an iterative approach utilising feedback from the RETURN researchers to refine the items and scoring guidance. An example of the scoring guidance for the domain of ‘overarching communication skills’ for the demonstration of ‘priorities, beliefs and challenges acknowledged’ is illustrated below: Patient’s priorities, beliefs and challenges acknowledged patients should not be challenged on their beliefs, priorities or challenges experienced previously, even if they are in direct conflict with the principles of the delivery nurse. These should simply be acknowledged as an experience that occurred. Score 0 if patient’s priorities/beliefs are challenged by the nurse e.g. Patient: “I couldn’t get a dentist because there weren’t any” Nurse “There was loads of NHS availability a year ago so that can’t be true”. Score 1 if some attempt is made to acknowledge but the patient’s priorities/beliefs are also challenged e.g. Patient “I couldn’t get a dentist because there weren’t any” Nurse “It sounds like it was really difficult for you to get yourself into the dentist, but there were dentists available”. Score 2 if patient’s priorities/beliefs and challenges are acknowledged during most of the session, but once or twice the nurse challenged the patients on these. Score 3 if acknowledgments rather than challenges are present. Patient: “I couldn’t get a dentist” Nurse: “Sounds like it was really tricky for you to get into a dentist in the past”. Evaluation procedures to support scoring throughout the RETURN main trial will also include the consistent use of the same scoring team and the employment of interrater reliability methods. Where an agreement rate of less than 60% is found between team members responsible for scoring throughout the course of the trial, additional scoring training will take place, again using inter-rater reliability to determine agreement rates. The RETURN checklist has been designed as a multi-functional tool for the implementation of fidelity strategies. Its functions are to act as a standardised training aide, a method to set competency expectations, a means of leveraging feedback to interventionists, a means of monitoring protocol adherence and competency levels throughout the main trial, and to assess the level of fidelity achieved in intervention deliveries at the end of the trial. patients should not be challenged on their beliefs, priorities or challenges experienced previously, even if they are in direct conflict with the principles of the delivery nurse. These should simply be acknowledged as an experience that occurred. Score 0 if patient’s priorities/beliefs are challenged by the nurse e.g. Patient: “I couldn’t get a dentist because there weren’t any” Nurse “There was loads of NHS availability a year ago so that can’t be true”. Score 1 if some attempt is made to acknowledge but the patient’s priorities/beliefs are also challenged e.g. Patient “I couldn’t get a dentist because there weren’t any” Nurse “It sounds like it was really difficult for you to get yourself into the dentist, but there were dentists available”. Score 2 if patient’s priorities/beliefs and challenges are acknowledged during most of the session, but once or twice the nurse challenged the patients on these. Score 3 if acknowledgments rather than challenges are present. Patient: “I couldn’t get a dentist” Nurse: “Sounds like it was really tricky for you to get into a dentist in the past”. Evaluation procedures to support scoring throughout the RETURN main trial will also include the consistent use of the same scoring team and the employment of interrater reliability methods. Where an agreement rate of less than 60% is found between team members responsible for scoring throughout the course of the trial, additional scoring training will take place, again using inter-rater reliability to determine agreement rates. The RETURN checklist has been designed as a multi-functional tool for the implementation of fidelity strategies. Its functions are to act as a standardised training aide, a method to set competency expectations, a means of leveraging feedback to interventionists, a means of monitoring protocol adherence and competency levels throughout the main trial, and to assess the level of fidelity achieved in intervention deliveries at the end of the trial. Several strategies were developed to document and address protocol deviations in the RETURN main trial: A coaching culture will be integrated into the training methodology to promote open communication and rapport between trainers and dental nurses. This aims to facilitate an environment where protocol deviations would be more likely to be reported, and where feedback would be enacted. This will take the form of regular, personalised, and constructive feedback designed to encourage confidence and build both communication and intervention skills. Additionally, monthly, each nurse will have at least one intervention audio-recording evaluated using the RETURN checklist with strengths and any areas for improvement noted. Checklists will be provided to the dental nurses once completed. Where low scores are found, additional intervention sessions will be scored, supplemented with a support site visit. Booster training will trigger where necessary through consistent low scores using the RETURN checklist. The protocol deviation plan will be clearly communicated to dental nurses at the outset of the RETURN main trial set-up phase. This transparent approach aims to cultivate an environment where protocol deviations are viewed as opportunities for learning rather than punitive measures. Learning from the feasibility study suggested that using scripted approaches to intervention delivery were unsuccessful, as is demonstrated in the following observation: The nurse opened the pack and put it on the table. They read through the patient pack introduction information printed on the materials very quietly, not making eye contact with the patient as they did this. The patient was listening intently, leaning forward slightly to be able to hear what the nurse was saying. I felt some of the meaning was lost during this explanation, as the nurse was so quiet and stilted, it was difficult to hear. The nurse came across as very unconfident and reliant on the written materials. This created no room for the patient discussion. Observation 02: Site 02, DN02. For the RETURN main trial therefore, there will be a conscious move away from scripted materials, and instead, training intensity will be increased. In addition, an easy-to-follow intervention crib sheet was developed (see Additional File ), alongside a written intervention training manual, designed to support intervention delivery beyond training (see Additional File ). During the feasibility study, limited resources at sites resulted in just one nurse from each of the two sites taking part in research activities, despite delivering training to multiple nurses in all three sites. As research activities were intended to integrate into nurses’ regular duties within urgent dental care settings, this constraint contributed to recruitment delays, exacerbated by factors such as COVID-19, staff sickness or holiday leave. To address these challenges in the RETURN main trial, additional ‘float’ dental nurses will be employed as part of the core research team to carry our research duties across sites, utilising funds earmarked for reimbursing dental practices for staff time spent on research activities. Furthermore, efforts will be made to train multiple dental nurses at each site, where feasible. These strategies will form part of the early site communications. Contamination was not found to be an issue within the feasibility study. Nonetheless, in the RETURN main trial, training will be provided around the importance of allocation adherence. In addition, portable research activity flow charts detailing the specific actions to follow within each study arm will be provided, supported by regular site visits from the research team. Questions will be included in the RETURN trial follow-up pertaining to contamination (i.e. control group question: ‘Did you receive any materials at your urgent care appointment to help you to find a dentist? If so, what did that look like? ). Training was identified as an area for improvement during the feasibility study. ‘Hiring’ dental nurses to deliver the RETURN intervention Confidence was found to be a major contributing factor to intervention delivery success, detailed in the feasibility observation below: I passed the booklet back to the nurse, and they started going through the booklet. They didn’t explain what the booklet was for. They read out the title on each page loudly, but the rest of the information on the pages was said very quietly and sound a little muddled. The walk through of the booklet didn’t flow, and it’s more like they were reading it to them themselves under their breath to familiarise themselves with the content. DN02: (page 2) “ For healthy teeth do I need to go? ” “ This is Megan , you can see about her story on the video ”. Page 3 is skipped. Page 4 “ Keeping on top of it ” “ It’s important to go all the time ” Page 5 “ This is a picture of a tooth that only the dentist could see , it shows the decay ”. It is very difficult to hear what DN02 was saying, and the overall feeling is someone who lacks confidence. I felt harsh making them deliver when clearly, they didn’t feel ready with any confidence. Observation 05, Site 01: DN02. At the setup phase of the feasibility study, it was stipulated that effective delivery of the intervention would require experienced nurses with proficient communication skills. This expectation was based on the belief that such traits would facilitate the skills required to successfully deliver the intervention. However, implementation revealed challenges to this ideal. Informal discussions with dental staff at sites, recorded in field notes, noted that dental teams could use trial participation as an opportunity to enhance the communication skills of their staff involved in the research. This experience highlights the existence of conflicting priorities when conducting research. As we found dental nurse attributes cannot be guaranteed, the RETURN main trial training will include elements specifically designed to increase confidence and communication skills, including enhanced role-play and a coaching style training approach. In addition, training sessions will not be fixed in length, and instead provision will be based on individualised need. This will be achievable as shadowing training is planned to occur concurrently with patient recruitment, so as not to hamper trial progress. Standardise training The BCC framework recommends training all interventionists together. In the primary dental care setting, this would require inviting dental teams to converge in a mutually convenient location, and taking staff members out of clinic was found to be problematic during the feasibility study. Instead, in the RETURN main trial, a model will be used where site personnel are trained together. As this method could affect the standardisation of the training delivered, multiple strategies were designed to mitigate that risk: Implementation of a ‘train the trainers’ training model led by a clinical psychologist. Using the same team of trainers throughout the trial. Using identical training materials for each site. Using the same role play tasks with all teams trained. Using a training manual and training videos. The development of a central website to house all training materials, as well as providing hard copies of all materials to all trainees. Use a training content checklist to ensure all training components were delivered to all dental teams (see Additional File ). Ensure dental nurse skill acquisition Skill acquisition was not measured as part of the feasibility study. However, observations demonstrated variation in competency between dental nurses. Therefore, a plan was developed for the RETURN main trial to test skill acquisition during the different phases of training: Training phase 1 Good Clinical Practice Training – A one-hour online module. Skill acquisition measured through an online quiz, with a pass mark of 80%. Training phase 2 Intervention training – three hours, face to face delivery with a mixture of didactic learning, open discussions, and role plays. Skill acquisition measured through discussion and observations by a RETURN trainer through an intervention delivery skill acquisition checklist (see Additional File ). Training phase 3 On the job shadowing training – the amount will depend on demonstration of competencies. Skill acquisition will be measured through in vitro observations using the RETURN checklist. Each interventionist will need to achieve a score of 80% within each intervention component in a single session to be signed off as competent to deliver the intervention independently. Scoring will be conducted by the RETURN trainers and scoring decisions will be supported by the guidance manual. Minimise ‘drift’ in dental nurse skills Skills drift was not explicitly monitored during the feasibility study. However, from feasibility observations, it was discovered that intervention skills needed to be practiced regularly to be maintained. Therefore, a strategy to reduce skills drift was developed for the RETURN main trial: Frequent (at least one per month, per nurse) scoring and feedback of audio-recorded interventions using the scoring checklist, including elaborating strengths and areas for development. Triggered site visits to provide additional booster training and support in the event of low scoring (< 60% in any one component). Triggered (by consistent low scores) or requested reflective practice sessions, wherein a selected audio-recording will be discussed with the dental team at site, focusing on intervention elements that went well, and things that could be improved or done differently. Maintaining a collaborative coaching style approach to all feedback provision, booster training and reflective practice sessions to maintain relationships between the trainers and the dental nurses. Accommodate dental nurse differences Stark differences between the skills and experience levels of the feasibility dental nurses were found. The dental nurses involved in the delivery of the RETURN intervention study were not selected by the research team, they were volunteered by the dental practice owners / managers due to their availability and expression of interest in taking part. DN02 had less than 2 years’ experience of dental nursing and lacked confidence with patient communication. DN01 had more than 10 years’ experience, demonstrated good communication skills and overall was more confident in their approach to the intervention. This quotation from DN02 describes this: Yeah. I don’t know it might be easy for other nurses but for my range of vocabulary to like GCSE, maybe some words I found difficult, and how it works, like the way it’s [training materials] worded was difficult. If it was more informal, like ‘What are we going to do?’ ‘We’re going to do this’. Like a chatty kind of presentation maybe. Interview with DN02 There were also differences in day-to-day responsibilities within their respective dental practices, with DN01 taking a more patient engaged role than DN02. These contrasting quotations demonstrate this: It’s very difficult, you know, especially for nurses because they do not have a lot of contact with patients. It’s only the dentist that takes over everything. So we do our own bit in surgery, cleaning, helping, but we don’t have conversations like that with patients. Interview with DN02 I like talking to patients and I like the interaction and chatting with them and, you know, talking to different people as well and finding out their barriers. I think we seem a bit more human to them as well when we sit down and have a chat with them and we’re not just the scary people who work in the dentist. Interview with DN01. An additional challenge identified during the feasibility study was the need for training to encompass multiple methods, accommodating a wide range of baseline research skill levels. This was highlighted by the following observation on the first day of recruitment at site 02: The nurse [DN02] told me that during the feasibility study training, they didn’t know what the word feasibility meant. They described that this word was in big letters on the very first training slide and all they could think about was wanting to Google what that word meant, so found it difficult to keep up with the rest of the training. Observation 01, Site 02: DN02 To maintain training standardisation whilst also acknowledging the challenge of variation between nurses likely be experienced in the main trial, an ‘on-the-job shadowing’ training element was developed. Shadowing training will involve a RETURN team member ‘chaperoning’ a dental nurse whilst they deliver interventions. Tailored support will be provided alongside real-time verbal and written feedback. This training is not time limited. Training will continue until the nurse both demonstrates competency through the scoring checklist and articulates to the trainers that they feel they have achieved a level of confidence sufficient to deliver the intervention independently. This style of ‘on-the-job’ shadowing training was developed for its ability to be highly individualised, and because it reflects the stye of training routinely undertaken by dental nurses in primary care. Enhance buy-in from dental nurses Enhancement of dental nurse buy-in was considered a priority for the upcoming RETURN trial. Within the dental practice setting, a practice owner often acts as the gatekeeper to research conduct. Those carrying out the research become involved later in the process, with vital opportunities to increase buy-in often missed. Accordingly, a series of dental nurse buy-in strategies were developed for implementation in the RETURN main trial: Continuing Professional Development (CPD) accreditation for all training. Training components designed to explain the purpose of the research, paying particular attention to patient benefit. An early interactive information session including dental nurses, highlighting the opportunities presented by the trial for enhanced patient interaction and training. Inclusion of communication skills training targeted to dental nurses. Monthly newsletters aimed at dental nurses and wider practice staff, with the addition of real dental nurse stories about their involvement in the trial and a quiz and prize element. Engagement lunches for dental nurses as a reward for participation. Use of communication modes congruent with dental nurse preferences i.e. WhatsApp messages rather than emails. Regular site visits to increase self-efficacy and confidence with research activities. Dental nurse awards evening to celebrate trial achievements (i.e. best recruiter etc.) Confidence was found to be a major contributing factor to intervention delivery success, detailed in the feasibility observation below: I passed the booklet back to the nurse, and they started going through the booklet. They didn’t explain what the booklet was for. They read out the title on each page loudly, but the rest of the information on the pages was said very quietly and sound a little muddled. The walk through of the booklet didn’t flow, and it’s more like they were reading it to them themselves under their breath to familiarise themselves with the content. DN02: (page 2) “ For healthy teeth do I need to go? ” “ This is Megan , you can see about her story on the video ”. Page 3 is skipped. Page 4 “ Keeping on top of it ” “ It’s important to go all the time ” Page 5 “ This is a picture of a tooth that only the dentist could see , it shows the decay ”. It is very difficult to hear what DN02 was saying, and the overall feeling is someone who lacks confidence. I felt harsh making them deliver when clearly, they didn’t feel ready with any confidence. Observation 05, Site 01: DN02. At the setup phase of the feasibility study, it was stipulated that effective delivery of the intervention would require experienced nurses with proficient communication skills. This expectation was based on the belief that such traits would facilitate the skills required to successfully deliver the intervention. However, implementation revealed challenges to this ideal. Informal discussions with dental staff at sites, recorded in field notes, noted that dental teams could use trial participation as an opportunity to enhance the communication skills of their staff involved in the research. This experience highlights the existence of conflicting priorities when conducting research. As we found dental nurse attributes cannot be guaranteed, the RETURN main trial training will include elements specifically designed to increase confidence and communication skills, including enhanced role-play and a coaching style training approach. In addition, training sessions will not be fixed in length, and instead provision will be based on individualised need. This will be achievable as shadowing training is planned to occur concurrently with patient recruitment, so as not to hamper trial progress. The BCC framework recommends training all interventionists together. In the primary dental care setting, this would require inviting dental teams to converge in a mutually convenient location, and taking staff members out of clinic was found to be problematic during the feasibility study. Instead, in the RETURN main trial, a model will be used where site personnel are trained together. As this method could affect the standardisation of the training delivered, multiple strategies were designed to mitigate that risk: Implementation of a ‘train the trainers’ training model led by a clinical psychologist. Using the same team of trainers throughout the trial. Using identical training materials for each site. Using the same role play tasks with all teams trained. Using a training manual and training videos. The development of a central website to house all training materials, as well as providing hard copies of all materials to all trainees. Use a training content checklist to ensure all training components were delivered to all dental teams (see Additional File ). Skill acquisition was not measured as part of the feasibility study. However, observations demonstrated variation in competency between dental nurses. Therefore, a plan was developed for the RETURN main trial to test skill acquisition during the different phases of training: Training phase 1 Good Clinical Practice Training – A one-hour online module. Skill acquisition measured through an online quiz, with a pass mark of 80%. Training phase 2 Intervention training – three hours, face to face delivery with a mixture of didactic learning, open discussions, and role plays. Skill acquisition measured through discussion and observations by a RETURN trainer through an intervention delivery skill acquisition checklist (see Additional File ). Training phase 3 On the job shadowing training – the amount will depend on demonstration of competencies. Skill acquisition will be measured through in vitro observations using the RETURN checklist. Each interventionist will need to achieve a score of 80% within each intervention component in a single session to be signed off as competent to deliver the intervention independently. Scoring will be conducted by the RETURN trainers and scoring decisions will be supported by the guidance manual. Good Clinical Practice Training – A one-hour online module. Skill acquisition measured through an online quiz, with a pass mark of 80%. Intervention training – three hours, face to face delivery with a mixture of didactic learning, open discussions, and role plays. Skill acquisition measured through discussion and observations by a RETURN trainer through an intervention delivery skill acquisition checklist (see Additional File ). On the job shadowing training – the amount will depend on demonstration of competencies. Skill acquisition will be measured through in vitro observations using the RETURN checklist. Each interventionist will need to achieve a score of 80% within each intervention component in a single session to be signed off as competent to deliver the intervention independently. Scoring will be conducted by the RETURN trainers and scoring decisions will be supported by the guidance manual. Skills drift was not explicitly monitored during the feasibility study. However, from feasibility observations, it was discovered that intervention skills needed to be practiced regularly to be maintained. Therefore, a strategy to reduce skills drift was developed for the RETURN main trial: Frequent (at least one per month, per nurse) scoring and feedback of audio-recorded interventions using the scoring checklist, including elaborating strengths and areas for development. Triggered site visits to provide additional booster training and support in the event of low scoring (< 60% in any one component). Triggered (by consistent low scores) or requested reflective practice sessions, wherein a selected audio-recording will be discussed with the dental team at site, focusing on intervention elements that went well, and things that could be improved or done differently. Maintaining a collaborative coaching style approach to all feedback provision, booster training and reflective practice sessions to maintain relationships between the trainers and the dental nurses. Stark differences between the skills and experience levels of the feasibility dental nurses were found. The dental nurses involved in the delivery of the RETURN intervention study were not selected by the research team, they were volunteered by the dental practice owners / managers due to their availability and expression of interest in taking part. DN02 had less than 2 years’ experience of dental nursing and lacked confidence with patient communication. DN01 had more than 10 years’ experience, demonstrated good communication skills and overall was more confident in their approach to the intervention. This quotation from DN02 describes this: Yeah. I don’t know it might be easy for other nurses but for my range of vocabulary to like GCSE, maybe some words I found difficult, and how it works, like the way it’s [training materials] worded was difficult. If it was more informal, like ‘What are we going to do?’ ‘We’re going to do this’. Like a chatty kind of presentation maybe. Interview with DN02 There were also differences in day-to-day responsibilities within their respective dental practices, with DN01 taking a more patient engaged role than DN02. These contrasting quotations demonstrate this: It’s very difficult, you know, especially for nurses because they do not have a lot of contact with patients. It’s only the dentist that takes over everything. So we do our own bit in surgery, cleaning, helping, but we don’t have conversations like that with patients. Interview with DN02 I like talking to patients and I like the interaction and chatting with them and, you know, talking to different people as well and finding out their barriers. I think we seem a bit more human to them as well when we sit down and have a chat with them and we’re not just the scary people who work in the dentist. Interview with DN01. An additional challenge identified during the feasibility study was the need for training to encompass multiple methods, accommodating a wide range of baseline research skill levels. This was highlighted by the following observation on the first day of recruitment at site 02: The nurse [DN02] told me that during the feasibility study training, they didn’t know what the word feasibility meant. They described that this word was in big letters on the very first training slide and all they could think about was wanting to Google what that word meant, so found it difficult to keep up with the rest of the training. Observation 01, Site 02: DN02 To maintain training standardisation whilst also acknowledging the challenge of variation between nurses likely be experienced in the main trial, an ‘on-the-job shadowing’ training element was developed. Shadowing training will involve a RETURN team member ‘chaperoning’ a dental nurse whilst they deliver interventions. Tailored support will be provided alongside real-time verbal and written feedback. This training is not time limited. Training will continue until the nurse both demonstrates competency through the scoring checklist and articulates to the trainers that they feel they have achieved a level of confidence sufficient to deliver the intervention independently. This style of ‘on-the-job’ shadowing training was developed for its ability to be highly individualised, and because it reflects the stye of training routinely undertaken by dental nurses in primary care. Enhancement of dental nurse buy-in was considered a priority for the upcoming RETURN trial. Within the dental practice setting, a practice owner often acts as the gatekeeper to research conduct. Those carrying out the research become involved later in the process, with vital opportunities to increase buy-in often missed. Accordingly, a series of dental nurse buy-in strategies were developed for implementation in the RETURN main trial: Continuing Professional Development (CPD) accreditation for all training. Training components designed to explain the purpose of the research, paying particular attention to patient benefit. An early interactive information session including dental nurses, highlighting the opportunities presented by the trial for enhanced patient interaction and training. Inclusion of communication skills training targeted to dental nurses. Monthly newsletters aimed at dental nurses and wider practice staff, with the addition of real dental nurse stories about their involvement in the trial and a quiz and prize element. Engagement lunches for dental nurses as a reward for participation. Use of communication modes congruent with dental nurse preferences i.e. WhatsApp messages rather than emails. Regular site visits to increase self-efficacy and confidence with research activities. Dental nurse awards evening to celebrate trial achievements (i.e. best recruiter etc.) Use a scripted curriculum or treatment manual Based on feasibility observations, scripts will not be utilised in the RETURN main trial. Instead, a selection of prompts will be provided to the nurses to ensure the intervention’s essential components are delivered. These prompts will take the form of the training manual (including intervention delivery cheat sheets), the intervention crib sheet, and videos demonstrating intervention delivery. Some components however, are ‘scripted’ within the intervention materials themselves, such as the goal and action planning section (see Additional File ). Assess non-specific effects through multiple methods and on an ongoing basis Non-specific factors (such as empathy and components that lend themselves to the target communication style) will be assessed as a stand-alone domain within the RETURN checklist. Nonspecific effects will also specifically be discussed during shadowing training. Ensure both adherence to the protocol and competency of intervention delivery Adherence and competency of intervention deliveries will be assessed through the application of the RETURN checklist throughout the main trial. In addition, 100% of all available recordings will be assessed at the end of the main trial to provide a comprehensive overview of the adherence and competency of intervention deliveries. A fidelity threshold of 80% in every domain per intervention delivery will be applied when scoring the recordings. Based on feasibility observations, scripts will not be utilised in the RETURN main trial. Instead, a selection of prompts will be provided to the nurses to ensure the intervention’s essential components are delivered. These prompts will take the form of the training manual (including intervention delivery cheat sheets), the intervention crib sheet, and videos demonstrating intervention delivery. Some components however, are ‘scripted’ within the intervention materials themselves, such as the goal and action planning section (see Additional File ). Non-specific factors (such as empathy and components that lend themselves to the target communication style) will be assessed as a stand-alone domain within the RETURN checklist. Nonspecific effects will also specifically be discussed during shadowing training. Adherence and competency of intervention deliveries will be assessed through the application of the RETURN checklist throughout the main trial. In addition, 100% of all available recordings will be assessed at the end of the main trial to provide a comprehensive overview of the adherence and competency of intervention deliveries. A fidelity threshold of 80% in every domain per intervention delivery will be applied when scoring the recordings. Ensure participants’ understanding of the intervention Although data collected from the patients during the feasibility study suggested that patients overwhelmingly found the intervention useful, understandable and relevant, it is helpful to outline here the steps taken to enhance participants’ understanding of the intervention during its development: The RETURN intervention is designed to be engaging, specifically targeted to the trial population. An extensive patient and public involvement (PPI) work stream fed into its design (full details have been published elsewhere ), with the aim of ensuring the materials were culturally relevant, containing congruent messages and images to the trial population. A design company and a professional illustrator were employed to embed these strategies. To account for different learning styles, information was presented and repeated using multiple formats - verbal, written, pictorial and videography. The intervention materials were written to a reading age of 8 years to ensure health literacy inclusivity. Intervention delivery sessions are formatted as reciprocal conversations, and therefore by design, mutual understanding between the patient and dental nurse is embedded. During training and throughout the recruitment period, intervention deliveries will be scored, and feedback provided to ensure that ‘reciprocity’ and patient understanding is embedded, with these criteria factored into the RETURN checklist. Ensure participants’ ability to perform behavioural skills The RETURN intervention seeks to target the behaviour of routine dental appointment visiting. To ensure patients’ ability to perform the behavioural skills required, the intervention was designed to be tailored, considering obstacles unique to individuals’ lives. The intervention culminates in a goal setting and action planning exercise, where participants think through their individual circumstances, and write out SMART (specific, measurable, achievable, relevant and time-bound) goals and plans to help them to overcome their barriers. In this way the target behavioural skills were articulated, discussed and broken down into small actions. From the feasibility observations, this element of the intervention needed improvement, specifically around patient engagement. The nurse put the booklet to one side, and then took the planning booklet from their knee. “We know that writing plans helps”. I felt this introduction didn’t really explain to the participant what the nurse was asking them to do – The nurse looked at me to help as they were getting their words muddled…The nurse devised the plan for the participant, rather than letting the participant make the plan for themselves. The patient set their goal themselves, but they did not put in much detail. They wrote down 3 words and didn’t discuss this with the nurse at all. DN02, Observation 11 For the RETURN main trial, several strategies will therefore be implemented to improve how assessment of behavioural skills were conducted during the intervention delivery sessions: Training will include a dedicated component on how to facilitate goal setting and action planning, emphasising the importance of facilitating and not leading the task, and how to encourage patients to think through and articulate their own mechanisms. Goal setting and action planning have been included on the RETURN checklist, and timely feedback will be provided. A follow-up text message will be sent to participants a week post-intervention including the participants’ own wording from their goals and plans set within the intervention sessions to reinforce behavioural skills and build self-efficacy. The 6-month follow-up telephone call to patients will explore their comprehension of the intervention and how meaningful they found it to track receipt. A component of the intervention conversation will encourage discussion around what was achieved during the intervention session. This has been designed to improve participant receipt of the intervention by setting intentions. This element is also included in the RETURN checklist assessment. Although data collected from the patients during the feasibility study suggested that patients overwhelmingly found the intervention useful, understandable and relevant, it is helpful to outline here the steps taken to enhance participants’ understanding of the intervention during its development: The RETURN intervention is designed to be engaging, specifically targeted to the trial population. An extensive patient and public involvement (PPI) work stream fed into its design (full details have been published elsewhere ), with the aim of ensuring the materials were culturally relevant, containing congruent messages and images to the trial population. A design company and a professional illustrator were employed to embed these strategies. To account for different learning styles, information was presented and repeated using multiple formats - verbal, written, pictorial and videography. The intervention materials were written to a reading age of 8 years to ensure health literacy inclusivity. Intervention delivery sessions are formatted as reciprocal conversations, and therefore by design, mutual understanding between the patient and dental nurse is embedded. During training and throughout the recruitment period, intervention deliveries will be scored, and feedback provided to ensure that ‘reciprocity’ and patient understanding is embedded, with these criteria factored into the RETURN checklist. The RETURN intervention seeks to target the behaviour of routine dental appointment visiting. To ensure patients’ ability to perform the behavioural skills required, the intervention was designed to be tailored, considering obstacles unique to individuals’ lives. The intervention culminates in a goal setting and action planning exercise, where participants think through their individual circumstances, and write out SMART (specific, measurable, achievable, relevant and time-bound) goals and plans to help them to overcome their barriers. In this way the target behavioural skills were articulated, discussed and broken down into small actions. From the feasibility observations, this element of the intervention needed improvement, specifically around patient engagement. The nurse put the booklet to one side, and then took the planning booklet from their knee. “We know that writing plans helps”. I felt this introduction didn’t really explain to the participant what the nurse was asking them to do – The nurse looked at me to help as they were getting their words muddled…The nurse devised the plan for the participant, rather than letting the participant make the plan for themselves. The patient set their goal themselves, but they did not put in much detail. They wrote down 3 words and didn’t discuss this with the nurse at all. DN02, Observation 11 For the RETURN main trial, several strategies will therefore be implemented to improve how assessment of behavioural skills were conducted during the intervention delivery sessions: Training will include a dedicated component on how to facilitate goal setting and action planning, emphasising the importance of facilitating and not leading the task, and how to encourage patients to think through and articulate their own mechanisms. Goal setting and action planning have been included on the RETURN checklist, and timely feedback will be provided. A follow-up text message will be sent to participants a week post-intervention including the participants’ own wording from their goals and plans set within the intervention sessions to reinforce behavioural skills and build self-efficacy. The 6-month follow-up telephone call to patients will explore their comprehension of the intervention and how meaningful they found it to track receipt. A component of the intervention conversation will encourage discussion around what was achieved during the intervention session. This has been designed to improve participant receipt of the intervention by setting intentions. This element is also included in the RETURN checklist assessment. Participant performance of the intervention skills will be assessed in settings in which the intervention might be applied Data was collected from patients of the feasibility study amid the first COVID lockdown restrictions (May – September 2020), and accordingly it was not possible to assess enactment at that time. Therefore, as part of the RETURN main trial telephone follow-up at three time points, questions will be included about whether and how the intervention materials and associated intervention skills had been used since leaving the urgent care dental setting. Questions will focus on which parts of the intervention had been used, whether the intervention skills had been enacted (i.e. phoning for a dental appointment, exploring which dental practice they may like to contact, attending a dental appointment) and how the intervention supported any actions taken to attend a routine dental appointment. Additionally, enactment strategies are embedded within the intervention materials themselves. Some materials are labelled ‘to look at at home’, providing encouragement and support in locating a dentist, making an appointment and thereafter attending an appointment – the behaviours targeted by the intervention. The full RETURN fidelity strategy is summarised in Table . The strategies presented there show the tangible actions taken to attend to the various intervention fidelity recommendations, which may help other researchers to think through the strategies that will apply to their studies (i.e. using audio recordings to monitor skills drift). Data was collected from patients of the feasibility study amid the first COVID lockdown restrictions (May – September 2020), and accordingly it was not possible to assess enactment at that time. Therefore, as part of the RETURN main trial telephone follow-up at three time points, questions will be included about whether and how the intervention materials and associated intervention skills had been used since leaving the urgent care dental setting. Questions will focus on which parts of the intervention had been used, whether the intervention skills had been enacted (i.e. phoning for a dental appointment, exploring which dental practice they may like to contact, attending a dental appointment) and how the intervention supported any actions taken to attend a routine dental appointment. Additionally, enactment strategies are embedded within the intervention materials themselves. Some materials are labelled ‘to look at at home’, providing encouragement and support in locating a dentist, making an appointment and thereafter attending an appointment – the behaviours targeted by the intervention. The full RETURN fidelity strategy is summarised in Table . The strategies presented there show the tangible actions taken to attend to the various intervention fidelity recommendations, which may help other researchers to think through the strategies that will apply to their studies (i.e. using audio recordings to monitor skills drift). This article presents a comprehensive fidelity strategy to be embedded within the RETURN main trial. To the best of the authors’ knowledge, this is the first published fidelity strategy for the testing of a BCI in the primary care dental setting. This strategy has sought to balance the needs of both the research and the dental practice context. Research has shown that outcomes are improved when interventions are delivered with a high degree of fidelity , and one review found that effect sizes are at least 2 to 3 times higher when interventions are delivered with high intervention fidelity . In addition, by devising and implementing a robust fidelity plan, theoretically this allows for the assessment of ‘infidelity’ and for exploration of how differences in fidelity may be associated with outcomes . The development of a comprehensive fidelity strategy for use in the RETURN main trial therefore seeks to provide the methodological assurances necessary to determine whether the RETURN intervention is effective or not. In addition, published fidelity strategies can serve as blueprints for other researchers, enabling the replication of interventions across various settings or populations . This facilitates accurate implementation and consistency among studies, ultimately promoting the reproducibility of findings. Furthermore, the dissemination of fidelity strategies enhances transparency and accountability in research, allowing stakeholders—including funding agencies, peer reviewers, and the broader scientific community—to assess the rigor and validity of study methodologies, thereby ensuring ethical conduct and integrity in research practices . We would encourage the publication of fidelity strategies as a way of sharing best practice to others in the field. One strong message from the findings of the feasibility analysis was the importance of the role of the research team in dental research. It is clear from this study that research teams facilitating BCIs in the primary dental care context need to be mindful of the constraints of the setting and the pressures and skill mix of the healthcare professionals within it. Whilst the primary aim of the strategies developed for the RETURN main trial is to enhance intervention fidelity, a secondary aim of the selected strategies is to minimise burden for the dental teams involved. This is important as the primary dental care setting routinely incurs challenges such as time and staffing limitations , and for sites working to provide urgent clinical care in a target driven remuneration system (such as the NHS) as in RETURN, there are additional pressures which may well have been exacerbated post-COVID-19 . An example of this ‘shift’ in burden is where the decision made to audio-record all of the intervention delivery sessions to monitor skills and assess delivery fidelity (rather than other methods such as asking the dental nurses to complete check-lists as has been adopted in other primary care dental trials ). This will reduce the time and process burden on the dental nurses within the wider context of the RCT which, outside of the intervention delivery, has its own lengthy procedural requirements (e.g. consenting, randomising, data collection, data entry etc.). Additionally, the use of audio-recordings for fidelity monitoring is considered the gold-standard , and whilst acknowledging that this method is researcher resource intensive, it is deemed the most appropriate method for use in the primary dental care context. This publication provides a thorough description of the RETURN fidelity strategy, which should be considered alongside the RETURN main trial results when they are published to assure the scientific integrity of our research practices. Limitations This study has several limitations. Observations and interviews were conducted at only two sites with two dental nurses due to the small-scale nature of the feasibility study and early termination due to the COVID-19 pandemic. This means that a narrow range of perspectives were included in the findings used to develop the fidelity strategy. Additionally, several BCC recommendations were not fully implemented in the RETURN fidelity strategy. Specifically: Monitoring of Control Participants : The fidelity plan did not include monitoring control participant activities, although post-delivery participant self-report contamination assessments were conducted. This decision was made to enhance the acceptability of audio recordings among dental teams and patients. Only intervention delivery sessions were recorded, with control group conduct comprehensively covered in training. Protocol Review Group : A protocol review group was not established to ensure the active ingredients of the intervention were fully operationalised due to resources limitations. Nevertheless, the intervention and training plan received input from two psychologists who were part of the RETURN team. Matching Interventionist Characteristics : Due to constraints within the setting, it was not feasible to match key characteristics of the trial population with those delivering the intervention. However, a deliberate choice was made to involve dental nurses rather than dentists in the study design to facilitate rapport building. This decision was support by PPI work. Use of Independent Coders : The use of independent coders was not feasible for the RETURN main trial due to resource limitations. However, as per recommendations by Borelli , the coding team was blind to outcome data. Pre and post-test measures : To minimise dental staff burden and maintain proportionate measures, pre- and post-test process and knowledge assessments were not utilised in the RETURN main trial. The RETURN feasibility study was conducted in England, UK within the context of the NHS primary dental care system. Within this system, the dental sites involved in the delivery of the RETURN research were providing commissioned urgent dental care in accordance with agreed General Dental Services (GDS) contracts. GDS contracts require a pre-defined number of Units of Dental Activity (UDAs) to be fulfilled within a year and for an agreed remuneration value . However, any unmet clinical delivery targets can result in financial claw-back. Given that within this system, there was no additional capacity allocated for the delivery of the RETURN research, there was potential for tension between clinical contractual obligations and research delivery. Consequently, the RETURN fidelity strategy was developed with this context in mind. Whilst the dental practice owners were financially compensated for staff time spent on the research delivery, no additional levers were in place to build research capacity, with those ‘doing’ the research often delivering their usual role alongside. This resulted in challenges and meant that the RETURN research team needed to be mindful of the context, and the fidelity strategies developed. In addition, those delivering the research (in this case dental nurses) were not directly in receipt of any remuneration for their additional efforts, and this was also considered during the development of our strategy. Comparisons of this context to other primary care dental health systems across the globe suggests alternative fidelity strategies could be employed to best suit different contexts, and that the fidelity approach laid out within the paper may need to be adapted to better suit each context. For example, in some States in the United States of America (USA), the dental health system is solely privately funded . A private dental health system, not constrained by targets in the same way as the GDS contracts within the NHS, in theory, could have more scope for research taking place alongside clinical delivery without it being squeezed out by business pressures. This could lead to a lighter-touch fidelity strategy employment. In addition, schemes such as the National Dental Practice-Based Research Network in the USA or the Australian Dental Practice-Based Research Network which build capacity for research delivery within dental practices could play a key role in research facilitation which again, may alter fidelity strategy approaches. Finally, an important consideration to acknowledge is what it means for an RCT where researchers intervene to influence intervention fidelity. It could be argued that by manipulating intervention fidelity it changes the implementation landscape to an extent that recorded outcomes are no longer the simple effect of trial allocation, and therefore, that this may not be representative of outcomes that would be achieved in the real-world . However, for reasons described throughout this article, the primary dental care environment is unique and challenging, and therefore the decision was taken to ensure that intervention fidelity will be closely monitored and improved throughout the RETURN main trial. Dental teams can be inexperienced with conducting research trials , and researchers also have a responsibility to those involved in the conduct of research to provide support and guidance to ensure the best outcomes for the trial. Conclusions and implications The fidelity strategy outlined in this paper serves as a blueprint for researchers conducting BCI trials in primary dental care settings. This environment presents unique challenges, necessitating a contextually informed approach to enhance fidelity. However, many strategies detailed herein could be transferable to other BCI trials in similar contexts, despite being specifically tailored for the RETURN trial. The RETURN fidelity strategy summary could be a useful tool for other BCI trialists in the primary dental care setting, as this provides tangible examples of how the strategies were operationalised. We image that the extent of these strategies will alter depending on the context, resource availability and the intervention itself. This publication outlines a best practice approach and should be read in conjunction with the forthcoming results of the RETURN main trial. This study has several limitations. Observations and interviews were conducted at only two sites with two dental nurses due to the small-scale nature of the feasibility study and early termination due to the COVID-19 pandemic. This means that a narrow range of perspectives were included in the findings used to develop the fidelity strategy. Additionally, several BCC recommendations were not fully implemented in the RETURN fidelity strategy. Specifically: Monitoring of Control Participants : The fidelity plan did not include monitoring control participant activities, although post-delivery participant self-report contamination assessments were conducted. This decision was made to enhance the acceptability of audio recordings among dental teams and patients. Only intervention delivery sessions were recorded, with control group conduct comprehensively covered in training. Protocol Review Group : A protocol review group was not established to ensure the active ingredients of the intervention were fully operationalised due to resources limitations. Nevertheless, the intervention and training plan received input from two psychologists who were part of the RETURN team. Matching Interventionist Characteristics : Due to constraints within the setting, it was not feasible to match key characteristics of the trial population with those delivering the intervention. However, a deliberate choice was made to involve dental nurses rather than dentists in the study design to facilitate rapport building. This decision was support by PPI work. Use of Independent Coders : The use of independent coders was not feasible for the RETURN main trial due to resource limitations. However, as per recommendations by Borelli , the coding team was blind to outcome data. Pre and post-test measures : To minimise dental staff burden and maintain proportionate measures, pre- and post-test process and knowledge assessments were not utilised in the RETURN main trial. The RETURN feasibility study was conducted in England, UK within the context of the NHS primary dental care system. Within this system, the dental sites involved in the delivery of the RETURN research were providing commissioned urgent dental care in accordance with agreed General Dental Services (GDS) contracts. GDS contracts require a pre-defined number of Units of Dental Activity (UDAs) to be fulfilled within a year and for an agreed remuneration value . However, any unmet clinical delivery targets can result in financial claw-back. Given that within this system, there was no additional capacity allocated for the delivery of the RETURN research, there was potential for tension between clinical contractual obligations and research delivery. Consequently, the RETURN fidelity strategy was developed with this context in mind. Whilst the dental practice owners were financially compensated for staff time spent on the research delivery, no additional levers were in place to build research capacity, with those ‘doing’ the research often delivering their usual role alongside. This resulted in challenges and meant that the RETURN research team needed to be mindful of the context, and the fidelity strategies developed. In addition, those delivering the research (in this case dental nurses) were not directly in receipt of any remuneration for their additional efforts, and this was also considered during the development of our strategy. Comparisons of this context to other primary care dental health systems across the globe suggests alternative fidelity strategies could be employed to best suit different contexts, and that the fidelity approach laid out within the paper may need to be adapted to better suit each context. For example, in some States in the United States of America (USA), the dental health system is solely privately funded . A private dental health system, not constrained by targets in the same way as the GDS contracts within the NHS, in theory, could have more scope for research taking place alongside clinical delivery without it being squeezed out by business pressures. This could lead to a lighter-touch fidelity strategy employment. In addition, schemes such as the National Dental Practice-Based Research Network in the USA or the Australian Dental Practice-Based Research Network which build capacity for research delivery within dental practices could play a key role in research facilitation which again, may alter fidelity strategy approaches. Finally, an important consideration to acknowledge is what it means for an RCT where researchers intervene to influence intervention fidelity. It could be argued that by manipulating intervention fidelity it changes the implementation landscape to an extent that recorded outcomes are no longer the simple effect of trial allocation, and therefore, that this may not be representative of outcomes that would be achieved in the real-world . However, for reasons described throughout this article, the primary dental care environment is unique and challenging, and therefore the decision was taken to ensure that intervention fidelity will be closely monitored and improved throughout the RETURN main trial. Dental teams can be inexperienced with conducting research trials , and researchers also have a responsibility to those involved in the conduct of research to provide support and guidance to ensure the best outcomes for the trial. The fidelity strategy outlined in this paper serves as a blueprint for researchers conducting BCI trials in primary dental care settings. This environment presents unique challenges, necessitating a contextually informed approach to enhance fidelity. However, many strategies detailed herein could be transferable to other BCI trials in similar contexts, despite being specifically tailored for the RETURN trial. The RETURN fidelity strategy summary could be a useful tool for other BCI trialists in the primary dental care setting, as this provides tangible examples of how the strategies were operationalised. We image that the extent of these strategies will alter depending on the context, resource availability and the intervention itself. This publication outlines a best practice approach and should be read in conjunction with the forthcoming results of the RETURN main trial. Below is the link to the electronic supplementary material. Supplementary Material 1 Supplementary Material 2 Supplementary Material 3 Supplementary Material 4 Supplementary Material 5 Supplementary Material 6 |
Association between Swallowing Outcomes and Dose to Critical Swallow Structures in Patients Undergoing Transoral Robotic Surgery and Post-Operative Radiation Therapy | 083947dd-097b-4d7b-b481-8292eef13416 | 11762566 | Surgical Procedures, Operative[mh] | Primary transoral robotic surgery (TORS) and definitive intensity modulated radiation therapy (IMRT) are both accepted treatment options for early-stage oropharyngeal cancer (OPC) with excellent survival outcomes and similar quality of life . The decision regarding treatment modality is based on individual patient and tumour factors, with the aim of optimising functional outcomes, in particular speech and swallow, without compromising oncological outcomes. Upfront TORS allows unimodality treatment in appropriately selected patients and pathologically directed adjuvant treatment in others, including de-intensification of radiation therapy (RT) and/or omission of chemotherapy . A randomised trial comparing definitive RT and TORS for OPC is inherently difficult. The ORATOR trial demonstrated that primary RT was associated with superior swallowing function compared to TORS at 1, 2 and 3 years. However, the difference was statistically significant only at 1 year, and did not meet the threshold for a clinically meaningful change at any timepoint . Various limitations of the ORATOR trial have been cited: small sample size, ‘over-treatment’ with adjuvant therapy, larger than necessary surgical margins, and the overuse of elective tracheostomies. The ORATOR2 trial attempted to evaluate de-escalated treatment of HPV-related OPC, by comparing surgical treatment (TORS and neck dissection followed by adjuvant RT based on pathology) versus non-surgical treatment (primary RT to 60 Gy with or without chemotherapy) . Swallow outcomes at 1 year were very good in both arms, however the trial was closed early due to two treatment-related deaths in the surgical arm. Retrospective studies suggest dysphagia at six months after completion of treatment is similar for patients who undergo primary TORS and neck dissection versus non-surgical management of early OPC . Recently-published randomised data supports the benefit of dysphagia-optimised intensity-modulated radiotherapy (DO-IMRT) for patients with oropharyngeal or hypopharyngeal cancer undergoing bilateral neck irradiation. A significant reduction in mean dose to the pharyngeal constrictor muscles was achieved using DO-IMRT, which correlated with improved swallow related quality of life at 12 months . Omission of RT to the primary site following TORS is another method to reduce treatment related toxicities and improve swallow function and quality of life. Various studies suggest omission of adjuvant irradiation of the primary site in well-selected patients may result in improved swallowing and speech outcomes while maintaining excellent local control . For patients undergoing definitive RT, increased dose received by dysphagia and aspiration-related structures (DARS) is associated with worse physical, functional and patient reported outcomes . This study aimed to describe the relationship between dose to DARS and swallow outcomes for patients undergoing TORS followed by PORT for early stage OPC.
Study Design and Participants A prospective, non-randomized cohort study was undertaken in a single Australian tertiary oncology centre. Recruitment was carried out consecutively between January 2017 and May 2019. The trial was approved by the Royal Prince Alfred Research and Ethics committee (Sydney, Australia; Protocol X17-0047). All participants provided written informed consent. Eligible patients were aged 18 years or over with AJCC 8th edition clinical stage I (T1-2 N0-1 M0) histologically-confirmed squamous cell carcinoma of the oropharynx, who were suitable for primary TORS and unilateral neck dissection and received post-operative radiation therapy (PORT) at our institution. Any p16/HPV status were eligible for inclusion. All cases were discussed in a dedicated multidisciplinary team (MDT) meeting prior to treatment. Patients deemed suitable by the MDT for either primary TORS or RT discussed these options with a surgeon and radiation oncologist before deciding on and proceeding with treatment. Patients were not eligible if they had a pre-existing diagnosis which might contribute to a communication or swallowing impairment or underwent TORS as a salvage procedure. Treatment Patients were considered suitable for single-staged TORS and unilateral selective neck dissection for cT1-2 N0-1 tonsil or lateralized base of tongue SCC, where clear margins could be reasonably achieved with favourable morbidity based on clinical and radiological assessment. In the case of close surgical margins (< 1 mm), re-resection was recommended where possible, prior to consideration of PORT. PORT to the ipsilateral neck was recommended for patients with pathological evidence of two or more lymph nodes, or presence of extranodal extension (ENE), and considered for a single node > 3 cm without ENE. PORT to the primary tumour bed was recommended for positive margins (where re-resection was not possible or would result in an unacceptable functional outcome), or presence of multiple adverse features including perineural invasion (PNI), lymphovascular invasion (LVI), close margins (< 1 mm), poorly differentiated tumour, or endophytic growth pattern with infiltrating borders. Our institution has historically had a preference towards de-escalating adjuvant radiotherapy to the primary site following TORS, and has previously reported on excellent rates of local control with this approach . Concurrent chemotherapy with PORT was recommended for positive margins, ENE, or extensive nodal burden. PORT was delivered to a dose of 60 Gy in 2 Gy per fraction over 6 weeks, with an optional simultaneous integrated boost to 63–66 Gy to areas of ENE or microscopic positive margins. Patients deemed to have low-moderate risk were treated with low-intermediate risk disease were treated to 54 Gy (1.8 Gy per fraction) at one of the treating clinicians’ discretion, similar to the approach tested in the ECOG-ACRIN E3311 trial . All patients were treated using intensity-modulated radiotherapy (IMRT) or RapidArc (VMAT) technique, with custom thermoplastic mask immobilisation and daily image guidance. Treatment plans were optimised according to the standard departmental protocol, without employing a ‘dysphagia-optimised IMRT’ technique such as used in the recently published ‘DARS’ study . DARS that were not contoured at the time of initial treatment were retrospectively contoured (according to guidelines by Christianen et al.) by a clinician blinded to the dose distribution, for inclusion in the dosimetric analysis . Dosimetric Analysis DARS included the superior, middle and inferior constrictor muscles (SCM, MCM, ICM respectively); cricopharyngeus muscle (CPM); oesophageal inlet muscle (OIM); cervical oesophagus (CE); base of tongue (BOT); supraglottic larynx (SL) and glottic larynx (GL) . Dosimetric parameters were extracted from the treatment planning system (Eclipse, Varian Medical Systems, Inc), including the mean dose, V50Gy, and V60Gy (the percentage of structure receiving at least 50 Gy or at least 60 Gy respectively). Swallowing Patient and clinician reported outcomes were prospectively recorded prior to TORS, and then 12 months post-completion of RT. All participants completed the MD Anderson Dysphagia Inventory (MDADI) , a 20-item instrument using a 5-point Likert scale to assess global, physical, emotional, and functional swallowing symptomology. Higher MDADI scores (up to total composite score of 100) indicate superior functioning and higher swallow-related quality of life. Our institution places a nasogastric tube (NGT) inserted at the time of TORS. Patients commence oral trials with the Speech Pathologist between day 1 and 3 post-operatively, starting with water then upgrading texture based on surgical clearance. The NGT is removed after the surgical, nursing, and allied health teams came to a consensus that the patient has demonstrated their ability to manage an oral diet, at which time the tube would be removed. All participants were reviewed during their inpatient surgical admission then weekly during radiation therapy by the treating Radiation Oncologist, dedicated Nurse Practitioner, Dietitian and Speech Pathologist, with standard proactive symptom management of acute toxicities. Routine swallow interventions included compensatory and rehabilitation exercises specific to the participant’s presenting condition as per usual clinical practice, although there was no standardised protocol for assessment and rehabilitation of swallow function as part of this study. Participants were encouraged to continue oral intake during PORT as a proactive approach to swallow therapy . Statistical Analysis Statistical analysis was carried out with system software R i386 3.2.2 (The R Foundation for Statistical Computing). Generalized Estimating Equations (GEE) were used to model the trajectory of swallowing outcome scores from pre-surgery to 12-months post-radiotherapy using the geepack and lme4 packages for each individual clinical and dosimetric variable. GEEs allow incorporation of participants with missing data at selected time points. The beta score is the coefficient of each predictor, arising out of the linear model for the MDADI score at 12 months. The confidence intervals (CIs) were calculated to reflect the corresponding 95% CIs for beta.
A prospective, non-randomized cohort study was undertaken in a single Australian tertiary oncology centre. Recruitment was carried out consecutively between January 2017 and May 2019. The trial was approved by the Royal Prince Alfred Research and Ethics committee (Sydney, Australia; Protocol X17-0047). All participants provided written informed consent. Eligible patients were aged 18 years or over with AJCC 8th edition clinical stage I (T1-2 N0-1 M0) histologically-confirmed squamous cell carcinoma of the oropharynx, who were suitable for primary TORS and unilateral neck dissection and received post-operative radiation therapy (PORT) at our institution. Any p16/HPV status were eligible for inclusion. All cases were discussed in a dedicated multidisciplinary team (MDT) meeting prior to treatment. Patients deemed suitable by the MDT for either primary TORS or RT discussed these options with a surgeon and radiation oncologist before deciding on and proceeding with treatment. Patients were not eligible if they had a pre-existing diagnosis which might contribute to a communication or swallowing impairment or underwent TORS as a salvage procedure.
Patients were considered suitable for single-staged TORS and unilateral selective neck dissection for cT1-2 N0-1 tonsil or lateralized base of tongue SCC, where clear margins could be reasonably achieved with favourable morbidity based on clinical and radiological assessment. In the case of close surgical margins (< 1 mm), re-resection was recommended where possible, prior to consideration of PORT. PORT to the ipsilateral neck was recommended for patients with pathological evidence of two or more lymph nodes, or presence of extranodal extension (ENE), and considered for a single node > 3 cm without ENE. PORT to the primary tumour bed was recommended for positive margins (where re-resection was not possible or would result in an unacceptable functional outcome), or presence of multiple adverse features including perineural invasion (PNI), lymphovascular invasion (LVI), close margins (< 1 mm), poorly differentiated tumour, or endophytic growth pattern with infiltrating borders. Our institution has historically had a preference towards de-escalating adjuvant radiotherapy to the primary site following TORS, and has previously reported on excellent rates of local control with this approach . Concurrent chemotherapy with PORT was recommended for positive margins, ENE, or extensive nodal burden. PORT was delivered to a dose of 60 Gy in 2 Gy per fraction over 6 weeks, with an optional simultaneous integrated boost to 63–66 Gy to areas of ENE or microscopic positive margins. Patients deemed to have low-moderate risk were treated with low-intermediate risk disease were treated to 54 Gy (1.8 Gy per fraction) at one of the treating clinicians’ discretion, similar to the approach tested in the ECOG-ACRIN E3311 trial . All patients were treated using intensity-modulated radiotherapy (IMRT) or RapidArc (VMAT) technique, with custom thermoplastic mask immobilisation and daily image guidance. Treatment plans were optimised according to the standard departmental protocol, without employing a ‘dysphagia-optimised IMRT’ technique such as used in the recently published ‘DARS’ study . DARS that were not contoured at the time of initial treatment were retrospectively contoured (according to guidelines by Christianen et al.) by a clinician blinded to the dose distribution, for inclusion in the dosimetric analysis .
DARS included the superior, middle and inferior constrictor muscles (SCM, MCM, ICM respectively); cricopharyngeus muscle (CPM); oesophageal inlet muscle (OIM); cervical oesophagus (CE); base of tongue (BOT); supraglottic larynx (SL) and glottic larynx (GL) . Dosimetric parameters were extracted from the treatment planning system (Eclipse, Varian Medical Systems, Inc), including the mean dose, V50Gy, and V60Gy (the percentage of structure receiving at least 50 Gy or at least 60 Gy respectively).
Patient and clinician reported outcomes were prospectively recorded prior to TORS, and then 12 months post-completion of RT. All participants completed the MD Anderson Dysphagia Inventory (MDADI) , a 20-item instrument using a 5-point Likert scale to assess global, physical, emotional, and functional swallowing symptomology. Higher MDADI scores (up to total composite score of 100) indicate superior functioning and higher swallow-related quality of life. Our institution places a nasogastric tube (NGT) inserted at the time of TORS. Patients commence oral trials with the Speech Pathologist between day 1 and 3 post-operatively, starting with water then upgrading texture based on surgical clearance. The NGT is removed after the surgical, nursing, and allied health teams came to a consensus that the patient has demonstrated their ability to manage an oral diet, at which time the tube would be removed. All participants were reviewed during their inpatient surgical admission then weekly during radiation therapy by the treating Radiation Oncologist, dedicated Nurse Practitioner, Dietitian and Speech Pathologist, with standard proactive symptom management of acute toxicities. Routine swallow interventions included compensatory and rehabilitation exercises specific to the participant’s presenting condition as per usual clinical practice, although there was no standardised protocol for assessment and rehabilitation of swallow function as part of this study. Participants were encouraged to continue oral intake during PORT as a proactive approach to swallow therapy .
Statistical analysis was carried out with system software R i386 3.2.2 (The R Foundation for Statistical Computing). Generalized Estimating Equations (GEE) were used to model the trajectory of swallowing outcome scores from pre-surgery to 12-months post-radiotherapy using the geepack and lme4 packages for each individual clinical and dosimetric variable. GEEs allow incorporation of participants with missing data at selected time points. The beta score is the coefficient of each predictor, arising out of the linear model for the MDADI score at 12 months. The confidence intervals (CIs) were calculated to reflect the corresponding 95% CIs for beta.
Participants There were 44 patients who underwent TORS for early stage OPC between 2017 and 2019. Of these, 25 patients were excluded for analysis for reasons including receiving PORT at an external site ( n = 6), not receiving PORT ( n = 18), or radiotherapy to the bilateral neck ( n = 1). The remaining 19 patients underwent TORS + PORT (to ipsilateral neck +/- primary site) and were included in the final analysis. Patient demographics, tumour stage and subsite, and treatment details are listed in Table . Primary tumours arose from the tonsil in 12 patients (63%), and base of tongue in seven patients (37%). The majority of tumours were T2 ( n = 12, 63%) and node positive ( n = 18, 95%). Almost all tumours were p16 positive ( n = 18, 95%). No patients experienced disease relapse or required further treatment during the study follow-up period. Radiation Therapy Of the 19 patients in the TORS + PORT group, the majority ( n = 14, 74%) received PORT to the ipsilateral neck alone, and the remainder ( n = 5, 26%) received treatment to the primary site and ipsilateral neck. Median and most commonly prescribed dose was 60 Gy in 30 fractions (range 54–66 Gy in 30 fractions). The most common indication for PORT was nodal involvement and extranodal extension. All patients completed treatment in full. Six patients (32%) received concurrent chemotherapy (Table ). Mean dose, V50Gy, and V60Gy to the base of tongue, superior, and middle pharyngeal constrictor was significantly lower in those who received PORT to the neck alone, compared to patients where the primary site was treated (Table ). Swallowing Following TORS, 17 (89%) participants received nasogastric tube (NGT) feeding (mean 6 days, range 0–24 days). All participants were consuming an oral diet prior to commencing PORT. Two patients (10%) who underwent definitive RT had a prophylactic gastrostomy tube placed prior to treatment, and one had a reactive NGT. These were removed by 6 months post treatment. Median MDADI score at baseline prior to TORS was 100 (range 95–100). At 12 months post-treatment, median MDADI score was higher in the patients who had PORT with omission of the primary site (median 91, range 23–95) compared to those where the primary site was included (median 83, range 38–92) (Fig. ). Relationship between Dose to DARS and Swallow Outcomes At 12 months post RT, poorer swallowing outcomes (lower MDADI) were associated with dose-parameters to OIM (V50Gy and V60Gy, beta − 1.7, p < 0.001 and beta − 1.5, p = 0.008, respectively), SPCM (V60Gy, beta − 0.98, p = 0.04) and CE (V60Gy, beta − 0.56 p = 0.05) (Table ). Addition of chemotherapy was also associated with lower MDADI at 12 months (beta − 7.9, p = 0.05).
There were 44 patients who underwent TORS for early stage OPC between 2017 and 2019. Of these, 25 patients were excluded for analysis for reasons including receiving PORT at an external site ( n = 6), not receiving PORT ( n = 18), or radiotherapy to the bilateral neck ( n = 1). The remaining 19 patients underwent TORS + PORT (to ipsilateral neck +/- primary site) and were included in the final analysis. Patient demographics, tumour stage and subsite, and treatment details are listed in Table . Primary tumours arose from the tonsil in 12 patients (63%), and base of tongue in seven patients (37%). The majority of tumours were T2 ( n = 12, 63%) and node positive ( n = 18, 95%). Almost all tumours were p16 positive ( n = 18, 95%). No patients experienced disease relapse or required further treatment during the study follow-up period.
Of the 19 patients in the TORS + PORT group, the majority ( n = 14, 74%) received PORT to the ipsilateral neck alone, and the remainder ( n = 5, 26%) received treatment to the primary site and ipsilateral neck. Median and most commonly prescribed dose was 60 Gy in 30 fractions (range 54–66 Gy in 30 fractions). The most common indication for PORT was nodal involvement and extranodal extension. All patients completed treatment in full. Six patients (32%) received concurrent chemotherapy (Table ). Mean dose, V50Gy, and V60Gy to the base of tongue, superior, and middle pharyngeal constrictor was significantly lower in those who received PORT to the neck alone, compared to patients where the primary site was treated (Table ).
Following TORS, 17 (89%) participants received nasogastric tube (NGT) feeding (mean 6 days, range 0–24 days). All participants were consuming an oral diet prior to commencing PORT. Two patients (10%) who underwent definitive RT had a prophylactic gastrostomy tube placed prior to treatment, and one had a reactive NGT. These were removed by 6 months post treatment. Median MDADI score at baseline prior to TORS was 100 (range 95–100). At 12 months post-treatment, median MDADI score was higher in the patients who had PORT with omission of the primary site (median 91, range 23–95) compared to those where the primary site was included (median 83, range 38–92) (Fig. ).
At 12 months post RT, poorer swallowing outcomes (lower MDADI) were associated with dose-parameters to OIM (V50Gy and V60Gy, beta − 1.7, p < 0.001 and beta − 1.5, p = 0.008, respectively), SPCM (V60Gy, beta − 0.98, p = 0.04) and CE (V60Gy, beta − 0.56 p = 0.05) (Table ). Addition of chemotherapy was also associated with lower MDADI at 12 months (beta − 7.9, p = 0.05).
This study is the first to report the relationship between dose to DARS and clinical swallow outcomes in the adjuvant post-TORS setting. The vast majority of published literature regarding the relationship between dosimetric parameters during head and neck radiotherapy and swallowing function exists in the setting of definitive radiotherapy. This study quantifies the radiation dose to DARS in a cohort of 19 patients undergoing TORS and PORT to a unilateral volume. Inclusion of the primary site in PORT was unsurprisingly associated with higher dose to DARS in close proximity to the oropharynx (BOT, SPCM, MPCM). Worse swallow function at 12 months post-treatment was associated with increased dose to OIM, SPCM and CE. These findings align with previous literature in the definitive RT setting, where increased dose to the pharyngeal constrictors and oesophagus is associated with worse dysphagia , and suggest possible areas for refinement of dysphagia-optimised IMRT (DO-IMRT) in the post-TORS setting. Proponents of TORS for early-stage OPC emphasise the advantage of decreased RT dose to swallowing structures . As expected, this study demonstrated consistently lower dose to DARS (specifically dose to SPCM, MPCM and BOT) where RT to the primary site was omitted. Most notably, mean dose to SPCM (31.3 Gy vs. 43.4 Gy), and to BOT (31.3 Gy vs. 43.6 Gy) was significantly lower for RT to neck alone vs. primary + neck. Even larger differences were seen in V50Gy and V60Gy, dose levels traditionally thought to be most strongly correlated with long-term dysphagia and were used as planning aims in the recently published DARS study (mean < 50 Gy) . Acknowledging that the sample size for each subset were low for the number of variables analysed, we observed higher MDADI scores for patients where radiotherapy to the primary site was omitted (median 91 vs. 82.5). Future studies should explore this relationship with appropriately powered participant numbers. There is growing evidence from the AVOID trial and single institution series to show that treatment de-escalation by selectively omitting primary site irradiation is able to safely preserve excellent oncologic outcomes while optimizing functional outcomes. In this cohort of early stage OPC receiving unilateral treatment, the high dose volumes to the oesophageal inlet muscle, superior constrictor muscle and cervical oesophagus were the only DARS dosimetric parameters that were associated with poorer swallow function at 12 months. This suggests a possible benefit to prioritizing an optimization objective of reduced 50–60 Gy to these structures, however external validation from larger data sets is required before translating these findings into clinical practice. It is also possible that the current study’s small sample size and relatively homogeneous doses to other swallowing structures may have hindered the ability to detect of other associations between DARS dosimetry and swallowing dysfunction that may exist. This study adds to the extensive literature on swallow outcomes after treatment for OPC by reporting detailed dosimetric data alongside swallowing outcome measurements at 12 months. Firstly, the dose de-escalation achieved by a TORS and pathologically guided adjuvant RT is quantified, specifically the impact of omission of RT to the primary site. Secondly, this study observed high dose volumes (V50Gy, V60Gy) to OIM, SPCM and CE were associated with worse swallow outcomes, generating the hypothesis that optimizing for these during the planning process may reduce treatment-related dysphagia. Incremental improvements in swallow related quality of life remain an important priority in a cohort of patients with excellent survival outcomes. This study was conducted in a single institution, which may skew the results due to institution-specific treatment preferences (e.g., a willingness to omit the primary site from PORT volume) and limit the generalizability of results. The study analysed a relatively small population, leading to reduced statistical power to detect statistically significant associations between dosimetry and swallowing, and biased estimates due to the influence of outliers. Despite the use of the validated MDADI tool, the lack of instrumental swallow assessment (i.e., fibreoptic endoscopic swallow study or videofluoroscopic swallow study) means the physiological impact of RT de-escalation on oropharyngeal function cannot be commented upon. Although the 12-month quality of life follow-up duration is useful to assess medium term toxicities of treatment, longer term follow up is also required given the excellent prognosis in this population. When considering larger, prospective studies for the future, employing a minimally clinically important difference for the MDADI (identified as a 10-point between-group difference in the composite score), would add to the clinical relevance of the outcomes. Despite these limitations, this prospective cohort study quantifies radiation dose to DARS in patients undergoing TORS and PORT and provides early evidence to inform optimization of RT treatment protocols in the post-TORS setting.
In patients undergoing PORT after TORS, higher radiation dose to the superior pharyngeal constrictor muscle (V60Gy), oesophageal inlet muscle (V50Gy and V60Gy), and cervical oesophagus (V60Gy) were predictive of worse swallowing outcomes at 12 months. We observed lower doses to certain DARS (base of tongue, superior and middle pharyngeal constrictors) and improvements in post-treatment swallow function in patients receiving PORT to the neck alone (versus primary + neck), suggesting that further study is warranted to assess the effectiveness and safety of this approach as a method of treatment de-escalation.
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Single Incision Pediatric Endoscopic Surgery: From Myth to Reality a Case Series | f4d79dfb-b232-4e2e-a18a-6fb2e78230e3 | 6780980 | Pediatrics[mh] | Single incision pediatric endoscopic surgery (SIPES) is a minimally invasive endosurgical technique that is increasingly being performed by pediatric surgeons globally, with continued development towards the variety of operations for which it can be adopted . After a transition of proven safety and equivalent to improved outcomes over morbidity, mortality, length of stay, postoperative pain requirements, and cosmesis, amongst other results, the use of SIPES has grown rapidly . Historically, since Georg Kelling’s 1901 approach of “Celioscopy” and Hans Jacobaeus’s 1910 first use of the laparoscopic approach in humans for diagnostic aid, the breadth over which laparoscopic procedures have been performed has continuously evolved towards increasingly complex procedures . Initial forays into laparoscopic techniques soon arose including adhesiolysis and diagnostic biopsy, with the first single-incision laparoscopic bilateral tubal ligation performed in 1968 by Dr. Clifford Wheeless, and the first multiport laparoscopic organ resection, a salpingectomy, performed by Dr. Tarasconi in 1975 . The eventual development of the computer chip allowed for projection of imaging to a screen allowing for the more modernized practice of laparoscopic surgery, subsequently prompting the first laparoscopic cholecystectomy in 1985 by Dr. Erich Mühe, and the first laparoscopic appendectomy in 1988 by Dr. Kurt Semm [ , , ]. Transitioning to single-incision techniques beyond the simple ligations and biopsies, the single-port approach arose for appendectomies with Dr. Marco Pelosi as early as 1992, for cholecystectomies with Dr. Navarra in 1997, and the first pediatrics single-incision appendectomy by Dr. Begin and SIPES gastrostomy by Dr. Keith Georgeson both in 1993 [ , , , ]. Additionally, as prevalence of SIPES continued to increase, its growth in the literature has mainly focused on appendectomies, cholecystectomies, alimentary procedures such as gastrostomies and jejunostomies, and herniorrhaphies [ , , , ]. Recently, the idea of single-incision laparoscopic surgical access for more complex cases such as colectomies, hepatectomies, or pancreatectomies has arisen, though is less practiced [ , , , ]. While multiport laparoscopic access moved beyond initial resistant preconceptions against the approach, it has since evolved into the currently ubiquitous technique for many surgically treatable diseases, including several cancers [ , , , , ]. In contrast, single-incision surgery techniques remain used by only a small subset of providers, regardless of current evidence of equivalent outcomes . Despite hesitancy against, previous studies have shown the safety of single-incision techniques for several procedures [ , , ]. Reported improvements of patient length of stay and non-inferior operative time and complications continue to stem controversy, with results such as operation time and complication rates shown to correlate to individual surgeon experience [ , , , ]. The present manuscript aims to review biases against single-incision surgery and discuss the evidence about them in the setting of three case reports exemplified below.
2.1. Case 1: SIPES-Assisted Mesenteric Lymphatic Cyst Excision with Ileocecectomy and Primary Anastomosis A Colorado Fetal Care Center consultation during a pregnancy otherwise complicated by hyperemesis showed a fetal abdominal cyst for which multidisciplinary counseling was performed. Differential diagnoses including ovarian cyst, choledochal cyst, intestinal duplication, and lymphovascular malformations were discussed. Postnatal ultrasound at age 3 weeks revealed a right lower quadrant cyst, which initially appeared to be an intestinal duplication cyst, for which subsequent intervention was planned. At 3 months of age, the child underwent surgery. A GelPOINT ® Mini Advanced Access Platform (Applied Medical Resources Corporation, Rancho Santa Margarita, CA, USA) was used with establishment of an 8 mm Hg pneumoperitoneum. An 8.5 cm multi-loculated lymphatic cystic lesion was identified in the mesentery integrated with the ileocolic junction. Due to its size a spinal needle was introduced under direct laparoscopic vision to obtain and send the lymphohemorrhagic fluid for cell count and cytology. Once determined to be a true mesenteric cyst, the suction catheter was used for further decompression, which allowed for anatomic delineation and delivery of the ileocecum via the port site. An extracorporeal ileocecectomy was performed with a hand-sewn anastomosis, the mesenteric defect was closed, and viscera returned. Fascia and skin were closed and by evening of the surgery he was tolerating a regular diet with normal bowel function. Estimated blood loss was less than 2 mL and total operative time was 2 h 53 min. He was discharged the following day without complications, and pathology was consistent with a lymphatic malformation. 2.2. Case 2: SIPES Splenectomy and Cholecystectomy A 12-year-old female with hereditary spherocytosis with cholelithiasis and 16 cm palpable splenomegaly was referred for elective splenectomy and cholecystectomy. After preoperatively completing her vaccines, she was later brought to the operating room, placed supine, induced with general anesthesia, lifted with a small bump under the left flank, and secured with tape. A 1.5 cm vertical incision at the base of the umbilicus was made and the Olympus QuadPort+ (Olympus Corporation of the Americas, Center Valley, PA, USA) was placed prior to establishment of 14 mm Hg pneumoperitoneum. Reverse Trendelenburg position, with more left side up was used to first perform the splenectomy. The stomach was mobilized medially with takedown of the gastrosplenic ligament using an ENSEAL ® device (Ethicon US, L.L.C., Somerville, NJ, USA; ). The superior splenophrenic ligaments were taken down completely prior to takedown of the splenocolic and splenorenal ligaments. The hilum was then dissected, with identification of a single splenic artery and vein using Maryland forceps to create clear windows. An Endo-GIA stapler with 3.0 mm, 2.5 mm, and 2.0 mm staple lines was used to fire across the hilum with assurance of hemostasis. Splenic dissection was completed with the ENSEAL ® and attention was brought to the gallbladder. At this point the patient was placed in reverse Trendelenburg, now with the right side up, and an additional 5 mm incision was made in the right upper quadrant for cephalo-lateral retraction of an extremely adherent intrahepatic gallbladder. Via the QuadPort+ the Hartmann’s pouch was retracted caudo-laterally and hook electrocautery was used to dissect off the peritoneum and dissect the triangle of Calot to obtain the critical view. The small cystic artery was taken down with hook electrocautery, and cystic duct laparoscopically clipped. The gallbladder was then dissected off the liver bed. The spleen was placed in an Endobag and morcellation accomplished inside the bag with a pair of ring-forceps prior to retrieval without spillage. The gallbladder was retrieved prior to port removal. Pneumoperitoneum was released, and fascia and skin closed. Estimated blood loss was less than 5 mL, and the operative time for the splenectomy was 2 h with an additional 67 min for the cholecystectomy. The patient was discharged on postoperative day two without complications and with resolution of symptoms. 2.3. Case 3: SIPES Distal Pancreatectomy with Splenectomy A 14-year-old otherwise healthy female presented acute epigastric/left upper quadrant abdominal pain with normal labs. Computed tomography scanning revealed a 4 cm homogenous distal pancreatic mass of low Hounsfield units, abutting the splenic vein though seemingly without distinct vessel involvement, also without further masses, surrounding ascites, ductal dilation, nor lymphadenopathy. Upon surgical consultation, we recommended a distal pancreatectomy with possible splenectomy (vaccines were given prior to surgery). In the operating room she was positioned supine with an nasogastric tube placement. A 1.5 cm incision was made at the base of the umbilicus followed by placement of a Gelport and establishment of 15 mm Hg pneumoperitoneum. On complete inspection there was no evidence of metastases. The lesser sac was entered, with visualization of the pancreatic body and tail, including the mass. The splenic flexure was mobilized using an ENSEAL ® device along the greater stomach curvature towards the hilum, with subsequent electrocautery dissection of the inferior border of the pancreas taken laterally towards the spleen. Further posterior dissection was performed, however, after full elevation of the distal pancreas it was evident that the splenic vein was tightly adherent to the mass. The decision was made to perform an additional splenectomy and two additional 5 mm step ports were added to the right and left upper quadrants to help in exposure. Short gastrics were then taken down via the ENSEAL ® , with hilar dissection using the Maryland and vascular Endo GIA™ stapler load (Medtronic Minimally Invasive Therapies, Minneapolis, MN, USA). The distal pancreas was then dissected posteriorly to the inferior mesenteric vein, with good margins prior to stapling across with a 3.5 mm 60 mm load. There appeared to be hemostasis, and fibrin sealant was added to the staple line. The pancreatic specimen was placed in an Endobag, though it was unable to be retrieved via the umbilical incision. A 3 cm Pfannenstiel incision was then created to retrieve the pancreatic specimen en block, with subsequent closure of the incision after retrieval. Pneumoperitoneum was then reestablished, with completion of the splenic dissection and retrieval after morcellation within the bag, also without spillage. All port sites were closed, and the patient was brought to recovery after placement of an epidural. Estimated blood loss was 100 mL and total operative time was 6 h 7 min. She recovered without issues and was discharged on postoperative day four. Pathology revealed solid pseudopapillary neoplasm, with no further masses found on subsequent surveillance imaging.
A Colorado Fetal Care Center consultation during a pregnancy otherwise complicated by hyperemesis showed a fetal abdominal cyst for which multidisciplinary counseling was performed. Differential diagnoses including ovarian cyst, choledochal cyst, intestinal duplication, and lymphovascular malformations were discussed. Postnatal ultrasound at age 3 weeks revealed a right lower quadrant cyst, which initially appeared to be an intestinal duplication cyst, for which subsequent intervention was planned. At 3 months of age, the child underwent surgery. A GelPOINT ® Mini Advanced Access Platform (Applied Medical Resources Corporation, Rancho Santa Margarita, CA, USA) was used with establishment of an 8 mm Hg pneumoperitoneum. An 8.5 cm multi-loculated lymphatic cystic lesion was identified in the mesentery integrated with the ileocolic junction. Due to its size a spinal needle was introduced under direct laparoscopic vision to obtain and send the lymphohemorrhagic fluid for cell count and cytology. Once determined to be a true mesenteric cyst, the suction catheter was used for further decompression, which allowed for anatomic delineation and delivery of the ileocecum via the port site. An extracorporeal ileocecectomy was performed with a hand-sewn anastomosis, the mesenteric defect was closed, and viscera returned. Fascia and skin were closed and by evening of the surgery he was tolerating a regular diet with normal bowel function. Estimated blood loss was less than 2 mL and total operative time was 2 h 53 min. He was discharged the following day without complications, and pathology was consistent with a lymphatic malformation.
A 12-year-old female with hereditary spherocytosis with cholelithiasis and 16 cm palpable splenomegaly was referred for elective splenectomy and cholecystectomy. After preoperatively completing her vaccines, she was later brought to the operating room, placed supine, induced with general anesthesia, lifted with a small bump under the left flank, and secured with tape. A 1.5 cm vertical incision at the base of the umbilicus was made and the Olympus QuadPort+ (Olympus Corporation of the Americas, Center Valley, PA, USA) was placed prior to establishment of 14 mm Hg pneumoperitoneum. Reverse Trendelenburg position, with more left side up was used to first perform the splenectomy. The stomach was mobilized medially with takedown of the gastrosplenic ligament using an ENSEAL ® device (Ethicon US, L.L.C., Somerville, NJ, USA; ). The superior splenophrenic ligaments were taken down completely prior to takedown of the splenocolic and splenorenal ligaments. The hilum was then dissected, with identification of a single splenic artery and vein using Maryland forceps to create clear windows. An Endo-GIA stapler with 3.0 mm, 2.5 mm, and 2.0 mm staple lines was used to fire across the hilum with assurance of hemostasis. Splenic dissection was completed with the ENSEAL ® and attention was brought to the gallbladder. At this point the patient was placed in reverse Trendelenburg, now with the right side up, and an additional 5 mm incision was made in the right upper quadrant for cephalo-lateral retraction of an extremely adherent intrahepatic gallbladder. Via the QuadPort+ the Hartmann’s pouch was retracted caudo-laterally and hook electrocautery was used to dissect off the peritoneum and dissect the triangle of Calot to obtain the critical view. The small cystic artery was taken down with hook electrocautery, and cystic duct laparoscopically clipped. The gallbladder was then dissected off the liver bed. The spleen was placed in an Endobag and morcellation accomplished inside the bag with a pair of ring-forceps prior to retrieval without spillage. The gallbladder was retrieved prior to port removal. Pneumoperitoneum was released, and fascia and skin closed. Estimated blood loss was less than 5 mL, and the operative time for the splenectomy was 2 h with an additional 67 min for the cholecystectomy. The patient was discharged on postoperative day two without complications and with resolution of symptoms.
A 14-year-old otherwise healthy female presented acute epigastric/left upper quadrant abdominal pain with normal labs. Computed tomography scanning revealed a 4 cm homogenous distal pancreatic mass of low Hounsfield units, abutting the splenic vein though seemingly without distinct vessel involvement, also without further masses, surrounding ascites, ductal dilation, nor lymphadenopathy. Upon surgical consultation, we recommended a distal pancreatectomy with possible splenectomy (vaccines were given prior to surgery). In the operating room she was positioned supine with an nasogastric tube placement. A 1.5 cm incision was made at the base of the umbilicus followed by placement of a Gelport and establishment of 15 mm Hg pneumoperitoneum. On complete inspection there was no evidence of metastases. The lesser sac was entered, with visualization of the pancreatic body and tail, including the mass. The splenic flexure was mobilized using an ENSEAL ® device along the greater stomach curvature towards the hilum, with subsequent electrocautery dissection of the inferior border of the pancreas taken laterally towards the spleen. Further posterior dissection was performed, however, after full elevation of the distal pancreas it was evident that the splenic vein was tightly adherent to the mass. The decision was made to perform an additional splenectomy and two additional 5 mm step ports were added to the right and left upper quadrants to help in exposure. Short gastrics were then taken down via the ENSEAL ® , with hilar dissection using the Maryland and vascular Endo GIA™ stapler load (Medtronic Minimally Invasive Therapies, Minneapolis, MN, USA). The distal pancreas was then dissected posteriorly to the inferior mesenteric vein, with good margins prior to stapling across with a 3.5 mm 60 mm load. There appeared to be hemostasis, and fibrin sealant was added to the staple line. The pancreatic specimen was placed in an Endobag, though it was unable to be retrieved via the umbilical incision. A 3 cm Pfannenstiel incision was then created to retrieve the pancreatic specimen en block, with subsequent closure of the incision after retrieval. Pneumoperitoneum was then reestablished, with completion of the splenic dissection and retrieval after morcellation within the bag, also without spillage. All port sites were closed, and the patient was brought to recovery after placement of an epidural. Estimated blood loss was 100 mL and total operative time was 6 h 7 min. She recovered without issues and was discharged on postoperative day four. Pathology revealed solid pseudopapillary neoplasm, with no further masses found on subsequent surveillance imaging.
Mirroring the growth of practice within the adult literature equivalents, single-incision pediatric endoscopic surgery has been increasing in application over a greater variety of cases in children, including in: appendectomy, cholecystectomy, pyloromyotomy, splenectomy, alimentary procedures, gynecological procedures, herniorrhaphy, and pancreatectomy [ , , , , , , , ]. The three SIPES cases above include a cystic lymphatic malformation resection, splenectomy with cholecystectomy, and pancreatectomy with splenectomy. These highlight the use of SIPES over complex, though not infrequent, cases seen by pediatric surgery, and serve to lead a discussion of five common myths regarding SIPES practice. 3.1. Myth 1: SIPES Practice Is Only Applicable to Simple Cases Single-incision surgery use in the pediatric realm has expanded beyond Dr. Georgeson’s SIPES gastrostomies described in 1993 and Dr. Esposito’s single trocar appendectomies described in 1998 to further include cholecystectomies, splenectomies, pyloromyotomies, intestinal surgeries, and gynecological procedures [ , , ]. The use of SIPES for pancreatic surgery in children is more limited in the literature, however, case 3 correlates with the feasibility shown in the rare case reports on the technique . The cases above show more complex cases that surgeons dedicated to the practice of SIPES can perform after they are more practiced and expert with the technique. As is the case with “standard” multiport equivalents, during single-incision approaches to difficult cases, the additional advantage of one or more assist ports for exposure is always available . Notably, the benefits of having a single-incision approach, should not preclude the addition of ports or access for forceps for retraction or exposure, as seen in cases 2 and 3. In these instances, an extra site allowed for improved retraction of the gallbladder cephalad and laterally, as well as allowed for safer dissection of the distal pancreatic mass with splenic attachment. This highlights how some patients’ anatomies combined with the technicality of having a single focal point for the instrument port may restrict some movements to a degree that may benefit from an assisting port [ , , ]. This additional option does not require SIPES approach to be aborted in full and exists with any equivalent multiport technique as well. Its prudent use may save any laparoscopic case from having to open. Other adaptive techniques that can be used in a SIPES approach include diagnostic evaluation, cystic decompression, and extracorporeal bowel manipulation, as seen in case 1, as well as endoscopic dissection, resection, morcellation, and ligation, as seen in cases 2 and 3. While these highlighted cases are more complex in nature, as surgeons become increasingly familiar with the technique of a single-incision approach, their practice can grow to encapsulate many of the cases they would otherwise approach multiport laparoscopically. Furthermore, case 2 highlights how a centralized single access approach from the umbilicus can allow for multiple operations over opposing abdominal quadrants which can be performed utilizing the same anesthetic and port site. SIPES can be adapted for a wide range of cases over a breadth of operative fields. 3.2. Myth 2: SIPES Practice Requires an Inordinate Amount of Training, with an Excessive Learning Curve Incorporation of a SIPES approach into practice has been somewhat limited by perceptions of technical difficulty of the new approach when compared to a more “traditional” multiport approach. Whereas the port sites in a multiport technique are typically spaced apart from each other and placed in a triangulated fashion towards the target in order to optimize ergonomics, precision, and effectiveness of motion, in a single-incision approach the single incision forces ports to remain close . Instead, this single-port access creates a single-port fulcrum point, beyond which distal triangulation must be performed . Furthermore, the crossed instruments traveling through the single-port fulcrum result in the left hand movements affecting the screen-right sided instrument and conversely the right hand affecting the screen-left one. These movements of the lateral hand causing opposite-sided motion on screen creates an effect that can cause even the most practiced multiport laparoscopic expert surgeon to initially feel out of their normal routine. However, studies show that expert multiport laparoscopic surgeons do have an easier time quickly adapting to these differences of the single-incision approach . Furthermore, in SIPES, articulation of instruments along the shaft, head, and handle (including flipping the handles upside down), as well as technological improvements towards smaller instrument diameters and port sizes, have allowed for both more mobility in exposure and instrument movement, thus minimizing restrictions from the fulcrum . A learning curve does exist for practice of SIPES prior to obtaining full operative familiarity, just as a learning curve exists in multiport approaches [ , , , , ]. Assessment of single-port learning curves suggest anywhere between 10 and 40 cholecystectomy cases are required prior to significant operative length improvements, and near 100 cases for appendectomy time improvements . Interestingly, experience in conventional laparoscopy may overlap into improved familiarity with the single-port technique. Some studies in adult literature suggest that expert operators in multiport laparoscopic may begin their single-incision learning curve at an already near-proficient skill level . Notably, single-incision comparisons of what constitutes a significant difference between expert and novice operative times and skilled task times may range, some reporting as low as a 5 min operative difference of performing an appendectomy, or as high as a 4 min task difference for every cutting or suturing task performed by the expert compared to the novice . While mathematically “significant” these differences may not hold as much clinical significance, depending on the setting. Both multi- and single-incision studies have shown some correlation between faster learning curves and previous video game skill levels as well . A component of the rapid development of multiport laparoscopic surgery has been workshops for trainees, such as the Fundamentals of Laparoscopic Surgery course offered by Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and the American College of Surgeons (ACS) . Similarly, computer-based workshops also exist worldwide . Adult single-incision workshops do exist, though are not as ubiquitous in training programs, which may perpetuate trepidation against its use . In these workshops, participants can develop their efficiency and hands-on practice to more quickly adapt to the single-port specific skills used. Workshops for SIPES have only recently developed but have been used to show skill improvement of fellows, residents, and medical students for SIPES . Possible apprehension regarding technique difficulty should not be a contraindication against use of SIPES, as trainees of all surgical levels have shown capability for learning. 3.3. Myth 3: SIPES Practice Causes Increased Complications Initial comparative studies between single-incision laparoscopic surgery and multiport laparoscopic equivalents over adult patients in several institutions revealed increased conversions to open, operative times, and port-side hernias [ , , ]. However, results from more recent randomized controlled trials are conflicting, with the only Cochrane review stating that no definitive conclusions can be drawn at this time . Less evidence exists in pediatric single incision versus multiple incision laparoscopic approaches, however, the overwhelming results show comparatively equivalent conversion rates to open, hernia rates, and overall postoperative morbidities [ , , , , ]. Naturally, these outcome studies may be limited in part by publication bias, however, the results stand in contrast to earlier publications in adults. There is a growing body of evidence regarding the advantages SIPES has over multiport laparoscopy. While initial evaluations in adult literature seemed to show increased pain with a single-incision approach, this may be outdated by the larger incisions and equipment required by the approach at its nascence [ , , ]. Studies in children have shown equivalent or even decreased pain scores with SIPES . The improvements that have allowed for smaller trocars and instruments through a consequently smaller fascial incision have been postulated to cause decreased pain secondary to decreased abdominal wall trauma, in addition to the improved cosmetic outcome they provide [ , , , ]. Furthermore, typical pediatric incisions are naturally smaller than adult equivalents. Increasingly, larger comparisons over patients with single versus multiport approaches over appendectomies have shown perioperative outcomes of pain are noninferior to decreased in single site approaches, though the degree of significance in some studies is as small as a single analgesic dose, which again may not be as significant clinically [ , , ]. Despite possible perceptions to the contrary, the possible superiority offered by SIPES especially regarding pain and cosmesis, in the setting of otherwise proven equivalence of morbidity rates in the pediatric literature, may be reason for favoring a SIPES approach compared to a multiport equivalent. 3.4. Myth 4: SIPES Practice Takes Longer Time in the Operating Theatre Literature evaluating operative times of single-port against multiport approaches vary by operation, though overall most are comparable in timing. Meta-analyses for adult operations performed by experienced operators show comparative operative times in colectomies, nephrectomies, and splenectomies [ , , ]. The largest comparative studies of adult appendectomies and cholecystectomies over these techniques seem to weigh towards increased operative time using a single-incision approach (cholecystectomies most commonly ranging 10 min longer, and appendectomies ranging 6 min longer); however, there is significant statistical heterogeneity in these comparisons [ , , ]. Naturally, all of these studies can be subject to self-selection bias. However, comparative studies published for single-incision operative times in children largely report comparative operative times, though this is limited by a paucity of high-level evidence. One study, including non-expert colectomy times for single-incision colectomy, showed 30 min longer operative time, however, when only experienced single-incision surgeon times were compared against multiport times there was no difference . The largest single institutional SIPES review reported an operative time increase for SIPES appendectomy of 7 min, a 9 min difference for cholecystectomy, 4 min for pyloromyotomy, and an 8 min difference for splenectomy . Heterogeneity of meta-analysis results for SIPES appendectomy times range from no difference to a 7 min difference overall . These outcomes both reinforce the aforementioned learning curve as well as correlate with multiport laparoscopic operative times . SIPES operative times can be variable, as can multiport times, and similarly greater SIPES expertise in technique allows for continued improvements with faster and safer operative times [ , , , , ]. 3.5. Myth 5: SIPES Practice Is More Expensive than Multiport Equivalents Comparative financial studies have shown SIPES to be equivalent in cost to multiport approaches for common pediatric surgical diseases [ , , ]. Assessments of both costs from operative time, as well as costs of operative tools, show equivalency over these disease states, with other studies showing equivalent hospital lengths of stay, returns, and complications [ , , , , ]. Initial increased costs for single-incision approaches reported in literature have been minimized with the advent of standard reusable laparoscopic instruments . Alternative methods shown to decrease cost include using conventional multiport equipment to a SIPES approach (i.e., using multiport trocars and instruments, which have shown to be adaptable in an effective and safe manner ). Notably, studies showing equivalency of SIPES versus multiport costs come from institutions with comparable operative times to multiport operative times, thus outlier institutions with longer SIPES times may have increased total procedural costs with the technique . Overall, evaluation of cost between SIPES equipment against multiport equipment has comparable results, with dependent costs of operative times showing similar calculated comparisons [ , , , ].
Single-incision surgery use in the pediatric realm has expanded beyond Dr. Georgeson’s SIPES gastrostomies described in 1993 and Dr. Esposito’s single trocar appendectomies described in 1998 to further include cholecystectomies, splenectomies, pyloromyotomies, intestinal surgeries, and gynecological procedures [ , , ]. The use of SIPES for pancreatic surgery in children is more limited in the literature, however, case 3 correlates with the feasibility shown in the rare case reports on the technique . The cases above show more complex cases that surgeons dedicated to the practice of SIPES can perform after they are more practiced and expert with the technique. As is the case with “standard” multiport equivalents, during single-incision approaches to difficult cases, the additional advantage of one or more assist ports for exposure is always available . Notably, the benefits of having a single-incision approach, should not preclude the addition of ports or access for forceps for retraction or exposure, as seen in cases 2 and 3. In these instances, an extra site allowed for improved retraction of the gallbladder cephalad and laterally, as well as allowed for safer dissection of the distal pancreatic mass with splenic attachment. This highlights how some patients’ anatomies combined with the technicality of having a single focal point for the instrument port may restrict some movements to a degree that may benefit from an assisting port [ , , ]. This additional option does not require SIPES approach to be aborted in full and exists with any equivalent multiport technique as well. Its prudent use may save any laparoscopic case from having to open. Other adaptive techniques that can be used in a SIPES approach include diagnostic evaluation, cystic decompression, and extracorporeal bowel manipulation, as seen in case 1, as well as endoscopic dissection, resection, morcellation, and ligation, as seen in cases 2 and 3. While these highlighted cases are more complex in nature, as surgeons become increasingly familiar with the technique of a single-incision approach, their practice can grow to encapsulate many of the cases they would otherwise approach multiport laparoscopically. Furthermore, case 2 highlights how a centralized single access approach from the umbilicus can allow for multiple operations over opposing abdominal quadrants which can be performed utilizing the same anesthetic and port site. SIPES can be adapted for a wide range of cases over a breadth of operative fields.
Incorporation of a SIPES approach into practice has been somewhat limited by perceptions of technical difficulty of the new approach when compared to a more “traditional” multiport approach. Whereas the port sites in a multiport technique are typically spaced apart from each other and placed in a triangulated fashion towards the target in order to optimize ergonomics, precision, and effectiveness of motion, in a single-incision approach the single incision forces ports to remain close . Instead, this single-port access creates a single-port fulcrum point, beyond which distal triangulation must be performed . Furthermore, the crossed instruments traveling through the single-port fulcrum result in the left hand movements affecting the screen-right sided instrument and conversely the right hand affecting the screen-left one. These movements of the lateral hand causing opposite-sided motion on screen creates an effect that can cause even the most practiced multiport laparoscopic expert surgeon to initially feel out of their normal routine. However, studies show that expert multiport laparoscopic surgeons do have an easier time quickly adapting to these differences of the single-incision approach . Furthermore, in SIPES, articulation of instruments along the shaft, head, and handle (including flipping the handles upside down), as well as technological improvements towards smaller instrument diameters and port sizes, have allowed for both more mobility in exposure and instrument movement, thus minimizing restrictions from the fulcrum . A learning curve does exist for practice of SIPES prior to obtaining full operative familiarity, just as a learning curve exists in multiport approaches [ , , , , ]. Assessment of single-port learning curves suggest anywhere between 10 and 40 cholecystectomy cases are required prior to significant operative length improvements, and near 100 cases for appendectomy time improvements . Interestingly, experience in conventional laparoscopy may overlap into improved familiarity with the single-port technique. Some studies in adult literature suggest that expert operators in multiport laparoscopic may begin their single-incision learning curve at an already near-proficient skill level . Notably, single-incision comparisons of what constitutes a significant difference between expert and novice operative times and skilled task times may range, some reporting as low as a 5 min operative difference of performing an appendectomy, or as high as a 4 min task difference for every cutting or suturing task performed by the expert compared to the novice . While mathematically “significant” these differences may not hold as much clinical significance, depending on the setting. Both multi- and single-incision studies have shown some correlation between faster learning curves and previous video game skill levels as well . A component of the rapid development of multiport laparoscopic surgery has been workshops for trainees, such as the Fundamentals of Laparoscopic Surgery course offered by Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and the American College of Surgeons (ACS) . Similarly, computer-based workshops also exist worldwide . Adult single-incision workshops do exist, though are not as ubiquitous in training programs, which may perpetuate trepidation against its use . In these workshops, participants can develop their efficiency and hands-on practice to more quickly adapt to the single-port specific skills used. Workshops for SIPES have only recently developed but have been used to show skill improvement of fellows, residents, and medical students for SIPES . Possible apprehension regarding technique difficulty should not be a contraindication against use of SIPES, as trainees of all surgical levels have shown capability for learning.
Initial comparative studies between single-incision laparoscopic surgery and multiport laparoscopic equivalents over adult patients in several institutions revealed increased conversions to open, operative times, and port-side hernias [ , , ]. However, results from more recent randomized controlled trials are conflicting, with the only Cochrane review stating that no definitive conclusions can be drawn at this time . Less evidence exists in pediatric single incision versus multiple incision laparoscopic approaches, however, the overwhelming results show comparatively equivalent conversion rates to open, hernia rates, and overall postoperative morbidities [ , , , , ]. Naturally, these outcome studies may be limited in part by publication bias, however, the results stand in contrast to earlier publications in adults. There is a growing body of evidence regarding the advantages SIPES has over multiport laparoscopy. While initial evaluations in adult literature seemed to show increased pain with a single-incision approach, this may be outdated by the larger incisions and equipment required by the approach at its nascence [ , , ]. Studies in children have shown equivalent or even decreased pain scores with SIPES . The improvements that have allowed for smaller trocars and instruments through a consequently smaller fascial incision have been postulated to cause decreased pain secondary to decreased abdominal wall trauma, in addition to the improved cosmetic outcome they provide [ , , , ]. Furthermore, typical pediatric incisions are naturally smaller than adult equivalents. Increasingly, larger comparisons over patients with single versus multiport approaches over appendectomies have shown perioperative outcomes of pain are noninferior to decreased in single site approaches, though the degree of significance in some studies is as small as a single analgesic dose, which again may not be as significant clinically [ , , ]. Despite possible perceptions to the contrary, the possible superiority offered by SIPES especially regarding pain and cosmesis, in the setting of otherwise proven equivalence of morbidity rates in the pediatric literature, may be reason for favoring a SIPES approach compared to a multiport equivalent.
Literature evaluating operative times of single-port against multiport approaches vary by operation, though overall most are comparable in timing. Meta-analyses for adult operations performed by experienced operators show comparative operative times in colectomies, nephrectomies, and splenectomies [ , , ]. The largest comparative studies of adult appendectomies and cholecystectomies over these techniques seem to weigh towards increased operative time using a single-incision approach (cholecystectomies most commonly ranging 10 min longer, and appendectomies ranging 6 min longer); however, there is significant statistical heterogeneity in these comparisons [ , , ]. Naturally, all of these studies can be subject to self-selection bias. However, comparative studies published for single-incision operative times in children largely report comparative operative times, though this is limited by a paucity of high-level evidence. One study, including non-expert colectomy times for single-incision colectomy, showed 30 min longer operative time, however, when only experienced single-incision surgeon times were compared against multiport times there was no difference . The largest single institutional SIPES review reported an operative time increase for SIPES appendectomy of 7 min, a 9 min difference for cholecystectomy, 4 min for pyloromyotomy, and an 8 min difference for splenectomy . Heterogeneity of meta-analysis results for SIPES appendectomy times range from no difference to a 7 min difference overall . These outcomes both reinforce the aforementioned learning curve as well as correlate with multiport laparoscopic operative times . SIPES operative times can be variable, as can multiport times, and similarly greater SIPES expertise in technique allows for continued improvements with faster and safer operative times [ , , , , ].
Comparative financial studies have shown SIPES to be equivalent in cost to multiport approaches for common pediatric surgical diseases [ , , ]. Assessments of both costs from operative time, as well as costs of operative tools, show equivalency over these disease states, with other studies showing equivalent hospital lengths of stay, returns, and complications [ , , , , ]. Initial increased costs for single-incision approaches reported in literature have been minimized with the advent of standard reusable laparoscopic instruments . Alternative methods shown to decrease cost include using conventional multiport equipment to a SIPES approach (i.e., using multiport trocars and instruments, which have shown to be adaptable in an effective and safe manner ). Notably, studies showing equivalency of SIPES versus multiport costs come from institutions with comparable operative times to multiport operative times, thus outlier institutions with longer SIPES times may have increased total procedural costs with the technique . Overall, evaluation of cost between SIPES equipment against multiport equipment has comparable results, with dependent costs of operative times showing similar calculated comparisons [ , , , ].
Once the activation energy of overcoming the learning curve has been accomplished, a growing number of cases have shown SIPES can be safely applied over a variety of cases, with noninferior objective outcomes of incisional hernia rates, conversions to an open approach, comparative morbidities and recovery times, and possible superiority of pain and cosmesis . Given the literature supporting SIPES can be subject to publication bias, examples of the extent of evidence regarding its use and outcomes have been highlighted over the various myths and preconceptions above. Nevertheless, the present review reflects on the interpretation of the limited literature about single-incision surgery in pediatric patients and is hence prone to bias itself. Limited evidence for SIPES approaches regarding feasibility, safety, and comparative results to multiport equivalents continues to grow with increased surgical application over increasingly more complex cases. Despite myths and perceptions that may arise when compared to multiport equivalents, SIPES can be performed over a comparable range of cases, with straightforward training, equivalent complication rates, similar case lengths, and analogous cost.
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Clinical communication in orthodontics: Any
questions? | 097e981b-a355-4669-8202-2281ddbe3334 | 9679555 | Dental[mh] | There is evidence to support that good patient–clinician communication can improve
the quality of care ( ), patient satisfaction ( ) and compliance with
treatment ( ). When communication is patient-centred, patients can also feel
empowered to partake in shared decision making about their care ( ) and patient
values and preferences are a pillar of evidence-based practice. Conversely, poor
communication is widely accepted as a contributing factor in many complaints ( ; ). Effective
communication is a key standard of the , and
registered dental professionals must demonstrate and maintain competence in this
skill as part of their ongoing practice. Within the context of orthodontic
interventions, a high burden of compliance rests with the patient. Communication
skills are therefore a domain of the Orthodontics curriculum, as set by the and developed with the Royal Colleges. Communication can be assessed in daily practice through workplace-based assessments,
Objective Structured Clinical Examinations (OSCEs), peer observation and feedback
from colleagues. This normally centres around defined observations, such as
explaining treatment options, or the likely risks involved. Patient perceptions are
not necessarily considered, and their input is required for a holistic assessment of
a clinician’s interpersonal skills. Patient satisfaction questionnaires are already
widely used as part of service evaluation in the secondary care setting and
patient-reported experience measures (PREMs) are becoming an increasingly important
part of evaluating quality and outcomes in healthcare ( ). We report the findings of a multicentre service evaluation into patient–clinician
communication within the secondary care orthodontic setting using the Communication
Assessment Tool (CAT); this being a reliable and validated instrument for
patient-reported assessment of clinician’s interpersonal and communication skills
( ). The aim of the present study was to measure the patient-perceived
standard of orthodontic clinicians’ communication and identify elements of
communication where performance is deficient. Clinician factors which influence
patient perceptions of communication were also explored.
This study was classified as a service evaluation and registered with the clinical
governance departments at both Guys and St Thomas NHS Foundation Trust (10930) and
Kings College London NHS Foundation Trust (DENT051-20). Ethical approval was not
required for this study as it was classified as a service evaluation. Participation
in this cross-sectional evaluation was entirely voluntary. Participants were
recruited from orthodontic new patient and treatment clinics at both secondary care
sites. Treatment clinics were heterogenous in nature and would also have included
treatment planning, review appointments and consenting procedures. Any patients aged
10 years and over attending the orthodontic department for treatment or consultation
were eligible for inclusion. Patients who required third-party translation services
were excluded. As this was a service evaluation using a form of patient satisfaction
questionnaire, a convenience sample of 200 patients (100 patients recruited at each
site) was deemed large enough by the investigators to gain a baseline level of
patient–clinician communication skills across the orthodontic clinics, comparable to
a previous sample using the CAT in the dental hospital setting ( ). Due
to the nature of the evaluation, a formal power calculation was not deemed
necessary.
The CAT instrument was developed to capture patient views on interpersonal skills
soon after an inpatient or outpatient clinical encounter, rather than over a period
of time. Initial field testing and focus group discussion during the development of
the tool specifically amalgamated domains on giving information about tests or
investigations, diagnoses and treatment into a single item based on individual
patient expectations (gave me as much information as I wanted). Separating these
domains was felt to be too narrow and not applicable to all clinical interactions.
The CAT was specifically designed and tested to be applicable across settings and
specialties and was also validated with a sample of patients with whom the majority
(69.7%) had seen their clinician more than once before ( ). The CAT was adapted from the original tool reported by on discussion with
the local clinical governance team. The only changes were to the headers ‘The
doctor’ and ‘The doctor’s staff’ to ‘Orthodontic clinician’ and ‘Orthodontic
department staff (front desk, nurses)’ to apply it to the hospital orthodontic
setting and clarify the individuals that patients were providing scores for ( ). This is comparable
to adaptations of the tool by and . The CAT comprises 15
statements such as ‘encouraged me to ask questions’, ‘gave me as much information as
I wanted’ and ‘spent the right amount of time with me’. It takes only several
minutes to complete ( ) and so is of minimal inconvenience to patients and has been
piloted and validated across both medical and dental settings ( ; ; ; ; ). Each element is scored by patients on a 5-point Likert scale as
follows: 1 = poor; 2 = fair; 3 = good; 4 = very good; and 5 = excellent. A mean
score for the first 14 items is calculated for the individual clinician while the
final item asks for feedback on other departmental staff, such as nurses or the
front desk. Although only a snapshot of patient experience, it can provide an
overall gauge of their perceptions of clinician’s communication skills. As most
scores tend to be clustered towards the higher end of the scale, it is recommended
to use the proportion of items rated ‘excellent’ as a more useful measure ( ).
Psychometric evaluation has found that anything less than ‘excellent’ is better
equated to this domain not being fully achieved in the eyes of the patient. The mean
‘excellent’ scores using the CAT can be calculated on the number of questions the
patient answered, excluding those left blank, as suggested with previous use of this
tool ( ). The modified CAT is plain English with a Flesch Reading Ease score of 71.3 and a
Flesch-Kincaid grade level of 5.4 and is therefore suitable for most US fifth
graders (aged 10–11 years). This is a similar reading level to that reported in the
literature for other versions of this tool ( ; ) and
most patients aged 10 years and over should be able to understand the CAT, with some
help from a guardian if needed. This age also conveniently includes most orthodontic
patients. For younger individuals who asked for help from a guardian, their view was
considered acceptable for completion of the CAT questionnaire. Any conflict was
decided among the patient and their guardian away from the clinical area. To avoid
confusion, patients were advised that ‘My orthodontic clinician’ refers to the
primary treating clinician, those spending the most time with them during the
appointment, and not that of a supervising consultant who may have provided a brief
opinion. Clinicians were given five paper copies of the CAT and asked to provide them to their
patients at the start of a clinical session. Clinicians were not aware of the
session being sampled beforehand and so were not able to modify bookings in advance.
In addition to the questionnaire responses, the following demographics were
collected: sex (patient and clinician); first language (patient and clinician); and
grade and region of the primary registrable dental qualification of the clinician.
Both clinician and patients were anonymised by providing each clinician with a
unique identifier that was used on all questionnaires to enable data linkage.
Patients were encouraged to complete the questionnaire at the end of the
appointment, ideally away from the clinical area in the waiting room or a side room
where available. A collection box was available in the reception area for patients
to return their completed questionnaire. Data were collated and presented in
aggregate using a pre-piloted Microsoft Excel (Microsoft, Redwood, WA, USA)
spreadsheet. No patient identifiable information was recorded, and individualised
feedback reports were also not provided to clinicians.
Pilot data using the CAT for standards of clinical communication in the orthodontic
setting have not yet been established. Previous studies have determined mean
excellence scores that were used as a composite reference standard: 76.3% of scores
were excellent in multiple medical settings ( ); 73.3% of scores were
excellent in the Dental Hospital setting ( ); and 74.4% of scores
were excellent in the orthognathic team setting ( ). Based on these, a
suggestive target standard was adopted where 75% of CAT scores should be rated
excellent by patients. This is generally calculated as a mean percentage ‘excellent’
for the first 14 items of the CAT but can be broken down individually to highlight
areas for improvement.
Data analyses were carried out independently by a statistician (NP). Descriptive
statistics and summary values were calculated. A series of univariable logistic
Generalised Estimating Equation models were fit with empirical standard errors to
examine associations among the response (excellent [response 5]) versus
unsatisfactory [combined responses 1–4]) and the clinician characteristics. In the
final model the significant predictors from the univariable analyses were included.
A two-tailed P value of 0.05 was considered statistically
significant. Statistical analyses were performed using STATA software version 16.1
(Stata Corp., College Station, TX, USA) and R Software version 4.0.3 (R Foundation
for Statistical Computing, Vienna, Austria).
Data collection was commenced at both sites from 19 April 2021 and ended on 21 June
2021. This period was required to sample the desired population in the context of
the COVID-19 pandemic and reduction in clinical capacity, as well as to account for
the varying timetables of the clinicians involved. The characteristics of patients
(n=204) and clinicians (n=55) involved in this service evaluation are presented in . The mean
number of CAT questionnaires per clinician was 3.71 (SD 0.99) with the mean age of
respondents being 17.9 (SD 7.9) years. In total, there were 275 CAT questionnaires
provided to clinicians. Some patients may have failed to attend, failed to complete
the CAT or simply fewer than five patients were booked in for that session. We did
not collect unused CAT questionnaires, but the remaining 71 questionnaires may have
been declined by patients or left blank for the aforementioned reasons. The final
sample of 204 consisted of responses mainly from treatment clinics (n=181), with the
remaining being from new patient consultations (n=23). The overall responses and mean score per item are presented in with no patients choosing to rate
any of the domains as ‘1=poor’. The overall mean score for any given domain was 4.86
(SD 0.21). The percentage of ‘5=excellent’ ratings per domain are also shown with
the overall percent-excellence for the first 14 items on the CAT being 88.2% (SD
0.16). The lowest scoring item was ‘encouraged me to ask questions’ with only 55.8%
of responses indicating that this domain was fulfilled. Predictors of excellent responses were also explored. Based on clinician
characteristics, there were lower odds of achieving an excellent response for items
4, 8, 9, 10, 11 and 14 compared to item 1, as demonstrated in . A similar finding was made for
item 15, although this domain is based on the orthodontic department staff rather
than the individual clinician. There were higher odds of achieving an excellent
response if English was not the first language of the treating clinician (1.05; 95%
CI: 1.00,1.09; p=0.03). Other factors including clinician grade, gender, region of
qualification and patient’s first language did not appear to alter the odds of
achieving an excellent response. The predicted probabilities of achieving an
excellent response for each of the CAT items from the GEE model are displayed in .
The results of this service evaluation show that there was a high standard of
patient-reported experience of clinical communication within the secondary care
orthodontic setting. The overall mean score per domain is comparable to prior
studies ( ; ) and a mean percent-excellent score of 88.2% exceeded the expected
target of 75% demonstrated in the literature ( ; ; ; ).
These results are from patient interactions across both treatment and new patient
clinics and so should be interpreted within the context of the hospital orthodontic
setting. A large proportion of patients are likely to have met their treating
clinician on multiple occasions and developed a rapport which may explain the bias
towards very positive outcomes. This is reassuring considering the longitudinal
nature of orthodontic treatment and the need for an effective clinician–patient
relationship to motivate and encourage compliance with our interventions.
Reassuringly, the CAT tool has been validated for use in patients who have seen
their clinician more than once before ( ). The highest excellent responses were for ‘treated me with respect’ (96%), ‘let me
talk without interruptions’ (95.1%) and ‘showed care and concern’ (95.6%). These
items are reported to have higher scores in other clinical settings ( ; ). We did not inform clinicians of the session being sampled; however,
these results should be viewed in relation to possible Hawthorne effect as
clinicians may have had time to read the CAT before patients were seated and hence
modified their communication on the day of data collection. Telephone and digital
versions of the CAT have been described by and this methodology,
such as a quick response (QR) code in the reception area, could instead be used in
future applications of the CAT. The lowest scoring item, ‘encouraged me to ask questions’ (55.8%), is the domain most
often reported to score lowest on the CAT ( ; ; ; ; ). Other lower scoring items included ‘talked in terms I could
understand’ (78.9%) and ‘understood my main concerns’ (82.3%). These raise areas of
development needed across all clinician groups and are particularly relevant to the
shared decision-making process, whereby healthcare decisions are made with the
active support of patients ( ; ). A proportion of
respondents (12.3%) appeared unsatisfied with their involvement in the
decision-making process (item 11). Along with effective communication, these were
key themes found to influence orthodontic treatment satisfaction in recent
qualitative research ( ). Without asking the questions and understanding a patient’s
main concerns, we cannot invite their true participation in this process ( ; ; ). They
are similarly disempowered if we use technical or inaccessible language during
clinical interactions. Health professional teams may naturally use more medical
terminology when discussing patient care and this may have contributed to some of
the responses for ‘talked in terms I could understand’. When discussions happen in
the presence of a patient, efforts should be made to clarify their
understanding. The sample size of 204 respondents is in keeping with comparable settings in the
existing literature ( ; ) and we included a relatively large number of clinicians to
explore associations between their characteristics and CAT scores, as well as to
reflect the workforce of the teaching hospital environment. The use of two centres
was also hoped to improve the generalisability of results. Data collection was
delayed several times by localised service disruptions and restrictions due to the
COVID-19 pandemic, which accounted for the data collection period. Ideally, sampling
more clinics repeatedly could have increased the numbers of patient responses for
each individual clinician. Patient and clinician sex was recorded as this has been
shown to have an influence on communication ( ) and both men and
women can differ in their communication styles ( ). Patient and clinician first
language was recorded, as a pilot study on the use of this tool had recognised this
as an important confounding factor with respect to patient perceptions of
communication ( ). The grade of the treating clinician and the region of their
primary registrable dental qualification were also noted. There is a diverse
workforce within both departments and clinicians may have had different experiences
of ‘softer’ skills training at both undergraduate and postgraduate level. These
basic demographics have similarly been collected when using the CAT to assess
hospitalist (secondary care) communication skills ( ). There were no differences between the two centres and no associations were found
between clinician characteristics and patient responses on the CAT, except for when
English was not the first language of the treating clinician. Here, there were
higher odds of achieving an excellent response. This was unexpected but may reflect
the large proportion of international postgraduate students in this study who must
meet minimum entry requirements in English language proficiency and often undergo
undergraduate training in English. It could also be suggested that as non-native
speakers, they may use more accessible language when communicating with patients.
Similarly, most patients were native English speakers (n=174, 85.3%) and they may
have chosen to score clinicians more favourably when recognising English was not
their first language. Finding no differences in the percent-excellence responses by
clinician sex or grade appears to contradict the findings of a similar study in the
dental hospital setting ( ) but is in keeping with a larger study into secondary care
medical practitioners ( ). We attempted to account for these variables but the
inherent positive bias of responses towards ‘excellent’ and the sample being from
predominantly female clinicians (65.2%) and postgraduate trainee/registrar grade
(62.3%) may have contributed to this. There were also a limited number of responses
for the orthodontic therapist grade (n=29, 14.2%) so results may have reduced
generalisability for these clinicians. We have demonstrated that the modified CAT can be implemented in the orthodontic
setting and may be useful across other dental specialty and primary dental care
services as both an audit tool and patient-reported experience measure. Oversight
from the local clinical governance teams meant we did not provide individual
feedback reports to clinicians so that the results of this service evaluation could
not be used for or against clinicians in the annual appraisal process. This is,
however, a beneficial element of the CAT that may be used at the individual or local
level to encourage reflective practice around communication and patient–clinician
interactions. Any training or development needs in communication identified as a
result of this service evaluation are instead intended to be addressed with a team
approach within the respective departments. Incorporating patients as key
stakeholders in communication skills training has previously been described in the
dental education literature ( ) and the opportunities to raise these findings
and enhance existing communication skills workshops is anticipated. We aimed to gain a snapshot of clinician’s communication skills across the
departments but did not examine the effects of clinic type or appointment length on
patient responses, although this could be explored in future applications of the CAT
in the orthodontic setting. Data on the exact nature of the clinical interaction,
such as a consent discussion, could be collected in future studies to elucidate if
differences in patient responses exist. Due to the impacts of COVID-19 on clinic
templates, there were reduced new patient clinics running at the time of the
evaluation and so responses for this clinic type were also relatively small (n=23),
limiting the value of subgroup analyses. However, it should be borne in mind that
the CAT was specifically designed and tested to be applicable across various
settings and to be reflective of the spectrum of clinical interactions that can be
held ( ). GDC Standards for the Dental Team (2013) are also clear that
effective communication skills should be displayed at all phases of patient care.
New patient consultations may involve more discussion, but it is at subsequent
visits where patients can have the opportunity to ask more questions or discuss
aspects of treatment including oral hygiene and appliance wear and care. We could
have collected data on whether this was the first time the patient had met their
clinician, as in previous studies ( ; ) which
could have enabled analyses on the effects of clinician–patient rapport on
responses. Future applications of the CAT in orthodontics would also benefit from a
sample including more new patient consultations. Another limitation to this study is that it was undertaken in the context of the
COVID-19 pandemic. Repeated disruptions to patient care do not appear to have been
detrimental to the perceived standards of communication; however, the routine
wearing of facemasks, visors and similar personal protective equipment by both
patients and clinicians may act as additional barriers to effective non-verbal
communication. This reinforces the importance of striving for excellence in the
domains of the CAT and ensuring patients have a positive interaction with their
clinicians.
There is a high standard of patient–clinician communication in the hospital
orthodontic setting. Key areas of development remain, including encouraging patients
to ask questions, talking in terms they can understand, recognising their main
concerns and involving them in the decision-making process. The results of this
service evaluation can be used to inform communication skills training and be
replicated in similar dental settings as part of quality improvement. The CAT only
provides a snapshot of a clinical encounter, but there is scope for the results of
authentic patient feedback to inform more in-depth qualitative research about the
patient experience in orthodontics.
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Adipocyte heterogeneity and tumor infiltration of adipose tissue in patients with metastatic breast cancer | ac3801a9-2a58-421f-8f78-bc2638553e4a | 11652757 | Forensic Medicine[mh] | BMI Body Mass Index CAAs Cancer-associated adipocytes FABP4 Fatty Acid Binding Protein 4 FFPE Formalin-Fixed Paraffin Embedded H&E Hematoxylin and Eosin IBC-NST Invasive Breast Cancer of No Special Type ILC Invasive Lobular Carcinoma MAT Mammary Adipose Tissue SAT Subcutaneous Adipose Tissue RAT Retroperitoneal Adipose Tissue UPTIDER UZ/KU Leuven Program for Tissue Donation to Enhance Research VAT Visceral Adipose Tissue WAT White Adipose Tissue
Introduction Many tumors develop in close proximity to or in direct contact with adipose tissue. This is particularly true for breast cancer, where mammary glands are surrounded by adipose-rich tissue . The interaction between tumor cells and their microenvironment is critical for tumor growth, tissue invasion and metastasis. Adipocytes are an often underinvestigated component of the tumor microenvironment, despite the important, bi-directional interaction exists between tumors and adipose tissue, where both tumor and adipose tissue mutually respond to and influence each other . Obesity is defined as abnormal or excessive fat accumulation and is usually reflected by a body mass index (BMI) of 30 kg/m 2 or more . It is associated with an increased risk of developing breast cancer, especially in postmenopausal women, and a worse prognosis after diagnosis of breast cancer. In individuals with obesity, adipocyte hypertrophy leads to metabolic dysregulation, immune cell recruitment, and inflamed white adipose tissue (WAT), contributing to an underlying chronic subclinical inflammation. WAT inflammation occurs across the spectrum of BMI and is likely contributing to the pathogenesis of breast cancer . As BMI has limitations in correctly assessing adiposity, adipocyte size has been proposed as an alternative method to quantify adiposity at tissue level using a digital pathology tool that we previously described and successfully applied . A recent study also demonstrated a link between breast cancer and adipose tissue dysfunction by assessing adipocyte size and macrophage infiltration . Adipose tissue is distributed throughout the human body, but the most prominent adipose tissue depots are grouped anatomically, including mammary (MAT), subcutaneous (SAT), retroperitoneal (RAT) and visceral adipose tissue (VAT). SAT lies beneath the skin and provides insulation, whereas VAT surrounds internal organs within the abdominal cavity . It is generally known that SAT is more involved in lipolysis and considered healthier than VAT . However, it is still unknown whether adipocyte size is similar in these different adipose tissue depots. Tumor infiltration in adipose tissue has been recognized as a common feature of primary invasive breast carcinomas, especially of invasive lobular carcinoma (ILC) . Comparative analysis has highlighted differences in lipid metabolism between primary ILC and invasive breast carcinoma of no special type (IBC-NST), with higher expression of fatty acid binding protein 4 (FABP4) in ILC . The role of FABP4 is currently under thorough investigation, particularly in conjunction with its key partner fatty acid translocase/CD36, primarily in patients with ovarian cancer . However, it is now also being studied in breast cancer as a potential therapeutic target to inhibit the fatty acid import into breast cancer cells . In our post-mortem tissue donation program UPTIDER (NCT04531696) , we have been systematically collecting samples of different fat depots from patients with metastatic breast cancer. In the present study, we investigated the adipocytes to understand regional differences in adipocyte size and tumor infiltration of adipose tissue in the advanced stages of the disease.
Methods 2.1 Patients Following written consent, patients with metastatic breast cancer were included in UPTIDER (NCT04531696) at UZ/KU Leuven. The set-up and conduct of our post-mortem tissue donation program have been published . Before the start of an autopsy, a harvest planning document is created for every patient to list the metastatic lesions and non-pathological tissues to be sampled. A sample is encoded as malignant when tumor is visible during gross inspection, otherwise it is encoded as normal. For this study, we included all retroperitoneal, subcutaneous, visceral and (contralateral) mammary fat tissue samples encoded as normal. If available, historical samples from the primary breast tumor were obtained. The slides were reviewed and one representative non-tumor infiltrated slide with mammary fat was selected. We additionally collected data on patient and tumor characteristics from medical files ( ). Rapid autopsies of the patients included in the present study were performed between January 2021 and April 2023. During autopsy, tissue samples of the retroperitoneal, subcutaneous, visceral, and mammary fat depots were taken if possible and fixed into formalin-fixed paraffin embedded (FFPE) blocks. 2.2 Histopathological characteristics Histopathological characterization was performed on the hematoxylin and eosin (H&E)-stained slides. The quality of the sample was assessed before digitalizing the slide. In case of tissue tearing or air bubbles present on the slide, another H&E-stained slide was obtained. In case tumor cells were detected in the autopsy samples, tumor cellularity and histological subtype were defined according to the WHO classification of breast tumors . 2.3 Digital pathology analysis Based on microscopic evidence and literature , we defined adipocytes distant from the tumor as those being at least 2 mm away from cancer cells as well as 2 mm away from normal epithelial and fibrotic areas. Thin fibrous septa that carry blood supply for the adipocytes (corresponding to perilobular fibrosis score 1) were not excluded since these do not affect the adipocyte size . Distant adipocyte size was measured using HALO version 2.3 (Vacuole module, Indica Labs, Corrales, CA) on digitally scanned H&E-stained slides . Annotation, segmentation, count and measurements of area and diameter of adipocytes were performed on the scanned fat tissue slides per patient. We extracted the area, perimeter, and diameter of each single adipocyte for each annotated region. The areas to be analyzed were drawn by H.I. and checked by breast pathologist in training G.Z. to obtain approximately 500 adipocytes and calculate the median adipocyte area, perimeter, and diameter. Adipocytes with incomplete membranes or adipocytes that touched the border of the image were manually excluded. 2.4 Statistics The violin plots describing the intra-patient inter-adipocyte region heterogeneity were created using the ggplot2 package (v3.4.3). Quantile regression analysis was performed to measure the association between median adipocyte area (as the outcome, in μm 2 ) and the groups of interest (as independent co-variates: Fat type of interest vs Reference fat type, ILC vs IBC-NST histological subtype) with an included random effect on patient ID. The analysis was performed using the lqmm package (v1.5.8) and the results were plotted using a forest plot with the ggplot2 package (v3.4.3) on R version 4.3. Spearman rank correlation was employed to study the strength of linear association between fat types of interest and independent variables (Age and BMI at death). A spearman correlation coefficient (Rs ≥ 0.6) was considered as a strong correlation.
Patients Following written consent, patients with metastatic breast cancer were included in UPTIDER (NCT04531696) at UZ/KU Leuven. The set-up and conduct of our post-mortem tissue donation program have been published . Before the start of an autopsy, a harvest planning document is created for every patient to list the metastatic lesions and non-pathological tissues to be sampled. A sample is encoded as malignant when tumor is visible during gross inspection, otherwise it is encoded as normal. For this study, we included all retroperitoneal, subcutaneous, visceral and (contralateral) mammary fat tissue samples encoded as normal. If available, historical samples from the primary breast tumor were obtained. The slides were reviewed and one representative non-tumor infiltrated slide with mammary fat was selected. We additionally collected data on patient and tumor characteristics from medical files ( ). Rapid autopsies of the patients included in the present study were performed between January 2021 and April 2023. During autopsy, tissue samples of the retroperitoneal, subcutaneous, visceral, and mammary fat depots were taken if possible and fixed into formalin-fixed paraffin embedded (FFPE) blocks.
Histopathological characteristics Histopathological characterization was performed on the hematoxylin and eosin (H&E)-stained slides. The quality of the sample was assessed before digitalizing the slide. In case of tissue tearing or air bubbles present on the slide, another H&E-stained slide was obtained. In case tumor cells were detected in the autopsy samples, tumor cellularity and histological subtype were defined according to the WHO classification of breast tumors .
Digital pathology analysis Based on microscopic evidence and literature , we defined adipocytes distant from the tumor as those being at least 2 mm away from cancer cells as well as 2 mm away from normal epithelial and fibrotic areas. Thin fibrous septa that carry blood supply for the adipocytes (corresponding to perilobular fibrosis score 1) were not excluded since these do not affect the adipocyte size . Distant adipocyte size was measured using HALO version 2.3 (Vacuole module, Indica Labs, Corrales, CA) on digitally scanned H&E-stained slides . Annotation, segmentation, count and measurements of area and diameter of adipocytes were performed on the scanned fat tissue slides per patient. We extracted the area, perimeter, and diameter of each single adipocyte for each annotated region. The areas to be analyzed were drawn by H.I. and checked by breast pathologist in training G.Z. to obtain approximately 500 adipocytes and calculate the median adipocyte area, perimeter, and diameter. Adipocytes with incomplete membranes or adipocytes that touched the border of the image were manually excluded.
Statistics The violin plots describing the intra-patient inter-adipocyte region heterogeneity were created using the ggplot2 package (v3.4.3). Quantile regression analysis was performed to measure the association between median adipocyte area (as the outcome, in μm 2 ) and the groups of interest (as independent co-variates: Fat type of interest vs Reference fat type, ILC vs IBC-NST histological subtype) with an included random effect on patient ID. The analysis was performed using the lqmm package (v1.5.8) and the results were plotted using a forest plot with the ggplot2 package (v3.4.3) on R version 4.3. Spearman rank correlation was employed to study the strength of linear association between fat types of interest and independent variables (Age and BMI at death). A spearman correlation coefficient (Rs ≥ 0.6) was considered as a strong correlation.
Results 3.1 Fat tissue sampling To characterize the main histopathological features and the adipocytes of the primary breast tumors, resection specimens at time of surgery were retrieved, of which 13 out of 22 (59.1 %) had sufficient fat available for investigation ( and ). At diagnosis, 4 out of 22 patients (18.2 %) had triple-negative breast cancer, 1 patient had ER+/PR+/HER2+ breast cancer (4.5 %), 1 patient had ER-/PR+/HER2- breast cancer (4.5 %), 2 patients had ER+/PR-/HER2- breast cancer (9.1 %) and the remaining 14 patients had ER+/PR+/HER2- breast cancer (63.6 %). Histologically, 5 patients (22.7 %) presented with ILC, 3 patients (13.6 %) with mixed IBC-NST/ILC, 1 patient (4.5 %) with mixed IBC-NST/metaplastic squamous cell carcinoma and the remaining 13 patients (59.1 %) with IBC-NST. Of these patients, 6 patients received neo-adjuvant therapy followed by mastectomy (n = 5) or breast conserving surgery (n = 1), while 12 other patients had primary surgery (mastectomy n = 5, breast conserving surgery n = 7). The median number of treatment lines was 6 with a range from 2 to 11 treatment lines. The patients had metastatic lesions present in different anatomical locations (overview from autopsy findings in ). Additionally, fat tissue samples were collected from subcutaneous (SAT), retroperitoneal (RAT), visceral (VAT), and (contralateral) mammary fat depots (MAT) from all patients during the post-mortem tissue donation ( A). Only 1 visceral non-tumor infiltrated fat sample and 6 contralateral mammary fat samples were not taken ( C). 3.2 Regional differences of fat samples For each patient, adipocyte parameters including area, diameter, and perimeter were assessed using HALO® to compare size across different fat depots ( ). As shown in A and B, median adipocyte area exhibited a heterogeneous distribution across patients and regions, with no statistically significant differences observed among the distinct fat regions ( C and ). We compared distant adipocyte size between MAT from the resection specimen at time of surgery and MAT at autopsy. Only 7 samples of the 15 MAT samples at autopsy showed sufficient adipose tissue for HALO® analysis. We observed no statistically significant differences in distant adipocyte size between the mammary fat from the resection specimen and the (contralateral) MAT taken at autopsy, although there was a trend towards smaller adipocytes in the mammary fat samples obtained at autopsy. To assess the correlation between adipocyte size and BMI or age at death, these parameters were visualized using scatter plots and correlations were investigated ( ). The strongest positive correlation was observed between BMI at death and adipocyte size in both the subcutaneous and visceral regions, with Spearman correlation coefficients of 0.55 and 0.54, respectively. 3.3 Infiltration of fat samples by the tumor In addition to the assessment of adipocyte size on post-mortem fat tissue samples initially deemed macroscopically devoid of tumor, we further conducted assessments to discern microscopic tumor presence or infiltration ( ). We observed a higher frequency of tumor infiltration in VAT (9 out of 21 or 42.9 %) compared to other regions (SAT 2 out of 22 or 9.1 %, RAT 2 out of 22 or 9.1 % and MAT 1 out of 16 or 6.3 %). Specifically, we found a higher incidence of tumor infiltration in post-mortem fat tissue samples in patients with primary breast cancer histologically classified as ILC. Among the patients with primary IBC-NST, 3 out of 13 (23.1 %) exhibited fat tissue infiltration, while 4 out of 5 patients (80 %) with primary ILC and all 3 patients with primary mixed IBC-NST/ILC showed infiltration in at least one of the fat tissue regions. Remarkably, patients with mixed IBC-NST/ILC histology exclusively demonstrated infiltration of the fat tissue by the ILC component of the tumor . We also examined adipocyte size of the distant adipocytes by histological subtype and found a trend of larger adipocytes in IBC-NST lesions compared to ILC lesions across all regions ( C).
Fat tissue sampling To characterize the main histopathological features and the adipocytes of the primary breast tumors, resection specimens at time of surgery were retrieved, of which 13 out of 22 (59.1 %) had sufficient fat available for investigation ( and ). At diagnosis, 4 out of 22 patients (18.2 %) had triple-negative breast cancer, 1 patient had ER+/PR+/HER2+ breast cancer (4.5 %), 1 patient had ER-/PR+/HER2- breast cancer (4.5 %), 2 patients had ER+/PR-/HER2- breast cancer (9.1 %) and the remaining 14 patients had ER+/PR+/HER2- breast cancer (63.6 %). Histologically, 5 patients (22.7 %) presented with ILC, 3 patients (13.6 %) with mixed IBC-NST/ILC, 1 patient (4.5 %) with mixed IBC-NST/metaplastic squamous cell carcinoma and the remaining 13 patients (59.1 %) with IBC-NST. Of these patients, 6 patients received neo-adjuvant therapy followed by mastectomy (n = 5) or breast conserving surgery (n = 1), while 12 other patients had primary surgery (mastectomy n = 5, breast conserving surgery n = 7). The median number of treatment lines was 6 with a range from 2 to 11 treatment lines. The patients had metastatic lesions present in different anatomical locations (overview from autopsy findings in ). Additionally, fat tissue samples were collected from subcutaneous (SAT), retroperitoneal (RAT), visceral (VAT), and (contralateral) mammary fat depots (MAT) from all patients during the post-mortem tissue donation ( A). Only 1 visceral non-tumor infiltrated fat sample and 6 contralateral mammary fat samples were not taken ( C).
Regional differences of fat samples For each patient, adipocyte parameters including area, diameter, and perimeter were assessed using HALO® to compare size across different fat depots ( ). As shown in A and B, median adipocyte area exhibited a heterogeneous distribution across patients and regions, with no statistically significant differences observed among the distinct fat regions ( C and ). We compared distant adipocyte size between MAT from the resection specimen at time of surgery and MAT at autopsy. Only 7 samples of the 15 MAT samples at autopsy showed sufficient adipose tissue for HALO® analysis. We observed no statistically significant differences in distant adipocyte size between the mammary fat from the resection specimen and the (contralateral) MAT taken at autopsy, although there was a trend towards smaller adipocytes in the mammary fat samples obtained at autopsy. To assess the correlation between adipocyte size and BMI or age at death, these parameters were visualized using scatter plots and correlations were investigated ( ). The strongest positive correlation was observed between BMI at death and adipocyte size in both the subcutaneous and visceral regions, with Spearman correlation coefficients of 0.55 and 0.54, respectively.
Infiltration of fat samples by the tumor In addition to the assessment of adipocyte size on post-mortem fat tissue samples initially deemed macroscopically devoid of tumor, we further conducted assessments to discern microscopic tumor presence or infiltration ( ). We observed a higher frequency of tumor infiltration in VAT (9 out of 21 or 42.9 %) compared to other regions (SAT 2 out of 22 or 9.1 %, RAT 2 out of 22 or 9.1 % and MAT 1 out of 16 or 6.3 %). Specifically, we found a higher incidence of tumor infiltration in post-mortem fat tissue samples in patients with primary breast cancer histologically classified as ILC. Among the patients with primary IBC-NST, 3 out of 13 (23.1 %) exhibited fat tissue infiltration, while 4 out of 5 patients (80 %) with primary ILC and all 3 patients with primary mixed IBC-NST/ILC showed infiltration in at least one of the fat tissue regions. Remarkably, patients with mixed IBC-NST/ILC histology exclusively demonstrated infiltration of the fat tissue by the ILC component of the tumor . We also examined adipocyte size of the distant adipocytes by histological subtype and found a trend of larger adipocytes in IBC-NST lesions compared to ILC lesions across all regions ( C).
Discussion While the adipose tissue plays a crucial role in the tumor microenvironment and significantly influences tumor development and metastasis, our understanding of the contribution of adipocytes in patients with breast cancer remains limited . This paper aimed to shed light on this topic by first exploring regional variations in adipocytes across different fat depots collected in the context of post-mortem tissue donation using digital pathology and, second, by investigating fat tissue tumor infiltration, to gain valuable insights into the complexities of adipose tissue in breast cancer. Understanding adipocyte size in the context of breast cancer is relevant for several reasons. First, since adipocyte size reflects of adiposity, accurate measurement is crucial. This is particularly important because BMI may not consistently and reliably reflect adipose tissue distribution throughout the body, adipose tissue inflammation or metabolic health . Additionally, the extent to which adipocytes biopsied from distinct anatomic regions differ from each other has not been investigated previously in patients with breast cancer. Obtaining these different fat tissues from living patients is not feasible or ethical due to the invasive nature and practical challenges associated with acquiring multiple biopsies from various adipose depots. Looking into previous studies, researchers have identified variations in fat metabolism among different fat regions in healthy women . These studies often highlighted increased lipolysis, higher lipid content, larger adipocytes, and greater metabolic and inflammatory activity in SAT compared to VAT and have generally considered SAT as healthier than VAT . Driven by our interest in assessing fat tissue variations in patients with breast cancer, we investigated regional disparities in distinct fat tissue depots, encompassing SAT, VAT, RAT, and MAT. Our analysis investigated characteristics of distant adipocytes—area, diameter, and perimeter—using specimens from resection surgeries or post-mortem samples. We found no significant differences in adipocyte size when comparing fat regions to each other, which could indicate relatively uniform adipose tissue status across these different fat depots in patients with metastatic breast cancer. This uniformity may indicate similar metabolic activity across these fat depots. Even though no significant differences could be demonstrated, there was a trend towards smaller adipocytes in the MAT obtained at autopsy compared to the matched mammary fat samples taken from the resection specimen at time of surgery. This could suggest a progressive change in the adipose tissue microenvironment in the breast during the course of metastatic breast cancer. This change might indicate a shift in the overall health of patients near the end of life, including factors like BMI, menopausal status, and effects of aging. Alternatively, it could also reflect the effects of treatment over time in this heavily treated patient cohort. Almost all patients were treated with multiple lines of endocrine therapy, however as previously reported we would expect to see a hypertrophic appearance of adipocytes in these samples which we did not observe here . Next to endocrine therapy, all patients received chemo- and/or radiotherapy which has been associated with smaller adipocyte size . Additionally, the results may also be influenced by the significant weight loss some patients experience at the end of their life, a factor that could be attributed to cancer-associated cachexia . It is widely recognized that cachexia, a multifactorial condition, impacts the quality of life of patients and response to therapy, which leads to poorer outcomes for cancer patients . Finally, the change in adipocyte size could signify a transition towards a more adverse adipose tissue phenotype, potentially influencing disease progression, treatment response, and patient outcomes . Further exploration of the underlying mechanisms behind these changes is necessary to fully grasp their clinical implications and potential therapeutic strategies. While a connection between BMI and adipocyte size is anticipated, the highest correlation between adipocyte size and BMI was found in VAT and SAT. This suggests that changes in BMI may be more reflective of changes in adipocyte size or adipose dysfunction in VAT and SAT compared to MAT and RAT. In addition to examining adipocyte size differences across fat depots, we also investigated tumor infiltration of fat tissue samples initially presumed to be macroscopically tumor-free. Contrary to initial expectations, we found tumor infiltration of fat tissue regions in 10 out of 22 patients. These samples revealed a more extensive disease state at autopsy, underscoring the pervasive nature of breast cancer metastases. One notable observation was the higher tumor infiltration in VAT as compared to other regions, irrespective of tumor histotype. When comparing different tumor histotypes, however, we found more fat tissue infiltration by ILC compared to IBC-NST. This is a common observation for primary ILC but was previously unexplored in the metastatic setting, despite being acknowledged in clinical contexts . It is worth noting that this observation might also be influenced by the greater number of visceral fat samples collected from patients with ILC, as more extensive random sampling of VAT was undertaken during autopsies for this specific cancer histotype. Although the comparison was not statistically significant, we observed that adipocytes were larger in IBC-NST when compared to ILC in all regions, further underscoring the divergent characteristics between these two breast cancer histotypes. This finding complements our previous findings of smaller size of cancer-associated adipocytes in ILC . Emerging evidence suggests that ILC exhibits a distinct lipid metabolism profile compared to IBC-NST [ , , ]. Pre-clinical studies have highlighted key differences, notably the upregulation of hormone-sensitive lipase and FABP4, both key proteins involved in lipid metabolism, as well as lower expression of perilipin A, a regulator of lipid droplet formation, in ILC as compared to IBC-NST . Another report also highlighted the role of lipid metabolism in endocrine resistance in ILC cell lines, showing distinct expression patterns in ILC compared to IBC-NST . The distinct lipid metabolism profile observed in ILC, characterized by alterations in key lipid metabolism-related proteins, could possibly be partially responsible for the different biological behaviour of ILC. We faced certain challenges in this descriptive study, such as the paucity of fat tissue within the primary resection specimens and at autopsy. Nevertheless, the immense effort of the UPTIDER rapid autopsy program enabled us to investigate invaluable adipose tissue samples that might otherwise not be available in patients with metastatic breast cancer . While the investigation primarily focused on distant adipocytes, it is crucial to note that cancer-associated adipocytes may hold greater clinical relevance for studies examining tumor-fat interactions or adipocyte size changes. These nuances underscore the intricacies involved in studying adipose tissue in the context of advanced breast cancer and emphasize the necessity for cautious interpretation and further research to elucidate the clinical implications of these findings.
Conclusion Our study investigated adipose tissue samples, collected during rapid autopsy from patients with metastatic breast cancer. The results revealed that adipocyte characteristics are relatively uniform across different fat depots in patients with metastatic breast cancer. Yet, we observed a trend towards smaller adipocytes in mammary fat at autopsy compared to surgery after diagnosis, indicating potential metabolic shifts over time. As could be expected, we found a significant positive correlation between adipocyte size and BMI, which was most pronounced for the subcutaneous and visceral adipose regions. Additionally, when we explored tumor infiltration in fat tissue, we found the highest frequency in the visceral component, mainly in patients with ILC. We also observed a trend for smaller adipocytes in ILC, underscoring the distinct nature of ILC tumors. These findings emphasize the importance of adipose tissue dynamics in understanding breast cancer metastasis. Further research is essential to elucidate these mechanisms and the role of adipose tissue in disease progression and resistance to treatment of metastatic breast cancer.
Hava Izci: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Gitte Zels: Writing – review & editing, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Anirudh Pabba: Writing – review & editing, Visualization, Validation, Software, Resources, Methodology, Investigation, Formal analysis, Data curation. Marion Maetens: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. François Richard: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Maxim De Schepper: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Data curation, Conceptualization. Josephine Van Cauwenberge: Writing – review & editing, Resources, Investigation, Data curation. Ha-Linh Nguyen: Writing – review & editing, Resources, Investigation, Data curation. Kristien Borremans: Writing – review & editing, Resources, Investigation, Data curation. Sophia Leduc: Writing – review & editing, Resources, Investigation, Data curation. Karen Van Baelen: Writing – review & editing, Resources, Investigation, Data curation. Sigrid Hatse: Writing – review & editing, Investigation. Tatjana Geukens: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Amena Mahdami: Writing – review & editing, Resources, Investigation, Data curation. Hans Wildiers: Writing – review & editing, Resources. Patrick Neven: Writing – review & editing, Resources. Wouter Van Den Bogaert: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Giuseppe Floris: Writing – review & editing, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Christine Desmedt: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization.
The project has been approved on November 30th, 2020, by the ethics committee of the University Hospitals Leuven (S64410).
This work was supported by the Klinische Onderzoeks-en Opleidingsraad (KOOR) of 10.13039/100012324 University Hospitals Leuven (Uitzonderlijke Financiering 2020), C1 of 10.13039/501100004040 KU Leuven (C14/21/114) and the Belgian foundation against cancer (C/2022/2046). The funders played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.
All authors have no competing financial or non-financial interests to declare.
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Ten lessons learnt: scaling and transitioning one of the largest mobile health communication programmes in the world to a national government | 4394ea0a-d0c6-4a8a-ab3e-ebf181fc526c | 8728354 | Health Communication[mh] | Over the past decade, there has been exponential growth in the number of ‘digital development’ programmes seeking to leverage technology to solve systemic challenges in almost every development domain, including healthcare. However, although investors have made a notable shift in recent years from funding pilots to scale-ups, many digital interventions still struggle to achieve scale and sustainability. Much has been written about the causes of ‘pilotitis’, a term used to describe the predominance of small digital development interventions that never scale and die the day the original funding runs out. The digital development community has also invested significant effort in articulating the cure to pilotitis—the principles of effective digital development. Nonetheless, key principals continue to be overlooked. This is perhaps because some remain largely theoretical in a context where few real-world examples of digital development interventions achieving not just scale, but sustainability, exist. In India, there are notable examples of digital health solutions successfully scaling across geographies to change health practices and generate demand for supply side services from the last decade. For example, a suite of complementary mobile health (mHealth) services designed between 2011 and 2013 by BBC Media Action in the state of Bihar have had an impact on a range of health outcomes at scale. These are: Mobile Academy, an Interactive Voice Response (IVR)-based training course to refresh frontline health workers’ (FLHWs) knowledge and improve their interpersonal communication skills. Mobile Kunji , an IVR and print-based job aid to support FLHWs’ interactions with families, and Kilkari which delivers stage-based, time-sensitive, weekly audio information directly to families’ phones to reinforce FLHWs’ counselling. As of April 2019, when Mobile Academy and Kilkari were transitioned to the national government, 206 000 FLHWs had graduated and Kilkari had reached 10 million subscribers. Although Mobile Kunji was used by 144,000 registered FLHWs for 7 years in Bihar, scaled to the states of Odisha and Uttar Pradesh, and had a significant impact on a range of health outcomes, it was not adopted at the national level. This paper reflects on the lessons learnt from designing, scaling and transitioning Mobile Academy and Kilkari to the national government in India, and why Mobile Kunji was not scaled. We first describe (1) why a user-paid business model failed to cover all programmatic costs in Bihar. We then discuss our pivot to a government-paid business model, and the following key learning: (2) you may pilot ‘apples’ but have to scale ‘oranges’; (3) trade-offs are required between ideal solution design and affordability; (4) programme components should be reassessed before scaling; (5) operational viability is a prerequisite for sustainability; (6) consider the true cost of open-source software; (7) taking informed consent in low-resource settings is challenging; (8) big data offer promise, but social norms and SIM change constrain use; (9) successful government engagements require significant capacity; (10) define governance structures and roadmaps up front.
mHealth projects rarely test the viability of sustainability strategies, including business models, at the pilot stage. Instead, they develop roadmaps for sustainability, which are often only implemented towards the end of a grant. At that point, it can be difficult to pivot if sustainability plans fail. In 2012, BBC Media Action began road-testing a user-paid business model, which involved revenue share agreements with six mobile network operators (MNOs) in Bihar, while it still had 3.5 years of donor funding left. It adopted this approach to test if it was feasible to ensure the sustainability of the services without funding from donors or the government. In 2011, formative research was conducted to identify willingness to pay for the suite of mHealth services. It identified that, although FLHWs were not willing to pay for a job aid they used every day (Mobile Kunji ), they were willing to pay approximately US$1.50 for the entire Mobile Academy course, billed on a ‘pay as you go’ basis at US$0.01 per min. It also found that mothers did not make financial decisions related to the phone, and fathers, who spent an average of US$1 a month on talk time, were only willing to pay approximately US$0.0125 per week for Kilkari for 18 months. They were not willing or able to pay the US$1 that it would cost to buy the entire service up front, because on average, mobile subscribers in Bihar in 2011 only spent $1 on phone credit per month. Most of the revenue generated by calls to Mobile Academy and from Kilkari went to the MNOs to cover their operating costs, which included the cost of maintaining their network infrastructure. Under the typical value-added services revenue share model in India in 2011, MNOs took 80%–90% of the revenue—leaving only 10%–20% to cover ongoing costs, including marketing. Although 50 000 FLHWs paid to complete Mobile Academy from their own pockets, and more than 168 969 families subscribed to receive reproductive, maternal, newborn and child health (RMNCH) advice from Kilkari at a cost of US$0.01 per week, this model did not generate enough revenue to cover the high cost of face-to-face marketing, in addition to operating costs. Face-to-face marketing proved necessary to reach low literate pregnant and postpartum women and their families in low-income, rural communities because digital marketing and marketing through the MNOs’ top-up shops mainly reached young men who either were not married or did not see the value in paying for preventative RMNCH information. Due to the high cost of acquiring subscribers, and the low price point that poor families could afford, this business model failed to cover all costs. But at least it ‘failed fast’, giving the team time to pivot to a government-paid business model. Under this new model, the government covered all call costs, making the service free to subscribers. Thanks to economies of scale, the government was also able to negotiate less expensive call rates with a single MNO for the suite of mobile health services. To identify and subscribe beneficiaries at scale, the programme integrated Kilkari with the government databases that track pregnancies and births in India. This enabled the automated subscription of millions of new and expecting mothers with no investment in marketing. Elsewhere globally, maternal messaging programmes in South Africa and Ghana have established vertical systems for enrolment into messaging programmes subscribing beneficiaries through face-to-face interactions with healthcare providers in the public sector. While face-to-face encounters provided an opportunity for providers to describe the programme to prospective beneficiaries, answer queries and capture informed consent, it too has cost implications for promoting the programme’s rollout in health facilities and training providers on registration procedures. In addition, implementation of face-to-face registration may have opportunity costs with regard to provider and beneficiary time, extending beneficiary time in the clinics and shifting provider time away from clinic care to enrolment and registration during the clinical encounter. The Kilkari programme’s ability to automate subscription based on data drawn from government-tracking registries has meant that large numbers of women at a population level can enter the programme with no additional burden to existing health systems or the clinical care received by women and children.
Large complex interventions that include integrated theories of change need to be reassessed if only some of these interventions are scaled. In Bihar, an overarching theory of change was developed for a layered communications programme. The resulting programme combined mass media, community mobilisation, interpersonal communication and mobile-based solutions to extend vital health information and advice to rural populations. The complementary suite of three mHealth services were nested under this broader programmatic theory of change and were designed under a single digital theory of change. They aimed to (1) improve FLHWs knowledge of preventative RMNCH behaviours and strengthen their interpersonal communications skills, (2) equip FLHWs with a high-quality job aid to support and standardise their interactions with families, and (3) provide new and expecting mothers and their families directly with audio information to reinforce messages communicated by FLHWs. When the national government scaled the mHealth services, it did so without the wider interventions including Mobile Kunji, which was not scaled because it was thought that smartphone job aids would make the IVR and print-based tools obsolete. Thus arguably Kilkari , which was designed to reinforce the information communicated by FLHWs and urges women to ask FLHWs questions about the content, may be even more effective in states and districts where FLHWs are also equipped with job aids to improve their communication skills, or where the environment is more supportive of behaviour change. Additionally, when Kilkari was adopted by the national government, new versions of the content had to be created to engage millions of new and expecting mothers and their families in multiple states, and to address national and state government priorities. User testing in Bihar had revealed that to improve comprehension and recall, information should be limited to one, simple, doable action per Kilkari call. However, when going to scale that was not always feasible and it was necessary to communicate several simple doable actions in each call.
The hard realities of delivering public health services at scale with constrained resources may require a much more pragmatic approach than many pilots employ. In a donor-funded pilot project, it is possible to design, test and develop an ‘ideal’ maternal messaging programme—particularly if the donor covers the cost of calls or SMS messages. For example, for Kilkari, trade-offs were required in three areas: (1) number of calls; (2) degree of language localisation; (3) times of day when calls were made to subscribers. In pilots, hyperlocalised content can be created for a small sample of women. Skilled project staff can support women who own phones in registering for the service. Accurate mobile numbers and the estimated due date of a child can be captured using software, devices and connectivity procured by the project. Data can flow into an independent, standalone database designed specifically for the service. Calls can be delivered at times of day that women find convenient. And finally, the project can send as many messages as it likes, so long as a donor is willing to pay. In the real world, however, ‘ideal’ programme design is rarely possible. When the Indian government decided to scale Mobile Academy and Kilkari nationally, several important compromises to the service design were required to accommodate its budget and procurement policies, and to overcome the challenges involved in trying to reach low-income illiterate women. It is critical that digital development solutions are designed based on the limits imposed by sustainability. This approach requires compromises. Otherwise, there is a significant risk that proposed digital solutions will ultimately be unaffordable. Number of lessons The ongoing operating costs of Mobile Academy and Kilkari were driven by the number of lessons and calls, respectively. During the pilot in Bihar, in-depth interviews indicated that families were only willing to pay for one Kilkari call per week, and FLHWs were only will to pay for a limited number of Mobile Academy lessons. Similarly, when the national government decided to adopt the services, it understandably expressed reservations about increasing the frequency of Kilkari calls from one to two per week because this would have doubled call costs and considerably increased the cost of the project’s technical infrastructure, which was already significant. Securing approval for Kilkari call costs at scale was already challenging at this early stage in the government’s adoption of the service. It was therefore agreed that families would receive just one Kilkari call per week to limit costs to an acceptable level. Language localisation The Cenus of India 2011 recorded 19,569 mother tongues, including 121 languages. Even in the so-called ‘Hindi-speaking belt’, people speak many other languages and dialects. User testing in five Hindi-speaking states revealed that rural women had a much poorer comprehension of Hindi than men, largely because they lived in media-dark homes and rarely left the confines of their compounds (Chamberlain et al , 2020). Rural men, in contrast, spent time in public spaces talking to a wider variety of people with different accents and dialects, and had greater exposure to shared radios and televisions. Efforts to meet the linguistic needs of all women in the Hindi-speaking belt were not financially viable at scale. As a result, a lowest common denominator Hindi that could be understood by the largest number of women was created. Timing of calls When Kilkari was only live in eight districts in Bihar, new and expecting mothers were called when they said they wanted to receive calls—that is, early in the morning, after lunch and in the early evening. However, when the government decided to scale up the service nationally, this approach was not considered financially viable. Instead, it was decided that Kilkari should make calls throughout the day—from 08:00 to 20:30—to maximise the utilisation of infrastructure and connectivity. Calling subscribers just three times a day would have involved making millions of calls in a much shorter window of time, which would have required significantly more infrastructure and connectivity to handle the load during those hours. Furthermore, this infrastructure and connectivity would have sat idle for much of the day when calls were not being made. Therefore, Kilkari was redesigned so that its infrastructure and connectivity were continuously used. This is a more cost-efficient approach, but it may result in calls being made at times of day when women are unable to answer phones.
The ongoing operating costs of Mobile Academy and Kilkari were driven by the number of lessons and calls, respectively. During the pilot in Bihar, in-depth interviews indicated that families were only willing to pay for one Kilkari call per week, and FLHWs were only will to pay for a limited number of Mobile Academy lessons. Similarly, when the national government decided to adopt the services, it understandably expressed reservations about increasing the frequency of Kilkari calls from one to two per week because this would have doubled call costs and considerably increased the cost of the project’s technical infrastructure, which was already significant. Securing approval for Kilkari call costs at scale was already challenging at this early stage in the government’s adoption of the service. It was therefore agreed that families would receive just one Kilkari call per week to limit costs to an acceptable level.
The Cenus of India 2011 recorded 19,569 mother tongues, including 121 languages. Even in the so-called ‘Hindi-speaking belt’, people speak many other languages and dialects. User testing in five Hindi-speaking states revealed that rural women had a much poorer comprehension of Hindi than men, largely because they lived in media-dark homes and rarely left the confines of their compounds (Chamberlain et al , 2020). Rural men, in contrast, spent time in public spaces talking to a wider variety of people with different accents and dialects, and had greater exposure to shared radios and televisions. Efforts to meet the linguistic needs of all women in the Hindi-speaking belt were not financially viable at scale. As a result, a lowest common denominator Hindi that could be understood by the largest number of women was created.
When Kilkari was only live in eight districts in Bihar, new and expecting mothers were called when they said they wanted to receive calls—that is, early in the morning, after lunch and in the early evening. However, when the government decided to scale up the service nationally, this approach was not considered financially viable. Instead, it was decided that Kilkari should make calls throughout the day—from 08:00 to 20:30—to maximise the utilisation of infrastructure and connectivity. Calling subscribers just three times a day would have involved making millions of calls in a much shorter window of time, which would have required significantly more infrastructure and connectivity to handle the load during those hours. Furthermore, this infrastructure and connectivity would have sat idle for much of the day when calls were not being made. Therefore, Kilkari was redesigned so that its infrastructure and connectivity were continuously used. This is a more cost-efficient approach, but it may result in calls being made at times of day when women are unable to answer phones.
A digital development solution may need to be entirely redesigned before it can be scaled. Integration with government systems and databases, for instance, may require significant changes to technical architecture. The overall solution may also need to be simplified, as too many moving parts are challenging for governments to procure and sustain. Before the scale up begins, it is important to reassess existing technical partners’ strengths and weaknesses. Do they have the skills, experience and—critically—staff capacity required for a national scale-up? Do they have senior engineers in-country to not only support but further develop the software? Are their licensing models cost-effective at national scale and do they allow for the transfer of ownership to the government at no additional cost?
One of the mantras of the digital development community is the value of open-source technologies as ‘global goods’. Based on the experience of this programme, it may prove not just more expensive to scale, enhance and support open-source software than to purchase unlimited capacity, in perpetuity licences for proprietary software applications, but also more challenging to transition open-source software to the government. A key source of revenue for proprietary software companies is the sale of annual maintenance contracts. Their business models depend on providing cost-effective, reliable support in the countries where their software is sold. But when it comes to open-source software, sometimes the only people capable of maintaining and further developing the software are those who built it. And there may be very few of those people. Moreover, it can be just as challenging for a government to adopt open-source software as proprietary software. If there is only one company capable of (re)developing and maintaining an open-source solution, government procurement policies may prevent it from contracting this company, because at least three valid bids from different providers may be required. Decisions to use open-source software at scale should be based not just on the functionality and performance of the software, but also on the size and sustainability of its user community, the availability of expert technical support in-country, the clarity of code and code labelling, and the quality of software documentation and user manuals. Propriety software can be just as—if not more—cost-effective than open-source software if the correct licences are negotiated. This programme negotiated one-off payments for unlimited capacity, in perpetuity software licences for Mobile Academy and Kilkari because they were cost-effective at scale. Critically, the programme ensured that these licenses could be transferred to the Indian government at no additional cost.
Mobile Academy and Kilkari were compelling candidates for government adoption not just because these services offered solutions to known challenges, but because they had demonstrated sustained demand from target populations, and could be set up and managed centrally with little face-to face training and were relatively straightforward and inexpensive to sustain. Mobile Kunji , which had also demonstrated sustained adoption by FLHWs at scale in three Indian states, and a significant impact on multiple health outcomes, was more challenging than Mobile Academy and Kilkari to adopt because it would have involved the procurement and distribution of a physical deck of printed cards (to accompany the IVR component of the job aid) to a million FLHWs across the nation; at least a day of face-to-face training and significant IVR call costs. Sources at the Ministry of Health and Family Welfare (MoHFW) say the government is routinely bombarded by pitches for complex digital solutions that involve many moving parts. But few digital development pilots are designed with government procurement policies, interoperability and operational feasibility at scale in mind. Furthermore, sustainability strategies tend to focus on capital investment rather than ongoing running costs and logistics. Future mHealth projects will require more emphasis on developing strategies for effectively responding to government procurement and distribution challenges, and on costing viable operational models at scale.
When Kilkari was first tested in eight districts in the state of Bihar in 2013, users dialled a toll-free number to subscribe to the service. In keeping with the regulations of the Telecom Regulatory Authority of India (TRAI), they had to confirm their subscription twice by pressing numbers on their mobile keypads. This requirement excluded many women who could not make outbound calls or navigate IVR prompts. The project then experimented with using a call centre to take informed consent from subscribers. But this was equally challenging, as rural women—who had never heard of the internet or data—struggled to understand the concept of ‘informed consent’. When the MoHFW decided to scale Kilkari nationally, making it free to all pregnant and postpartum women, it received an exemption from TRAI consent guidelines. It was thought that the benefits of rapidly disseminating free health information outweighed concerns around data protection. As a precaution, however, users were given the ability to unsubscribe at the end of every call. The National Health Mission in each state planned to train FLHWs to inform pregnant women and mothers of babies about Kilkari and to equip them to answer questions about the service. But because this sensitisation did not happen in some locations, families were caught off-guard when they suddenly started receiving Kilkari calls. Although many were pleasantly surprised by the arrival of Kilkari in their lives, others immediately unsubscribed from the service or disconnected the calls, thinking they were spam. As concerns about data protection and privacy grow among the citizens of developing countries, governments and non-governmental organisations will need to identify how to take informed consent to capture personal and sensitive data in a cost-effective way, without excluding potential beneficiaries. The pathway to achieving this has yet to be defined but may benefit from learning elsewhere. Efforts are underway in South Africa as part of the MomConnect national maternal messaging programme to enhance data capture consent language and processes. Cognitive interviews that are being conducted with pregnant women and providers are anticipated to yield revised informed consent language, which can be used to enable data use for a range of purposes, including sending health information messages, conducting health services research and recontacting beneficiaries.
India’s nationwide effort to register pregnancies, births and the provision of RMNCH services, and to maintain an up-to-date FLHW database is a Herculean task. In addition to exceedingly high rates of SIM change among rural populations (44% see LeFevre et al , 2021 ), the gender gap in both mobile phone access and digital literacy is a significant barrier. In a context where only 14% of adult women pan India own a smartphone and only 56% have access to the household phone in states such as Madhya Pradesh, the mobile numbers associated with women in government databases are likely to belong to male family members. Digital development solutions that rely on accurate mobile numbers for women should proceed with caution, designing content that not just speaks to mothers, but also fathers, because they may be equal if not dominant participants in the mHealth programme.
When the programme first designed the suite of mHealth services in the state of Bihar, it worked closely with the state government on strategy, content and training, but procured and delivered the services independently. This changed when the states of Odisha and Uttar Pradesh decided to adopt Mobile Academy and Mobile Kunji , and then again when the MoHFW decided to scale Mobile Academy and Kilkari nationally. At these points, the team shifted to supporting first state governments and then later the national government in directly procuring the elements of each mHealth service. This proved resource-intensive and time-consuming. The programme needed to dedicate considerable staff resources, for much longer, to support government departments in launching the services and rolling them out. For example, it took 6 months of sustained engagement to agree the scope of the scale-up and to receive approval to proceed with the implementation. It is critical that digital implementers—and their investors—are realistic about the timelines and resources required for government adoptions and scale-ups.
Key learning from a decade of designing and scaling digital solutions in partnership with state and national government indicates the critical importance of: (1) identifying how the proposed intervention can support priority government programmes; (2) working with the strongest possible government sponsor from day 1, (3) agreeing roles and responsibilities for all stakeholders up front, (4) agreeing a shared strategy for co-management, including the establishment of a programme management unit and regular joint project review meetings. Furthermore, (5) buy-in is enhanced if the government has a financial stake in the scale-up at the outset, and (6) agreeing a clear roadmap at the outset for the transition of ownership to government is key, but be prepared to adapt to unexpected challenges and opportunities.
Mobile Academy and Kilkari represent two of the few examples, globally, of how to achieve digital sustainability at scale. Implementation lessons learnt from this journey are a reality check. They underline the criticality of reassessing every aspect of an ideal pilot programme before scale-up, and the recognition that compromises may need to be made in service design. Making a digital programme affordable is likely to involve sacrifices, which may reduce the intensity, frequency and precise tailoring or targeting of an intervention. Patience and sustained investment—particularly in learning and evaluation—are required to optimise digital solutions at scale and amplify their impact. Hasty transitions may result in lost opportunities. Furthermore, scale-ups and transitions are not controlled scientific experiments. The expectation that a pilot project will be replicable at significant scale is wishful thinking. Public sector procurement will cause delays, funding streams will no longer be in sync and different project components may not happen on time. Planning for these challenges and having the resilience to adapt to the unforeseeable should be regarded as a sign of mHealth maturity.
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The impact of COVID-19 pandemic and lockdown on emergency psychiatry department admissions | 9cebca66-94f1-4deb-a2d1-0f414cd65963 | 10798784 | Psychiatry[mh] | On March 11, 2020, the World Health Organization declared COVID-19 a pandemic, and the first COVID-19 case in Turkey was reported on the same day in Istanbul (Ministry of Health of the Turkish Republic, 2020). On March 20, 2020, all health institutions that had at least 2 branches of infectious diseases, internal diseases, and chest diseases and had adult intensive care facilities were declared as pandemic hospitals by the Ministry of Health. The government of the Turkish Republic imposed the first full quarantine order between March 30 and May 31, 2020. Psychiatry wards and outpatient psychiatry units served with restricted capacities during quarantine, but the psychiatry emergency departments (PED) worked at full capacity to tend to mental health problems. According to the number of daily cases throughout the pandemic, these restrictions were applied for certain periods. The vaccination program in Turkey was initiated on January 14, 2021. Owing to the increase in the number of cases, the second quarantine period was implemented between April 29 and May 17, 2021. In June 2021, a gradual normalization process was announced. Previous studies on the severe acute respiratory syndrome epidemic reported that mental health was adversely affected during times of quarantine. Several studies have shown that the pandemic led to a rise in overall psychological distress and potentially increased the occurrence of anxiety, depressive disorders, insomnia, post-traumatic stress disorder, and eating disorders. [ – ] Various studies have been conducted to evaluate the effect of this shift in psychiatric conditions on the amount and characteristics of psychiatric emergency admissions. Admissions to our hospital, a major institution in the area, could be indicative of the mental health status of the community during the pandemic. During the pandemic, our hospital, like many others, had to significantly reduce face-to-face services in outpatient clinics and decrease the capacity of our inpatient unit. The number and range of reasons for referrals to our psychiatric emergency services were significantly impacted by this situation. Examining the extent and character of this shift is essential to comprehend the impact of the pandemic on mental health. Some studies suggest that during the COVID-19 pandemic, mental health deteriorated before lockdowns were introduced. In several studies during lockdown, a substantial decrease in the total number of psychiatric emergency consultations and admissions was observed, when compared to the same period in 2019 or the first 2 months of 2020. [ – ] A study investigated the 40-day period during the initial pandemic and found a decrease in psychiatric admissions in Italy. Similarly, Abbas et al found a decrease in both referrals and admissions to mental health trusts in the United Kingdom. On the other hand, some studies reported a possible increase in emergency room visits during the lockdown period (LP) for anxiety, depression, and suicidal behavior. [ , , ] Higher levels of anxiety and depression were reported at the start of the lockdown in the United Kingdom, which declined rapidly. Younger women, those from more socially disadvantaged backgrounds, with preexisting mental health conditions, lower educational attainment, lower income, living alone, or with children were identified as risk factors for worse mental health outcomes. Exploring the characteristics of psychiatric emergency room admissions during the quarantine period may help us understand the effects of forced isolation on admissions to psychiatric emergencies. The current study investigated the impact of quarantine orders adopted in Turkey on emergency psychiatry room visits during 3 different time periods: prelock down, lockdown, and postlock down periods. Our second aim was to assess PED admissions in terms of sociodemographic and clinical characteristics during the first year of the pandemic, in comparison to the prepandemic year and the second year of the pandemic, in which vaccines were introduced in Turkey.
2.1. Study design and setting This was a retrospective cross-sectional that included subjects consecutively admitted to the psychiatric emergency services at the University, Department of Psychiatry. The University covers the health needs of 400,000 inhabitants. The psychiatry clinic offers psychiatric emergency care 24 hours a day and provides treatment for different psychiatric conditions, including geriatric psychiatry, consultation-liaison inpatient and outpatient services, and locked wards for patients with severe mental health conditions. The University Psychiatry Clinic has continued to serve as a preventive measure during the pandemic. The inpatient unit capacity was reduced by 50%, and hospitalization criteria were limited to suicidality and severe aggressive behavior. 2.2. Data collection We obtained admission records from the Department of Psychiatry of the University. Since we aimed to evaluate all emergency department admissions that met the inclusion criteria in the specified period, no sample size calculation was made. The collected information included sociodemographic data, previous psychiatric history, attending symptoms, suicidal ideation/intent, the International Classification of Diseases 10 (ICD-10) diagnosis, decision of hospitalization in emergency care, comorbid medical illness, and the presence of multiple visits (more than 2 in 2 months). Patients were divided into 3 different age categories: 18–40 years old, 40–65 years old, and ≥65 years old. The study did not include individuals admitted to emergency care to prescribe their usual medicines to prevent bias (Fig. ). The Non-Invasive Clinical Research Ethics Committee of the Istanbul University—Cerrahpaşa, Cerrahpaşa Faculty of Medicine approved the study (study number: 526363). 2.3. Time periods The number of patients admitted to and hospitalized in the PED monthly during the partial LP in the first wave of the pandemic (March 30, 2020–May 31, 2020) was compared with the same period in 2019 and the postlockdown months in 2020 (June 1, 2020–July 31, 2020). Additionally, we compared 3 time periods to follow the changes in admissions during the pandemic: March 11, 2019–March 11, 2020 (prepandemic period); March 11, 2020–March 11, 2021 (pandemic) and March 11, 2021–March 11, 2022, when the vaccines were introduced and gradually used among the general population in Turkey. We also investigated the number of monthly PED visits between March 2019 and March 2022. 2.4. Data analysis Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 21. Descriptive analyses of included variables were performed for the lockdown, pre-and post-LP, and prepandemic and the first and second years of the pandemic. The mean and standard deviation (SD) or median and interquartile range according to the distribution of the data for continuous variables and the frequency and percentage for categorical variables were reported. Normality of the continuous variables was demonstrated via Kolmogorov–Smirnov test, coefficient of variation, histogram and Q–Q plot. Comparisons between the groups were evaluated with Kruskal–Wallis test for continuous variables. Post hoc Dunn test was used for assessing the significant groups in continuous variables. Chi-squared or Fisher exact tests were applied for categorical variables. Post hoc Bonferroni test was applied to determine the significant groups between more than 2 categorical groups. Analyzes for variables with missing data were performed on the available data. Statistical significance was set at P < .05. Binomial logistic regression analysis was performed for variables considered to be related to suicidal behavior, frequent PED visits, and hospitalization, and the data were presented as odds ratios (OR) and 95% confidence intervals (95% CI). Variables with a P -value below 0.250 in univariate analysis were assessed with binomial regression analysis. Enter method was used in regression analysis. The level of statistical significance was set at P < .05.
This was a retrospective cross-sectional that included subjects consecutively admitted to the psychiatric emergency services at the University, Department of Psychiatry. The University covers the health needs of 400,000 inhabitants. The psychiatry clinic offers psychiatric emergency care 24 hours a day and provides treatment for different psychiatric conditions, including geriatric psychiatry, consultation-liaison inpatient and outpatient services, and locked wards for patients with severe mental health conditions. The University Psychiatry Clinic has continued to serve as a preventive measure during the pandemic. The inpatient unit capacity was reduced by 50%, and hospitalization criteria were limited to suicidality and severe aggressive behavior.
We obtained admission records from the Department of Psychiatry of the University. Since we aimed to evaluate all emergency department admissions that met the inclusion criteria in the specified period, no sample size calculation was made. The collected information included sociodemographic data, previous psychiatric history, attending symptoms, suicidal ideation/intent, the International Classification of Diseases 10 (ICD-10) diagnosis, decision of hospitalization in emergency care, comorbid medical illness, and the presence of multiple visits (more than 2 in 2 months). Patients were divided into 3 different age categories: 18–40 years old, 40–65 years old, and ≥65 years old. The study did not include individuals admitted to emergency care to prescribe their usual medicines to prevent bias (Fig. ). The Non-Invasive Clinical Research Ethics Committee of the Istanbul University—Cerrahpaşa, Cerrahpaşa Faculty of Medicine approved the study (study number: 526363).
The number of patients admitted to and hospitalized in the PED monthly during the partial LP in the first wave of the pandemic (March 30, 2020–May 31, 2020) was compared with the same period in 2019 and the postlockdown months in 2020 (June 1, 2020–July 31, 2020). Additionally, we compared 3 time periods to follow the changes in admissions during the pandemic: March 11, 2019–March 11, 2020 (prepandemic period); March 11, 2020–March 11, 2021 (pandemic) and March 11, 2021–March 11, 2022, when the vaccines were introduced and gradually used among the general population in Turkey. We also investigated the number of monthly PED visits between March 2019 and March 2022.
Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) version 21. Descriptive analyses of included variables were performed for the lockdown, pre-and post-LP, and prepandemic and the first and second years of the pandemic. The mean and standard deviation (SD) or median and interquartile range according to the distribution of the data for continuous variables and the frequency and percentage for categorical variables were reported. Normality of the continuous variables was demonstrated via Kolmogorov–Smirnov test, coefficient of variation, histogram and Q–Q plot. Comparisons between the groups were evaluated with Kruskal–Wallis test for continuous variables. Post hoc Dunn test was used for assessing the significant groups in continuous variables. Chi-squared or Fisher exact tests were applied for categorical variables. Post hoc Bonferroni test was applied to determine the significant groups between more than 2 categorical groups. Analyzes for variables with missing data were performed on the available data. Statistical significance was set at P < .05. Binomial logistic regression analysis was performed for variables considered to be related to suicidal behavior, frequent PED visits, and hospitalization, and the data were presented as odds ratios (OR) and 95% confidence intervals (95% CI). Variables with a P -value below 0.250 in univariate analysis were assessed with binomial regression analysis. Enter method was used in regression analysis. The level of statistical significance was set at P < .05.
3.1. Comparison of psychiatric emergency department admissions and hospitalizations during a 2 - month period in lockdown period, prelockdown period, and postlockdown period We found an increase in emergency psychiatric admissions during the LP compared with the pre-LP. (Fig. ). A total of 293 patients were admitted to the PED during the initial LP, while 140 patients were admitted during the same period in 2019 (the total number of visits increased by 109%). There was a significant increase in PED admissions in all age groups (18–40 years old, 40–65 years old, and ≥65 years old) independent of sex ( P = .98, df = 2, X 2 = 0.022). In the post-LP, the number of admissions decreased to 86, which was lower than that in the prelockdown months. Apart from occupational status, no statistical differences were observed among the prelockdown, lockdown, and post-LPs with regard to sociodemographic variables. While anxiety disorders, bipolar disorders, and psychotic disorders were the most common diagnoses in the prepandemic period, patients with anxiety disorders were the most frequently represented group in emergency psychiatry visits during lockdown (N = 110, 37.4%). Anxiety disorders significantly increased in the LP compared with the same period in the previous year, in contrast to the decrease in psychotic and bipolar disorders. Patients diagnosed with anxiety disorders in PED during lockdown were predominantly women (62.7%), with a mean age of 40 years (SD = ±14.44). Most of them were previously diagnosed with anxiety disorders (58.2%), and 43% had comorbid medical illnesses. The rate of patients visiting the PED with suicidal intent or attempt and hospitalization was significantly lower during partial lockdown compared to pre-LP. The data regarding the comparison of the sociodemographic and clinical characteristics of the patients admitted to the PED in the LP and non-LP are provided in Table . 3.2. Comparison of psychiatric emergency department visits and hospitalizations during 12 - month period in 2021, 2020, and 2019 A total of 700 PED visits were reported between March 11, 2019 and March 11, 2020 which dropped to 685 in the second year of the pandemic between March 11, 2020 and March 11, 2021. This number further decreased to 404 (excluding prescriptions) between 11 March 2021 and March 11, 2022. The decline in PED visits was 3.1% and 42% during the first and second years of the pandemic, compared to prepandemic year respectively. Patients diagnosed with anxiety and depressive disorders and obsessive-compulsive disorder (OCD) during the first year of the pandemic visited the PED more frequently than in the prepandemic year. In contrast, patients with psychotic disorders had significantly fewer PED visits in the first year of the pandemic. Patients with bipolar disorder also had fewer PED visits compared to the previous year, although this was not statistically significant. In the second year, there was a trend toward prepandemic year ratios. Psychiatric hospitalizations and suicidal intent/behavior declined compared to prepandemic levels yet they tended to increase slightly in the second year, but remained at a level lower than the prepandemic year. The data regarding the comparison of the sociodemographic and clinical characteristics of the patients admitted to the PED during a 12-month period in 2021, 2020, and 2021 are provided in Table . When the most frequent diagnoses regarding PED visits were investigated across different age ranges; it was found that in the age group 18–40 years old, in the first year of the pandemic anxiety disorders increased significantly from 17.6 to 26.1% and decreased to 21.1% in the second year ( P = .017), in the age group 40–65 years old depressive disorder related visits increased significantly from 14 to 28% and decreased to 19.4% ( P < .001). In both conditions, no statistically significant difference was found between first and second years of the pandemic. In patients over 65 years of age, no statistically significant difference was found for emergency diagnosis, yet more patients with depression sought help from the emergency department, the number of depressive disorder-related visits increased from 8.8 to 28.3%. 3.3. Regression analysis Logistic regression analysis was performed for variables related to suicidal intent/attempt, frequent PED visits, and hospitalization. Data are presented as OR and 95% CI. The level of statistical significance was set at P < .05. Factors related to suicide attempts during the first year of the pandemic were depressive disorders ( P = .017; OR: 2.89; 95% CI: 1.21–6.89). Factors related to hospitalization were bipolar (OR: 2.87; 95% CI: 1.51–5.46) and psychotic disorders (OR: 4.88; 95% CI: 2.6–9.14). Factors related to frequent emergency visits included previous diagnosis of psychiatric disorder (OR: 14.34; 95% CI: 1.94–105.86) and being widowed (OR: 2.91; 1.30–6.52). A previous diagnosis of a psychiatric disorder (OR: 10.34; 95% CI 1.36–78.83) predicted frequent emergency visits during lockdown. (Table ).
Comparison of psychiatric emergency department admissions and hospitalizations during a 2 - month period in lockdown period, prelockdown period, and postlockdown period We found an increase in emergency psychiatric admissions during the LP compared with the pre-LP. (Fig. ). A total of 293 patients were admitted to the PED during the initial LP, while 140 patients were admitted during the same period in 2019 (the total number of visits increased by 109%). There was a significant increase in PED admissions in all age groups (18–40 years old, 40–65 years old, and ≥65 years old) independent of sex ( P = .98, df = 2, X 2 = 0.022). In the post-LP, the number of admissions decreased to 86, which was lower than that in the prelockdown months. Apart from occupational status, no statistical differences were observed among the prelockdown, lockdown, and post-LPs with regard to sociodemographic variables. While anxiety disorders, bipolar disorders, and psychotic disorders were the most common diagnoses in the prepandemic period, patients with anxiety disorders were the most frequently represented group in emergency psychiatry visits during lockdown (N = 110, 37.4%). Anxiety disorders significantly increased in the LP compared with the same period in the previous year, in contrast to the decrease in psychotic and bipolar disorders. Patients diagnosed with anxiety disorders in PED during lockdown were predominantly women (62.7%), with a mean age of 40 years (SD = ±14.44). Most of them were previously diagnosed with anxiety disorders (58.2%), and 43% had comorbid medical illnesses. The rate of patients visiting the PED with suicidal intent or attempt and hospitalization was significantly lower during partial lockdown compared to pre-LP. The data regarding the comparison of the sociodemographic and clinical characteristics of the patients admitted to the PED in the LP and non-LP are provided in Table .
Comparison of psychiatric emergency department visits and hospitalizations during 12 - month period in 2021, 2020, and 2019 A total of 700 PED visits were reported between March 11, 2019 and March 11, 2020 which dropped to 685 in the second year of the pandemic between March 11, 2020 and March 11, 2021. This number further decreased to 404 (excluding prescriptions) between 11 March 2021 and March 11, 2022. The decline in PED visits was 3.1% and 42% during the first and second years of the pandemic, compared to prepandemic year respectively. Patients diagnosed with anxiety and depressive disorders and obsessive-compulsive disorder (OCD) during the first year of the pandemic visited the PED more frequently than in the prepandemic year. In contrast, patients with psychotic disorders had significantly fewer PED visits in the first year of the pandemic. Patients with bipolar disorder also had fewer PED visits compared to the previous year, although this was not statistically significant. In the second year, there was a trend toward prepandemic year ratios. Psychiatric hospitalizations and suicidal intent/behavior declined compared to prepandemic levels yet they tended to increase slightly in the second year, but remained at a level lower than the prepandemic year. The data regarding the comparison of the sociodemographic and clinical characteristics of the patients admitted to the PED during a 12-month period in 2021, 2020, and 2021 are provided in Table . When the most frequent diagnoses regarding PED visits were investigated across different age ranges; it was found that in the age group 18–40 years old, in the first year of the pandemic anxiety disorders increased significantly from 17.6 to 26.1% and decreased to 21.1% in the second year ( P = .017), in the age group 40–65 years old depressive disorder related visits increased significantly from 14 to 28% and decreased to 19.4% ( P < .001). In both conditions, no statistically significant difference was found between first and second years of the pandemic. In patients over 65 years of age, no statistically significant difference was found for emergency diagnosis, yet more patients with depression sought help from the emergency department, the number of depressive disorder-related visits increased from 8.8 to 28.3%.
Logistic regression analysis was performed for variables related to suicidal intent/attempt, frequent PED visits, and hospitalization. Data are presented as OR and 95% CI. The level of statistical significance was set at P < .05. Factors related to suicide attempts during the first year of the pandemic were depressive disorders ( P = .017; OR: 2.89; 95% CI: 1.21–6.89). Factors related to hospitalization were bipolar (OR: 2.87; 95% CI: 1.51–5.46) and psychotic disorders (OR: 4.88; 95% CI: 2.6–9.14). Factors related to frequent emergency visits included previous diagnosis of psychiatric disorder (OR: 14.34; 95% CI: 1.94–105.86) and being widowed (OR: 2.91; 1.30–6.52). A previous diagnosis of a psychiatric disorder (OR: 10.34; 95% CI 1.36–78.83) predicted frequent emergency visits during lockdown. (Table ).
Our study indicates that mental health was adversely affected in the 8 weeks following the start of the first lockdown at our university in Istanbul. There was a 109% increase in emergency psychiatry department admissions during the lockdown compared to the same periods in 2019, which was observed across all age groups and in both sexes. The sudden increase in psychiatry emergency admissions declined rapidly after the first lockdown which ended May 31, 2020. In subsequent lockdowns similar increase in psychiatry emergency admissions didn’t occur, probably due to the adaptation of the population to the quarantine-implemented orders. Patients presenting with PED during lockdown were more likely to be diagnosed with anxiety and depressive disorders. Anxiety disorders significantly increased during the first lockdown, whereas patients with bipolar and psychotic disorders had significantly lower admissions than those in the previous year. There was a 3.1% and a 42% decline in PED visits during the first year and second year of the pandemic, respectively. Psychiatric hospitalizations and suicidal intent/behavior declined compared to the prepandemic year, yet they tended to increase slightly in the second year, although they remained lower than in the prepandemic year. Depressive disorders were found to predict suicidal ideation, while bipolar and psychotic disorders were found to predict hospitalization in the first year. A previous diagnosis of psychiatric disorders was associated with a higher risk of frequent visits to the PED (more than 2 per month) during both the lockdown and the first year of the pandemic. Suicidal behavior and hospitalizations were lower during lockdown, and no significant increase was found in frequent visits compared to the same months in the previous year. We found that the quarantine, particularly during the initial lockdown, had an obvious adverse impact on PED visits. In the current study, patients visiting the PED during lockdown were more likely to be diagnosed with anxiety and depressive disorders. Similar to our findings, Fancourt et al found that the highest levels of depression and anxiety occurred in the early stages of lockdown in 2020 in the United Kingdom and it declined rapidly. In a longitudinal study in Spain, Sanguino et al found that there was an adverse impact of the pandemic during confinement, and that it did not rapidly return to precrisis levels, although it improved as the emergency situation subsided. Other studies from Italy, the United Kingdom, and Denmark reported a decrease in referrals and admissions during the lockdown [ , , ] while a previous study from Turkey reported that the total number of PED visits decreased during the lockdown, but the rates of patients presenting with anxiety and depressive disorders increased significantly in the lockdown compared to other times. On the contrary, Gómez-Ramiro et al and Capuzzi et al reported lower visitation rates in patients with anxiety and depressive disorders, respectively. Authors suggest that the use of telemedicine and fear of infection may explain the decreased admissions of patients who were not severely ill. Patients diagnosed with anxiety disorders in the emergency unit during lockdown were predominantly women, most of whom were previously diagnosed with anxiety disorders (58.2%), and about 43% had comorbid medical illnesses. These findings are in accordance with some of the previously defined risk factors for a higher level of anxiety, such as being a woman, younger age, having lower educational attainment, having lower income, having preexisting psychiatric conditions, and living alone or with children. Previous studies on the mental health effects of the COVID-19 pandemic have also reported an increased risk of depression and anxiety in individuals with chronic medical diseases. Frequent visits to the PED during lockdown were previously found to be associated with depressive disorders, a history of mental illness, and aggressive behaviors. In accordance with this study, the previous diagnosis of psychiatric disorder predicted frequent emergency visits during the lockdown. The number of patients presenting to the emergency psychiatric unit with bipolar and psychotic disorders, as well as hospitalizations and suicidal behavior, decreased significantly in lockdown. There could be multiple reasons for this result. One of them could be many patients with severe mental disorders living with their family members in Turkey, which may have been protected by increased social support. Nonetheless, those who are more vulnerable could face significant difficulties in getting medical care during the pandemic. Additionally, patients affiliated with the mood and psychotic disorders units of the clinic continued to closely follow up via telemedicine in case of necessity. Diminished experiences of negative emotions and cognitive impairments in schizophrenia may reduce the perception of traumatic events. Therefore, this group might have been less affected by the traumatic conditions created by the pandemic. Similar to our findings, Dionisi et al in Romania found that inpatient admissions for affective and psychotic disorders declined in lockdown compared to the pre-LP, after which a compensatory increase was observed in the number of hospitalizations for psychotic or affective disorders, which did not exceed the prepandemic levels. Although there has not been any major change in emergency ambulance services’ referral of patients to institutions during the pandemic, patients who tested positive for COVID-19 and required psychiatric hospitalization were directed to a healthcare center other than our hospital, as determined by the Ministry of Health. This situation might have had an effect on the reduced admissions for this group. Emergency department utilization in psychiatry has declined in many countries during the pandemic. Overall, we found that there was a decline in PED visits by about 3.1% and 42% in the first and second years of the pandemic, respectively, compared to the prepandemic year. Similar to our results, a previous study from a mental health epicenter in Turkey reported that the volume of PED visits in 2020 decreased by 12% compared to that in 2019. We found a significant increase in PED visits for patients diagnosed with anxiety and depressive disorders during the first year of the pandemic, which is in accordance with previous studies. Our findings regarding the increase in OCD support those of previous reports that indicated the worsening of OCD symptoms during the pandemic. [ , – ] In the second year, anxiety and depressive disorders showed a downward trend, but did not reach the prepandemic year levels. OCD rates declined in the second year, very close to the prepandemic times. This downward trend can be attributed to the decline in the level of anxiety due to adaptation and the introduction of vaccines. Psychotic disorder rates declined in the first year, but rose again in the second year of the pandemic to a level that did not achieve the rates of the prepandemic year. Lesser interruptions in the everyday life of patients with schizophrenia, compared to other diagnostic groups, might explain this decline. No significant difference was found in the visitation rates of bipolar patients during the first and second years of the pandemic compared to the prepandemic year, corresponding with previous studies. Women and young adults were found to be more affected by anxiety during the pandemic period. We also found that younger adults were at a higher risk of developing anxiety disorders. When most frequent diagnoses regarding PED visits were investigated across different age ranges, we found that younger adults were more likely to present to the emergency room with anxiety disorders and middle-aged patients were more likely to present with depressive disorders in the first year of the pandemic. In this study, PED visits due to suicidal intent and inpatient admissions declined significantly in the first year of the pandemic and increased in the second year, but did not reach the prepandemic year levels. Avoidance of hospitals due to the fear of contamination, but also the restriction in hospitazaion cirteria to very severe psychiatric conditions may be one of the several reasons for this decline. In a large study from Denmark, the authors found that the pandemic has been associated with a decrease in psychiatric hospitalizations. Several studies reported the same way [ , , ] along with the impact of the pandemic. There have been contradictory findings regarding suicide rates during the pandemic, in some studies no significant change was observed in suicidal behavior. In accordance with our findings, some studies reported significantly decreased rates of suicide attempts or suicidal ideation in patients admitted to the PED during the pandemic. [ , , ] Previously authors suggested that this may be a real decline or it is due to the fact that patients are not presenting to the ED. By contrast, an increase in suicide rates in the second wave was reported from Japan and also an increase in suicidal ideation was observed in the post-LP in 2020 in Italy. The period of the pandemic when the study was conducted, methodological differences such as sample size, and cultural or economic variables may have affected the results. We found that factors related to suicide attempts during the first year of the pandemic were depressive disorders ( P = .017; OR: 2.89; 95% CI: 1.21–6.89) which is a well-known risk factor for suicide at other times. During the first year of the pandemic, we found that factors related to hospitalization were bipolar (OR: 2.87; 95% CI: 1.51–5.46) and psychotic disorders (OR:4.88; 95% CI: 2.6–9.14) which was in accordance with the restricted hospitalization criteria confined to more severe mental illnesses. Factors related to frequent emergency visits were previous diagnosis of psychiatric disorder (OR: 14.34; CI: 1.94–105.86) and being widowed (OR: 2.91; CI: 1.30–6.52) in the first year of the pandemic. Previous research has also highlighted psychiatric diagnoses for worse mental health outcomes during pandemics. [ , , ] The strengths of the study would involve: the data contains up-to-date information from a large hospital in Istanbul, in an area that was severely affected by the pandemic. Furthermore, the study provides long-term investigation including both the first and second year of the pandemic about psychiatric emergency care. 4.1. Limitations This study was retrospective and conducted in a single university psychiatry clinic, and the results may not be generalizable to the general population. As there is no data regarding the rate of patients applying to the emergency ambulance service, it is not possible to assess the impact of this situation on applications to the PED.
This study was retrospective and conducted in a single university psychiatry clinic, and the results may not be generalizable to the general population. As there is no data regarding the rate of patients applying to the emergency ambulance service, it is not possible to assess the impact of this situation on applications to the PED.
Overall, our findings suggest that there was a surge in depression and anxiety in the early stages of lockdown, but declined rapidly at the end of the lockdown, and this surge did not recur during lockdowns in the following years of the pandemic. The pandemic has been associated with a decline in PED visits; however, among the major diagnostic categories, we found that the rate of anxiety, depressive disorders, and OCD increased significantly in the first year. In contrast, psychotic disorders declined and bipolar disorders remained the same. Psychiatric hospitalizations and suicidal intent/behavior declined compared to the prepandemic levels yet they tended to increase slightly in the second year, but remained at a level lower than the prepandemic year. Patients with a previous psychiatric history presented with heightened emergency admission during the lockdown and pandemic. For future lockdowns, these data underscore the importance of supporting people to help alleviate the distress caused by the enforced isolation, especially for patients with a previous psychiatric disorder. As a surge in anxiety and depression in admissions did not occur in consecutive LPs, we might conclude that individuals have the potential for learning to adapt to the psychological distress of lockdown. In the second year, there was a trend toward prepandemic year ratios yet we don’t know long-term trajectories of psychiatric distress due to the pandemic. Therefore, government policy should focus on mental health needs urgently. Furthermore, preventing major psychiatric disorders should be a priority.
Conceptualization: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen. Data curation: Beril Kara Esen. Formal analysis: Beril Kara Esen. Investigation: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen. Methodology: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen. Project administration: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen. Supervision: Cana Aksoy Poyraz. Writing—original draft: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen. Writing—review & editing: Cana Aksoy Poyraz, Büşra Uçar Bostan, Elif Burcu Ersungur Çelik, Beril Kara Esen.
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Incidence of Chronic Thromboembolic Pulmonary Hypertension After Pulmonary Embolism in the Era of Direct Oral Anticoagulants: From the | d258ed2e-b7c7-479a-9c36-0efd6f740577 | 11935678 | Pathologic Processes[mh] | In the routine clinical practice of the direct oral anticoagulant era, the cumulative detection of chronic thromboembolic pulmonary hypertension after acute pulmonary embolism was 2.3% at 3 years. Factors were identified at the time of acute pulmonary embolism diagnosis to recognize patients who are more likely to be diagnosed with chronic thromboembolic pulmonary hypertension in the future.
Chronic thromboembolic pulmonary hypertension after acute pulmonary embolism remains an unresolved issue in the direct oral anticoagulant era, and risk stratification for predicting chronic thromboembolic pulmonary hypertension could be useful.
The data, analytic methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure. However, if the relevant review board or ethics committee approve data sharing and all investigators of the COMMAND VTE Registry‐2 provide consent, the deidentified participant data will be shared on a request basis through the principal investigator. Study protocol will also be available. The data will be shared as Excel files via e‐mail during the proposed investigation period. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline. Study Participants The COMMAND VTE Registry‐2 is a multicenter, retrospective cohort study initiated by physicians, which enrolled consecutive patients diagnosed with acute symptomatic VTE confirmed by imaging examinations or autopsy from 31 centers in Japan between January 2015 and August 2020, following the introduction of DOACs for VTE treatment in Japan. Detailed information on the registry's design has been previously documented. Hospital databases were queried for clinical diagnoses and/or imaging examinations, and we included consecutive patients meeting the criteria for acute symptomatic VTE diagnosis within 31 days of symptom onset throughout the study duration. The study protocol received approval from the appropriate review boards or ethics committees at all 31 participating centers. Written informed consent from individual patients was not required, because we utilized clinical data obtained during routine clinical care. Moreover, none of the patients declined participation when contacted for follow‐up, and opt‐out forms were available on each institution's website. This approach was consistent with the epidemiological study guidelines issued by the Ministry of Health, Labor, and Welfare in Japan. Outcomes We examined the incidence of detection and risk factors of CTEPH among patients enrolled in the registry who were confirmed to have acute PE. Data Collection and Clinical Follow‐Up Patient characteristic data were extracted from medical records or hospital databases based on predefined criteria, using an electronic case report form within a web‐based database system. The index time was defined as the time of acute PE diagnosis, and the end of follow‐up was defined as the time of death, loss to follow‐up, or the time of the last data collection at the end of the study period. The patient characteristics and clinical data were collected at the time of VTE diagnosis. Data entry was conducted by VTE specialists at each institution, with automatic checks for missing or conflicting entries and values outside the anticipated range. Further validation checks were carried out at the central registry office. After confirmation of diagnosis of CTEPH by the registry office, for all cases of CTEPH, the additional information on hemodynamics, the course of respiratory distress, and the outpatient follow‐up status for patients with CTEPH were collected by re‐evaluating the images and clinical course at each institution. Hypoxemia was characterized by an arterial oxygen partial pressure <60 mm Hg or a hemoglobin oxygen saturation percentage <90%. Right heart load was defined as the existence of right ventricular dilation or estimated systolic pulmonary arterial pressure of ≥40 mm Hg by echocardiography, or presence of enlarged right ventricular findings (right ventricular diameter/left ventricular diameter ≥0.9) on computed tomography. The detailed definitions of other patient characteristics are provided in Data . Follow‐up information was collected mainly by medical records review. If needed, supplementary details were obtained via communication with patients, their family members, and/or referring physicians through telephone and/or correspondence. The last round of data collection for follow‐up events took place from September 2021 to April 2022. An independent clinical events committee (Data ), blinded to patient characteristics, thoroughly examined all detailed clinical records to ensure the precision and reliability of the reported events. The adjudication process was carried out from June to August 2022. Diagnosis of CTEPH The primary outcome in the current study was detection rate of CTEPH during the entire follow‐up period, which was based on clinical diagnosis of CTEPH by experts at each institution according to the guidelines at the time this registry was planned and enrolled. , CTEPH was diagnosed by right heart catheterization results and impaired pulmonary perfusion due to the presence of organized thrombi. At all 31 participating institutions, pulmonary perfusion scintigraphy was feasible. The patients received follow‐up evaluations for as long as possible at these 31 participating institutions, during which pulmonary perfusion scintigraphy and echocardiography evaluations were conducted at the discretion of the attending physician. Additionally, right heart catheterization was performed as needed. The diagnostic criteria for CTEPH by right heart catheterization were mean pulmonary arterial pressure (mPAP) ≥25 mm Hg and pulmonary capillary wedge pressure ≤15 mm Hg, in accordance with the guidelines at the time of designing the present registry. , The organic thrombi and abnormal pulmonary perfusion were diagnosed by expert radiologists and cardiologists at each institution using perfusion pulmonary scintigraphy, pulmonary angiography, and contrast‐enhanced pulmonary computed tomography. Only patients with confirmed symptomatic acute VTE were enrolled into the COMMAND VTE Registry‐2. Therefore, patients with CTEPH with no acute thrombus at all were excluded at screening. On the other hand, patients with CTEPH whose discovery was triggered by the development of a new acute PE (acute on chronic PE) were included in this registry. Statistical Analysis Categorical variables were expressed as frequencies and percentages. Continuous variables were described using either the mean and SD or the median and interquartile range, depending on their distribution. χ 2 or Fisher exact tests were utilized to compare categorical variables, while Student t test or the Wilcoxon rank‐sum test was used for continuous variables, depending on their distributions. The Kaplan–Meier method was applied to assess time‐to‐event data related to the development of CTEPH. In the current study, we divided the study population into 2 groups according to the development of CTEPH during the follow‐up period (CTEPH group and non‐CTEPH group), and compared clinical characteristics at baseline between the 2 groups. In addition, we investigated the risk factors of CTEPH using the multivariable Cox proportional hazard model. The potential variables included in the multivariable analysis were selected based on P values <0.05 in the univariate analysis (women, days from symptom onset to diagnosis, hypoxemia, right ventricular load on echocardiography, and/or computed tomography, D‐dimer, unprovoked PE, and active cancer). To account for the effects of mortality on the nonfatal outcomes during the follow‐up, we constructed a Fine and Gray's subdistribution hazard model with all‐cause mortality as a competing risk. Proportional hazard assumptions for the primary variables and the risk‐adjusting variables were assessed using plots of log (time) versus log [−log (survival)], stratified by the variable. The assumptions were generally acceptable for all the primary variables and risk‐adjusting variables. Those variables with missing values of 20% or more were not selected, even if P values for the variables were <0.05 in the univariate analysis. Statistical significance was defined as a 2‐sided P value <0.05. Analysis was conducted using the SPSS software package (IBM Japan, Tokyo), version 29 and R version 4.3.3.
The COMMAND VTE Registry‐2 is a multicenter, retrospective cohort study initiated by physicians, which enrolled consecutive patients diagnosed with acute symptomatic VTE confirmed by imaging examinations or autopsy from 31 centers in Japan between January 2015 and August 2020, following the introduction of DOACs for VTE treatment in Japan. Detailed information on the registry's design has been previously documented. Hospital databases were queried for clinical diagnoses and/or imaging examinations, and we included consecutive patients meeting the criteria for acute symptomatic VTE diagnosis within 31 days of symptom onset throughout the study duration. The study protocol received approval from the appropriate review boards or ethics committees at all 31 participating centers. Written informed consent from individual patients was not required, because we utilized clinical data obtained during routine clinical care. Moreover, none of the patients declined participation when contacted for follow‐up, and opt‐out forms were available on each institution's website. This approach was consistent with the epidemiological study guidelines issued by the Ministry of Health, Labor, and Welfare in Japan.
We examined the incidence of detection and risk factors of CTEPH among patients enrolled in the registry who were confirmed to have acute PE.
Patient characteristic data were extracted from medical records or hospital databases based on predefined criteria, using an electronic case report form within a web‐based database system. The index time was defined as the time of acute PE diagnosis, and the end of follow‐up was defined as the time of death, loss to follow‐up, or the time of the last data collection at the end of the study period. The patient characteristics and clinical data were collected at the time of VTE diagnosis. Data entry was conducted by VTE specialists at each institution, with automatic checks for missing or conflicting entries and values outside the anticipated range. Further validation checks were carried out at the central registry office. After confirmation of diagnosis of CTEPH by the registry office, for all cases of CTEPH, the additional information on hemodynamics, the course of respiratory distress, and the outpatient follow‐up status for patients with CTEPH were collected by re‐evaluating the images and clinical course at each institution. Hypoxemia was characterized by an arterial oxygen partial pressure <60 mm Hg or a hemoglobin oxygen saturation percentage <90%. Right heart load was defined as the existence of right ventricular dilation or estimated systolic pulmonary arterial pressure of ≥40 mm Hg by echocardiography, or presence of enlarged right ventricular findings (right ventricular diameter/left ventricular diameter ≥0.9) on computed tomography. The detailed definitions of other patient characteristics are provided in Data . Follow‐up information was collected mainly by medical records review. If needed, supplementary details were obtained via communication with patients, their family members, and/or referring physicians through telephone and/or correspondence. The last round of data collection for follow‐up events took place from September 2021 to April 2022. An independent clinical events committee (Data ), blinded to patient characteristics, thoroughly examined all detailed clinical records to ensure the precision and reliability of the reported events. The adjudication process was carried out from June to August 2022.
CTEPH The primary outcome in the current study was detection rate of CTEPH during the entire follow‐up period, which was based on clinical diagnosis of CTEPH by experts at each institution according to the guidelines at the time this registry was planned and enrolled. , CTEPH was diagnosed by right heart catheterization results and impaired pulmonary perfusion due to the presence of organized thrombi. At all 31 participating institutions, pulmonary perfusion scintigraphy was feasible. The patients received follow‐up evaluations for as long as possible at these 31 participating institutions, during which pulmonary perfusion scintigraphy and echocardiography evaluations were conducted at the discretion of the attending physician. Additionally, right heart catheterization was performed as needed. The diagnostic criteria for CTEPH by right heart catheterization were mean pulmonary arterial pressure (mPAP) ≥25 mm Hg and pulmonary capillary wedge pressure ≤15 mm Hg, in accordance with the guidelines at the time of designing the present registry. , The organic thrombi and abnormal pulmonary perfusion were diagnosed by expert radiologists and cardiologists at each institution using perfusion pulmonary scintigraphy, pulmonary angiography, and contrast‐enhanced pulmonary computed tomography. Only patients with confirmed symptomatic acute VTE were enrolled into the COMMAND VTE Registry‐2. Therefore, patients with CTEPH with no acute thrombus at all were excluded at screening. On the other hand, patients with CTEPH whose discovery was triggered by the development of a new acute PE (acute on chronic PE) were included in this registry.
Categorical variables were expressed as frequencies and percentages. Continuous variables were described using either the mean and SD or the median and interquartile range, depending on their distribution. χ 2 or Fisher exact tests were utilized to compare categorical variables, while Student t test or the Wilcoxon rank‐sum test was used for continuous variables, depending on their distributions. The Kaplan–Meier method was applied to assess time‐to‐event data related to the development of CTEPH. In the current study, we divided the study population into 2 groups according to the development of CTEPH during the follow‐up period (CTEPH group and non‐CTEPH group), and compared clinical characteristics at baseline between the 2 groups. In addition, we investigated the risk factors of CTEPH using the multivariable Cox proportional hazard model. The potential variables included in the multivariable analysis were selected based on P values <0.05 in the univariate analysis (women, days from symptom onset to diagnosis, hypoxemia, right ventricular load on echocardiography, and/or computed tomography, D‐dimer, unprovoked PE, and active cancer). To account for the effects of mortality on the nonfatal outcomes during the follow‐up, we constructed a Fine and Gray's subdistribution hazard model with all‐cause mortality as a competing risk. Proportional hazard assumptions for the primary variables and the risk‐adjusting variables were assessed using plots of log (time) versus log [−log (survival)], stratified by the variable. The assumptions were generally acceptable for all the primary variables and risk‐adjusting variables. Those variables with missing values of 20% or more were not selected, even if P values for the variables were <0.05 in the univariate analysis. Statistical significance was defined as a 2‐sided P value <0.05. Analysis was conducted using the SPSS software package (IBM Japan, Tokyo), version 29 and R version 4.3.3.
Study Patients and Detection of CTEPH After the VTE specialists at each institution screened 51313 patients with suspected VTE for eligibility, a total of 5197 patients with acute symptomatic VTE were enrolled in this registry (Figure ). After excluding 2410 patients without acute PE, the current study population consisted of 2787 patients with acute PE and the median follow‐up period was 747 (interquartile range: 221–1383) days. Among the 2787 patients with acute PE, 48 CTEPH were identified during follow‐up. The cumulative detection rate (95% CI) of development of CTEPH was 1.0 (0.6–1.4)% at 180 days, 1.7 (1.1–2.3)% at 1 year, 2.0 (1.4–2.6)% at 2 years, and 2.3 (1.7–2.9)% at 3 years (Figure ). The mPAP was 34 [27–39] mm Hg, and the pulmonary vascular resistance was 4.9 [3.7–7.6] Wood units. Images of a representative case are presented in Figure . Patient Characteristics and Treatment Strategies Patient characteristics, laboratory tests at diagnosis, and antithrombic treatment strategies are shown in Table . The mean age was 66.6±15.4 years, and 1578 (56.6%) patients were women. In the entire cohort of patients with PE, during the follow‐up, anticoagulation was discontinued in 1039 individuals. Specifically, anticoagulation was stopped within 90 days in 245 cases, within 180 days in 505 cases, and within 365 days in 761 cases. We observed pulmonary embolism recurrence in 105 individuals. During the follow‐up period, 48 patients were detected with CTEPH (CTEPH group). Compared with patients who were not diagnosed with CTEPH (non‐CTEPH group), the CTEPH group was more likely to be women (77.1% versus 56.3%, P =0.004). The CTEPH group had a significantly higher prevalence of hypoxemia (70.8% versus 44.0%, P <0.001) and right heart load on echocardiography and/or computed tomography at diagnosis (91.7% versus 40.5%, P <0.001) than the non‐CTEPH group. The days from onset to diagnosis were significantly longer in the CTEPH group than in the non‐CTEPH group. In terms of the risk of VTE, unprovoked PE was higher (79.2% versus 40.2%), and active cancer risk was lower (6.3% versus 28.0%) in the CTEPH group than in the non‐CTEPH group. The CTEPH group had lower D‐dimer values (6.0 [3.9–10.9] versus 11.4 [5.8–22.6] μg/mL, P <0.001) and higher B‐type natriuretic peptide (407.1 [252.6–784.0] versus 59.1 [20.8–191.8] pg/mL, P <0.001) and N‐terminal pro‐B‐type natriuretic peptide values (2172.0 [1050.5–4033.8] versus 439.5 [112.0–1837.5] pg/mL, P <0.001) at diagnosis than the non‐CTEPH group. Troponin T and I values were not significantly different between the 2 groups. The choice of antithrombotic therapy was not significantly different between the 2 groups, but the period until the initial discontinuation of anticoagulation was significantly longer in the CTEPH group than in the non‐CTEPH group (1022 [646–1592] versus 349 [104–962] days, P <0.001). Clinical Course of Patients With CTEPH Among 48 patients with CTEPH, 47 (97.9%) were diagnosed with CTEPH within 3 years after acute PE. The majority of patients underwent comprehensive follow‐up assessments, including blood tests, echocardiograms, pulmonary perfusion scintigraphy, and other diagnostic evaluations, at the initial institutions. The diagnosis of CTEPH was subsequently established within the same institutions. Two cases were referred to other institutions during the course and received follow‐up care there. The time intervals from the index acute PE to the referral were 195 days and 214 days, respectively. These 2 cases were subsequently referred back to the initial institutions due to a recurrence of dyspnea, leading to the diagnosis of CTEPH. Among the 48 cases, 24 cases had persistent dyspnea from index acute PE, while the remaining 24 cases experienced the recurrence or onset of dyspnea during the course. The duration from acute PE to the recurrence or onset of dyspnea was 109 [32–473] days. At the 3‐month mark from the index acute PE, 34 cases exhibited symptoms of dyspnea. Two patients had anticoagulation discontinued before the onset of CTEPH (214 days, 247 days). Two patients experienced recurrent VTE events before the onset of CTEPH. The 2 patients who experienced recurrent VTE events were different from the 2 patients for whom anticoagulation was discontinued. Balloon pulmonary angioplasty was performed in 26 cases, and pulmonary endarterectomy was performed in 3 cases. Seven of the total 48 patients with CTEPH died, but no death was directly related to CTEPH itself. The causes of death for the 7 patients with CTEPH were malignant disease in 4 cases, infection in 1 case, chronic obstructive pulmonary disease in 1 case, and unknown in 1 case. Overall survival rate of the patients who developed CTEPH after acute PE was 95.7% at 1 year, 93.5% at 2 years, 88.4% at 3 years, 85.0% at 4 years, 85.0% at 5 years, and 72.9% at 6 years (Figure ). Risk Factors of CTEPH The independent risk factors for CTEPH by multivariable Cox regression analysis included women (adjusted hazard ratio [HR] 2.09 [95% CI, 1.05–4.14]; P =0.04), longer interval from symptom onset to diagnosis (each 1 day, adjusted HR 1.04 [95% CI, 1.01–1.07]; P =0.01), hypoxemia at diagnosis (adjusted HR 2.52 [95% CI, 1.26–5.04]; P =0.009), right heart load on echocardiography and/or computed tomography (adjusted HR 9.28 [95% CI, 3.19–27.00]; P <0.001), lower D‐dimer level (each 1 μg/mL, adjusted HR 0.96 [95% CI, 0.92–0.99]; P =0.02), and unprovoked PE (adjusted HR 2.77 [95% CI, 1.22–6.30]; P =0.02) (Table ). The results of the multivariable model with all‐cause mortality as a competing risk were generally similar; however, D‐dimer did not show a statistically significant difference (Table ).
CTEPH After the VTE specialists at each institution screened 51313 patients with suspected VTE for eligibility, a total of 5197 patients with acute symptomatic VTE were enrolled in this registry (Figure ). After excluding 2410 patients without acute PE, the current study population consisted of 2787 patients with acute PE and the median follow‐up period was 747 (interquartile range: 221–1383) days. Among the 2787 patients with acute PE, 48 CTEPH were identified during follow‐up. The cumulative detection rate (95% CI) of development of CTEPH was 1.0 (0.6–1.4)% at 180 days, 1.7 (1.1–2.3)% at 1 year, 2.0 (1.4–2.6)% at 2 years, and 2.3 (1.7–2.9)% at 3 years (Figure ). The mPAP was 34 [27–39] mm Hg, and the pulmonary vascular resistance was 4.9 [3.7–7.6] Wood units. Images of a representative case are presented in Figure .
Patient characteristics, laboratory tests at diagnosis, and antithrombic treatment strategies are shown in Table . The mean age was 66.6±15.4 years, and 1578 (56.6%) patients were women. In the entire cohort of patients with PE, during the follow‐up, anticoagulation was discontinued in 1039 individuals. Specifically, anticoagulation was stopped within 90 days in 245 cases, within 180 days in 505 cases, and within 365 days in 761 cases. We observed pulmonary embolism recurrence in 105 individuals. During the follow‐up period, 48 patients were detected with CTEPH (CTEPH group). Compared with patients who were not diagnosed with CTEPH (non‐CTEPH group), the CTEPH group was more likely to be women (77.1% versus 56.3%, P =0.004). The CTEPH group had a significantly higher prevalence of hypoxemia (70.8% versus 44.0%, P <0.001) and right heart load on echocardiography and/or computed tomography at diagnosis (91.7% versus 40.5%, P <0.001) than the non‐CTEPH group. The days from onset to diagnosis were significantly longer in the CTEPH group than in the non‐CTEPH group. In terms of the risk of VTE, unprovoked PE was higher (79.2% versus 40.2%), and active cancer risk was lower (6.3% versus 28.0%) in the CTEPH group than in the non‐CTEPH group. The CTEPH group had lower D‐dimer values (6.0 [3.9–10.9] versus 11.4 [5.8–22.6] μg/mL, P <0.001) and higher B‐type natriuretic peptide (407.1 [252.6–784.0] versus 59.1 [20.8–191.8] pg/mL, P <0.001) and N‐terminal pro‐B‐type natriuretic peptide values (2172.0 [1050.5–4033.8] versus 439.5 [112.0–1837.5] pg/mL, P <0.001) at diagnosis than the non‐CTEPH group. Troponin T and I values were not significantly different between the 2 groups. The choice of antithrombotic therapy was not significantly different between the 2 groups, but the period until the initial discontinuation of anticoagulation was significantly longer in the CTEPH group than in the non‐CTEPH group (1022 [646–1592] versus 349 [104–962] days, P <0.001).
CTEPH Among 48 patients with CTEPH, 47 (97.9%) were diagnosed with CTEPH within 3 years after acute PE. The majority of patients underwent comprehensive follow‐up assessments, including blood tests, echocardiograms, pulmonary perfusion scintigraphy, and other diagnostic evaluations, at the initial institutions. The diagnosis of CTEPH was subsequently established within the same institutions. Two cases were referred to other institutions during the course and received follow‐up care there. The time intervals from the index acute PE to the referral were 195 days and 214 days, respectively. These 2 cases were subsequently referred back to the initial institutions due to a recurrence of dyspnea, leading to the diagnosis of CTEPH. Among the 48 cases, 24 cases had persistent dyspnea from index acute PE, while the remaining 24 cases experienced the recurrence or onset of dyspnea during the course. The duration from acute PE to the recurrence or onset of dyspnea was 109 [32–473] days. At the 3‐month mark from the index acute PE, 34 cases exhibited symptoms of dyspnea. Two patients had anticoagulation discontinued before the onset of CTEPH (214 days, 247 days). Two patients experienced recurrent VTE events before the onset of CTEPH. The 2 patients who experienced recurrent VTE events were different from the 2 patients for whom anticoagulation was discontinued. Balloon pulmonary angioplasty was performed in 26 cases, and pulmonary endarterectomy was performed in 3 cases. Seven of the total 48 patients with CTEPH died, but no death was directly related to CTEPH itself. The causes of death for the 7 patients with CTEPH were malignant disease in 4 cases, infection in 1 case, chronic obstructive pulmonary disease in 1 case, and unknown in 1 case. Overall survival rate of the patients who developed CTEPH after acute PE was 95.7% at 1 year, 93.5% at 2 years, 88.4% at 3 years, 85.0% at 4 years, 85.0% at 5 years, and 72.9% at 6 years (Figure ).
CTEPH The independent risk factors for CTEPH by multivariable Cox regression analysis included women (adjusted hazard ratio [HR] 2.09 [95% CI, 1.05–4.14]; P =0.04), longer interval from symptom onset to diagnosis (each 1 day, adjusted HR 1.04 [95% CI, 1.01–1.07]; P =0.01), hypoxemia at diagnosis (adjusted HR 2.52 [95% CI, 1.26–5.04]; P =0.009), right heart load on echocardiography and/or computed tomography (adjusted HR 9.28 [95% CI, 3.19–27.00]; P <0.001), lower D‐dimer level (each 1 μg/mL, adjusted HR 0.96 [95% CI, 0.92–0.99]; P =0.02), and unprovoked PE (adjusted HR 2.77 [95% CI, 1.22–6.30]; P =0.02) (Table ). The results of the multivariable model with all‐cause mortality as a competing risk were generally similar; however, D‐dimer did not show a statistically significant difference (Table ).
The main findings of this study were as follows. First, the cumulative detection of CTEPH after acute PE in routine clinical practice in the DOAC era was 2.3% at 3 years. Second, women, longer interval from symptom onset to diagnosis, hypoxemia at diagnosis, right heart load, lower D‐dimer level, and unprovoked PE were independently associated with diagnosis of CTEPH. The treatment strategies were not significantly associated with diagnosis of CTEPH. This study examined the incidence of diagnosis of CTEPH from one of the largest VTE registries with longest follow‐up in the DOAC era. Therefore, our report is important in clarifying the detection rate of CTEPH after acute PE in real clinical practice in the DOAC era. When considering the incidence of CTEPH, the accuracy of the diagnosis of the acute PE event and CTEPH is crucial. The data of the COMMAND VTE Registry‐2 were collected by VTE specialists only from expert centers in Japan. Therefore, the data were reliable compared with studies from insurance databases using disease codes. In this study, >80% of patients with acute PE were treated with DOACs. This study revealed that even in the DOAC era, the incidence of detection of CTEPH was generally similar to those in the previous reports in the warfarin era, , , , , , , suggesting the importance of development of CTEPH after acute PE even in the DOAC era. After the introduction of DOACs for VTE, DOACs have become widely used in daily clinical practice, which could have a benefit of potentially lower bleeding risk than warfarin in the treatment course of acute PE. , , , , , , In addition, DOACs might be more effective in terms of thrombus resolution compared with warfarin, which could have a beneficial effect in preventing development of CTEPH after acute PE. However, evaluating the effect of different types of anticoagulation therapy on development of CTEPH in the randomized control trials was difficult due to the low event rate of development of CTEPH. Therefore, our results are useful in providing clinicians some insight into the issue of development of CTEPH. In the FOCUS study, a prospective follow‐up study of acute PE in the DOAC era, the incidence of CTEPH was confirmed to be 2.3% over ≈2 years. The FOCUS study revealed that post‐PE impairment (the deterioration of right heart function and pulmonary hypertension assessed by echocardiography, clinical, functional, and laboratory parameters) was associated with the development of CTEPH during follow‐up. However, since only 16 out of 1017 patients with acute PE developed CTEPH, individual factors contributing to its development were not examined. Our results, showing a 2.3% detection rate over 3 years, were similar to those of the FOCUS study. Moreover, with 48 cases of diagnosed CTEPH, it was possible to examine risk factors. In this regard, our study, although a retrospective study, may complement FOCUS studies on the incidence and diagnosis of CTEPH in the DOAC era. This study revealed several important potential risk factors for the development of CTEPH including women, longer interval from symptom onset to diagnosis, hypoxemia at diagnosis, right heart load, lower D‐dimer level, and unprovoked PE. The prevalence of CTEPH worldwide does not differ by sex, whereas women were previously reported to be more prevalent among patients with CTEPH in Japan. , In this study, at the time of diagnosis of CTEPH, all other potential causes such as connective tissue diseases were ruled out. Thus, the likelihood of conditions such as pulmonary arterial hypertension being diagnosed as CTEPH is extremely low. Therefore, while the cause of the observed sex difference may be attributed to racial disparities, a definitive reason has not been identified. “Longer interval from symptom onset to diagnosis” suggested that delayed diagnosis could increase the risk of development of CTEPH. Thrombi in acute PE that have persisted since onset become less responsive to anticoagulant therapy. A previous report suggested that the majority of thrombi that persisted 1 month after the onset of acute PE also remained present even a year later. “Lower D‐dimer value” evokes the possibility of acute on chronic PE. In other words, there is a possibility that in cases in which pre‐existing organized thrombi were already present in the pulmonary arteries, the addition of a new thromboembolism (even if the volume of fresh thrombus was relatively limited) may lead to the manifestation of symptoms, ultimately resulting in the diagnosis of acute pulmonary embolism (index PE). These cases should be considered as acute on chronic PE, and they were in a state close to CTEPH at the time of the index PE. On the other hand, since this study is retrospective, information on clinical course and follow‐up imaging was available. Therefore, the likelihood of mistakenly enrolling patients with pure CTEPH as acute PE was extremely low. “Extent of right heart load or the severity of hypoxia” as the risk factors for the diagnosis of CTEPH despite “lower D‐dimer value” might suggest the presence of pre‐existing organized thrombi in the pulmonary arteries. An alternative explanation for the lower D‐dimer levels could be attributed to the failure to capture the peak values, possibly due to the considerable time elapsed since the onset of acute PE. Note that in the subdistribution hazard model for CTEPH diagnosis with all‐cause mortality as a competing risk, the D‐dimer levels did not show statistical significance, and therefore, this interpretation should be approached with caution. The reason that unprovoked PE has been indicated as a risk factor cannot be excluded as being due to survivor bias. Patients with PE caused by active cancer have a poor prognosis, and it is presumed that there were patients who could not survive until developing CTEPH. Active cancer is considered a provoked PE, and it is possible that unprovoked PE that did not include active cancer could show a higher risk of CTEPH. In this registry, a total of 692 participants (24.8%) died during the study period. The median time to all‐cause mortality was 163 days. Of these, 403 (58.2%) deaths were due to malignancy. However, unprovoked PE was an independent risk factor even in a model with all‐cause mortality as a competing risk (Table ). These risk factors might be useful for risk stratification during a long‐term follow‐up period after acute PE. Patients with multiple overlapping risk factors may warrant close follow‐up by specialists. In addition, it might also be important to notify clinicians of the need to be aware of the potential risk of development CTEPH after acute PE. Our results suggest that the delay in diagnosing and treating acute PE may have a stronger impact on the development of CTEPH than the choice of treatment strategy. In the era of DOACs, early detection of PE and raising awareness about the disease concept of PE may be crucial in reducing the onset of CTEPH. If patients with CTEPH with mPAP exceeding 30 mm Hg did not receive appropriate treatment, the 5‐year survival rate was <50%. However, during the entire follow‐up period of this study, there were no patients with CTEPH who died directly due to CTEPH itself. This may be attributed to factors such as good access to treatments, including balloon pulmonary angioplasty, in Japan. On the other hand, more than half of the deceased patients with CTEPH died due to malignancies. Therefore, in an environment where CTEPH is adequately treated, the most critical aspect to watch for during follow‐up might be the emergence of malignancies. Limitations This study has several limitations. First, this study was a retrospective observational study. Therefore, the selection of treatment strategies, timing and method of follow‐up, and duration of anticoagulation therapy were left to the discretion of the attending physicians. In addition, detection of CTEPH was based on clinical diagnosis of CTEPH by experts at each institution. Thus, there could be some underdiagnosis of CTEPH. However, we believe it to be sufficiently useful data to demonstrate the incidence of CTEPH detected after acute PE in routine clinical practice in the era of DOACs. Second, demographics, practice protocols, and clinical results among patients with VTE in Japan might exhibit disparities compared with those observed elsewhere. Third, we followed the current Japanese guidelines for the hemodynamic definitions for CTEPH as an mPAP ≥25 mm Hg and a pulmonary capillary wedge pressure ≤15 mm Hg by right heart catheterization, while some other guidelines adopted an mPAP >20 mm Hg as the definition of pulmonary hypertension. , Fourth, although we carefully evaluated the patients with CTEPH, including their imaging examinations and clinical course, to avoid the misidentification of CTEPH as acute PE, we could not completely rule out the possibility of such a misidentification. Fifth, The COMMAND VTE Registry‐2 was conducted in the DOAC era, making it impossible to directly compare the CTEPH diagnosis rate with the pre‐DOAC era. Additionally, the choice of anticoagulant therapy also reflects the DOAC era. Sixth, the factors included in the multivariate analysis were selected based on the P values from the univariate analysis due to insufficient existing evidence. However, this approach is data‐driven and may only apply to the current data set, so validation with other data sets is necessary.
This study has several limitations. First, this study was a retrospective observational study. Therefore, the selection of treatment strategies, timing and method of follow‐up, and duration of anticoagulation therapy were left to the discretion of the attending physicians. In addition, detection of CTEPH was based on clinical diagnosis of CTEPH by experts at each institution. Thus, there could be some underdiagnosis of CTEPH. However, we believe it to be sufficiently useful data to demonstrate the incidence of CTEPH detected after acute PE in routine clinical practice in the era of DOACs. Second, demographics, practice protocols, and clinical results among patients with VTE in Japan might exhibit disparities compared with those observed elsewhere. Third, we followed the current Japanese guidelines for the hemodynamic definitions for CTEPH as an mPAP ≥25 mm Hg and a pulmonary capillary wedge pressure ≤15 mm Hg by right heart catheterization, while some other guidelines adopted an mPAP >20 mm Hg as the definition of pulmonary hypertension. , Fourth, although we carefully evaluated the patients with CTEPH, including their imaging examinations and clinical course, to avoid the misidentification of CTEPH as acute PE, we could not completely rule out the possibility of such a misidentification. Fifth, The COMMAND VTE Registry‐2 was conducted in the DOAC era, making it impossible to directly compare the CTEPH diagnosis rate with the pre‐DOAC era. Additionally, the choice of anticoagulant therapy also reflects the DOAC era. Sixth, the factors included in the multivariate analysis were selected based on the P values from the univariate analysis due to insufficient existing evidence. However, this approach is data‐driven and may only apply to the current data set, so validation with other data sets is necessary.
In this large real‐world VTE registry in the DOAC era, the cumulative detection of CTEPH after acute PE was 2.3% at 3 years. Several independent risk factors for CTEPH were identified, which could be useful for screening a high‐risk population for CTEPH after acute PE.
Part of the support for the COMMAND VTE Registry‐2 was provided by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number JP 21K16022. However, the research funding did not influence the study's design, implementation, data collection, analysis, interpretation, or manuscript preparation, review, or approval.
Dr N. Ikeda received lecture fees from Bayer Healthcare, Bristol‐Myers Squibb, and Daiichi‐Sankyo. Dr Yamashita received lecture fees from Bayer Healthcare, Bristol‐Myers Squibb, Pfizer, and Daiichi‐Sankyo, and grant support from Bayer Healthcare and Daiichi‐Sankyo. Dr Morimoto reports lecture fees from Bristol‐Myers Squibb, Daiichi Sankyo, Japan Lifeline, Kowa, Kyocera, Novartis, and Toray; manuscript fees from Bristol‐Myers Squibb and Kowa; and advisory board for Sanofi. Dr Kaneda received lecture fees from Bristol‐Myers Squibb, Pfizer, and Daiichi‐Sankyo. Dr Nishimoto received lecture fees from Bayer Healthcare, Bristol‐Myers Squibb, Pfizer, and Daiichi‐Sankyo. Dr S. Ikeda received lecture fees from Bayer Healthcare, Bristol‐Myers Squibb, and Daiichi‐Sankyo. Dr Ogihara received a research fund from Bayer Healthcare and lecture fees from Bayer Healthcare, Bristol‐Myers Squibb, and Daiichi‐Sankyo. Dr Koitabashi received lecture fees from Bayer Healthcare and grant support from Pfizer. The remaining authors have no disclosures to report.
Data S1 Table S1 Figure S1 References [ , , , ]
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Root Niches of Blueberry Imprint Increasing Bacterial-Fungal Interkingdom Interactions along the Soil-Rhizosphere-Root Continuum | b0d3f4d6-2ff3-4121-ba18-1c27dbab8911 | 10269492 | Microbiology[mh] | Plant root-associated microbiomes are essential to the health and productivity of host plants, providing multiple benefits to host plants, including nutrient uptake, growth promotion, resistance to pathogens, and stress tolerance ( , ). Furthermore, microbiomes can contribute to soil health and environmental sustainability by promoting soil nutrient turnover and maintaining soil fertility, such as by facilitating carbon and nitrogen cycling in ecosystems by decomposing soil organic matter and fixing atmospheric nitrogen ( ). Thus, rational utilization of root-associated microbiomes is increasingly considered for sustainable agricultural production ( ). Moreover, the antagonistic, competitive, or mutualistic interactions between the microbes activate the energy flow and nutrient cycles in underground microecosystems, playing a basic role in shaping and structuring complex microbial networks ( ). By providing novel metabolic capabilities to their microbial associates, host plants contribute to niche-specialized inhabitant adaptation, which can influence soil function and plant productivity ( ). Therefore, understanding the taxonomic and functional components and the interactions among microbial communities along the soil-rhizosphere-root continuum is critical for the precise manipulation of beneficial microbiota to achieve sustainable ecosystem functions ( , ). Blueberry ( Vaccinium spp.) is an agricultural crop cultivated worldwide for its high economic value. Its fruits contain high amounts of phenols and anthocyanins, which have beneficial effects in maintaining blood sugar levels, reducing oxidative stress, and preventing cardiovascular diseases, as well as anti-inflammatory, antimicrobial, and antitumor activities ( , ). Although the shallow root systems and sparse root hairs limit the efficient uptake of water and nutrients, blueberry plants are well adapted to acidic soil conditions ( , ). This adaptation could be associated with the establishment of beneficial interactions with soil microorganisms ( ). Thus, revealing the contribution of microorganisms in the adaptation of blueberry to acidic soils could provide a basis for harnessing microorganisms to promote the adaptation of blueberry to various soil conditions to improve yield and fruit quality and reduce chemical inputs. A recent study showed that blueberry rhizosphere-isolated strains with auxin production, phosphorus solubilization, and nitrogen fixation capacities can increase the germination rate of blueberry seeds, which is considered helpful in promoting the growth of blueberry ( ). In addition, ericoid mycorrhizal (ERM) fungi can form symbiotic relationships with blueberry roots that can play a critical role in the survival of plants growing in habitats with low soil pH and slow organic matter turnover by secreting a broad range of enzymes, including cellulases, proteases, polyphenol oxidases, and phosphatases, which decompose complex organic compounds and enhance the fitness and nutrient acquisition of the host plant ( ). Several studies have focused on the impact of host cultivars ( ), differential habitats ( , , ), and agricultural practices ( ), but further exploration of the interactions of blueberry root-associated microorganisms along the soil-rhizosphere-root continuum is needed. Plant health and productivity are intimately associated with the microbial communities that inhabit the soil-rhizosphere-root continuum ( ). As influenced by plant root activity, the diversity and composition of the root-associated microbiome transition from the external to the internal part of the plant root system, shaping specific plant root compartment niches in terms of the bulk soil, the rhizosphere, the rhizoplane, and the endosphere ( , ). The bulk soil, which has high microbial diversity, serves as a reservoir, providing specific microorganisms for each compartment niche. The rhizosphere and rhizoplane microbial communities are shaped by the metabolic activities of plant roots, and a subset of rhizosphere microbes penetrate the plant roots and colonize the endosphere, which is subject to the plant immune system. Ultimately, each compartment niche develops a microbial community with distinctive structural characteristics ( ). The diverse microbial communities in each ecological niche of the root system are influenced by complex factors associated with the assembly process. Thus, the assembly process provides important insights for discovering the differences in community composition, and quantifying these processes is vital to elucidate the mechanisms governing microbial community structure ( ). Microbes can be inherited by vertical transmission from seeds and can also colonize various plant compartment niches via air, soil, and nearby plants, forming a dynamic community in response to the combined effects of the host plant and environmental factors ( ). Plant microbiome assembly develops with plant growth and is influenced by deterministic and stochastic processes, such as biotic- and abiotic-factor-mediated selection or random drift and dispersal events, respectively ( , ). The assembly process of plant root-associated microbes is recruited through a two-step selection mode and is driven by many factors, such as edaphic factors and plant root metabolites and exudates ( , ). However, we still lack a comprehensive understanding of the assembly processes of the blueberry root-associated microbiome, which is intimately related to the network of plant-microbe interactions. Microbial co-occurrence network analysis allows the characterization of potential microbial interactions in various habitats ( , ), specifically to visualize the response patterns of taxonomic groups to various plant compartment niches and to identify keystone microbes that significantly shape community composition ( , ). For instance, the average degree and modularity of topological characteristics present the connectivity and complexity of members in co-occurrence networks ( ). The interactions between bacteria and fungi, with dynamic changes, are intimately related to plant growth and development. A recent study revealed that interactions between oomycetes, fungi, and bacteria can contribute greatly to plant survival and that bacterial communities play an essential role in maintaining a balanced interkingdom network by protecting plants against pathogens ( ). Furthermore, the interkingdom interactions between bacteria and fungi clearly shift during different stages of plant development, and microbial network hubs play a crucial role in maintaining plant fitness and nutrition during plant growth ( ). Therefore, specific microbes that inhabit different compartment niches and may have important ecological functions in the mutually beneficial symbiotic relationship between plants and microbes can be tapped via a co-occurrence network. In this regard, we aimed to explore the variable characteristics of the blueberry root-associated microbiome along the soil-rhizosphere-root continuum, as well as microbial assembly processes and co-occurrence networks. The diversity and community composition of the bacterial and fungal communities in the bulk soil, rhizosphere soil, and root endosphere were explored in these three root compartment niches of three host cultivars, rabbiteye blueberry, northern highbush blueberry, and southern highbush blueberry. We hypothesized that the interkingdom interactions of bacterial and fungal communities would increase along the soil-rhizosphere-root continuum. Hence, our objectives were to (i) determine how blueberry root-associated microbial community composition differs across root compartment niches, (ii) elucidate the assembly processes in each compartment niche, and (iii) explore the interkingdom network patterns along the soil-rhizosphere-root continuum.
Diversity and abundance of root-associated microbial communities. The Chao1 and Shannon indices of the bacterial and fungal communities were significantly higher in the bulk soil than in the rhizosphere soil and root endosphere, except for the Chao1 index of the fungal community in the rhizosphere soil ( and ). The root compartment niches clearly had significant effects on the alpha diversity of the bacterial and fungal communities and showed a decreasing trend along the soil-rhizosphere-root continuum of blueberry. Nonmetric multidimensional scaling (NMDS) ordinations and two-way permutational multivariate analysis of variance (PERMANOVA) indicated that the variations in both bacterial and fungal communities were mainly explained by the root compartment niches ( R 2 = 0.564, P < 0.001; R 2 = 0.339, P < 0.001) and then by the host cultivars ( R 2 = 0.161, P < 0.001; R 2 = 0.182, P < 0.001) ( and ; Table S1 in the supplemental material). In addition, both bacterial and fungal communities were clustered into three groups, and analysis of similarity (ANOSIM) tests ( and ) showed significant differences in the taxonomic compositions of these three compartment niches. These results indicated that the compartment niches had strong effects on the diversity and abundance of bacterial and fungal communities compared to those of the host cultivars of the blueberry plants. Compositions of the root-associated microbial communities. The compositions of the bacterial and fungal communities varied among the three root compartment niches. Actinobacteria (36.7%, 35.1%, 58.6%) and Proteobacteria (31.5%, 28.0%, 28.6%) were the predominant phyla in the bacterial community composition of the three compartment niches, with Actinobacteria being more abundant in the root endosphere and Proteobacteria being more abundant in the bulk soil ( ). The root compartment niches also altered the low-abundance phyla, with Myxococcota , Gemmatimonadota , Verrucomicrobiota , and Nitrospirota being the most abundant in the bulk soil and decreasing along the soil-rhizosphere-root continuum of blueberry roots. Interestingly, the low-abundance phyla Acidobacteria , Firmicutes , and Chloroflexi were more abundant in the rhizosphere. For fungal communities, Sordariomycetes , Dothideomycetes , and Mortierellomycetes were significantly enriched in the bulk soil, with Sordariomycetes being the most abundant class, and significantly reduced in both the rhizosphere and endosphere. Archaeorhizomycetes , Tremellomycetes , and Pezizomycetes were significantly enriched in the rhizosphere, while Eurotiomycetes , Agaricomycetes , and Leotiomycetes were more abundant in the root endosphere ( ). Furthermore, the ERM fungi Helotiales (2.3%, 1.8%, and 19.0%), Chaetothyriales (1.4%, 7.2%, and 15.0%), and Sebacinales (0%, 7.1%, and 5.4%) were observed in the three compartment niches and were significantly enriched in the root endosphere (Fig. S1). Biomarkers of bacteria and fungi in the three compartment niches. The distinct taxa of the three compartment niches were evaluated by linear discriminant analysis (LDA) effect size (LEfSe) scores at the phylum, class, and order levels. A total of 33 distinct bacterial biomarkers were identified (LDA ≥ 4.0, P < 0.05), including 7, 9, and 17 biomarkers of phylum, class, and order, respectively, mainly associated with the phyla Firmicutes , Myxococcota , Actinobacteria , Chloroflexi , Gemmatimonadota , Acidobacteria , and Nitrospirota ( ; Fig. S2). A total of 20 fungal biomarkers, including 3, 4, and 13 biomarkers of phylum, class, and order, respectively, were distributed among different niches. These biomarkers were associated with the classes Mortierellomycetes , Pezizomycetes , Dothideomycetes , and Tremellomycetes ( ; Fig. S2). Assembly processes of bacterial and fungal communities. To explore the process of microbiome assembly among the various compartment niches of blueberry roots, we performed a null model analysis. Stochastic processes were the predominant drivers of both bacterial and fungal communities in the bulk soils ( ). The relative contributions of deterministic processes belonging to homogeneous selection were higher in the rhizosphere (66%) and endosphere (55%) bacterial communities, whereas higher relative contributions of stochastic processes belonging to undominated processes were observed in the rhizosphere (75%) and endosphere (65%) fungal communities ( and ; Table S2). It was clear that deterministic processes increased and stochastic processes decreased along the soil-rhizosphere-root continuum for both bacterial and fungal communities in the blueberry roots. Collectively, deterministic processes had a greater influence on the assembly processes of bacterial communities in the rhizosphere and endosphere, while stochastic processes were the dominant assembly processes of fungal communities. In particular, the assembly of bacterial communities in the rhizosphere and endosphere was more strongly dominated by deterministic processes than that of fungal communities. Bacterial-fungal community interkingdom co-occurrence networks. We further performed a co-occurrence network analysis to assess the bacterial-fungal interkingdom interactions among root compartment niches. The relative proportions of bacterial nodes and correlations increased consistently from the soils to the endosphere, while fungi showed the opposite trend. The average degree in the bacterial-fungal interkingdom co-occurrence network decreased from the bulk soil to the endosphere ( ; Table S3). In the bulk soil, the average degrees were much higher in fungal communities than in bacterial communities, with average degrees of 7.961 and 4.169, respectively (Fig. S3 and Tables S3 and S4). Bacterial-fungal interkingdom interactions were clearly high in the rhizosphere, while their proportions of positive interactions increased from the soil to the endosphere ( ; Table S6). Hence, the different compartment niches of blueberry roots markedly influenced the bacterial-fungal interkingdom network interaction patterns, and positive bacterial-fungal interkingdom interactions gradually dominated in the co-occurrence networks along the soil-rhizosphere-root continuum. Several keystone taxa with the highest node degrees were identified in the bulk soil, rhizosphere, and endosphere, which mainly belonged to the phyla Proteobacteria , Actinobacteria , Acidobacteria , and Chloroflexi in the bacterial communities (Table S7) and the classes Eurotiomycetes , Leotiomycetes , Sordariomycetes , and Agaricomycetes in the fungal communities (Table S8). Functional profiles of microbial communities in different compartment niches. The proportions of the top 10 functions in the bulk soil, rhizosphere, and endosphere were 73.62%, 91.00%, and 94.59% of the overall functionality, respectively ( ; Fig. S4 and Table S9). The bacterial community mainly performs the functions of chemoheterotrophy and aerobic chemoheterotrophy in each compartment niche, specifically in the rhizosphere and endosphere. The bacterial communities in the rhizosphere and endosphere showed stronger capacities for cellulolysis and nitrogen fixation than for aromatic compound degradation. Notably, the relative abundance of cellulolysis-associated microbes was significantly higher in the rhizosphere than in the bulk soil and endosphere ( ). The main ecological guild varied significantly among the different compartment niches; the highest relative abundance of ericoid mycorrhizae was in the root endosphere (14.1%), that of soil saprotrophs was in the rhizosphere (17.3%), and a high relative abundance of plant pathogens was in the bulk soil (12.4%) ( ). In particular, operational taxonomic unit 1602 (OTU1602) from the ecological guild of ericoid mycorrhizae was identified, and its relative abundance varied among the three cultivars ( ). The relative abundance of plant pathogens decreased along the soil-rhizosphere-root continuum from the bulk soil to the rhizosphere to the endosphere by 12.4%, 0.8%, and 0.1%, respectively.
The Chao1 and Shannon indices of the bacterial and fungal communities were significantly higher in the bulk soil than in the rhizosphere soil and root endosphere, except for the Chao1 index of the fungal community in the rhizosphere soil ( and ). The root compartment niches clearly had significant effects on the alpha diversity of the bacterial and fungal communities and showed a decreasing trend along the soil-rhizosphere-root continuum of blueberry. Nonmetric multidimensional scaling (NMDS) ordinations and two-way permutational multivariate analysis of variance (PERMANOVA) indicated that the variations in both bacterial and fungal communities were mainly explained by the root compartment niches ( R 2 = 0.564, P < 0.001; R 2 = 0.339, P < 0.001) and then by the host cultivars ( R 2 = 0.161, P < 0.001; R 2 = 0.182, P < 0.001) ( and ; Table S1 in the supplemental material). In addition, both bacterial and fungal communities were clustered into three groups, and analysis of similarity (ANOSIM) tests ( and ) showed significant differences in the taxonomic compositions of these three compartment niches. These results indicated that the compartment niches had strong effects on the diversity and abundance of bacterial and fungal communities compared to those of the host cultivars of the blueberry plants.
The compositions of the bacterial and fungal communities varied among the three root compartment niches. Actinobacteria (36.7%, 35.1%, 58.6%) and Proteobacteria (31.5%, 28.0%, 28.6%) were the predominant phyla in the bacterial community composition of the three compartment niches, with Actinobacteria being more abundant in the root endosphere and Proteobacteria being more abundant in the bulk soil ( ). The root compartment niches also altered the low-abundance phyla, with Myxococcota , Gemmatimonadota , Verrucomicrobiota , and Nitrospirota being the most abundant in the bulk soil and decreasing along the soil-rhizosphere-root continuum of blueberry roots. Interestingly, the low-abundance phyla Acidobacteria , Firmicutes , and Chloroflexi were more abundant in the rhizosphere. For fungal communities, Sordariomycetes , Dothideomycetes , and Mortierellomycetes were significantly enriched in the bulk soil, with Sordariomycetes being the most abundant class, and significantly reduced in both the rhizosphere and endosphere. Archaeorhizomycetes , Tremellomycetes , and Pezizomycetes were significantly enriched in the rhizosphere, while Eurotiomycetes , Agaricomycetes , and Leotiomycetes were more abundant in the root endosphere ( ). Furthermore, the ERM fungi Helotiales (2.3%, 1.8%, and 19.0%), Chaetothyriales (1.4%, 7.2%, and 15.0%), and Sebacinales (0%, 7.1%, and 5.4%) were observed in the three compartment niches and were significantly enriched in the root endosphere (Fig. S1).
The distinct taxa of the three compartment niches were evaluated by linear discriminant analysis (LDA) effect size (LEfSe) scores at the phylum, class, and order levels. A total of 33 distinct bacterial biomarkers were identified (LDA ≥ 4.0, P < 0.05), including 7, 9, and 17 biomarkers of phylum, class, and order, respectively, mainly associated with the phyla Firmicutes , Myxococcota , Actinobacteria , Chloroflexi , Gemmatimonadota , Acidobacteria , and Nitrospirota ( ; Fig. S2). A total of 20 fungal biomarkers, including 3, 4, and 13 biomarkers of phylum, class, and order, respectively, were distributed among different niches. These biomarkers were associated with the classes Mortierellomycetes , Pezizomycetes , Dothideomycetes , and Tremellomycetes ( ; Fig. S2).
To explore the process of microbiome assembly among the various compartment niches of blueberry roots, we performed a null model analysis. Stochastic processes were the predominant drivers of both bacterial and fungal communities in the bulk soils ( ). The relative contributions of deterministic processes belonging to homogeneous selection were higher in the rhizosphere (66%) and endosphere (55%) bacterial communities, whereas higher relative contributions of stochastic processes belonging to undominated processes were observed in the rhizosphere (75%) and endosphere (65%) fungal communities ( and ; Table S2). It was clear that deterministic processes increased and stochastic processes decreased along the soil-rhizosphere-root continuum for both bacterial and fungal communities in the blueberry roots. Collectively, deterministic processes had a greater influence on the assembly processes of bacterial communities in the rhizosphere and endosphere, while stochastic processes were the dominant assembly processes of fungal communities. In particular, the assembly of bacterial communities in the rhizosphere and endosphere was more strongly dominated by deterministic processes than that of fungal communities.
We further performed a co-occurrence network analysis to assess the bacterial-fungal interkingdom interactions among root compartment niches. The relative proportions of bacterial nodes and correlations increased consistently from the soils to the endosphere, while fungi showed the opposite trend. The average degree in the bacterial-fungal interkingdom co-occurrence network decreased from the bulk soil to the endosphere ( ; Table S3). In the bulk soil, the average degrees were much higher in fungal communities than in bacterial communities, with average degrees of 7.961 and 4.169, respectively (Fig. S3 and Tables S3 and S4). Bacterial-fungal interkingdom interactions were clearly high in the rhizosphere, while their proportions of positive interactions increased from the soil to the endosphere ( ; Table S6). Hence, the different compartment niches of blueberry roots markedly influenced the bacterial-fungal interkingdom network interaction patterns, and positive bacterial-fungal interkingdom interactions gradually dominated in the co-occurrence networks along the soil-rhizosphere-root continuum. Several keystone taxa with the highest node degrees were identified in the bulk soil, rhizosphere, and endosphere, which mainly belonged to the phyla Proteobacteria , Actinobacteria , Acidobacteria , and Chloroflexi in the bacterial communities (Table S7) and the classes Eurotiomycetes , Leotiomycetes , Sordariomycetes , and Agaricomycetes in the fungal communities (Table S8).
The proportions of the top 10 functions in the bulk soil, rhizosphere, and endosphere were 73.62%, 91.00%, and 94.59% of the overall functionality, respectively ( ; Fig. S4 and Table S9). The bacterial community mainly performs the functions of chemoheterotrophy and aerobic chemoheterotrophy in each compartment niche, specifically in the rhizosphere and endosphere. The bacterial communities in the rhizosphere and endosphere showed stronger capacities for cellulolysis and nitrogen fixation than for aromatic compound degradation. Notably, the relative abundance of cellulolysis-associated microbes was significantly higher in the rhizosphere than in the bulk soil and endosphere ( ). The main ecological guild varied significantly among the different compartment niches; the highest relative abundance of ericoid mycorrhizae was in the root endosphere (14.1%), that of soil saprotrophs was in the rhizosphere (17.3%), and a high relative abundance of plant pathogens was in the bulk soil (12.4%) ( ). In particular, operational taxonomic unit 1602 (OTU1602) from the ecological guild of ericoid mycorrhizae was identified, and its relative abundance varied among the three cultivars ( ). The relative abundance of plant pathogens decreased along the soil-rhizosphere-root continuum from the bulk soil to the rhizosphere to the endosphere by 12.4%, 0.8%, and 0.1%, respectively.
Root compartment niches shape diverse microbial communities. Different plant compartment niches harbor specific microbiomes ( , ). Our results indicated that root compartment niches dominantly shaped the root-associated microbial communities, with decreasing alpha diversity along the soil-rhizosphere-root continuum. The gradual shifts in microbial communities include enrichment and depletion processes from the surrounding soil microbiota ( ). Previous studies have shown that plants can alter microbial communities by secreting bioactive molecules, including primary metabolites and secondary metabolites, into the rhizosphere ( ). The interaction between microbial substrate uptake and plant exudative traits forms a molecular mechanism to regulate microbial communities, such as the recruitment of the colonization of bacterial communities that prefer aromatic organic acids by regulating the content of aromatic organic acids ( ). In addition to providing typical carbon and nitrogen substrates, roots actively regulate the rhizosphere microbial community by secreting specific chemicals ( ). Since microbial communities with the ability to promote growth and activate induced systemic resistance are highly tolerant of coumarins, plants can participate in shaping the rhizosphere microbiome by regulating coumarin-biosynthetic pathways ( ). The rhizosphere microbiome acts as an important inoculum reservoir and, thus, contributes to the construction of the endosphere microbial community ( ). The host immune system has a strong influence on the enrichment and depletion processes of the microbial community from the rhizosphere to the endosphere, and only a fraction of the microbiota in the rhizosphere with traits that subvert the host immune processes have the potential to colonize the endosphere ( ). Consequently, this leads to differentiation of microbial communities in various compartment niches. Furthermore, host selection effects are enhanced along the soil-rhizosphere-root continuum with the recruitment, filtration, and enrichment of microbial taxa with specific functions in different compartment niches. In contrast to environmental factors, such as fertilization practice or site, host selection dominates in shaping the assembly of microbial communities, primarily through compartment niches and then host species ( ). This was also evident in our study, where variations in the taxonomic compositions of blueberry root microbiomes were dominated by the root compartment niches rather than by the host cultivars ( ; Table S1). Studies on Zea mays , Triticum aestivum , and Hordeum vulgare show that different species have an effect on the composition of the microbiomes ( ), while different genotypes of Arabidopsis thaliana show that different host genotypes have a limited effect on the root microbiomes ( , ). Although different host plant subspecies, cultivars, and genotypes can harbor distinct microbial communities, within individual species, this effect typically appears rather weak ( , , ). Therefore, the root compartment niche is the primary driver shaping the composition of root-associated microbial communities, rather than the blueberry cultivar. The varied compartment niches affected the proportions of the root-associated microbial community composition of blueberry. Consistent with previous studies, Actinobacteria and Proteobacteria were the most abundant phyla in the bacterial community ( ), and our results showed that Actinobacteria was the dominant phylum in the endosphere. Members of Actinobacteria possess a potential suppressive effect on plant pathogens ( ), and the increased proportion in the endosphere may have been related to the selection of functions that correspond to plant health requirements. Moreover, the increased proportions of Firmicutes and Chloroflexi in the rhizosphere indicated a potential dominant function in nutrient cycling, as these microorganisms are related to carbon and nitrogen cycling ( , ). Thus, the different community compositions of each compartment niche were likely related to their functional requirements for biotic stress reduction or nutrient cycling. Similarly, the fungal communities showed compartment-specific enrichment patterns, with high proportions of Archaeorhizomycetes and Tremellomycetes in the rhizosphere and high proportions of Eurotiomycetes , Agaricomycetes , and Leotiomycetes in the endosphere ( ). Members of Archaeorhizomycetes are considered to have saprotrophic potential and are dependent on root-derived carbon compounds ( ), which may be attributed to the active root metabolism that enhances their assembly in the rhizosphere. Due to the poor root system of blueberry plants, they can be symbiotic with ERM fungi to cope with their limitations in nutrient uptake and adaptation to low soil pH ( ). Therefore, the high relative abundances of ERM fungi belonging to Eurotiomycetes , Agaricomycetes , and Leotiomycetes in the endosphere were likely to be potentially beneficial in fulfilling root nutrient requirements. Dynamic ecological roles of bacterial and fungal communities along the soil-rhizosphere-root continuum. The assembly process of root-associated microbes is influenced by many factors, such as root exudates, the plant immune system, and soil physicochemical properties. Revealing the dynamic ecological processes of plant root-associated microbiome assembly will facilitate the utilization of possible approaches to adjust the microbial community to provide beneficial functions for soil and plant health. These environmentally friendly approaches can be applied to agricultural practices to avoid excessive fertilizer additions ( , ). Previous studies have indicated that various compartment niches are driven by distinct assembly processes during the development of plants ( ). Our results showed that deterministic processes played a more significant role in the assembly of bacterial communities in the rhizosphere and endosphere than in the assembly of fungal communities. Compared with fungi, most bacteria have a narrow tolerance range for growth and are more sensitive to variations in microenvironmental responses ( , , ). The rhizosphere is a carbon-rich compartment niche as a consequence of root exudation or rhizodeposition, providing a more diverse microenvironment for microorganisms ( ). There was a significant correlation between bacterial communities and the phosphorus content of the rhizosphere soil (Fig. S5). To meet the requirement for phosphorus, plants secrete low-molecular-weight organic acids in the rhizosphere to increase phosphorus availability, while plants recruit and select for specific microbial communities with phosphorus-solubilizing capacity in the rhizosphere ( ). Therefore, it is reasonable that the metabolic activity of roots contributes to the variation in soil physicochemical properties in the microenvironment, which makes the assembly of bacterial communities more susceptible to being driven by deterministic processes. Furthermore, deterministic processes in fungal communities that gradually increased along the soil-rhizosphere-root continuum were observed. Previous studies suggest that in a relatively homogeneous natural tropical forest, fungi are more highly associated with plant phylogeny than bacteria are ( ). Simultaneously, specific fungi can form biotrophic relationships with plants ( ), particularly with the poorly developed root systems of blueberry, which can form symbiotic associations with specific fungi ( ). Therefore, this could be a response to a plant host effect, in which the plants exert a stronger selective effect on the fungal community, contributing to a progressive increase in the influence of deterministic processes from the rhizosphere to the endosphere. Rich and diverse relationships between bacteria and fungi, such as antagonistic and cooperative relationships, influence the dynamics of microbial communities ( ). Our study indicated that higher positive bacterial-fungal interkingdom interactions were observed along the soil-rhizosphere-root continuum. The positive interactions that exist between bacteria and fungi may be due to their mutualistic and commensal ecological interactions ( ). In general, recalcitrant organic matter, such as lignin and cellulose, is largely degraded by fungi and releases products like phenolic compounds and water-soluble sugars that are utilized by bacteria ( ). Additionally, there are certain bacteria that can facilitate the formation of ectomycorrhizae, colonize the surface of fungal hyphae, and benefit from the exudates of the fungi ( ). Several studies have also identified partial bacterial taxa that interact with fungi ( ). It has been suggested that the greater numberof positive relationships observed in the rhizosphere of Astragalus mongholicus implied a higher degree of cooperative interactions, which may contribute to plant resistance against abiotic and biotic stresses ( ). Host plants and root-associated microbial communities are an evolutionary unit of common interest, and root-associated microbes can regulate host root traits through belowground nutrient acquisition strategies of nutrient scavenging and nutrient mining. Plants reallocate the release of root exudates and the recruitment of beneficial microorganisms, respectively, to ultimately achieve nutrient acquisition and plant growth ( , ). Previous studies show that the synergistic interaction of arbuscular mycorrhizal fungi and nitrogen-fixing rhizobial bacteria can provide different limiting nutrients for plant growth ( ). This indicates that the association between bacterial and fungal communities acts as an essential driver of plant health and that plants have the potential to exploit the positive interactions of bacterial and fungal communities to meet functional requirements. In addition, interactions within and among fungal and bacterial communities are important for sustaining multiple ecosystem functions ( ). They are the basic consumer trophic level of the soil food web and are therefore influenced by higher trophic levels of soil biota ( ). As major soil protists, the high association of certain cercozoan taxa with bacteria and fungi suggests a hierarchical structure of trophic networks in which predators gain dominance over other predators ( ). However, positively correlated cooperative or synthetic relationships between bacteria and fungi are likely to be a shift toward resistant prey organisms in trophic interactions with protists ( , ). Keystone taxa of the blueberry root-associated microbiome and their ecological functions. The keystone microbial species were positively associated with plant productivity and could be considered potential candidates for manipulating microorganisms to promote plant production and reduce fertilizer inputs ( ). Our results showed that there were 19 and 12 keystone taxa belonging to Proteobacteria and Actinobacteria (Table S8), respectively, that had high relative abundances in each compartment niche of blueberry roots. Previous studies have shown that a positive correlation between the relative abundance of Proteobacteria and the rate of nitrogen application was observed during long-term nitrogen fertilization, suggesting that Proteobacteria were strongly affected by nitrogen addition ( , ). The increased abundance of Proteobacteria could be attributed to the copiotroph life history strategy, which favors the nutrient-sufficient habitat ( ). Thus, the high relative abundance of Proteobacteria could promote nitrogen consumption and turnover, which may potentially participate in soil nitrogen cycling and contribute to the nitrogen fixation effect ( ). Notably, Actinobacteria was the dominant taxon of the bacterial community in the root endosphere. Members of Actinobacteria have been noted to play a crucial role in plant disease suppression by producing secondary metabolites like antibiotics and antifungal compounds ( , ). Therefore, it is possible that bacterial communities were recruited from rhizosphere soils and bulk soils for the functions required by plants ( ). On these bases, we speculate that these keystone taxa may play critical ecological roles in promoting soil nutrient cycling and enhancing the abiotic or biotic stress tolerance of host plants. Furthermore, our results indicated that the class Sordariomycetes was an abundant fungal taxon in the bulk soil, rhizosphere, and endosphere but gradually declined along the soil-rhizosphere-root continuum, which is consistent with previous studies showing that members of Sordariomycetes were the predominant fungal taxa in the soil ( ) and that their abundance was positively related to the nitrogen concentration ( , ). Additionally, 7 keystone taxa in Eurotiales were observed in the bulk soil and rhizosphere (Table S8). It was reported that most species in the order Eurotiales in the class Eurotiomycetes possess N 2 O-producing activity ( ). Moreover, our results indicated that fungal keystone taxa in Helotiales , Chaetothyriales , and Sebacinales were more abundant in the rhizosphere and endosphere (Table S8), where these orders contain the known ERM fungi ( ). The genus Oidiodendron was predominant in the endosphere and belongs to the ERM fungi, which play a critical role in promoting blueberry root growth and development, particularly in nutrient-deprived habitats ( , , ). Previous studies have shown that ERM fungi have the ability to reciprocally exchange carbon and phosphorus, along with the ability to decompose complex organic compounds to enhance the nutrient acquisition and fitness of plants ( , ). Thus, keystone fungal species may potentially play an ecological role as decomposers, facilitating rhizosphere turnover of plant-derived carbon and providing additional organic nutrients to plants. Collectively, our results suggest that plants can recruit specific microbes to satisfy the functions that are required by host plants in different compartment niches ( ). While the identification of keystone taxa has provided insight into the contributions of microorganisms to improve the productivity and health of host plants, the beneficial functions of microorganisms for plants need to be further explored. Conclusions. This study demonstrates that root compartment niches strongly influence the diversity, community compositions, and co-occurrence network patterns of the blueberry root-associated microbiome. Root compartment niches predominate over host cultivars of blueberry in shaping the root-associated microbiome. Totals of 33 and 20 distinct biomarkers, respectively, were identified in the bacterial and fungal communities of different compartment niches. As host effects increased, deterministic processes gradually increased along the soil-rhizosphere-root continuum for both bacterial and fungal communities. The complexity of bacterial-fungal interkingdom interactions decreased along the soil-rhizosphere-root continuum, while positive interactions gradually dominated in the co-occurrence networks. Functional predictions showed that bacterial communities in the rhizosphere had higher capacities for cellulolysis, and the ecological guilds of fungal communities in the root endosphere, rhizosphere, and bulk soil were ericoid mycorrhizae, soil saprotrophs, and plant pathogens, respectively. These findings provide insight into the variation and assembly processes in different root compartment niches of blueberry, as well as the interkingdom interactions and potentially beneficial functions, which may contribute to the manipulation of microorganisms to promote productivity and enhance plant tolerance to biotic/abiotic stresses.
Different plant compartment niches harbor specific microbiomes ( , ). Our results indicated that root compartment niches dominantly shaped the root-associated microbial communities, with decreasing alpha diversity along the soil-rhizosphere-root continuum. The gradual shifts in microbial communities include enrichment and depletion processes from the surrounding soil microbiota ( ). Previous studies have shown that plants can alter microbial communities by secreting bioactive molecules, including primary metabolites and secondary metabolites, into the rhizosphere ( ). The interaction between microbial substrate uptake and plant exudative traits forms a molecular mechanism to regulate microbial communities, such as the recruitment of the colonization of bacterial communities that prefer aromatic organic acids by regulating the content of aromatic organic acids ( ). In addition to providing typical carbon and nitrogen substrates, roots actively regulate the rhizosphere microbial community by secreting specific chemicals ( ). Since microbial communities with the ability to promote growth and activate induced systemic resistance are highly tolerant of coumarins, plants can participate in shaping the rhizosphere microbiome by regulating coumarin-biosynthetic pathways ( ). The rhizosphere microbiome acts as an important inoculum reservoir and, thus, contributes to the construction of the endosphere microbial community ( ). The host immune system has a strong influence on the enrichment and depletion processes of the microbial community from the rhizosphere to the endosphere, and only a fraction of the microbiota in the rhizosphere with traits that subvert the host immune processes have the potential to colonize the endosphere ( ). Consequently, this leads to differentiation of microbial communities in various compartment niches. Furthermore, host selection effects are enhanced along the soil-rhizosphere-root continuum with the recruitment, filtration, and enrichment of microbial taxa with specific functions in different compartment niches. In contrast to environmental factors, such as fertilization practice or site, host selection dominates in shaping the assembly of microbial communities, primarily through compartment niches and then host species ( ). This was also evident in our study, where variations in the taxonomic compositions of blueberry root microbiomes were dominated by the root compartment niches rather than by the host cultivars ( ; Table S1). Studies on Zea mays , Triticum aestivum , and Hordeum vulgare show that different species have an effect on the composition of the microbiomes ( ), while different genotypes of Arabidopsis thaliana show that different host genotypes have a limited effect on the root microbiomes ( , ). Although different host plant subspecies, cultivars, and genotypes can harbor distinct microbial communities, within individual species, this effect typically appears rather weak ( , , ). Therefore, the root compartment niche is the primary driver shaping the composition of root-associated microbial communities, rather than the blueberry cultivar. The varied compartment niches affected the proportions of the root-associated microbial community composition of blueberry. Consistent with previous studies, Actinobacteria and Proteobacteria were the most abundant phyla in the bacterial community ( ), and our results showed that Actinobacteria was the dominant phylum in the endosphere. Members of Actinobacteria possess a potential suppressive effect on plant pathogens ( ), and the increased proportion in the endosphere may have been related to the selection of functions that correspond to plant health requirements. Moreover, the increased proportions of Firmicutes and Chloroflexi in the rhizosphere indicated a potential dominant function in nutrient cycling, as these microorganisms are related to carbon and nitrogen cycling ( , ). Thus, the different community compositions of each compartment niche were likely related to their functional requirements for biotic stress reduction or nutrient cycling. Similarly, the fungal communities showed compartment-specific enrichment patterns, with high proportions of Archaeorhizomycetes and Tremellomycetes in the rhizosphere and high proportions of Eurotiomycetes , Agaricomycetes , and Leotiomycetes in the endosphere ( ). Members of Archaeorhizomycetes are considered to have saprotrophic potential and are dependent on root-derived carbon compounds ( ), which may be attributed to the active root metabolism that enhances their assembly in the rhizosphere. Due to the poor root system of blueberry plants, they can be symbiotic with ERM fungi to cope with their limitations in nutrient uptake and adaptation to low soil pH ( ). Therefore, the high relative abundances of ERM fungi belonging to Eurotiomycetes , Agaricomycetes , and Leotiomycetes in the endosphere were likely to be potentially beneficial in fulfilling root nutrient requirements.
The assembly process of root-associated microbes is influenced by many factors, such as root exudates, the plant immune system, and soil physicochemical properties. Revealing the dynamic ecological processes of plant root-associated microbiome assembly will facilitate the utilization of possible approaches to adjust the microbial community to provide beneficial functions for soil and plant health. These environmentally friendly approaches can be applied to agricultural practices to avoid excessive fertilizer additions ( , ). Previous studies have indicated that various compartment niches are driven by distinct assembly processes during the development of plants ( ). Our results showed that deterministic processes played a more significant role in the assembly of bacterial communities in the rhizosphere and endosphere than in the assembly of fungal communities. Compared with fungi, most bacteria have a narrow tolerance range for growth and are more sensitive to variations in microenvironmental responses ( , , ). The rhizosphere is a carbon-rich compartment niche as a consequence of root exudation or rhizodeposition, providing a more diverse microenvironment for microorganisms ( ). There was a significant correlation between bacterial communities and the phosphorus content of the rhizosphere soil (Fig. S5). To meet the requirement for phosphorus, plants secrete low-molecular-weight organic acids in the rhizosphere to increase phosphorus availability, while plants recruit and select for specific microbial communities with phosphorus-solubilizing capacity in the rhizosphere ( ). Therefore, it is reasonable that the metabolic activity of roots contributes to the variation in soil physicochemical properties in the microenvironment, which makes the assembly of bacterial communities more susceptible to being driven by deterministic processes. Furthermore, deterministic processes in fungal communities that gradually increased along the soil-rhizosphere-root continuum were observed. Previous studies suggest that in a relatively homogeneous natural tropical forest, fungi are more highly associated with plant phylogeny than bacteria are ( ). Simultaneously, specific fungi can form biotrophic relationships with plants ( ), particularly with the poorly developed root systems of blueberry, which can form symbiotic associations with specific fungi ( ). Therefore, this could be a response to a plant host effect, in which the plants exert a stronger selective effect on the fungal community, contributing to a progressive increase in the influence of deterministic processes from the rhizosphere to the endosphere. Rich and diverse relationships between bacteria and fungi, such as antagonistic and cooperative relationships, influence the dynamics of microbial communities ( ). Our study indicated that higher positive bacterial-fungal interkingdom interactions were observed along the soil-rhizosphere-root continuum. The positive interactions that exist between bacteria and fungi may be due to their mutualistic and commensal ecological interactions ( ). In general, recalcitrant organic matter, such as lignin and cellulose, is largely degraded by fungi and releases products like phenolic compounds and water-soluble sugars that are utilized by bacteria ( ). Additionally, there are certain bacteria that can facilitate the formation of ectomycorrhizae, colonize the surface of fungal hyphae, and benefit from the exudates of the fungi ( ). Several studies have also identified partial bacterial taxa that interact with fungi ( ). It has been suggested that the greater numberof positive relationships observed in the rhizosphere of Astragalus mongholicus implied a higher degree of cooperative interactions, which may contribute to plant resistance against abiotic and biotic stresses ( ). Host plants and root-associated microbial communities are an evolutionary unit of common interest, and root-associated microbes can regulate host root traits through belowground nutrient acquisition strategies of nutrient scavenging and nutrient mining. Plants reallocate the release of root exudates and the recruitment of beneficial microorganisms, respectively, to ultimately achieve nutrient acquisition and plant growth ( , ). Previous studies show that the synergistic interaction of arbuscular mycorrhizal fungi and nitrogen-fixing rhizobial bacteria can provide different limiting nutrients for plant growth ( ). This indicates that the association between bacterial and fungal communities acts as an essential driver of plant health and that plants have the potential to exploit the positive interactions of bacterial and fungal communities to meet functional requirements. In addition, interactions within and among fungal and bacterial communities are important for sustaining multiple ecosystem functions ( ). They are the basic consumer trophic level of the soil food web and are therefore influenced by higher trophic levels of soil biota ( ). As major soil protists, the high association of certain cercozoan taxa with bacteria and fungi suggests a hierarchical structure of trophic networks in which predators gain dominance over other predators ( ). However, positively correlated cooperative or synthetic relationships between bacteria and fungi are likely to be a shift toward resistant prey organisms in trophic interactions with protists ( , ).
The keystone microbial species were positively associated with plant productivity and could be considered potential candidates for manipulating microorganisms to promote plant production and reduce fertilizer inputs ( ). Our results showed that there were 19 and 12 keystone taxa belonging to Proteobacteria and Actinobacteria (Table S8), respectively, that had high relative abundances in each compartment niche of blueberry roots. Previous studies have shown that a positive correlation between the relative abundance of Proteobacteria and the rate of nitrogen application was observed during long-term nitrogen fertilization, suggesting that Proteobacteria were strongly affected by nitrogen addition ( , ). The increased abundance of Proteobacteria could be attributed to the copiotroph life history strategy, which favors the nutrient-sufficient habitat ( ). Thus, the high relative abundance of Proteobacteria could promote nitrogen consumption and turnover, which may potentially participate in soil nitrogen cycling and contribute to the nitrogen fixation effect ( ). Notably, Actinobacteria was the dominant taxon of the bacterial community in the root endosphere. Members of Actinobacteria have been noted to play a crucial role in plant disease suppression by producing secondary metabolites like antibiotics and antifungal compounds ( , ). Therefore, it is possible that bacterial communities were recruited from rhizosphere soils and bulk soils for the functions required by plants ( ). On these bases, we speculate that these keystone taxa may play critical ecological roles in promoting soil nutrient cycling and enhancing the abiotic or biotic stress tolerance of host plants. Furthermore, our results indicated that the class Sordariomycetes was an abundant fungal taxon in the bulk soil, rhizosphere, and endosphere but gradually declined along the soil-rhizosphere-root continuum, which is consistent with previous studies showing that members of Sordariomycetes were the predominant fungal taxa in the soil ( ) and that their abundance was positively related to the nitrogen concentration ( , ). Additionally, 7 keystone taxa in Eurotiales were observed in the bulk soil and rhizosphere (Table S8). It was reported that most species in the order Eurotiales in the class Eurotiomycetes possess N 2 O-producing activity ( ). Moreover, our results indicated that fungal keystone taxa in Helotiales , Chaetothyriales , and Sebacinales were more abundant in the rhizosphere and endosphere (Table S8), where these orders contain the known ERM fungi ( ). The genus Oidiodendron was predominant in the endosphere and belongs to the ERM fungi, which play a critical role in promoting blueberry root growth and development, particularly in nutrient-deprived habitats ( , , ). Previous studies have shown that ERM fungi have the ability to reciprocally exchange carbon and phosphorus, along with the ability to decompose complex organic compounds to enhance the nutrient acquisition and fitness of plants ( , ). Thus, keystone fungal species may potentially play an ecological role as decomposers, facilitating rhizosphere turnover of plant-derived carbon and providing additional organic nutrients to plants. Collectively, our results suggest that plants can recruit specific microbes to satisfy the functions that are required by host plants in different compartment niches ( ). While the identification of keystone taxa has provided insight into the contributions of microorganisms to improve the productivity and health of host plants, the beneficial functions of microorganisms for plants need to be further explored.
This study demonstrates that root compartment niches strongly influence the diversity, community compositions, and co-occurrence network patterns of the blueberry root-associated microbiome. Root compartment niches predominate over host cultivars of blueberry in shaping the root-associated microbiome. Totals of 33 and 20 distinct biomarkers, respectively, were identified in the bacterial and fungal communities of different compartment niches. As host effects increased, deterministic processes gradually increased along the soil-rhizosphere-root continuum for both bacterial and fungal communities. The complexity of bacterial-fungal interkingdom interactions decreased along the soil-rhizosphere-root continuum, while positive interactions gradually dominated in the co-occurrence networks. Functional predictions showed that bacterial communities in the rhizosphere had higher capacities for cellulolysis, and the ecological guilds of fungal communities in the root endosphere, rhizosphere, and bulk soil were ericoid mycorrhizae, soil saprotrophs, and plant pathogens, respectively. These findings provide insight into the variation and assembly processes in different root compartment niches of blueberry, as well as the interkingdom interactions and potentially beneficial functions, which may contribute to the manipulation of microorganisms to promote productivity and enhance plant tolerance to biotic/abiotic stresses.
Study site and sample collection. The study site was located in the Blueberry Germplasm Resource Station (31°60′N, 119°20′E), Lishui, Nanjing, Jiangsu Province, China. The soil type is a Hydragric Anthrosol, according to the World Reference Base for Soil Resources classification. The sampling area was established in 2013 and covers an area of approximately 30,000 m 2 with flat topography. Three blueberry cultivars were used, including rabbiteye blueberry, northern highbush blueberry, and southern highbush blueberry. The selected plants were grown with consistent and conventional management practices from the same field. Six sampling sites were selected randomly for each blueberry cultivar, and each sampling site was 15 by 15 m 2 . For representative samples, a multipoint composite sampling method was adopted, with each composite sample used for subsequent analysis representing 12 individual samples. Each rhizosphere soil and root sample was collected randomly at a 10-cm depth with a clean spade from three individual blueberry plants at the same growth stage from four directions in October 2021 ( ). Bulk soil samples were collected from sampling sites for each blueberry cultivar in the absence of planting and fertilization. Samples were stored at low temperatures and delivered immediately to the laboratory. For rhizosphere soil samples, soil closely adhered to the roots was collected using a sterilized brush and then sieved through a 2-mm sieve. For root endosphere samples, the roots were rinsed three times using sterile water and then transferred into 50-mL sterilized tubes and sonicated for 3 min at 60 Hz (sonication for 30 s, break for 30 s, 3 cycles) to clear the microbes from the rhizoplane. After sonication, the roots were transferred to 2-mL sterile centrifuge tubes, flash-frozen with liquid nitrogen, and then stored in an ultralow-temperature refrigerator ( ). Individual soil samples were kept at −20°C and −80°C for soil physiochemical analysis and microbial community analysis, respectively. Illumina sequencing and bioinformatic analysis. DNA samples were extracted from 0.5-g amounts of bulk soil, rhizosphere soil, and root endosphere samples using FastDNA spin kits (MP Biomedicals, Santa Ana, CA, USA) following the manufacturer’s instructions. The V5-V7 region of the bacterial 16S rRNA gene and the internal transcribed spacer 1 (ITS1) region of the fungal rRNA gene were amplified. The PCR amplification was sequenced on the Illumina MiSeq PE300 platform (Illumina, San Diego, USA). Detailed DNA extraction and amplification methods are described in the supplemental material. The accession number of the raw sequences is PRJNA907196 (NCBI Sequence Read Archive). The raw sequences were denoised and sorted, the operational taxonomic units (OTUs) clustered using UPARSE (version 7.1) at a similarity of 97%, and chimeric sequences identified and removed using UCHIME. The taxonomy of each sequence was based on our previous methods using the UNITE (version 8.0, http://unite.ut.ee/index.php ) and SILVA (version 13.8, http://www.arb-silva.de ) databases for fungi and bacteria, respectively ( ). In total, 2,162,807 bacterial and 2,597,238 fungal sequence reads were acquired and clustered into 4,470 and 3,856 OTUs, respectively. Statistical analysis. Alpha diversity indices (Chao1 and Shannon) were calculated using Mothur software (version 1.30.2), and beta diversity was assessed by calculating the Bray-Curtis dissimilarity matrix and then ordinated using nonmetric multidimensional scaling analysis (NMDS) by QIIME software (version 1.9.1) ( ). Analysis of similarity (ANOSIM) was conducted to determine differences between blueberry compartment niches ( ). Two-way PERMANOVA was used to test the relative contributions of various factors to community dissimilarity. Linear discriminant analysis (LDA) effect size (LEfSe) was performed (LDA score of >4.0, P < 0.05) in order to identify the biomarkers within the different compartment niches. The beta nearest-taxon index (βNTI) was calculated by a null model (999 randomizations) to assess the relative importance of deterministic processes (|βNTI| above 2) and stochastic processes (|βNTI| below 2) in driving microbiome assembly ( ). These processes were categorized based on the βNTI and Bray-Curtis-based Raup-Crick index (RC Bray ) values into (i) heterogeneous selection, (ii) homogeneous selection, (iii) dispersal limitation, (iv) homogenizing dispersal, and (v) undominated ecological processes according to (i) βNTI above +2, (ii) βNTI below −2, (iii) |βNTI| below 2 and RC Bray above 0.95, (iv) |βNTI| below 2 and RC Bray below −0.95, and (v) |βNTI| below 2 and |RC Bray | below 0.95, respectively ( , ). Microbial community co-occurrence networks and interkingdom co-occurrence network analysis were constructed using OTUs with relative abundances of >0.5%. A valid co-occurrence correlation between OTUs was identified as statistically significant at a Spearman’s coefficient of r > 0.7 or r < −0.7 and ( P value of <0.01). The P values were modified by Benjamini-Hochberg’s false discovery rate method for multiple-testing corrections ( ). The co-occurrence network analysis was conducted with iGraph and Hmisc in R ( , ) and visualized with Gephi software (version 0.9.3). Topological characteristics were applied to characterize the complexity of interactions and network structures of patterns among bacteria and fungi ( ). The functional profiles of bacteria and fungi were predicted using FAPROTAX (version 1.1) and FUNGuild (version 1.0), respectively, and analyzed at https://cloud.majorbio.com/ . Data availability statement. The data that support the findings of this study are available from the National Center for Biotechnology Information (NCBI) Sequence Read Archive ( http://trace.ncbi.nlm.nih.gov/Traces/sra/ ) under accession number PRJNA907196 .
The study site was located in the Blueberry Germplasm Resource Station (31°60′N, 119°20′E), Lishui, Nanjing, Jiangsu Province, China. The soil type is a Hydragric Anthrosol, according to the World Reference Base for Soil Resources classification. The sampling area was established in 2013 and covers an area of approximately 30,000 m 2 with flat topography. Three blueberry cultivars were used, including rabbiteye blueberry, northern highbush blueberry, and southern highbush blueberry. The selected plants were grown with consistent and conventional management practices from the same field. Six sampling sites were selected randomly for each blueberry cultivar, and each sampling site was 15 by 15 m 2 . For representative samples, a multipoint composite sampling method was adopted, with each composite sample used for subsequent analysis representing 12 individual samples. Each rhizosphere soil and root sample was collected randomly at a 10-cm depth with a clean spade from three individual blueberry plants at the same growth stage from four directions in October 2021 ( ). Bulk soil samples were collected from sampling sites for each blueberry cultivar in the absence of planting and fertilization. Samples were stored at low temperatures and delivered immediately to the laboratory. For rhizosphere soil samples, soil closely adhered to the roots was collected using a sterilized brush and then sieved through a 2-mm sieve. For root endosphere samples, the roots were rinsed three times using sterile water and then transferred into 50-mL sterilized tubes and sonicated for 3 min at 60 Hz (sonication for 30 s, break for 30 s, 3 cycles) to clear the microbes from the rhizoplane. After sonication, the roots were transferred to 2-mL sterile centrifuge tubes, flash-frozen with liquid nitrogen, and then stored in an ultralow-temperature refrigerator ( ). Individual soil samples were kept at −20°C and −80°C for soil physiochemical analysis and microbial community analysis, respectively.
DNA samples were extracted from 0.5-g amounts of bulk soil, rhizosphere soil, and root endosphere samples using FastDNA spin kits (MP Biomedicals, Santa Ana, CA, USA) following the manufacturer’s instructions. The V5-V7 region of the bacterial 16S rRNA gene and the internal transcribed spacer 1 (ITS1) region of the fungal rRNA gene were amplified. The PCR amplification was sequenced on the Illumina MiSeq PE300 platform (Illumina, San Diego, USA). Detailed DNA extraction and amplification methods are described in the supplemental material. The accession number of the raw sequences is PRJNA907196 (NCBI Sequence Read Archive). The raw sequences were denoised and sorted, the operational taxonomic units (OTUs) clustered using UPARSE (version 7.1) at a similarity of 97%, and chimeric sequences identified and removed using UCHIME. The taxonomy of each sequence was based on our previous methods using the UNITE (version 8.0, http://unite.ut.ee/index.php ) and SILVA (version 13.8, http://www.arb-silva.de ) databases for fungi and bacteria, respectively ( ). In total, 2,162,807 bacterial and 2,597,238 fungal sequence reads were acquired and clustered into 4,470 and 3,856 OTUs, respectively.
Alpha diversity indices (Chao1 and Shannon) were calculated using Mothur software (version 1.30.2), and beta diversity was assessed by calculating the Bray-Curtis dissimilarity matrix and then ordinated using nonmetric multidimensional scaling analysis (NMDS) by QIIME software (version 1.9.1) ( ). Analysis of similarity (ANOSIM) was conducted to determine differences between blueberry compartment niches ( ). Two-way PERMANOVA was used to test the relative contributions of various factors to community dissimilarity. Linear discriminant analysis (LDA) effect size (LEfSe) was performed (LDA score of >4.0, P < 0.05) in order to identify the biomarkers within the different compartment niches. The beta nearest-taxon index (βNTI) was calculated by a null model (999 randomizations) to assess the relative importance of deterministic processes (|βNTI| above 2) and stochastic processes (|βNTI| below 2) in driving microbiome assembly ( ). These processes were categorized based on the βNTI and Bray-Curtis-based Raup-Crick index (RC Bray ) values into (i) heterogeneous selection, (ii) homogeneous selection, (iii) dispersal limitation, (iv) homogenizing dispersal, and (v) undominated ecological processes according to (i) βNTI above +2, (ii) βNTI below −2, (iii) |βNTI| below 2 and RC Bray above 0.95, (iv) |βNTI| below 2 and RC Bray below −0.95, and (v) |βNTI| below 2 and |RC Bray | below 0.95, respectively ( , ). Microbial community co-occurrence networks and interkingdom co-occurrence network analysis were constructed using OTUs with relative abundances of >0.5%. A valid co-occurrence correlation between OTUs was identified as statistically significant at a Spearman’s coefficient of r > 0.7 or r < −0.7 and ( P value of <0.01). The P values were modified by Benjamini-Hochberg’s false discovery rate method for multiple-testing corrections ( ). The co-occurrence network analysis was conducted with iGraph and Hmisc in R ( , ) and visualized with Gephi software (version 0.9.3). Topological characteristics were applied to characterize the complexity of interactions and network structures of patterns among bacteria and fungi ( ). The functional profiles of bacteria and fungi were predicted using FAPROTAX (version 1.1) and FUNGuild (version 1.0), respectively, and analyzed at https://cloud.majorbio.com/ .
The data that support the findings of this study are available from the National Center for Biotechnology Information (NCBI) Sequence Read Archive ( http://trace.ncbi.nlm.nih.gov/Traces/sra/ ) under accession number PRJNA907196 .
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Integrated Transcriptomic and Metabolomic Analysis of | b5dd28fc-1ef2-4781-afd0-41d524469aa2 | 11720156 | Biochemistry[mh] | Cotton is a major source of renewable natural fibers for the textile industry and of vegetable oil for the food/feed industry . Of the more than 50 Gossypium species identified thus far, four were domesticated for fiber production around the world, namely G. herbaceum (A1), G. arboreum (A2), G. hirsutum (AD1), G. barbadense (AD2) . However, cotton growth and development were greatly affected by a range of biotic and abiotic stresses, such as saline-alkali soil, high temperatures, drought, pests, and pathogens, resulting in considerable yield losses and fiber quality reduction . Verticillium wilt (VW), a soil-borne vascular disease that severely affects plants , is principally attributed to the pathogen Verticillium dahliae (Vd), which has a broad range of hosts, including more than 700 plant species in the Malvaceae, Fabaceae, Solanaceae, and Rosaceae families . Once colonized in cotton plants, Vd mycelia or spores quickly spread through the xylem vessels via transpiration, obstructing the transport of water and nutrients in the vascular tissues. It also secreted toxic substances, eventually leading to symptoms of vascular bundle browning, leaf yellowing, wilting, defoliation, and even plant death . Given the presence of Vd hyphae within plant vascular tissues and the dormancy of spores in the form of microsclerotia, conventional soil amendments, solar irradiation exposure, or fungicide treatments have been proved ineffective in VW disease control . According to statistical data from the Agricultural Technology Extension Service Center of the Ministry of Agriculture and Rural Affairs of China in 2021, the losses caused by VW accounted for 32.94% of total cotton losses caused by various diseases in China . In recent years, climate change, continuous monoculture, and frequent introduction of new cotton varieties and hybrids have exacerbated the occurrence of VW worldwide . Despite being derived from the full hybridization between the same diploid ancestors, G. hirsutum and G. barbadense exhibit significant differences in plant traits such as fiber quality, yield, and environmental adaptability . G. hirsutum , approximately accounting for 95% of global cotton production , is the most extensively cultivated species due to its advantages of high yield and strong adaptation, while it lacks resistant germplasm and superior fiber quality genes. G. barbadense , on the contrary, is renowned for its superior fiber length, strength, and ultra fineness, and VW resistance, contributing less than 5% to global cotton production . Given these characteristics, it remains of great significance to introduce resistance genes from G. barbadense into G . hirsutum to significantly enhance its resistance to VW . Therefore, investigating the distinctions between G. hirsutum and G. barbadense at the transcriptional and metabolic levels could help us understand the resistance mechanism of cotton to VW, identify key genes for VW resistance, and provide genetic materials for molecular breeding of VW resistance. Transcriptomics is a discipline that studies the transcriptional levels in the cells or tissues of target organisms at specific developmental stages, locations, or physiological conditions, to dissect the molecular mechanisms behind complex biological pathways and trait regulatory networks . Currently, transcriptome sequencing technology (RNA-seq) has been widely applied in plant disease resistance mechanisms to understand the interactions between plants and pathogens, and to identify relevant metabolic pathways and key genes . Some transcriptomic results have identified metabolic pathways and differentially expressed genes (DEGs) associated with plant disease resistance; among these, hypersensitive response regulation and potassium ion transmembrane transport were highly activated in rice plant defense against blast disease , while chitinase, cytochrome P450 , and GST were highly up-regulated in peanut defense against rust disease . Similarity, we also noticed that the GST gene cluster was involved in cotton-resistant response against VW . Metabolomics can detect changes in metabolites in cells or tissues, which helps determine the relationship between metabolites and plant biochemistry. Metabolome sequencing is also a key link connecting gene function and phenotypic variations, making it an important discipline after genomics, transcriptomics, and proteomics . When pathogens invaded organs or tissues, plant metabolites were subjected to a series of changes, which might generate signaling molecules to activate the immune system to suppress or kill pathogens. In the metabolomic studies of Solanaceae bacterial wilt, 63 differentially accumulated metabolites (DAMs) were found to be closely related to the biosynthetic pathways of plant hormones, phenylpropanoids, and flavonoids . In the metabolites of Zanthoxylum bungeanum Maxim rust disease, most of the metabolites were proved to belong to lipid and lipid-like molecules, phenylpropanoids, and polyketones, organic heterocyclic compounds . In the interaction between susceptible/resistant watermelon varieties and Fusarium oxysporum , significant changes were observed in related metabolites, such as jasmonic acid-isoleucine, methyl jasmonate, melatonin, and lysine, implying their important roles in pathogen defense . To understand the complex and variable biological processes, the conjoint analyses of RNA-seq and metabolomics could better reveal the molecular mechanisms of regulatory processes at different expression levels. Referring to the previous studies, it was observed through joint analysis that silver nanoparticles (AgNPs) activate plant hormone signaling and glutathione metabolism pathways, protecting rice seedlings from blast fungus infection ; it was also observed that HmF6′H1, an acetyl-coenzyme A 6′-hydroxylase, can promote the accumulation of simple coumarins in Heracleum moellendorffii Hance to resist infection by powdery mildew , and that DEGs and DAMs related to glutathione metabolism pathways can make great contributions to the response of rice to salt stress . In this study, VW-susceptible TM-1 and VW-resistant Hai7124 were selected to perform transcriptome and metabonomic analyses. Root samples were separately collected at 0, 1, and 2 days after V991 inoculation for sequencing analysis. Multiple pair comparisons among the samples generated a number of DEGs and DAMs, which were then submitted to enrichment analysis in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Combining identified key candidate genes and metabolites, this study lays the foundation for the functional validation of candidate genes in subsequent research.
2.1. Sequencing of the Transcriptome and Analysis of Quality Control To systematically elucidate the critical genes and signaling pathways in plant defense mechanisms against VW infection, 18 RNA-seq libraries were constructed from root samples of the representative varieties TM-1 and Hai7124. The samples were taken at 0, 1, and 2 days after inoculation (DAI) of V991. After removing low-quality reads, a total of 802.88 million clean reads were obtained, with an average clean read (M) of 38.12–49.15 per sample. The Q30 values of all the samples exceeded 91.95%, and the GC content ranged from 43.43% to 45.61%. Mapping the clean reads of each sample to the reference genome showed alignment efficiencies ranging from 94.04% to 97.27% . Based on the annotated reference genome, a total of 72,752 expressed genes were identified in our RNA-Seq dataset. The expression levels of these genes were quantified using the number of fragments per kilobase of transcript per million mapped reads (FPKM). To confirm the accuracy of the RNA-seq data, principal component analysis (PCA) across the 18 samples was performed, and two main components, namely PC1 and PC2, were obtained, which contributed 34.71% and 22.85% of the total variation, respectively. The three biological replicates at different time points showed a high similarity between different samples ( A). Pearson’s correlation coefficient (PCC) analysis on all the RNA-seq samples showed a gene expression correlation of over 90% for each sample ( B). These results suggest that the transcriptome data are of high quality which meets the standards for the subsequent DEG identification and their functional enrichment analysis. 2.2. DEG Identification and Expression Pattern Analysis Nine pairwise comparisons were performed on all the samples, resulting in 39,976 DEGs ( C). By comparing the different infection stages within the susceptible TM-1 and within the resistant Hai7124, there were more DEGs identified in the former (TM-1-0DAI vs. TM-1-1DAI, TM-1-0DAI vs. TM-1-2DAI, and TM-1-1DAI vs. TM-1-2DAI) than in the latter (Hai7124-0DAI vs. Hai7124-1DAI, Hai7124-0DAI vs. Hai7124-2DAI, and Hai7124-1DAI vs. Hai7124-2DAI). A similar phenomenon was also observed during early infection (0DAI to 1DAI). The difference between TM-1 and Hai7124 was also manifested in the period when the minimum number of DEGs appears, with the former showing the smallest DEGs in the comparison of TM-1-1DAI vs. TM-1-2DAI, while the latter showed Hai7124-0DAI vs. Hai7124-2DAI. For the pairwise comparisons of different varieties at the same infection stage (DAI), it was observed that the pair TM-1-0DAI vs. Hai7124-0DAI had the highest number of DEGs, while the pair TM-1-2DAI vs. Hai7124-2DAI had the lowest number of DEGs. In addition, more up-regulated DEGs were identified in the resistant variety than in susceptible varieties. To investigate the spatiotemporal expression patterns of genes, 28,069 DEGs in TM-1 and 8904 genes in Hai7124 were separately submitted to short time-series expression miner (STEM) analysis ( D,E). The findings indicated that a substantial majority of the DEGs in TM-1, 90.57% of the total 28,069 DEGs, were significantly clustered into 3 distinct expression profiles. Among these profiles, in profile 7, which clustered 13,599 DEGs, 48.44%, showed a continuous up-regulation trend; in profile 0, which clustered 6924 DEGs, 24.67%, showed an overall down-regulation trend; and in profile 1, which clustered 4900 DEGs, 17.46%, showed an initial down-regulation followed by an up-regulation trend. On the other hand, 8221 DEGs (92.33% of the total) in Hai7124 were clustered in 4 expression profiles. Among these profiles, profile 1, which clustered3,351 DEGs, 37.63%, showed an initial down-regulation followed by sustained up-regulation trend; profile 7, which clustered 2104 DEGs, 23.63%, showed a continuous up-regulation trend; profile 0, which clustered 1363 DEGs, 15.31%, demonstrated a sustained down-regulation trend; and profile 3, which clustered 1403 DEGs, 15.76%, showed a periodic pattern of initial down-regulation, followed by up-regulation, and then another down-regulation. 2.3. Functional Enrichment Analysis of DEGs The functional enrichment analyses were performed on the DEGs in the significantly clustered expression profiles (0, 1, and 7) in TM-1 and Hai7124 using the GO and KEGG databases. In profile 0, the DEGs were enriched in metabolic processes, cellular processes, cellular anatomical entities, and catalytic activities in the first three GO terms of biological processes (BP), cellular components (CC), and molecular functions (MF) ( F). As profile 0 exhibited a sustained down-regulation trend, which was more prevalent in susceptible TM-1 than in resistant Hai7124, KEGG enrichment analysis showed that the common pathways in both TM-1 and Hai7124 included hormone signal transduction, circadian rhythm-plant, MAPK signaling pathway-plant, and phosphatidylinositol signaling system . In profile 1, the DEGs were enriched in the GO terms of processes related to cellular processes, metabolic processes, cellular anatomical entities, catalytic activities, and binding ( G). KEGG enrichment analysis revealed that the common pathways in both genotypes included flavonoid biosynthesis, circadian rhythm-plant, biosynthesis of various plant secondary metabolites, and plant hormone signal transduction . In particular, the significant enrichment of profile 1 DEGs in the biosynthesis of secondary metabolites and plant hormone signal transduction suggested their crucial role in resisting pathogen invasion. In profile 7, the DEGs were enriched in the GO terms of cellular processes, metabolic processes, cellular anatomical entities, binding, and catalytic activities ( H). KEGG enrichment analysis revealed that the key pathways in TM-1 were related to ribosome biogenesis, carotenoid biosynthesis, base excision repair, nitrogen metabolism, and endocytosis, which are associated with growth and development. In contrast, the key pathways in Hai7124 were associated with plant defense, such as ABC transporters, phenylpropanoid biosynthesis, flavonoid biosynthesis, and plant–pathogen interactions . 2.4. Metabolomic Comparative Analysis of Different Strains To investigate the metabolic differences between TM-1 and Hai7124 during cotton VW infection, untargeted metabolomic sequencing was performed on the 18 samples, and quality control analysis was performed on the sequencing data. PCA analysis showed that PC1 scored 20.81% and PC2 scored 13.81%, indicating significant metabolic phenotype differences between the two samples, and high similarity among the three biological replicates . The correlation coefficients exceeding 0.8 in the correlation analysis of the QC samples suggested significant consistency . A total of 995 metabolites were identified in the 18 samples, which were categorized into 11 major classes: alkaloids and derivatives (7, 0.7%); benzenoids (38, 3.82%); lignans, neolignans, and related compounds (1, 0.1%); lipids and lipid-like molecules (215, 21.51%); nucleosides, nucleotides, and analogues (7, 0.7%); organic acids and derivatives (84, 8.44%); organic nitrogen compounds (13, 1.31%); organic oxygen compounds (30, 3.02%;, organoheterocyclic compounds (60, 6.03%); others (514, 51.66%); and phenylpropanoids and polyketides (27, 2.71%) ( A). Based on the general threshold criteria of Variable Importance in Projection (VIP) equal to or greater than 1, Fold Change Screening Value equals to 2, and p -value less than 0.05, a total of 402 DAMs were identified through nine groups of pairwise comparisons. In the comparisons between different time points after V991 inoculation in the same variety, it was found that the largest numbers of DAMs were identified in the groups of TM-1-0DAI vs. TM-1-2DAI (80 DAMs) and Hai7124-1DAI vs. Hai7124-2DAI (50 DAMs), while the least numbers of DAMs were observed in TM-1-1DAI vs. TM-1-2DAI and Hai7124-0DAI vs. Hai7124-1DAI ( B). Significantly, different varieties showed DAMs at the same infecting time points; the maximum and minimum DAMs were identified in the groups of TM-1-1DAI vs. Hai7124-1DAI (189 ones) and TM-1-2DAI vs. Hai7124-2DAI (108 ones), respectively. After removing duplicates, a total of 137 and 97 DAMs were separately obtained in TM-1 and Hai7124 via different infection time point comparisons. Subsequently, via K-means clustering analysis, the DAMs of TM-1 and Hai7124, were classified into 7 and 8 clusters, respectively ( C,D). In TM-1, subclusters 4 and 5 demonstrated a consistent increasing expression trend with time advances after V991 infection. Conversely, subclusters 1 and 2 showed a decreasing expression trend with time advances after infection. In Hai7124, subcluster 4 displayed a consistent increasing expression trend with time advances after infection. Subcluster 1 showed a decreasing expression trend with time advances. In both TM-1 and Hai7124, carboxylic acid derivatives and sphingolipids showed a decreasing expression trend with time advances after V991 infection V991, while glycerophospholipids and fatty acyls exhibited a continuous increasing expression trend . It could be speculated that glycerophospholipids and fatty acyls play important roles in early resistant responses against Vd invasion. Comparison of DAMs between TM-1 and Hai7124 at the identical time point identified 22 common DAMs ( E). KEGG enrichment analysis indicated that the majority of common DAMs were significant enriched in pathways of valine, leucine, and isoleucine degradation, glutathione metabolism, metabolic pathways, and propanoate metabolism ( F). 2.5. Conjoint Analysis of DEGs and DAMs To dissect the macroscopic developmental processes of biological systems, a joint analysis of transcriptomic and metabolomic data of the two cultivars was performed in this study. The results revealed that the pathways that DAMs and DEGs co-enriched included glutathione metabolism, valine, leucine, and isoleucine degradation, propionate metabolism, ABC transport, secondary metabolite biosynthesis, and metabolic pathways . Further calculation of Pearson correlation coefficients was performed for the 5814 DEGs and 22 DAMs, generating nine quadrant plots ( A–C) and a correlation clustering heatmap ( D). The expression patterns of DEGs and DAMs in the first and ninth quadrants were opposite, implying that the changes in these DAMs might be negatively regulated by DEGs. In the third and seventh quadrants, the expression patterns of DEGs and DAMs showed consistency, implying that the variations of these DAMs might be positively regulated by the corresponding DEGs. In addition, during the processes of V991 infection in TM-1 and Hai7124 (0, 1, and 2 days), the metabolite putrescine was positively regulated by GH_D04G0634 , GH_D11G2329 , and GH_D13G1106 . The correlation clustering heatmap results showed that the red part represents a positive correlation between DEGs and DAMs, while the green part represents a negative correlation. Notably, putrescine was significantly positively correlated with GH_D11G2329 . Based on the joint analysis of DEGs and DAMs, it could be speculated that the glutathione metabolism pathway is vital for resisting Vd invasion. The correlation analysis revealed a significant association between putrescine and corresponding DEGs, such as the gene-encoding glutathione S-transferase (GST). Network analysis demonstrated that DEGs and DAMs in the glutathione metabolism signaling pathway formed hub genes in the network, supporting the aforementioned correlation analysis ( E and ). Additionally, a schematic diagram of the glutathione metabolism pathway was constructed . In total, 9 DEGs were screened in TM-1 and Hai7124 at 0, 1, and 2 DAI through transcriptomic analysis, which belonged to GST; glutathione dehydrogenase/transferase (DHAR); peroxiredoxin 6 (PRDX6); isocitrate dehydrogenase 1 (IDH1); and γ-glutamylcyclotransferase (GGCT). Meanwhile, 5 DAMs involved in this pathway were identified by metabolomic analysis, namely putrescine, spermine, glycine, L-cysteine, and 5-oxoproline. In the findings from the joint analysis of transcriptomics and metabolomics, the DEG GH_D11G2329 ( GHGSTF8 ) participating in the glutathione metabolism pathway showed an up-regulated expression pattern in TM-1 during V991 infection, indicating a potential role in VW resistance. 2.6. Verification of Gene Expression qRT-PCR To validate the accuracy of the transcriptomic analysis results, 20 genes were randomly selected and analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) experiments . Detailed information on the primer design is listed in . The housekeeping gene GhUBQ7 (DQ116441) served as a reference control for the analysis of relative quantification. The results confirmed that the expression trends observed in qRT-PCR were consistent with the transcriptomic sequencing results, indicating the reliability of the transcriptomic sequencing.
To systematically elucidate the critical genes and signaling pathways in plant defense mechanisms against VW infection, 18 RNA-seq libraries were constructed from root samples of the representative varieties TM-1 and Hai7124. The samples were taken at 0, 1, and 2 days after inoculation (DAI) of V991. After removing low-quality reads, a total of 802.88 million clean reads were obtained, with an average clean read (M) of 38.12–49.15 per sample. The Q30 values of all the samples exceeded 91.95%, and the GC content ranged from 43.43% to 45.61%. Mapping the clean reads of each sample to the reference genome showed alignment efficiencies ranging from 94.04% to 97.27% . Based on the annotated reference genome, a total of 72,752 expressed genes were identified in our RNA-Seq dataset. The expression levels of these genes were quantified using the number of fragments per kilobase of transcript per million mapped reads (FPKM). To confirm the accuracy of the RNA-seq data, principal component analysis (PCA) across the 18 samples was performed, and two main components, namely PC1 and PC2, were obtained, which contributed 34.71% and 22.85% of the total variation, respectively. The three biological replicates at different time points showed a high similarity between different samples ( A). Pearson’s correlation coefficient (PCC) analysis on all the RNA-seq samples showed a gene expression correlation of over 90% for each sample ( B). These results suggest that the transcriptome data are of high quality which meets the standards for the subsequent DEG identification and their functional enrichment analysis.
Nine pairwise comparisons were performed on all the samples, resulting in 39,976 DEGs ( C). By comparing the different infection stages within the susceptible TM-1 and within the resistant Hai7124, there were more DEGs identified in the former (TM-1-0DAI vs. TM-1-1DAI, TM-1-0DAI vs. TM-1-2DAI, and TM-1-1DAI vs. TM-1-2DAI) than in the latter (Hai7124-0DAI vs. Hai7124-1DAI, Hai7124-0DAI vs. Hai7124-2DAI, and Hai7124-1DAI vs. Hai7124-2DAI). A similar phenomenon was also observed during early infection (0DAI to 1DAI). The difference between TM-1 and Hai7124 was also manifested in the period when the minimum number of DEGs appears, with the former showing the smallest DEGs in the comparison of TM-1-1DAI vs. TM-1-2DAI, while the latter showed Hai7124-0DAI vs. Hai7124-2DAI. For the pairwise comparisons of different varieties at the same infection stage (DAI), it was observed that the pair TM-1-0DAI vs. Hai7124-0DAI had the highest number of DEGs, while the pair TM-1-2DAI vs. Hai7124-2DAI had the lowest number of DEGs. In addition, more up-regulated DEGs were identified in the resistant variety than in susceptible varieties. To investigate the spatiotemporal expression patterns of genes, 28,069 DEGs in TM-1 and 8904 genes in Hai7124 were separately submitted to short time-series expression miner (STEM) analysis ( D,E). The findings indicated that a substantial majority of the DEGs in TM-1, 90.57% of the total 28,069 DEGs, were significantly clustered into 3 distinct expression profiles. Among these profiles, in profile 7, which clustered 13,599 DEGs, 48.44%, showed a continuous up-regulation trend; in profile 0, which clustered 6924 DEGs, 24.67%, showed an overall down-regulation trend; and in profile 1, which clustered 4900 DEGs, 17.46%, showed an initial down-regulation followed by an up-regulation trend. On the other hand, 8221 DEGs (92.33% of the total) in Hai7124 were clustered in 4 expression profiles. Among these profiles, profile 1, which clustered3,351 DEGs, 37.63%, showed an initial down-regulation followed by sustained up-regulation trend; profile 7, which clustered 2104 DEGs, 23.63%, showed a continuous up-regulation trend; profile 0, which clustered 1363 DEGs, 15.31%, demonstrated a sustained down-regulation trend; and profile 3, which clustered 1403 DEGs, 15.76%, showed a periodic pattern of initial down-regulation, followed by up-regulation, and then another down-regulation.
The functional enrichment analyses were performed on the DEGs in the significantly clustered expression profiles (0, 1, and 7) in TM-1 and Hai7124 using the GO and KEGG databases. In profile 0, the DEGs were enriched in metabolic processes, cellular processes, cellular anatomical entities, and catalytic activities in the first three GO terms of biological processes (BP), cellular components (CC), and molecular functions (MF) ( F). As profile 0 exhibited a sustained down-regulation trend, which was more prevalent in susceptible TM-1 than in resistant Hai7124, KEGG enrichment analysis showed that the common pathways in both TM-1 and Hai7124 included hormone signal transduction, circadian rhythm-plant, MAPK signaling pathway-plant, and phosphatidylinositol signaling system . In profile 1, the DEGs were enriched in the GO terms of processes related to cellular processes, metabolic processes, cellular anatomical entities, catalytic activities, and binding ( G). KEGG enrichment analysis revealed that the common pathways in both genotypes included flavonoid biosynthesis, circadian rhythm-plant, biosynthesis of various plant secondary metabolites, and plant hormone signal transduction . In particular, the significant enrichment of profile 1 DEGs in the biosynthesis of secondary metabolites and plant hormone signal transduction suggested their crucial role in resisting pathogen invasion. In profile 7, the DEGs were enriched in the GO terms of cellular processes, metabolic processes, cellular anatomical entities, binding, and catalytic activities ( H). KEGG enrichment analysis revealed that the key pathways in TM-1 were related to ribosome biogenesis, carotenoid biosynthesis, base excision repair, nitrogen metabolism, and endocytosis, which are associated with growth and development. In contrast, the key pathways in Hai7124 were associated with plant defense, such as ABC transporters, phenylpropanoid biosynthesis, flavonoid biosynthesis, and plant–pathogen interactions .
To investigate the metabolic differences between TM-1 and Hai7124 during cotton VW infection, untargeted metabolomic sequencing was performed on the 18 samples, and quality control analysis was performed on the sequencing data. PCA analysis showed that PC1 scored 20.81% and PC2 scored 13.81%, indicating significant metabolic phenotype differences between the two samples, and high similarity among the three biological replicates . The correlation coefficients exceeding 0.8 in the correlation analysis of the QC samples suggested significant consistency . A total of 995 metabolites were identified in the 18 samples, which were categorized into 11 major classes: alkaloids and derivatives (7, 0.7%); benzenoids (38, 3.82%); lignans, neolignans, and related compounds (1, 0.1%); lipids and lipid-like molecules (215, 21.51%); nucleosides, nucleotides, and analogues (7, 0.7%); organic acids and derivatives (84, 8.44%); organic nitrogen compounds (13, 1.31%); organic oxygen compounds (30, 3.02%;, organoheterocyclic compounds (60, 6.03%); others (514, 51.66%); and phenylpropanoids and polyketides (27, 2.71%) ( A). Based on the general threshold criteria of Variable Importance in Projection (VIP) equal to or greater than 1, Fold Change Screening Value equals to 2, and p -value less than 0.05, a total of 402 DAMs were identified through nine groups of pairwise comparisons. In the comparisons between different time points after V991 inoculation in the same variety, it was found that the largest numbers of DAMs were identified in the groups of TM-1-0DAI vs. TM-1-2DAI (80 DAMs) and Hai7124-1DAI vs. Hai7124-2DAI (50 DAMs), while the least numbers of DAMs were observed in TM-1-1DAI vs. TM-1-2DAI and Hai7124-0DAI vs. Hai7124-1DAI ( B). Significantly, different varieties showed DAMs at the same infecting time points; the maximum and minimum DAMs were identified in the groups of TM-1-1DAI vs. Hai7124-1DAI (189 ones) and TM-1-2DAI vs. Hai7124-2DAI (108 ones), respectively. After removing duplicates, a total of 137 and 97 DAMs were separately obtained in TM-1 and Hai7124 via different infection time point comparisons. Subsequently, via K-means clustering analysis, the DAMs of TM-1 and Hai7124, were classified into 7 and 8 clusters, respectively ( C,D). In TM-1, subclusters 4 and 5 demonstrated a consistent increasing expression trend with time advances after V991 infection. Conversely, subclusters 1 and 2 showed a decreasing expression trend with time advances after infection. In Hai7124, subcluster 4 displayed a consistent increasing expression trend with time advances after infection. Subcluster 1 showed a decreasing expression trend with time advances. In both TM-1 and Hai7124, carboxylic acid derivatives and sphingolipids showed a decreasing expression trend with time advances after V991 infection V991, while glycerophospholipids and fatty acyls exhibited a continuous increasing expression trend . It could be speculated that glycerophospholipids and fatty acyls play important roles in early resistant responses against Vd invasion. Comparison of DAMs between TM-1 and Hai7124 at the identical time point identified 22 common DAMs ( E). KEGG enrichment analysis indicated that the majority of common DAMs were significant enriched in pathways of valine, leucine, and isoleucine degradation, glutathione metabolism, metabolic pathways, and propanoate metabolism ( F).
To dissect the macroscopic developmental processes of biological systems, a joint analysis of transcriptomic and metabolomic data of the two cultivars was performed in this study. The results revealed that the pathways that DAMs and DEGs co-enriched included glutathione metabolism, valine, leucine, and isoleucine degradation, propionate metabolism, ABC transport, secondary metabolite biosynthesis, and metabolic pathways . Further calculation of Pearson correlation coefficients was performed for the 5814 DEGs and 22 DAMs, generating nine quadrant plots ( A–C) and a correlation clustering heatmap ( D). The expression patterns of DEGs and DAMs in the first and ninth quadrants were opposite, implying that the changes in these DAMs might be negatively regulated by DEGs. In the third and seventh quadrants, the expression patterns of DEGs and DAMs showed consistency, implying that the variations of these DAMs might be positively regulated by the corresponding DEGs. In addition, during the processes of V991 infection in TM-1 and Hai7124 (0, 1, and 2 days), the metabolite putrescine was positively regulated by GH_D04G0634 , GH_D11G2329 , and GH_D13G1106 . The correlation clustering heatmap results showed that the red part represents a positive correlation between DEGs and DAMs, while the green part represents a negative correlation. Notably, putrescine was significantly positively correlated with GH_D11G2329 . Based on the joint analysis of DEGs and DAMs, it could be speculated that the glutathione metabolism pathway is vital for resisting Vd invasion. The correlation analysis revealed a significant association between putrescine and corresponding DEGs, such as the gene-encoding glutathione S-transferase (GST). Network analysis demonstrated that DEGs and DAMs in the glutathione metabolism signaling pathway formed hub genes in the network, supporting the aforementioned correlation analysis ( E and ). Additionally, a schematic diagram of the glutathione metabolism pathway was constructed . In total, 9 DEGs were screened in TM-1 and Hai7124 at 0, 1, and 2 DAI through transcriptomic analysis, which belonged to GST; glutathione dehydrogenase/transferase (DHAR); peroxiredoxin 6 (PRDX6); isocitrate dehydrogenase 1 (IDH1); and γ-glutamylcyclotransferase (GGCT). Meanwhile, 5 DAMs involved in this pathway were identified by metabolomic analysis, namely putrescine, spermine, glycine, L-cysteine, and 5-oxoproline. In the findings from the joint analysis of transcriptomics and metabolomics, the DEG GH_D11G2329 ( GHGSTF8 ) participating in the glutathione metabolism pathway showed an up-regulated expression pattern in TM-1 during V991 infection, indicating a potential role in VW resistance.
To validate the accuracy of the transcriptomic analysis results, 20 genes were randomly selected and analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) experiments . Detailed information on the primer design is listed in . The housekeeping gene GhUBQ7 (DQ116441) served as a reference control for the analysis of relative quantification. The results confirmed that the expression trends observed in qRT-PCR were consistent with the transcriptomic sequencing results, indicating the reliability of the transcriptomic sequencing.
Cotton, as an important economic crop, makes great contributions to global economic development. Currently, more than 50 species have been identified within the cotton genus, among which G. hirsutum and G. barbadense are widely cultivated allotetraploid species . G. hirsutum has the traits of high yields yet average fiber quality, while G. barbadense exhibits the opposite characteristics . However, the VW disease could cause annual yield losses of approximately 10–35%, since the majority of G. hirsutum varieties are susceptible to VW, ultimately posing a significant economic threat worldwide . Conventional control measures such as crop rotation or chemical fumigation have been proved ineffective against VW, due to fact that the pathogen survives in the environment in the form of hyphae, spores, and microsclerotia. It is stimulated by cotton root exudates and begins to initiate infection at the root tips. During the infection process, the hyphae penetrate the root epidermal cells, move through the xylem, and colonize the vascular tissues, eventually reaching the petiole base. This can lead to browning of the cotton vascular bundles, leaf yellowing, wilting, defoliation, and even plant death . Moreover, the pathogens exist in the soil in the form of dormant spores, enabling them to infect multiple generations of crops . Therefore, it is necessary for breeders to focus on developing resistant varieties to meet production needs. However, the condition we faced is that G. hirsutum varieties lack resistance genes and quantitative trait loci (QTL) associated with VW . To address this issue, introducing genes of VW resistance from G. barbadense into G. hirsutum provides a useful strategy to significantly enhance cotton defense . Meanwhile, key SNP loci related to VW resistance in G. hirsutum and G. barbadense could be used to identify resistance genes and breed resistant varieties. For instance, critical SNP substitutions in GhWAKL14 (A/C) resulted in amino acid changes (S/R), enhancing resistance of G . hirsutum but rendering G. barbadense susceptible to Fusarium wilt . Similarly, critical SNP substitutions in GhGLR4.8 (C/A) led to amino acid alterations (L/I), enhancing Fusarium wilt resistance in G. hirsutum . Similar methods have also been applied to the defense mechanisms of economically important crops against pathogens, such as onions , wheat , soybeans , and citrus . 3.1. RNA-Seq of Cotton in Response to VW Currently, RNA-seq has been widely applied to study the interaction mechanisms between plants and pathogens, such as in maize , wheat , and rice . In this study, RNA-seq analysis was performed on the roots of TM-1 and Hai7124 at 0, 1, and 2 DPAs after VW infection. Pairwise analysis between different samples identified a total of 39,976 DEGs. Trend analysis of temporal expression patterns of TM-1 and Hai7124 DEGs revealed three common expression patterns. Expression profile 0 showed a continuous downregulation trend, which was more prevalent in the susceptible TM-1 than in the resistant Hai7124. Expression profile 7 exhibited a continuous upregulation trend, with TM-1 showing more key pathways related to growth and development, including ribosome replication, base excision repair, nitrogen metabolism, and endocytosis. In contrast, Hai7124 showed more active pathways related to plant defense, including secondary metabolite biosynthesis, phenylpropane biosynthesis, flavonoid biosynthesis, and plant–pathogen interactions. The findings indicate that Hai7124 may possess the key genes conferring resistance to VW. Research indicates that during VW infection, cotton notably increases the accumulation of secondary metabolites . The phenylpropanoid metabolic pathway produces numerous natural compounds, such as flavonoids and lignin, which are extensively involved in various physiological activities in plants . In cotton, the silencing of the GhCOMT gene results in reduced lignin content and decreased resistance to Vd . Conversely, overexpression of GhLac1 leads to increased lignin content and enhanced resistance to Vd . Flavonoid biosynthesis is crucial for muskmelon defense against downy mildew . KEGG-enriched pathways via longitudinal and transverse comparisons of TM-1 and Hai7124 DEGs included the glutathione metabolism pathway. Studies indicated that glutathione metabolism is crucial for antioxidant stress and pathogenicity within Fusarium graminearum , cadmium tolerance in Arabidopsis , and early resistance to Bacterial wilt in tobacco . This suggested that our RNA-seq results highly align with these findings, indicating them to be crucial for combating VW infection. 3.2. Metabolomic Analysis of Cotton in Response to VW Currently, metabolomics has been primarily applied to analyze the types, quantities, intrinsic factors, and variations in plant metabolites under different environmental conditions, making it a valuable tool for studying plant–pathogen interactions . In this study, we identified altogether 402 DAMs through pairwise comparisons. K-means clustering analysis revealed that the expression levels of glycerophospholipids and fatty acyls in TM-1 and Hai7124 increased continuously after the Vd infection. Previous studies have indicated that the accumulation of glycerophospholipids is vital for barley under salt stress ; compounds composed of flavonoids, amino acids, and glycerophospholipids in Tibetan hulless barley respond to osmotic stress (cold, high salt, and drought) ; metabolites such as fatty acyls are significantly induced in salt-tolerant wild rice compared to salt-sensitive rice . Therefore, it is speculated that glycerophospholipids and fatty acyls play key roles in early resistance to VW invasion. In the longitudinal comparison analysis of TM-1 and Hai7124 infected with V991, a total of 22 DAMs were identified. KEGG analysis of these 22 DAMs indicated a significant enrichment in the glutathione metabolism pathway. Currently, research on cotton VW has mainly focused on gene expression levels, with fewer studies on the metabolite level. The findings of this study complement this aspect and establish a basis for cotton resistance to VW. Metabolomic analysis has been widely applied in other plant disease resistance studies. For example, under Phytophthora infestans stress, resistant potato varieties accumulate salicylic acid, phenylpropanoids, terpenoids, and arachidonic acid, which is vital for thickening the cell wall . In multiomics studies, metabolites such as linolenic acid, vitamin E, choline, and riboflavin contribute to enhancing resistance to rice blast disease . In Fusarium wilt disease research in wheat, the accumulation of proline (Pro) and alanine (Ala) enhances wheat resistance, whereas a decrease in cysteine (Cys) exacerbates sensitivity . After infection with tomato yellow leaf curl virus, significant changes in the abundance of polyamines, phenols, and indoles were detected in resistant and susceptible tomato varieties. Salicylic acid accumulated significantly in resistant tomatoes, suggesting its important role in tomato disease resistance . 3.3. Conjoint Analysis of Metabolome and Transcriptome in Cotton Response to VW When pathogens invade plants, they trigger the expression of genes associated with plant defense mechanisms, thereby synthesizing disease-resistant proteins or other compounds that resist pathogen invasion. Therefore, the combined analysis of transcriptome and metabolome is utilized to screen target genes and to elucidate target metabolic pathways . For example, the enzymes encoded by the tau cluster of the GST family may play a crucial role in maintaining the delicate balance between the production and scavenging of H 2 O 2 . This establishes a new equilibrium that enhances the functions of CAT and POD, thereby strengthening the plant’s response to Vd . This study identified nine enriched pathways in cotton response to VW through combined KEGG analysis of transcriptome and metabolome. The longitudinal and transverse pairwise analysis of DEGs in the transcriptome and the longitudinal comparison analysis of DAMs in the metabolome collectively enriched the glutathione metabolism pathway. The results of the nine-quadrant map and correlation clustering heatmap indicated that the metabolite spermine in the glutathione metabolism pathway was positively regulated by the annotated DEGs in this pathway. Furthermore, the construction of the glutathione metabolism pathway diagram revealed the involvement of spermine, spermidine, glutamic acid, L-cysteine, and 5-oxoproline in this pathway. Exogenous application of polyamines (spermine, spermidine, and spermine) significantly increased the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR), maintaining their internal homeostasis of apricot and enhancing its resistance to black spot disease . Glycine can increase soil absorption of heavy metals, alleviating plant toxicity caused by heavy metals . Hydrogen sulfide and cysteine can alleviate cadmium-induced growth inhibition in Arabidopsis and enhance its tolerance to cadmium . In the study of necrotic pathogens, it was found that the infected alfalfa significantly accumulated 5-oxoproline and malic acid, possibly enhancing its resistance to necrotic pathogens . RNA-seq identified GST, DHAR, PRDX6, IDH1, and GGCT as participating in this pathway, with correlation analysis showing a significant association between putrescine and the gene-encoding GST. In this study, the DEG GH_D11G2329 ( GSTF8 ) was selected from the glutathione metabolism pathway. GSTs are a multifunctional enzyme encoded by a multigene superfamily that plays a detoxification role in various plants . In the study of salt tolerance in the rice landrace HD961, a comprehensive analysis of the transcriptome and metabolome revealed that the glutathione metabolism pathway was significantly enriched, and a total of seven metabolites and 48 DEGs identified, most of which belong to the GST family. Among these, L-cysteine was the most active compound in response to salt stress. GSTU2 showed a significant correlation with metabolites such as L-cysteine, spermidine, and L-ornithine. Additionally, there was a notable correlation between GSH and 16 genes. These findings suggest that these specific genes and glutathione metabolites play a crucial role in rice’s response to salt stress . Previous research has emphasized the vital importance of GSTs in combating peanut rust , cotton VW , and wheat Powdery mildew . SA (salicylic acid) is one of the primary defense-related hormones involved in the response to various biotrophic and hemibiotrophic pathogens, and plays an auxiliary role against necrotrophic pathogens . Vd initially behaves as a biotrophic pathogen during the early stages of infection but shifts to a necrotrophic lifestyle in the later stages. Therefore, the SA signaling pathway is required to confer resistance to Vd . Additionally, the complex metabolic pathways of plant secondary metabolites often intersect with SA signaling. In the glutathione metabolism pathway, GaGSTF9 may regulate reactive oxygen species content via catalyzing the reduction in tripeptide glutathione (GSH), thereby positively influencing cotton resistance to Vd and SA content . Additionally, the constitutive overexpression of the gene encoding the key rate-limiting enzyme in spermine biosynthesis, GhSAMDC (S-adenosylmethionine decarboxylase), in Arabidopsis thaliana enhances resistance to Vd by activating SA signaling pathways . Therefore, it is believed that the glutathione metabolism pathway plays an important role in early defense mechanisms of cotton against VW infection. In consideration of the relative disadvantages of traditional hybridization, self-cross, and backcross techniques adopted between TM-1 and Hai7124, such as long period, large population, and heavy workload, the candidate genes are even suggested to perform the genetic transformation for further cotton breeding. The more precise and efficient methods, including transgenic modification and gene editing by CRISPR-cas9 system, could break the reproductive isolation and trait linkage, finally achieving synchronous improvement in fiber yield, quality, and multiple resistances.
Currently, RNA-seq has been widely applied to study the interaction mechanisms between plants and pathogens, such as in maize , wheat , and rice . In this study, RNA-seq analysis was performed on the roots of TM-1 and Hai7124 at 0, 1, and 2 DPAs after VW infection. Pairwise analysis between different samples identified a total of 39,976 DEGs. Trend analysis of temporal expression patterns of TM-1 and Hai7124 DEGs revealed three common expression patterns. Expression profile 0 showed a continuous downregulation trend, which was more prevalent in the susceptible TM-1 than in the resistant Hai7124. Expression profile 7 exhibited a continuous upregulation trend, with TM-1 showing more key pathways related to growth and development, including ribosome replication, base excision repair, nitrogen metabolism, and endocytosis. In contrast, Hai7124 showed more active pathways related to plant defense, including secondary metabolite biosynthesis, phenylpropane biosynthesis, flavonoid biosynthesis, and plant–pathogen interactions. The findings indicate that Hai7124 may possess the key genes conferring resistance to VW. Research indicates that during VW infection, cotton notably increases the accumulation of secondary metabolites . The phenylpropanoid metabolic pathway produces numerous natural compounds, such as flavonoids and lignin, which are extensively involved in various physiological activities in plants . In cotton, the silencing of the GhCOMT gene results in reduced lignin content and decreased resistance to Vd . Conversely, overexpression of GhLac1 leads to increased lignin content and enhanced resistance to Vd . Flavonoid biosynthesis is crucial for muskmelon defense against downy mildew . KEGG-enriched pathways via longitudinal and transverse comparisons of TM-1 and Hai7124 DEGs included the glutathione metabolism pathway. Studies indicated that glutathione metabolism is crucial for antioxidant stress and pathogenicity within Fusarium graminearum , cadmium tolerance in Arabidopsis , and early resistance to Bacterial wilt in tobacco . This suggested that our RNA-seq results highly align with these findings, indicating them to be crucial for combating VW infection.
Currently, metabolomics has been primarily applied to analyze the types, quantities, intrinsic factors, and variations in plant metabolites under different environmental conditions, making it a valuable tool for studying plant–pathogen interactions . In this study, we identified altogether 402 DAMs through pairwise comparisons. K-means clustering analysis revealed that the expression levels of glycerophospholipids and fatty acyls in TM-1 and Hai7124 increased continuously after the Vd infection. Previous studies have indicated that the accumulation of glycerophospholipids is vital for barley under salt stress ; compounds composed of flavonoids, amino acids, and glycerophospholipids in Tibetan hulless barley respond to osmotic stress (cold, high salt, and drought) ; metabolites such as fatty acyls are significantly induced in salt-tolerant wild rice compared to salt-sensitive rice . Therefore, it is speculated that glycerophospholipids and fatty acyls play key roles in early resistance to VW invasion. In the longitudinal comparison analysis of TM-1 and Hai7124 infected with V991, a total of 22 DAMs were identified. KEGG analysis of these 22 DAMs indicated a significant enrichment in the glutathione metabolism pathway. Currently, research on cotton VW has mainly focused on gene expression levels, with fewer studies on the metabolite level. The findings of this study complement this aspect and establish a basis for cotton resistance to VW. Metabolomic analysis has been widely applied in other plant disease resistance studies. For example, under Phytophthora infestans stress, resistant potato varieties accumulate salicylic acid, phenylpropanoids, terpenoids, and arachidonic acid, which is vital for thickening the cell wall . In multiomics studies, metabolites such as linolenic acid, vitamin E, choline, and riboflavin contribute to enhancing resistance to rice blast disease . In Fusarium wilt disease research in wheat, the accumulation of proline (Pro) and alanine (Ala) enhances wheat resistance, whereas a decrease in cysteine (Cys) exacerbates sensitivity . After infection with tomato yellow leaf curl virus, significant changes in the abundance of polyamines, phenols, and indoles were detected in resistant and susceptible tomato varieties. Salicylic acid accumulated significantly in resistant tomatoes, suggesting its important role in tomato disease resistance .
When pathogens invade plants, they trigger the expression of genes associated with plant defense mechanisms, thereby synthesizing disease-resistant proteins or other compounds that resist pathogen invasion. Therefore, the combined analysis of transcriptome and metabolome is utilized to screen target genes and to elucidate target metabolic pathways . For example, the enzymes encoded by the tau cluster of the GST family may play a crucial role in maintaining the delicate balance between the production and scavenging of H 2 O 2 . This establishes a new equilibrium that enhances the functions of CAT and POD, thereby strengthening the plant’s response to Vd . This study identified nine enriched pathways in cotton response to VW through combined KEGG analysis of transcriptome and metabolome. The longitudinal and transverse pairwise analysis of DEGs in the transcriptome and the longitudinal comparison analysis of DAMs in the metabolome collectively enriched the glutathione metabolism pathway. The results of the nine-quadrant map and correlation clustering heatmap indicated that the metabolite spermine in the glutathione metabolism pathway was positively regulated by the annotated DEGs in this pathway. Furthermore, the construction of the glutathione metabolism pathway diagram revealed the involvement of spermine, spermidine, glutamic acid, L-cysteine, and 5-oxoproline in this pathway. Exogenous application of polyamines (spermine, spermidine, and spermine) significantly increased the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione reductase (GR), maintaining their internal homeostasis of apricot and enhancing its resistance to black spot disease . Glycine can increase soil absorption of heavy metals, alleviating plant toxicity caused by heavy metals . Hydrogen sulfide and cysteine can alleviate cadmium-induced growth inhibition in Arabidopsis and enhance its tolerance to cadmium . In the study of necrotic pathogens, it was found that the infected alfalfa significantly accumulated 5-oxoproline and malic acid, possibly enhancing its resistance to necrotic pathogens . RNA-seq identified GST, DHAR, PRDX6, IDH1, and GGCT as participating in this pathway, with correlation analysis showing a significant association between putrescine and the gene-encoding GST. In this study, the DEG GH_D11G2329 ( GSTF8 ) was selected from the glutathione metabolism pathway. GSTs are a multifunctional enzyme encoded by a multigene superfamily that plays a detoxification role in various plants . In the study of salt tolerance in the rice landrace HD961, a comprehensive analysis of the transcriptome and metabolome revealed that the glutathione metabolism pathway was significantly enriched, and a total of seven metabolites and 48 DEGs identified, most of which belong to the GST family. Among these, L-cysteine was the most active compound in response to salt stress. GSTU2 showed a significant correlation with metabolites such as L-cysteine, spermidine, and L-ornithine. Additionally, there was a notable correlation between GSH and 16 genes. These findings suggest that these specific genes and glutathione metabolites play a crucial role in rice’s response to salt stress . Previous research has emphasized the vital importance of GSTs in combating peanut rust , cotton VW , and wheat Powdery mildew . SA (salicylic acid) is one of the primary defense-related hormones involved in the response to various biotrophic and hemibiotrophic pathogens, and plays an auxiliary role against necrotrophic pathogens . Vd initially behaves as a biotrophic pathogen during the early stages of infection but shifts to a necrotrophic lifestyle in the later stages. Therefore, the SA signaling pathway is required to confer resistance to Vd . Additionally, the complex metabolic pathways of plant secondary metabolites often intersect with SA signaling. In the glutathione metabolism pathway, GaGSTF9 may regulate reactive oxygen species content via catalyzing the reduction in tripeptide glutathione (GSH), thereby positively influencing cotton resistance to Vd and SA content . Additionally, the constitutive overexpression of the gene encoding the key rate-limiting enzyme in spermine biosynthesis, GhSAMDC (S-adenosylmethionine decarboxylase), in Arabidopsis thaliana enhances resistance to Vd by activating SA signaling pathways . Therefore, it is believed that the glutathione metabolism pathway plays an important role in early defense mechanisms of cotton against VW infection. In consideration of the relative disadvantages of traditional hybridization, self-cross, and backcross techniques adopted between TM-1 and Hai7124, such as long period, large population, and heavy workload, the candidate genes are even suggested to perform the genetic transformation for further cotton breeding. The more precise and efficient methods, including transgenic modification and gene editing by CRISPR-cas9 system, could break the reproductive isolation and trait linkage, finally achieving synchronous improvement in fiber yield, quality, and multiple resistances.
4.1. Cultivation of Materials and Preparation of Strains The cotton varieties TM-1 ( G. hirsutum ) and Hai7124 ( G. barbadense ) were preserved in our laboratory (TM-1 and Hai7124 were provided by Dr. Fang Liu’s research group at the Institute of Cotton Research). TM-1 and Hai7124 are two important cultivated cotton varieties. TM-1 exhibits stable agronomic traits and medium-level fiber quality, and it does not contain Bt, making it an excellent recipient for the introduction of exogenous genes. It is frequently used in constructing genetic linkage maps, serving as background material for developing substitution lines . Hai7124 is characterized by its ultra-long or superfine quality fibers and exhibits strong resistance to VW . The VW pathogen strain used was the highly pathogenic isolate V991 of Vd Kleb (V991 was provided by Professor Yingfan Cai from Henan University). The seeds of both cotton varieties were defuzzed using concentrated sulfuric acid, thoroughly washed with water, and air-dried. Uniform and fully developed seeds were selected and planted in a sterilized substrate composed of sand and vermiculite in a ratio of 3:2 in the greenhouse of Anyang Institute of Technology. The cultivation took place within a controlled greenhouse environment maintained at a temperature of 28 °C, adhering to a photoperiod of 16 h of light followed by 8 h of darkness, maintaining a relative humidity of 68%. Once the first true leaves of the cotton plants fully expanded, root tissues with consistent growth were collected as the wild-type (WT) control treatment. These roots were quickly transferred into collection tube that had been pre-cooled in liquid nitrogen to ensure the preservation of the samples. They were subsequently cryopreserved in liquid nitrogen and stored in an ultra-low temperature freezer set at −80 °C for future use. Additionally, we selected cotton plants exhibiting consistent growth for infection using the V991 strain (2 mL of V991 per plant), and root tissues were collected at days 1 and 2 post-infection. We rinsed the roots with tap water to remove soil, and then we collected the primary roots of the cotton plants below the hypocotyl. We quickly wrapped the root in aluminum foil and placed it into a pre-cooled collection tube with liquid nitrogen (0.5 g per replicate, consistent with the collection method for WT). One portion of the root tissues was allocated for transcriptome sequencing, while another portion was designated for metabolome sequencing. The preserved pathogen strain was cultured on potato dextrose agar (PDA) plates. These plates were placed in an inverted position in a dark incubator with temperature controlled at 25 °C for 7 days. Subsequently, approximately 2 mm 2 fungal plaques were transferred to Czapek Dox liquid medium using sterilized toothpicks and placed at 25 °C in the dark incubator with a shaking speed of 150 r/min for 7 days. Prior to inoculation, the mycelium was filtered through four layers of gauze. The density of the resulting spore suspension was then measured using a hemocytometer. Then the suspension was diluted with ddH 2 O to a concentration of 1 × 10 7 spores/mL, and the cotton roots were inoculated . 4.2. Extraction of RNA and Construction of Library The FastPure Universal Plant Total RNA Isolation Kit (RC411) from Vazyme was used to isolate the total RNA. The RNA’s concentration and quality were assessed using a NanoDrop 2000 spectrophotometer, and agarose gel electrophoresis was performed to check for RNA contamination and degradation. Samples that passed the quality standards were forwarded to Igenebook Biotechnology Co., Ltd., Wuhan, China for library construction and sequencing. The library construction used the NEBNext ® Ultra™ RNA Library Prep Kit (NEB, Ipswich, MA, USA), and PCR amplification was performed to obtain cDNA libraries. A Qubit 4.0 Fluorometer was employed to measure the concentration of the libraries, while the fragment sizes were assessed with a QSep400. The Qubit Fluorometer was again used to quantify the libraries. Once the libraries passed quality control, 18 cDNA libraries (from two cotton strains at 0, 1, and 2 days) were sequenced using the combinatorial probe-anchor synthesis (cPAS) technology. 4.3. Transcriptome Sequencing The initial sequencing data were processed to filter out impurities to obtain clean reads. The reference genome of Gossypium hirsutum was downloaded, and alignment was performed using HISAT2 ( https://www.cottongen.org/species/Gossypium_hirsutum/UTX-TM1_v2.1 , accessed on 13 March 2024). The clean reads were assembled and expression levels were evaluated using StringTie version 2.0.4 software. RNA differential expression analysis between two different samples was performed by DESeq2 software ( https://www.omicshare.com/tools/ , accessed on 21 August 2024) (and by the edgeR package in R version 4.4.1 for comparisons between two samples). The genes/transcripts identified based on a false discovery rate (FDR) < 0.05 and absolute fold change ≥ 2 were considered differentially expressed genes/transcripts. OmicShare was employed to conduct functional enrichment analysis for KEGG pathways and GO categories ( https://www.omicshare.com/tools/ , accessed on 23 August 2024). 4.4. Metabolic Analysis (LC−MS/MS) Root tissue samples were taken at 0, 1, and 2 DAI after being inoculated with V991 and subsequently sent to Igenebook Biotechnology Co., Ltd. for untargeted metabolite profiling. The extraction and analysis of the metabolites were performed through liquid chromatography/mass spectrometry (LC-MS) . The raw data files were loaded into TraceFinder version 3.2.0 for analysis. Each metabolite was screened according to criteria including retention time and mass-to-charge ratio. To ensure accurate identification of metabolites, peak alignment was conducted on various samples. During the alignment process, we maintained a retention time deviation of 0.2 min and allowed for a mass deviation of 5 parts per million (ppm) to ensure accurate identification. Peak areas were quantified, and spectral matching was conducted against mzCloud alongside a locally established database ( https://www.mzcloud.org/ , accessed on 30 January 2024). In order to ensure accuracy in the data, the raw quantitative results were subjected to normalization processes. This step was crucial for facilitating the identification and relative quantification of metabolites present in the samples under investigation. The metabolites that were identified during this process were meticulously annotated with reference to several authoritative databases. Specifically, the KEGG database ( https://www.genome.jp/kegg/pathway.html , accessed on 31 January 2024), the HMDB database ( https://hmdb.ca/metabolites , accessed on 31 January 2024), and the LIPIDMaps database ( http://www.lipidmaps.org/ , accessed on 31 January 2024) were employed to ensure comprehensive and accurate annotations of the metabolites. DAMs were selected using a threshold of variable importance in projection (VIP) ≥ 1, a fold change of 2, and p ≤ 0.05. The method chosen for calculating the p -value is ANOVA ( https://cloud.metware.cn , accessed on 17 August 2024). Finally, pathway and other functional analyses were conducted to uncover the biological significance of the metabolites. 4.5. Gene Expression Analyses via qRT-PCR In order to ensure the precision and dependability of the transcriptome data, a selection of 20 genes was randomly chosen for validation through real-time quantitative PCR (qRT-PCR). GbUBQ7 was identified as the reference gene candidate based on the sequencing data from the transcriptome. The design of specific primers was accomplished using the Primer-BLAST tool available on the NCBI website, with primer sequences detailed in . The RNA samples used were the same as those returned from the transcriptome sequencing conducted by iGeneTech Co., Ltd., Seoul, Republic of Korea cDNA was synthesized from RNA through reverse transcription using the HiScript III RT SuperMix specifically designed for quantitative PCR, which includes a gDNA wiper to eliminate genomic DNA contamination. Subsequently, qRT-PCR assays were conducted with a ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China). The quantification of gene expression levels was carried out utilizing the 2 −ΔΔCt approach . Three independent biological replicates along with three technical replicates were set up for both the control and experimental groups to ensure reproducibility and data reliability.
The cotton varieties TM-1 ( G. hirsutum ) and Hai7124 ( G. barbadense ) were preserved in our laboratory (TM-1 and Hai7124 were provided by Dr. Fang Liu’s research group at the Institute of Cotton Research). TM-1 and Hai7124 are two important cultivated cotton varieties. TM-1 exhibits stable agronomic traits and medium-level fiber quality, and it does not contain Bt, making it an excellent recipient for the introduction of exogenous genes. It is frequently used in constructing genetic linkage maps, serving as background material for developing substitution lines . Hai7124 is characterized by its ultra-long or superfine quality fibers and exhibits strong resistance to VW . The VW pathogen strain used was the highly pathogenic isolate V991 of Vd Kleb (V991 was provided by Professor Yingfan Cai from Henan University). The seeds of both cotton varieties were defuzzed using concentrated sulfuric acid, thoroughly washed with water, and air-dried. Uniform and fully developed seeds were selected and planted in a sterilized substrate composed of sand and vermiculite in a ratio of 3:2 in the greenhouse of Anyang Institute of Technology. The cultivation took place within a controlled greenhouse environment maintained at a temperature of 28 °C, adhering to a photoperiod of 16 h of light followed by 8 h of darkness, maintaining a relative humidity of 68%. Once the first true leaves of the cotton plants fully expanded, root tissues with consistent growth were collected as the wild-type (WT) control treatment. These roots were quickly transferred into collection tube that had been pre-cooled in liquid nitrogen to ensure the preservation of the samples. They were subsequently cryopreserved in liquid nitrogen and stored in an ultra-low temperature freezer set at −80 °C for future use. Additionally, we selected cotton plants exhibiting consistent growth for infection using the V991 strain (2 mL of V991 per plant), and root tissues were collected at days 1 and 2 post-infection. We rinsed the roots with tap water to remove soil, and then we collected the primary roots of the cotton plants below the hypocotyl. We quickly wrapped the root in aluminum foil and placed it into a pre-cooled collection tube with liquid nitrogen (0.5 g per replicate, consistent with the collection method for WT). One portion of the root tissues was allocated for transcriptome sequencing, while another portion was designated for metabolome sequencing. The preserved pathogen strain was cultured on potato dextrose agar (PDA) plates. These plates were placed in an inverted position in a dark incubator with temperature controlled at 25 °C for 7 days. Subsequently, approximately 2 mm 2 fungal plaques were transferred to Czapek Dox liquid medium using sterilized toothpicks and placed at 25 °C in the dark incubator with a shaking speed of 150 r/min for 7 days. Prior to inoculation, the mycelium was filtered through four layers of gauze. The density of the resulting spore suspension was then measured using a hemocytometer. Then the suspension was diluted with ddH 2 O to a concentration of 1 × 10 7 spores/mL, and the cotton roots were inoculated .
The FastPure Universal Plant Total RNA Isolation Kit (RC411) from Vazyme was used to isolate the total RNA. The RNA’s concentration and quality were assessed using a NanoDrop 2000 spectrophotometer, and agarose gel electrophoresis was performed to check for RNA contamination and degradation. Samples that passed the quality standards were forwarded to Igenebook Biotechnology Co., Ltd., Wuhan, China for library construction and sequencing. The library construction used the NEBNext ® Ultra™ RNA Library Prep Kit (NEB, Ipswich, MA, USA), and PCR amplification was performed to obtain cDNA libraries. A Qubit 4.0 Fluorometer was employed to measure the concentration of the libraries, while the fragment sizes were assessed with a QSep400. The Qubit Fluorometer was again used to quantify the libraries. Once the libraries passed quality control, 18 cDNA libraries (from two cotton strains at 0, 1, and 2 days) were sequenced using the combinatorial probe-anchor synthesis (cPAS) technology.
The initial sequencing data were processed to filter out impurities to obtain clean reads. The reference genome of Gossypium hirsutum was downloaded, and alignment was performed using HISAT2 ( https://www.cottongen.org/species/Gossypium_hirsutum/UTX-TM1_v2.1 , accessed on 13 March 2024). The clean reads were assembled and expression levels were evaluated using StringTie version 2.0.4 software. RNA differential expression analysis between two different samples was performed by DESeq2 software ( https://www.omicshare.com/tools/ , accessed on 21 August 2024) (and by the edgeR package in R version 4.4.1 for comparisons between two samples). The genes/transcripts identified based on a false discovery rate (FDR) < 0.05 and absolute fold change ≥ 2 were considered differentially expressed genes/transcripts. OmicShare was employed to conduct functional enrichment analysis for KEGG pathways and GO categories ( https://www.omicshare.com/tools/ , accessed on 23 August 2024).
Root tissue samples were taken at 0, 1, and 2 DAI after being inoculated with V991 and subsequently sent to Igenebook Biotechnology Co., Ltd. for untargeted metabolite profiling. The extraction and analysis of the metabolites were performed through liquid chromatography/mass spectrometry (LC-MS) . The raw data files were loaded into TraceFinder version 3.2.0 for analysis. Each metabolite was screened according to criteria including retention time and mass-to-charge ratio. To ensure accurate identification of metabolites, peak alignment was conducted on various samples. During the alignment process, we maintained a retention time deviation of 0.2 min and allowed for a mass deviation of 5 parts per million (ppm) to ensure accurate identification. Peak areas were quantified, and spectral matching was conducted against mzCloud alongside a locally established database ( https://www.mzcloud.org/ , accessed on 30 January 2024). In order to ensure accuracy in the data, the raw quantitative results were subjected to normalization processes. This step was crucial for facilitating the identification and relative quantification of metabolites present in the samples under investigation. The metabolites that were identified during this process were meticulously annotated with reference to several authoritative databases. Specifically, the KEGG database ( https://www.genome.jp/kegg/pathway.html , accessed on 31 January 2024), the HMDB database ( https://hmdb.ca/metabolites , accessed on 31 January 2024), and the LIPIDMaps database ( http://www.lipidmaps.org/ , accessed on 31 January 2024) were employed to ensure comprehensive and accurate annotations of the metabolites. DAMs were selected using a threshold of variable importance in projection (VIP) ≥ 1, a fold change of 2, and p ≤ 0.05. The method chosen for calculating the p -value is ANOVA ( https://cloud.metware.cn , accessed on 17 August 2024). Finally, pathway and other functional analyses were conducted to uncover the biological significance of the metabolites.
In order to ensure the precision and dependability of the transcriptome data, a selection of 20 genes was randomly chosen for validation through real-time quantitative PCR (qRT-PCR). GbUBQ7 was identified as the reference gene candidate based on the sequencing data from the transcriptome. The design of specific primers was accomplished using the Primer-BLAST tool available on the NCBI website, with primer sequences detailed in . The RNA samples used were the same as those returned from the transcriptome sequencing conducted by iGeneTech Co., Ltd., Seoul, Republic of Korea cDNA was synthesized from RNA through reverse transcription using the HiScript III RT SuperMix specifically designed for quantitative PCR, which includes a gDNA wiper to eliminate genomic DNA contamination. Subsequently, qRT-PCR assays were conducted with a ChamQ Universal SYBR qPCR Master Mix (Vazyme, Nanjing, China). The quantification of gene expression levels was carried out utilizing the 2 −ΔΔCt approach . Three independent biological replicates along with three technical replicates were set up for both the control and experimental groups to ensure reproducibility and data reliability.
In this study, to identify key DEGs and DAMs related to resistance to VW in G. hirsutum and G. barbadense , and cultivate new disease-resistant varieties, RNA-seq and metabolomic analyses were conducted on root tissues of the resistant material Hai7124 and the susceptible material TM-1 at the early stages (0, 1, and 2 DAI) of V991 infection. The analysis of DEGs and DAMs using KEGG enrichment demonstrated that nine pathways were co-enriched, including glutathione metabolism, propionate metabolism, and pyrimidine metabolism. Through joint analysis, the glutathione metabolism pathway was identified as potentially significantly contributing to the early response of cotton to VW infection. A glutathione metabolism pathway map was constructed, revealing a significant positive correlation between the metabolite putrescine and DEGs within GSTs. Based on the comprehensive analysis, it is suggested that the DEG GH_D11G2329 ( GSTF8 ) could play a role in cotton response to VW infection. These results provided abundant information for screening the crucial VW-resistant genes and metabolites, thereby establishing a strong basis for further studying the molecular mechanism behind plant defense against VW infection.
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Targeted delivery and stimulus-responsive release of anticancer drugs for efficient chemotherapy | b33e9633-3513-4511-b57a-0d89101c6ac1 | 8530493 | Pharmacology[mh] | Introduction Although considerable progress has been achieved in the fields of radiotherapy and surgery, chemotherapy still plays an irreplaceable role in the treatment of various types of cancer (Shi et al., ; Wu et al., ; Wang et al., ; Zhang et al., ). Doxorubicin hydrochloride (DOX) is one of the most commonly used antibiotics that can effectively reduce the growth and progression of cancer through several pathways, such as mitochondrial depolarization and nuclear DNA damage (Song et al., ; Xiong et al., ). However, the main hurdles that limit its use include severe toxicity, low bioavailability, serious adverse effects on normal tissues, and even cancer relapse in many clinical indications (Perez-Herrero & Fernandez-Medarde, ; Kim et al., ; Mi et al., ). Nanoparticles that can selectively and efficiently deliver drugs to tumor tissues and kill malignant cells have attracted great research interest as one of the most promising strategies to address these issues (Torchilin, ; Cabral & Kataoka, ; Sindhwani et al., ; Izci et al., ). In the past decade, a variety of vectors, such as cationic liposomes (Vaidya et al., ), polymer micelles (Yang et al., ), cell exosomes (Barile & Vassalli, ), and gold/magnetic nanoparticles (Singh et al., ) with targeting ligands (e.g. proteins, small molecules, and polysaccharides) have been employed to construct drug delivery carriers to facilitate tumor accumulation and induce tumor cell death (Zhang et al., ; Yoo et al., ). However, there are some limitations to the clinical use of nanoparticle-mediated DOX therapy, in particular, the complex preparation process, which may lead to batch-to-batch variation of DOX loads. More importantly, hampered DOX release and inefficient intracellular target enrichment (e.g. mitochondria and nucleus) after nanoparticles administration may also hinder it therapeutic efficacy. Hitherto, diverse drug release mechanisms have attracted the interest of researchers to address this issue. They take advantage of the environmental differences between tumor cells and normal cells, such as lower oxygen levels and pH, higher thiol levels, and enzyme overexpression, to achieve the controlled release of anticancer drugs while reducing the side effects to normal tissues (Shi et al., ; Ma et al., ; Yi et al., ; Zha et al., ). In addition, to the best of our knowledge, calcium carbonate (CaCO 3 ) is sensitive to pH changes and can achieve controlled drug release through the acidic extracellular environment in solid tumor tissues and in the lysosomes inside cancer cells. Furthermore, Ca 2+ and CO 3 2− are naturally occurring ions, inherently possessing good biocompatibility and biosafety. Its capability to load various drugs and its large specific surface area also makes CaCO 3 an ideal drug vector for use in the treatment of cancer (Zhao et al., ; Dong et al., ; Dizaj et al., ; Xu et al., ). As it is well known, mitochondria and nucleus are two important intracellular therapeutic targets by DOX (Song et al., ; Xiong et al., ). Previous studies on DOX-loaded CaCO 3 delivery system (DOX/CaCO 3 system) are mainly focused on the effects of system on cell growth inhibition, cell cycle arrest, and cell apoptosis (Peng et al., ; Li et al., ; Yang et al., ). As far as we know, inadequate attention has been paid to study the effect of DOX/CaCO 3 system on its intracellular therapeutic targets. The purpose of our study is to develop a DOX/CaCO 3 system to effectively inhibit tumor growth as well as to study the effects of the system on mitochondrial morphologies, nuclear DNA damage, and diverse proteins involved in these processes to provide a more comprehensive understanding in this field. Herein, we used a modified nanoprecipitation technique to prepare a biotinylated hyaluronic acid (BHA)-guided pH-responsive CaCO 3 nanoparticle system to achieve targeted and controlled DOX delivery and provide effective cancer therapy . As depicted in , the DOX is encapsulated in the core composed of protamine sulfate (PS) and CaCO 3 , then BHA is modified onto the surface of the core. Biotin (vitamin B7) has been reported to bind to biotin receptors that are overexpressed on the surface of various tumor cells (Segura et al., ; Ren et al., ; Jelonek et al., ). Negatively charged hyaluronic acid (HA) has good biocompatibility, is capable of self-assembly, and improves tumor cell targeting efficiency because of the high expression of CD44 in various tumor cells (Mattheolabakis et al., ; He et al., ; Huang & Huang, ). With the aid of these functional components, the delivery system we fabricated can specifically deliver the anticancer drug DOX to tumor cells and mediate its efficient diffusion to the mitochondria and nuclei of its target cells. To confirm the functions of each component in the delivery vector, the physicochemical properties, antitumor efficacy, and systemic effects of the DOX-loaded nanoparticles were assessed. Briefly, because of the high specificity and affinity of BHA to tumor cells, the most obvious enrichment of DOX was observed in the tumor cells treated with DOX@BHNP. Due to the pH sensitivity of CaCO 3 , the nanoparticles were disassembled in the endosome and lysosome after endocytosis, and an obvious enrichment of DOX in the mitochondria and nuclei of the target cells was observed in the in vitro study. Consequently, DOX@BHNP system significantly destroyed the mitochondria, induced DNA damage, regulated the expression of diverse proteins involved in these process, caused cell cycle arrest and tumor cell apoptosis. The enhanced tumor inhibitory effects and reduced side effects observed in both in vitro and in vivo studies indicate the promising application of dual-functionalized nanoparticles in cancer treatment.
Materials and methods 2.1. Materials Hyaluronic acid was purchased from Shandong Freda Biochem Co., Ltd. (Jinan, China). Protamine sulfate, biotin, and ethylenediamine were purchased from Sigma-Aldrich (Shanghai, China). Analytical grade anhydrous calcium chloride (CaCl 2 ) and anhydrous sodium carbonate (Na 2 CO 3 ) were obtained from ANPEL Laboratory Technologies Co., Ltd. (Shanghai, China). 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was supplied by Amresco (Dallas, TX). Dimethylsulfoxide (DMSO) was purchased from Sigma-Aldrich (Shanghai, China). Doxorubicin hydrochloride, dimethylformamide (DMF), dicyclohexylcarbodiimide (DCC), N-hydroxysulfosuccinimide (sulfo-NHS), 1-ethyl-3-(dimethylaminopropyl)-carbodiimide (EDC), and 1-hydroxybenzotriazole (HOBt) were provided by J&K Scientific Co., Ltd. (Shanghai, China). 5,5′,6,6′-Tetrachloro-1,1′,3,3′-tetraethylbenzimidazolyl-carbocyanine iodide (JC-1) was purchased from Beyotime Biotechnology (Shanghai, China). The antibodies of p-H 2 AX, GAPDH, Bcl-2, and cleaved caspase-3 were provided by CST. Detailed information on the suppliers of cells and animals are provided in the Supporting Information (SI) . 2.2. Synthesis of biotinylated hyaluronic acid Biotin (2.44 g), DCC (2.47 g), and NHS (1.38 g) were added to a solution of DMF (10 mL) under continuous stirring and were reacted at 30 °C for 2 h. Then, the solvent was evaporated and precipitated in acetone to obtain biotin–NHS. Ethylenediamine trimethylamine (5 mL) was then added and the mixture was stirred at 30 °C for another 12 h to obtain biotin-ethylenediamine. After that, 170 mg of HA was dispersed in PBS buffer (1 mL, pH = 6.0) and activated, and 70 mg of biotin-ethylenediamine was added and continuously stirred at 30 °C for 24 h. The resulting solution was dialyzed and lyophilized to obtain BHA. Specific details about this experiment are provided in the SI. 2.3. Construction and characterization of drug-loaded nanoparticles Deionized water was used to dissolve the materials and their compositions were as follows: component A (35 μL): 30 μL Ca 2+ solution (CaCl 2 , 0.02 M)+5 μL anticancer DOX solution (10 μg µL −1 ); component B (55 μL): 40 µL CO 3 2– solution (Na 2 CO 3 , 0.01 M) and 15 µL PS solution (2 μg µL −1 ). Subsequently, component B was added to component A dropwise and mixed gently for 10 min to obtain a solution (90 μL) containing the hybrid nanoparticles DOX@PS/CaCO 3 (hereafter termed as ‘DOX@NP’). Mono-functionalized drug-loaded nanoparticles DOX@HA/PS/CaCO 3 (hereafter termed as ‘DOX@HNP’) were prepared by gently mixing 10 µL of HA solution (1 μg µL −1 ) with the DOX@NP solution for 10 min. Dual-functionalized DOX-loaded nanoparticles DOX@BHA/PS/CaCO 3 (hereafter termed as ‘DOX@BHNP’) were obtained by gently mixing the solution containing BHA (10 µg) with the DOX@NP solution (90 µL) for 10 min. The drug-loading capacity (DLC) and drug encapsulation efficiency (DEE) of the nanoparticles were determined through their absorbance at 488 nm using a spectrophotometer. Using an external calibration standard curve, the fluorescence intensity was converted into the concentration of non-encapsulated DOX, obtaining the DLC and DEE. A Zetasizer (Malvern Zetasizer Nano ZS90, Malvern, UK) was used to measure the size and zeta potential of the nanoparticles suspended in deionized water. All the data in our study were reported based on three independent measurements. The morphology of the BHA-functionalized drug delivery system was imaged using transmission electron microscopy (TEM) (Talo L120C G2). 2.4. In vitro drug release assay The drug release properties of DOX from our synthesized delivery system were investigated (DOX amount: 200 µg) using a dialysis bag (MWCO 3500) containing 4 mL of a drug-loaded nanoparticle suspension immersed in 10 mL of a Tris–HCl solution (pH = 5.3, 6.5, and 7.4). The samples were continuously oscillated in a shaking water bath at a speed of 150 rpm at a constant temperature of 37 °C. One milliliter of the sample was taken from the solution at different time points for fluorescence spectroscopy, and then replaced with the same volume of fresh medium. The concentration of released DOX was measured using a Cary Eclipse fluorescence spectrophotometer (Agilent Technologies, Santa Clara, CA). The fluorescence intensity of the blank Tris–HCl solution (pH = 5.3, 6.5, and 7.4) was also measured and used for correction. The experimental procedure performed was as previously described by Xu et al. . 2.5. In vitro cell uptake assay Cell internalization was qualitatively observed using a confocal laser scanning microscope (CLSM) (Zeiss, LSM800, Oberkochen, Germany). Briefly, 1 × 10 5 cells were seeded into special petri dishes and stabilized before incubation with different reagents at a DOX concentration of 6 μg mL −1 for 4 h and then carefully washed with PBS. Additionally, HO-(CH 2 O) n -H was added to fix the cells which were cultured in an 35 °C incubator for 15 min. To avoid interference, the fixed cells were rinsed again with PBS after incubation. Hoechst 33342 was used to stain the cells nuclei for 15 min which were then washed with PBS. The fluorescence of Hoechst 33342 and DOX was then directly determined via CLSM. Cellular uptake was quantitatively studied using flow cytometry (CytoFLEX S). Briefly, the cells in the culture medium were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After culturing for 24 h, the culture medium was replaced with 2 mL of fresh medium containing a particular reagent with a DOX concentration of 6 μg mL −1 . After 4 h of co-incubation, the cells were washed three times with PBS, dislodged using a trypsin solution, centrifuged at 1500 rpm at 4 °C for 3 min, and then re-suspended in PBS. Finally, the cells were filtered and analyzed via flow cytometry. 2.6. In vitro cytotoxicity assay MTT was used to evaluate the cytotoxicity of the different drug-loaded nanoparticles (Hao et al., ). Briefly, after treating the cells with blank nanoparticles, free DOX, DOX@NP, DOX@HNP, and DOX@BHNP at different DOX concentrations, 20 µL MTT solution was added, and the resulting formazan product was dissolved in DMSO solution. The optical density (OD) value at 570 nm was measured using a microplate reader (Bio-Rad 550, Hercules, CA). The OD value of the cells incubated in culture medium containing 10% fetal bovine serum (FBS) was also measured as a control. In addition, after the tumor cells were incubated with DOX@BHNP for 4 h, mitochondrial morphology was observed via bio-TEM. Specific details about this experiment are provided in the SI. 2.7. Cell apoptosis assay Cell apoptosis was quantitatively studied using flow cytometry. Briefly, cells suspended in the culture medium were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After incubation with free DOX, DOX@NP, DOX@HNP, and DOX@BHNP at a DOX concentration of 6 µg mL −1 , the tumor cells were collected and resuspended in PBS. Apoptotic cells were detected using an Annexin V-Pacific Blue/SYTOX Double Stain Apoptosis Detection Kit via flow cytometry. For comparison, cells incubated in a culture medium containing 10% FBS were used as a control. 2.8. Cell cycle assay In this assay, the cells were quantitatively analyzed using flow cytometry. Briefly, cells were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After incubation with DOX@BHNP at a DOX concentration of 6 µg mL −1 , the cells were harvested, washed with PBS, and fixed in chilled 75% ethanol for 24 h at 4 °C. The cells were then treated with a mixture of RNase A and SYTOX for 30 min at 37 °C. The cell cycle distribution was examined using flow cytometry. The DNA content at different phases of the cell cycle was also analyzed using ModFit software (Verity Software House, Topsham, ME). 2.9. Mitochondrial membrane potential determination The mitochondrial membrane potential of 4T1 cells was determined via staining with 5,5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolylcarbocyanine iodide (JC-1) and detected using a fluorescence spectrophotometer. Specific details about this experiment are provided in the SI. 2.10. Western blot assay Briefly, 4T1 cells were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After co-incubated with fresh culture medium containing a particular agent (free DOX, DOX@NP, DOX@HNP, and DOX@BHNP, respectively) for 24 h, the cells were rinsed twice with precooled PBS and lysed to extract proteins for western blot assay. The western blot assay processes are described in detail in the SI. 2.11. In vivo chemotherapy When their tumor volumes reached approximately 80 mm 3 , 4T1 tumor-bearing mice were randomly divided into three groups and administered an intravenous injection of either (i) PBS, (ii) free DOX, or (iii) DOX@BHNP group, at a dosage of 6 mg kg −1 DOX in 100 μL PBS every two days for up to 12 days. The body weight of the mice and their tumor volumes were recorded during the experimental period, before euthanization, and during imaging. After treatment for 18 days, the tumors, hearts, livers, spleens, lungs, and kidneys of the mice were collected, sectioned, and stained with hematoxylin and eosin (H&E). In addition, the tumors were harvested for western blot and immunohistochemical (IHC) assay, Ki67 and the TUNEL staining. The details are provided in the SI.
Materials Hyaluronic acid was purchased from Shandong Freda Biochem Co., Ltd. (Jinan, China). Protamine sulfate, biotin, and ethylenediamine were purchased from Sigma-Aldrich (Shanghai, China). Analytical grade anhydrous calcium chloride (CaCl 2 ) and anhydrous sodium carbonate (Na 2 CO 3 ) were obtained from ANPEL Laboratory Technologies Co., Ltd. (Shanghai, China). 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) was supplied by Amresco (Dallas, TX). Dimethylsulfoxide (DMSO) was purchased from Sigma-Aldrich (Shanghai, China). Doxorubicin hydrochloride, dimethylformamide (DMF), dicyclohexylcarbodiimide (DCC), N-hydroxysulfosuccinimide (sulfo-NHS), 1-ethyl-3-(dimethylaminopropyl)-carbodiimide (EDC), and 1-hydroxybenzotriazole (HOBt) were provided by J&K Scientific Co., Ltd. (Shanghai, China). 5,5′,6,6′-Tetrachloro-1,1′,3,3′-tetraethylbenzimidazolyl-carbocyanine iodide (JC-1) was purchased from Beyotime Biotechnology (Shanghai, China). The antibodies of p-H 2 AX, GAPDH, Bcl-2, and cleaved caspase-3 were provided by CST. Detailed information on the suppliers of cells and animals are provided in the Supporting Information (SI) .
Synthesis of biotinylated hyaluronic acid Biotin (2.44 g), DCC (2.47 g), and NHS (1.38 g) were added to a solution of DMF (10 mL) under continuous stirring and were reacted at 30 °C for 2 h. Then, the solvent was evaporated and precipitated in acetone to obtain biotin–NHS. Ethylenediamine trimethylamine (5 mL) was then added and the mixture was stirred at 30 °C for another 12 h to obtain biotin-ethylenediamine. After that, 170 mg of HA was dispersed in PBS buffer (1 mL, pH = 6.0) and activated, and 70 mg of biotin-ethylenediamine was added and continuously stirred at 30 °C for 24 h. The resulting solution was dialyzed and lyophilized to obtain BHA. Specific details about this experiment are provided in the SI.
Construction and characterization of drug-loaded nanoparticles Deionized water was used to dissolve the materials and their compositions were as follows: component A (35 μL): 30 μL Ca 2+ solution (CaCl 2 , 0.02 M)+5 μL anticancer DOX solution (10 μg µL −1 ); component B (55 μL): 40 µL CO 3 2– solution (Na 2 CO 3 , 0.01 M) and 15 µL PS solution (2 μg µL −1 ). Subsequently, component B was added to component A dropwise and mixed gently for 10 min to obtain a solution (90 μL) containing the hybrid nanoparticles DOX@PS/CaCO 3 (hereafter termed as ‘DOX@NP’). Mono-functionalized drug-loaded nanoparticles DOX@HA/PS/CaCO 3 (hereafter termed as ‘DOX@HNP’) were prepared by gently mixing 10 µL of HA solution (1 μg µL −1 ) with the DOX@NP solution for 10 min. Dual-functionalized DOX-loaded nanoparticles DOX@BHA/PS/CaCO 3 (hereafter termed as ‘DOX@BHNP’) were obtained by gently mixing the solution containing BHA (10 µg) with the DOX@NP solution (90 µL) for 10 min. The drug-loading capacity (DLC) and drug encapsulation efficiency (DEE) of the nanoparticles were determined through their absorbance at 488 nm using a spectrophotometer. Using an external calibration standard curve, the fluorescence intensity was converted into the concentration of non-encapsulated DOX, obtaining the DLC and DEE. A Zetasizer (Malvern Zetasizer Nano ZS90, Malvern, UK) was used to measure the size and zeta potential of the nanoparticles suspended in deionized water. All the data in our study were reported based on three independent measurements. The morphology of the BHA-functionalized drug delivery system was imaged using transmission electron microscopy (TEM) (Talo L120C G2).
In vitro drug release assay The drug release properties of DOX from our synthesized delivery system were investigated (DOX amount: 200 µg) using a dialysis bag (MWCO 3500) containing 4 mL of a drug-loaded nanoparticle suspension immersed in 10 mL of a Tris–HCl solution (pH = 5.3, 6.5, and 7.4). The samples were continuously oscillated in a shaking water bath at a speed of 150 rpm at a constant temperature of 37 °C. One milliliter of the sample was taken from the solution at different time points for fluorescence spectroscopy, and then replaced with the same volume of fresh medium. The concentration of released DOX was measured using a Cary Eclipse fluorescence spectrophotometer (Agilent Technologies, Santa Clara, CA). The fluorescence intensity of the blank Tris–HCl solution (pH = 5.3, 6.5, and 7.4) was also measured and used for correction. The experimental procedure performed was as previously described by Xu et al. .
In vitro cell uptake assay Cell internalization was qualitatively observed using a confocal laser scanning microscope (CLSM) (Zeiss, LSM800, Oberkochen, Germany). Briefly, 1 × 10 5 cells were seeded into special petri dishes and stabilized before incubation with different reagents at a DOX concentration of 6 μg mL −1 for 4 h and then carefully washed with PBS. Additionally, HO-(CH 2 O) n -H was added to fix the cells which were cultured in an 35 °C incubator for 15 min. To avoid interference, the fixed cells were rinsed again with PBS after incubation. Hoechst 33342 was used to stain the cells nuclei for 15 min which were then washed with PBS. The fluorescence of Hoechst 33342 and DOX was then directly determined via CLSM. Cellular uptake was quantitatively studied using flow cytometry (CytoFLEX S). Briefly, the cells in the culture medium were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After culturing for 24 h, the culture medium was replaced with 2 mL of fresh medium containing a particular reagent with a DOX concentration of 6 μg mL −1 . After 4 h of co-incubation, the cells were washed three times with PBS, dislodged using a trypsin solution, centrifuged at 1500 rpm at 4 °C for 3 min, and then re-suspended in PBS. Finally, the cells were filtered and analyzed via flow cytometry.
In vitro cytotoxicity assay MTT was used to evaluate the cytotoxicity of the different drug-loaded nanoparticles (Hao et al., ). Briefly, after treating the cells with blank nanoparticles, free DOX, DOX@NP, DOX@HNP, and DOX@BHNP at different DOX concentrations, 20 µL MTT solution was added, and the resulting formazan product was dissolved in DMSO solution. The optical density (OD) value at 570 nm was measured using a microplate reader (Bio-Rad 550, Hercules, CA). The OD value of the cells incubated in culture medium containing 10% fetal bovine serum (FBS) was also measured as a control. In addition, after the tumor cells were incubated with DOX@BHNP for 4 h, mitochondrial morphology was observed via bio-TEM. Specific details about this experiment are provided in the SI.
Cell apoptosis assay Cell apoptosis was quantitatively studied using flow cytometry. Briefly, cells suspended in the culture medium were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After incubation with free DOX, DOX@NP, DOX@HNP, and DOX@BHNP at a DOX concentration of 6 µg mL −1 , the tumor cells were collected and resuspended in PBS. Apoptotic cells were detected using an Annexin V-Pacific Blue/SYTOX Double Stain Apoptosis Detection Kit via flow cytometry. For comparison, cells incubated in a culture medium containing 10% FBS were used as a control.
Cell cycle assay In this assay, the cells were quantitatively analyzed using flow cytometry. Briefly, cells were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After incubation with DOX@BHNP at a DOX concentration of 6 µg mL −1 , the cells were harvested, washed with PBS, and fixed in chilled 75% ethanol for 24 h at 4 °C. The cells were then treated with a mixture of RNase A and SYTOX for 30 min at 37 °C. The cell cycle distribution was examined using flow cytometry. The DNA content at different phases of the cell cycle was also analyzed using ModFit software (Verity Software House, Topsham, ME).
Mitochondrial membrane potential determination The mitochondrial membrane potential of 4T1 cells was determined via staining with 5,5′,6,6′-tetrachloro-1,1′,3,3′-tetraethylbenzimidazolylcarbocyanine iodide (JC-1) and detected using a fluorescence spectrophotometer. Specific details about this experiment are provided in the SI.
Western blot assay Briefly, 4T1 cells were seeded in a six-well plate at a density of 2 × 10 5 cells per well. After co-incubated with fresh culture medium containing a particular agent (free DOX, DOX@NP, DOX@HNP, and DOX@BHNP, respectively) for 24 h, the cells were rinsed twice with precooled PBS and lysed to extract proteins for western blot assay. The western blot assay processes are described in detail in the SI.
In vivo chemotherapy When their tumor volumes reached approximately 80 mm 3 , 4T1 tumor-bearing mice were randomly divided into three groups and administered an intravenous injection of either (i) PBS, (ii) free DOX, or (iii) DOX@BHNP group, at a dosage of 6 mg kg −1 DOX in 100 μL PBS every two days for up to 12 days. The body weight of the mice and their tumor volumes were recorded during the experimental period, before euthanization, and during imaging. After treatment for 18 days, the tumors, hearts, livers, spleens, lungs, and kidneys of the mice were collected, sectioned, and stained with hematoxylin and eosin (H&E). In addition, the tumors were harvested for western blot and immunohistochemical (IHC) assay, Ki67 and the TUNEL staining. The details are provided in the SI.
Results and discussion 3.1. Preparation and characterization of the nanoparticles Herein, an anti-cancer drug delivery system was prepared using a classic nano-precipitation technique, where it was functionalized to specifically target tumor ligands using BHA. The schematic synthesis of BHA is described in and Figure S1A , where BHA was also characterized via 1 H NMR spectroscopy (Bruker AM 400, Rheinstetten, Germany). As shown in Figure S1B , the characteristic peaks between 2 and 3 of biotin were observed in BHA (within the red dotted line), indicating its successful synthesis. Furthermore, to prepare the dual-functionalized drug delivery system, negatively charged BHA was introduced into positively charged co-precipitated DOX@PS/CaCO 3 cores to form DOX@BHA/PS/CaCO 3 nanoparticles (DOX@BHNP) via self-assembly through electrostatic forces . In this system, CaCO 3 is a well-known acid stimulus-responsive drug delivery vehicle that can achieve effective drug release in tumor cell lysosomes. Additionally, PS as a template macromolecule could provide binding sites for Ca 2+ and promote the formation of well-dispersed CaCO 3 nanoparticles with excellent cell-penetrating properties and nucleus-targeting abilities. At the same time, its positive characteristics are conducive to the assembly of negatively charged functional ligands such as BHA to the delivery system. BHA endows the nanoparticles with tumor-targeting ability via an interaction with CD44 and biotin receptors on the tumor cells, as well as improve the stability of drug-loaded nanoparticles in the blood circulation. The entrapment efficiency and drug-loading data are presented in . All tested NPs showed a narrow size distribution and the entrapment efficiency and DLC of DOX in the NPs were more than 85% and 11.6%, respectively, implying that DOX was encapsulated into the network complex of PS and CaCO 3 effectively. More importantly, the batch-to-batch variation of DOX loading level in DOX@BHNP system was studied, and it was proved that the variation of the synthetic download amount of different batches was negligible . To evaluate the effect of BHA on the physical and chemical properties of the dual-functionalized nanoparticles, nanoparticles with different BHA content ranging from 5 to 20 µg were prepared and analyzed via DLS and flow cytometry. As shown in Figure S2 , when the amount of BHA was 10 µg, the mean fluorescence intensity (MFI) of the cells was relatively higher. Thus, in this study, we fixed the amount of BHA to 10 µg to prepare the DOX@BHNP nanoparticles (Duan & Li, ). The TEM images of DOX@NP, DOX@HNP, and DOX@BHNP particles respectively display a regular spherical morphology, and are homogeneously dispersed as individual particles in distilled water, with an average diameter of approximately 200 nm, similar to the size measured via DLS . Owing to the adsorption of HA and BHA, the surface of DOX@HNP and DOX@BHNP is covered with a transparent film . Furthermore, the stability of a drug delivery system is a crucial factor for its bioavailability. Hence, the morphologies of particles on the 6th day were investigated and found that the increase in particle size and the change in morphology were negligible ( , Figures S3–S4 ). The acid-responsive cumulative drug release characteristics of DOX@BHNP were evaluated. Tris–HCl solutions of pH 7.4, 6.5, and 5.3 were used to simulate blood circulation, the acidic environment of the tumor microenvironment, and lysosomes, respectively. As shown in , in a solution of pH 5.3, more than 80%±2.3 of DOX was released within 10 h, revealing that DOX@BHNP could release DOX efficiently under the acidic conditions in the tumor lysosome. In contrast, the DOX released from DOX@BHNP nanoparticles dramatically decreased to 45%±2.4 and 25%±3.7 at pH 6.5 and pH 7.4, respectively. The pH-sensitive release mechanism of DOX from DOX@BHNP is mainly because the CaCO 3 component in the nanoparticle skeleton is easily decomposed under acidic conditions, resulting in the control of DOX release. Given the slightly acidic environment (pH 5.0–6.0) of cancer endosomes and the weakly alkaline environment (pH 7.4) in the blood and normal cells, this feature is suitable as an acid trigger for improving the rate of intracellular drug release and reducing the incidence of side effects (Gao et al., ; Dizaj et al., ; Liu et al., ). 3.2. Cellular uptake After 4 h of incubation with different reagents, the cellular uptake behavior of DOX by 4T1 tumor cells was investigated via CLSM. The cells nuclei were labeled with Hoechst 33342 (blue fluorescence), and red fluorescence was observed from DOX. As shown in , the accumulation of red fluorescence in the cytoplasmic region of the cells in the free DOX group was better than that in the DOX@NP group, likely because small DOX molecules can enter the cells through the rapid passive diffusion, which is better than the unfunctionalized carrier that enters the cell through endocytosis as verified in previous studies (Zhang et al., ; Liu et al., ). In contrast, the cells treated with HA- or BHA-modified nanoparticles showed significantly enhanced red fluorescence compared to the free DOX group. As expected, the highest fluorescence intensity was detected in the 4T1 cells treated with dual-functionalized nanoparticles (DOX@BHNP), showing the synergetic tumor-targeting effects of biotin and HA, resulting in an increase in intracellular DOX concentration. The intracellular DOX concentrations in the cells treated with different reagents were quantitatively studied via flow cytometry , and the MFI of cells incubated with DOX@BHNP was significantly higher than that of the cells treated with free DOX, DOX@NP, or DOX@HNP. Treatment of HeLa and MCF-7 cells exhibited similar results and is presented in Figure S5–S6 . 3.3. Cytotoxicity evaluation The cytotoxicity of our hybrid nanoparticles was evaluated using the MTT assay in 4T1, HeLa, and MCF-7 cells after treatment with different reagents. As depicted in , a concentration ranges of the blank solution (NP) from 0 to 300 µg mL −1 did not show obvious cytotoxicity (cell viability >90%), which was attributed to all components in our drug delivery system having good biocompatibility within the given dose range. The antitumor effects of the drug-loaded hybrid nanoparticles were also studied and are shown in and Figure S7 . As expected, after BHA functionalization, DOX@BHNPs with active targeting ability could be easily absorbed by tumor cells and showed the highest tumor cell inhibitory activity. For example, the median lethal dose of DOX@BHNP to 4T1 cells is approximately 1–2 µg mL −1 , which is about half that of the free DOX group (2–4 µg mL −1 ). Flow cytometry analysis of Annexin V-Pacific Blue/SYTOX double staining showed that the number of apoptotic 4T1 cells was significantly increased when cells were treated with DOX@BHNP , which was consistent with the results of the MTT assay and CLSM visualization. DOX has been reported to kill tumor cells by inducing nuclear DNA damage or mitochondrial depolarization. Herein, the distribution of DOX in subcellular organelles delivered using a multifunctional carrier was also studied. As shown in , DOX mainly accumulated in the nuclear region and the mitochondria of the cells after co-incubation with DOX@BHNP for 12 h, which further indicated that DOX could be released from the BHNP platform in the endo/lysosome in an acidic environment and diffused to the nuclei and mitochondria. After the 4T1 cells were treated with DOX@BHNP for 24 h, their morphology and mitochondrial membrane potential were observed via bio-TEM and fluorescence spectrophotometry, respectively. As shown in , the mitochondrial morphology showed obvious destruction from the release of DOX compared to the untreated cell. Additionally, compared with normal mitochondria (showing red fluorescence), cells incubated with DOX@BHNP exhibited more green fluorescence, indicating that the mitochondria were damaged . A comparison of the incidence of apoptosis between untreated and DOX@BHNP-treated 4T1 cells showed that the cells were arrested in the G2/M phase in DOX@BHNP-treated cells , indicating a delay in the cell cycle progression. As shown in , the nucleus of 4T1 cell in the DOX@BHNP treatment group is no longer a regular circle, and there is obvious DNA leakage around it. At the molecular level, the up-regulation of phosphorylation of p-H 2 AX (DNA damage related protein), cleaved caspase-3 (pro-apoptosis protein), and down-regulation of Bcl-2 (anti-apoptosis protein) are clearly observed in the 4T1 cells following DOX@BHNP treatment . These results demonstrate that the targeting drug delivery systems can damage mitochondria, induce nuclear DNA leakage, and inhibit the proliferation of tumor cells. 3.4. In vivo therapeutic evaluation Before in vivo application, the biocompatibility of DOX@BHNP nanoparticles was evaluated by hemocompatibility assays. As presented in Figure S8A,B, in all nanoparticles concentrations ranging from 100 to 600 μg mL −1 , hemolysis was less than 6%. Moreover, the morphology of erythrocytes did not change under this series of nanoparticle concentrations, while the erythrocytes were lysed in the positive control (H 2 O solution) ( Figure S8C ). This indicates that the drug delivery system has good blood compatibility and can be used in vivo . Then, the tumor biodistribution of DOX@BHNP was monitored using noninvasive near-infrared optical imaging. Briefly, free DOX, DOX@NP and DOX@BHNP were intravenously injected into 4T1 tumor-bearing mice, after administration for 24 h, the mice were sacrificed, and their major organs and tumor tissues were collected. The fluorescence signal of DOX in the different tissues and organs was imaged using a small animal imaging system. As shown in , due to the enhanced permeability and the retention (EPR) effect of nanoparticles, tumor in DOX@NP-treated mice shows a stronger fluorescence signal than mice administered with free DOX. In addition, owing to the active targeting property of the DOX@BHNP, the fluorescence signal in the DOX@BHNP treated tumor tissue is the strongest, suggesting that the BHA functionalized vector can effectively accumulate DOX in tumors. shows the relative fluorescence signal of DOX in tumors and main organs. It is worth noting that the mice in the DOX@NP and DOX@BHNP groups showed little DOX accumulation in the heart compared to those treated with free DOX, suggesting that the biocompatibility of DOX-loaded CaCO 3 nanoparticles can effectively reduce the cardiotoxicity caused by free DOX (Dwivedi et al., ). Further, the distribution of DOX in the sections of the tumor tissues slides was determined via CLSM . Compared with the tumor sections treated with free DOX and DOX@NP, those in the DOX@BHNP group showed a more extensive distribution of red fluorescence throughout the entire tumor tissue section. This result indicated that the dual-functionalized drug delivery system could deliver DOX much deeper into the tumor tissue than free DOX or no targeted system. In vivo antitumor therapeutic evaluations were performed by intravenously injecting DOX@BHNP into 4T1 tumor-bearing mice when their tumor volumes have already reached ∼80 mm 3 . After determining the tumor targeting ability of DOX@BHNP during antitumor therapy, it was observed that administration of DOX@BHNP had no significant effect on the body weight of the mice while retaining its therapeutic efficacy. As shown in , the tumor size in mice treated with free DOX or PBS increased up to 5 or 12 times after five consecutive injections. On the contrary, with its excellent tumor targeting and acid-triggered drug release abilities, DOX@BHNP significantly suppressed tumor growth, showing only a twofold increase in tumor size at day 18 (from ∼83 to ∼155 mm 3 ). The morphology of tumors isolated from the different groups at the end of the study is shown in . In particular, the results of the histological analysis further confirmed that DOX-loaded BHNPs were the most effective in inducing cell apoptosis and reducing cell proliferation among the treatments administered. As shown in Figure S9, H&E assays were used to analyze the histology of the major organs and tumors in each group after 18 days of first administration. A slight toxicity was observed in the heart tissue of the free DOX-treated group, which may be related to the non-targeted distribution of DOX. In contrast, the DOX@BHNP-treated mice showed no detectable pathological abnormalities or tissue damage in the liver, spleen, lung, heart, and kidney, when compared with the PBS-treated group. The IHC assay results revealed that in DOX@BHNP-treated mice, the positive expression of p-H 2 AX and cleaved caspase-3 was the strongest, and the expression of Bcl-2 was relative low in DOX@BHNP-treated mice . Western blot assay shows that the expression of Bcl-2 is significantly suppressed after DOX@BHNP treatment and the expression of p-H 2 AX and cleaved caspase-3 is up-regulated . The results of western blot assay are good consistent with IHC assay, indicating that DOX@BHNP could successfully induce mitochondrial damage, nuclear DNA leakage, and tumor cell apoptosis in vivo . Overall, the in vivo antitumor results were consistent with the in vitro cytotoxicity data and clearly indicated that the dual-functionalized drug-loaded nanoparticles had significant anticancer effects and low toxicity, and could greatly improve the efficacy of cancer therapy in the future.
Preparation and characterization of the nanoparticles Herein, an anti-cancer drug delivery system was prepared using a classic nano-precipitation technique, where it was functionalized to specifically target tumor ligands using BHA. The schematic synthesis of BHA is described in and Figure S1A , where BHA was also characterized via 1 H NMR spectroscopy (Bruker AM 400, Rheinstetten, Germany). As shown in Figure S1B , the characteristic peaks between 2 and 3 of biotin were observed in BHA (within the red dotted line), indicating its successful synthesis. Furthermore, to prepare the dual-functionalized drug delivery system, negatively charged BHA was introduced into positively charged co-precipitated DOX@PS/CaCO 3 cores to form DOX@BHA/PS/CaCO 3 nanoparticles (DOX@BHNP) via self-assembly through electrostatic forces . In this system, CaCO 3 is a well-known acid stimulus-responsive drug delivery vehicle that can achieve effective drug release in tumor cell lysosomes. Additionally, PS as a template macromolecule could provide binding sites for Ca 2+ and promote the formation of well-dispersed CaCO 3 nanoparticles with excellent cell-penetrating properties and nucleus-targeting abilities. At the same time, its positive characteristics are conducive to the assembly of negatively charged functional ligands such as BHA to the delivery system. BHA endows the nanoparticles with tumor-targeting ability via an interaction with CD44 and biotin receptors on the tumor cells, as well as improve the stability of drug-loaded nanoparticles in the blood circulation. The entrapment efficiency and drug-loading data are presented in . All tested NPs showed a narrow size distribution and the entrapment efficiency and DLC of DOX in the NPs were more than 85% and 11.6%, respectively, implying that DOX was encapsulated into the network complex of PS and CaCO 3 effectively. More importantly, the batch-to-batch variation of DOX loading level in DOX@BHNP system was studied, and it was proved that the variation of the synthetic download amount of different batches was negligible . To evaluate the effect of BHA on the physical and chemical properties of the dual-functionalized nanoparticles, nanoparticles with different BHA content ranging from 5 to 20 µg were prepared and analyzed via DLS and flow cytometry. As shown in Figure S2 , when the amount of BHA was 10 µg, the mean fluorescence intensity (MFI) of the cells was relatively higher. Thus, in this study, we fixed the amount of BHA to 10 µg to prepare the DOX@BHNP nanoparticles (Duan & Li, ). The TEM images of DOX@NP, DOX@HNP, and DOX@BHNP particles respectively display a regular spherical morphology, and are homogeneously dispersed as individual particles in distilled water, with an average diameter of approximately 200 nm, similar to the size measured via DLS . Owing to the adsorption of HA and BHA, the surface of DOX@HNP and DOX@BHNP is covered with a transparent film . Furthermore, the stability of a drug delivery system is a crucial factor for its bioavailability. Hence, the morphologies of particles on the 6th day were investigated and found that the increase in particle size and the change in morphology were negligible ( , Figures S3–S4 ). The acid-responsive cumulative drug release characteristics of DOX@BHNP were evaluated. Tris–HCl solutions of pH 7.4, 6.5, and 5.3 were used to simulate blood circulation, the acidic environment of the tumor microenvironment, and lysosomes, respectively. As shown in , in a solution of pH 5.3, more than 80%±2.3 of DOX was released within 10 h, revealing that DOX@BHNP could release DOX efficiently under the acidic conditions in the tumor lysosome. In contrast, the DOX released from DOX@BHNP nanoparticles dramatically decreased to 45%±2.4 and 25%±3.7 at pH 6.5 and pH 7.4, respectively. The pH-sensitive release mechanism of DOX from DOX@BHNP is mainly because the CaCO 3 component in the nanoparticle skeleton is easily decomposed under acidic conditions, resulting in the control of DOX release. Given the slightly acidic environment (pH 5.0–6.0) of cancer endosomes and the weakly alkaline environment (pH 7.4) in the blood and normal cells, this feature is suitable as an acid trigger for improving the rate of intracellular drug release and reducing the incidence of side effects (Gao et al., ; Dizaj et al., ; Liu et al., ).
Cellular uptake After 4 h of incubation with different reagents, the cellular uptake behavior of DOX by 4T1 tumor cells was investigated via CLSM. The cells nuclei were labeled with Hoechst 33342 (blue fluorescence), and red fluorescence was observed from DOX. As shown in , the accumulation of red fluorescence in the cytoplasmic region of the cells in the free DOX group was better than that in the DOX@NP group, likely because small DOX molecules can enter the cells through the rapid passive diffusion, which is better than the unfunctionalized carrier that enters the cell through endocytosis as verified in previous studies (Zhang et al., ; Liu et al., ). In contrast, the cells treated with HA- or BHA-modified nanoparticles showed significantly enhanced red fluorescence compared to the free DOX group. As expected, the highest fluorescence intensity was detected in the 4T1 cells treated with dual-functionalized nanoparticles (DOX@BHNP), showing the synergetic tumor-targeting effects of biotin and HA, resulting in an increase in intracellular DOX concentration. The intracellular DOX concentrations in the cells treated with different reagents were quantitatively studied via flow cytometry , and the MFI of cells incubated with DOX@BHNP was significantly higher than that of the cells treated with free DOX, DOX@NP, or DOX@HNP. Treatment of HeLa and MCF-7 cells exhibited similar results and is presented in Figure S5–S6 .
Cytotoxicity evaluation The cytotoxicity of our hybrid nanoparticles was evaluated using the MTT assay in 4T1, HeLa, and MCF-7 cells after treatment with different reagents. As depicted in , a concentration ranges of the blank solution (NP) from 0 to 300 µg mL −1 did not show obvious cytotoxicity (cell viability >90%), which was attributed to all components in our drug delivery system having good biocompatibility within the given dose range. The antitumor effects of the drug-loaded hybrid nanoparticles were also studied and are shown in and Figure S7 . As expected, after BHA functionalization, DOX@BHNPs with active targeting ability could be easily absorbed by tumor cells and showed the highest tumor cell inhibitory activity. For example, the median lethal dose of DOX@BHNP to 4T1 cells is approximately 1–2 µg mL −1 , which is about half that of the free DOX group (2–4 µg mL −1 ). Flow cytometry analysis of Annexin V-Pacific Blue/SYTOX double staining showed that the number of apoptotic 4T1 cells was significantly increased when cells were treated with DOX@BHNP , which was consistent with the results of the MTT assay and CLSM visualization. DOX has been reported to kill tumor cells by inducing nuclear DNA damage or mitochondrial depolarization. Herein, the distribution of DOX in subcellular organelles delivered using a multifunctional carrier was also studied. As shown in , DOX mainly accumulated in the nuclear region and the mitochondria of the cells after co-incubation with DOX@BHNP for 12 h, which further indicated that DOX could be released from the BHNP platform in the endo/lysosome in an acidic environment and diffused to the nuclei and mitochondria. After the 4T1 cells were treated with DOX@BHNP for 24 h, their morphology and mitochondrial membrane potential were observed via bio-TEM and fluorescence spectrophotometry, respectively. As shown in , the mitochondrial morphology showed obvious destruction from the release of DOX compared to the untreated cell. Additionally, compared with normal mitochondria (showing red fluorescence), cells incubated with DOX@BHNP exhibited more green fluorescence, indicating that the mitochondria were damaged . A comparison of the incidence of apoptosis between untreated and DOX@BHNP-treated 4T1 cells showed that the cells were arrested in the G2/M phase in DOX@BHNP-treated cells , indicating a delay in the cell cycle progression. As shown in , the nucleus of 4T1 cell in the DOX@BHNP treatment group is no longer a regular circle, and there is obvious DNA leakage around it. At the molecular level, the up-regulation of phosphorylation of p-H 2 AX (DNA damage related protein), cleaved caspase-3 (pro-apoptosis protein), and down-regulation of Bcl-2 (anti-apoptosis protein) are clearly observed in the 4T1 cells following DOX@BHNP treatment . These results demonstrate that the targeting drug delivery systems can damage mitochondria, induce nuclear DNA leakage, and inhibit the proliferation of tumor cells.
In vivo therapeutic evaluation Before in vivo application, the biocompatibility of DOX@BHNP nanoparticles was evaluated by hemocompatibility assays. As presented in Figure S8A,B, in all nanoparticles concentrations ranging from 100 to 600 μg mL −1 , hemolysis was less than 6%. Moreover, the morphology of erythrocytes did not change under this series of nanoparticle concentrations, while the erythrocytes were lysed in the positive control (H 2 O solution) ( Figure S8C ). This indicates that the drug delivery system has good blood compatibility and can be used in vivo . Then, the tumor biodistribution of DOX@BHNP was monitored using noninvasive near-infrared optical imaging. Briefly, free DOX, DOX@NP and DOX@BHNP were intravenously injected into 4T1 tumor-bearing mice, after administration for 24 h, the mice were sacrificed, and their major organs and tumor tissues were collected. The fluorescence signal of DOX in the different tissues and organs was imaged using a small animal imaging system. As shown in , due to the enhanced permeability and the retention (EPR) effect of nanoparticles, tumor in DOX@NP-treated mice shows a stronger fluorescence signal than mice administered with free DOX. In addition, owing to the active targeting property of the DOX@BHNP, the fluorescence signal in the DOX@BHNP treated tumor tissue is the strongest, suggesting that the BHA functionalized vector can effectively accumulate DOX in tumors. shows the relative fluorescence signal of DOX in tumors and main organs. It is worth noting that the mice in the DOX@NP and DOX@BHNP groups showed little DOX accumulation in the heart compared to those treated with free DOX, suggesting that the biocompatibility of DOX-loaded CaCO 3 nanoparticles can effectively reduce the cardiotoxicity caused by free DOX (Dwivedi et al., ). Further, the distribution of DOX in the sections of the tumor tissues slides was determined via CLSM . Compared with the tumor sections treated with free DOX and DOX@NP, those in the DOX@BHNP group showed a more extensive distribution of red fluorescence throughout the entire tumor tissue section. This result indicated that the dual-functionalized drug delivery system could deliver DOX much deeper into the tumor tissue than free DOX or no targeted system. In vivo antitumor therapeutic evaluations were performed by intravenously injecting DOX@BHNP into 4T1 tumor-bearing mice when their tumor volumes have already reached ∼80 mm 3 . After determining the tumor targeting ability of DOX@BHNP during antitumor therapy, it was observed that administration of DOX@BHNP had no significant effect on the body weight of the mice while retaining its therapeutic efficacy. As shown in , the tumor size in mice treated with free DOX or PBS increased up to 5 or 12 times after five consecutive injections. On the contrary, with its excellent tumor targeting and acid-triggered drug release abilities, DOX@BHNP significantly suppressed tumor growth, showing only a twofold increase in tumor size at day 18 (from ∼83 to ∼155 mm 3 ). The morphology of tumors isolated from the different groups at the end of the study is shown in . In particular, the results of the histological analysis further confirmed that DOX-loaded BHNPs were the most effective in inducing cell apoptosis and reducing cell proliferation among the treatments administered. As shown in Figure S9, H&E assays were used to analyze the histology of the major organs and tumors in each group after 18 days of first administration. A slight toxicity was observed in the heart tissue of the free DOX-treated group, which may be related to the non-targeted distribution of DOX. In contrast, the DOX@BHNP-treated mice showed no detectable pathological abnormalities or tissue damage in the liver, spleen, lung, heart, and kidney, when compared with the PBS-treated group. The IHC assay results revealed that in DOX@BHNP-treated mice, the positive expression of p-H 2 AX and cleaved caspase-3 was the strongest, and the expression of Bcl-2 was relative low in DOX@BHNP-treated mice . Western blot assay shows that the expression of Bcl-2 is significantly suppressed after DOX@BHNP treatment and the expression of p-H 2 AX and cleaved caspase-3 is up-regulated . The results of western blot assay are good consistent with IHC assay, indicating that DOX@BHNP could successfully induce mitochondrial damage, nuclear DNA leakage, and tumor cell apoptosis in vivo . Overall, the in vivo antitumor results were consistent with the in vitro cytotoxicity data and clearly indicated that the dual-functionalized drug-loaded nanoparticles had significant anticancer effects and low toxicity, and could greatly improve the efficacy of cancer therapy in the future.
Conclusions In summary, a BHA-guided dual-functionalized CaCO 3 -based drug delivery system (DOX@BHNP) with target specificity and acid-triggered drug-releasing capability was developed to effectively deliver DOX to the mitochondria and nuclei of tumor cells. The drug-loaded nanoparticles have a well-defined spherical structure and are homogeneously dispersed as individual particles, as observed via TEM. Their average diameter was approximately 209 ± 10 nm, and no significant dimensional changes were observed via DLS after being placed in dark for six days, showing that the nanoparticles had good stability. The batch-to-batch variation of DOX loading level in DOX@BHNP system was negligible under eight independent experiments. The in vitro antitumor experiments demonstrated that DOX@BHNP system has remarkable tumor accumulation, good pH sensitivity, significant mitochondrial destruction and nuclear DNA damage. Virtually, an effective solid tumor inhibition was observed in vivo , suggesting that the hybrid nanosystem could be used as an effective and safe carrier for the delivery of chemotherapeutic drugs for use in cancer treatment.
Supplemental Material Click here for additional data file.
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Smoking cessation intervention in Australian general practice: a secondary analysis of a cluster randomised controlled trial | 745dd39c-77ba-4e7a-a428-8d8db2e7e8f8 | 8103929 | Family Medicine[mh] | Smoking is the primary risk factor for the development of many chronic conditions, including chronic obstructive pulmonary disease (COPD). Despite the progressive nature of COPD and the negative impacts on an individual’s quality of life, approximately 40% of people with COPD continue to smoke, and often find it more difficult to quit than other smokers. , Given their high degree of contact with the population, GPs are well placed to assist in smoking cessation. Despite this, a study conducted across 30 urban and rural general practice clinics in Australia reported that GPs provided smoking-related advice to only 55% of smokers who were ready to change their smoking behaviours. A number of barriers have been reported by GPs that limit their ability to routinely provide smoking cessation support. These range from practitioner-related barriers, such as ‘forgetting to discuss smoking’ and ‘lack of training and skills’, to more structural barriers, such as a ‘lack of time’. Thus, new strategies need to be explored in order to target all smokers within the general practice setting. One such strategy may be to incorporate pharmacist collaboration in the provision of smoking cessation support in this setting. Current evidence suggests that smoking cessation interventions delivered by pharmacists are effective at improving the rates of abstinence. However, the effectiveness of such interventions when integrated within an Australian general practice setting has not been evaluated. RADICALS — Review of airway dysfunction and interdisciplinary community-based care of adult long-term smokers — was a two-arm, cluster randomised controlled trial that implemented an interdisciplinary model of care involving GPs and other practice staff, pharmacists, and physiotherapists in Australian general practices, and evaluated its effectiveness on health-related quality of life (HRQoL) at 6 months. A total of 1050 participants were recruited for the RADICALS trial, which included 690 current smokers, 350 ex-smokers, and 10 never-smokers; 272 had spirometry confirmed COPD at baseline. The main outcomes of the trial were changes in St George’s Respiratory Questionnaire (SGRQ) score, COPD Assessment Test (CAT) score, dyspnoea score, smoking abstinence, and lung function. The effect of the RADICALS interdisciplinary primary care-based model for COPD ( n = 272) has been evaluated and the findings for these outcomes have been presented elsewhere. The effect of the RADICALS intervention on smoking abstinence and other smoking-related outcomes among all current smokers involved in the trial ( n = 690) has not been previously reported. If found to be effective, such a model could be a feasible approach to providing cessation services within the community. The aim of this secondary analysis was to evaluate the effectiveness of a pharmacist-coordinated intervention on smoking abstinence among smokers aged ≥ 40 years, and to examine the effects of the intervention on readiness to quit and the use of cessation aids.
Design and study population RADICALS was conducted in Melbourne general practices between March 2015 and January 2018. The RADICALS study protocol and baseline findings have been described in detail elsewhere. , Briefly, group or solo GP clinics in Melbourne with ≥ 1000 patients on their databases were approached. Upon obtaining signed agreement, practices were block randomised (block sizes of four and six) to the control or intervention groups. Eligible participants were those aged ≥ 40 years who had visited the clinic at least twice in the previous year and self-reported being a current or an ex-smoker with a smoking history of ≥ 10 pack years, or those who had a documented diagnosis of COPD on clinic records or were being managed with COPD-specific medications. At each clinic, trained research assistants identified potential participants based on the eligibility criteria and contacted them via mail or telephone. Upon obtaining written informed consent, participants were interviewed at the practice. For the present analysis, the authors excluded participants who were ex-smokers ( n = 350) or never smokers ( n = 10). Only those who reported being a current smoker in baseline interviews were included in this analysis ( n = 690). Study arms All smokers in the RADICALS trial, regardless of their diagnosis, were eligible for the smoking cessation intervention. Copies of the Supporting Smoking Cessation: a Guide For Health Professionals publication were provided to clinic staff in both groups. Intervention group GPs in the intervention clinics continued to provide routine care to their patients. Smoking cessation support at intervention clinics was coordinated by a pharmacist appointed at each site as part of the study. The pharmacist contacted the GP for initiating any prescription medications for smoking cessation. Pharmacists had smoking cessation training through QUIT Victoria (a government funded agency that promotes smoking cessation and offers a range of information, services, and tools for smokers and health professionals), which included an online training module consisting of educational videos and other materials. , Pharmacists provided smoking cessation support guided by a treatment algorithm developed by Thomas et al . Smoking cessation support was tailored to the individual’s readiness to quit and consisted of a counselling session during baseline interviews, telephone follow-up calls at 1 week and 1 month from the initial consultation, and a referral to Quitline, a free telephone support and counselling service to help people quit smoking. Telephone follow-ups re-emphasised the importance of quitting. Over-the-counter and/or prescription medications (through the GP) for smoking cessation were also recommended, if appropriate. Current smokers with spirometry-confirmed COPD were referred for a home medicines review (HMR) and home-based pulmonary rehabilitation (HomeBase). Performed by an accredited consultant pharmacist, the HMR consisted of an interview with the participants in their homes (about 1.5 hours’ duration) to assess and enhance medication use. The pharmacist also provided further individualised smoking cessation support, including recommendations for pharmacotherapy, if relevant. A report including recommendations for optimising medication use (especially for COPD and to assist smoking cessation), and any issues or concerns identified during the interview, was forwarded by the pharmacist to the individual’s GP following completion of the HMR. The 8-week HomeBase programme was conducted by a trained physiotherapist and consisted of one home visit and seven once-weekly follow-up telephone calls. The programme comprised individually prescribed, home-based aerobic and resistance exercise training and telephone calls based on motivational interviewing that included discussions on smoking behaviour and quitting using the 5As approach (ask, advise, assess, assist, arrange). Control group GPs in control clinics continued to provide routine care to their patients. In addition, participants were referred to Quitline. Follow-up Participants were followed up at 6 months by research assistants blind to group allocation. Follow-up was conducted face-to-face or via telephone, and involved the completion of a structured questionnaire and a carbon monoxide (CO) breath test in participants who self-reported abstinence at the 6-month follow-up. Outcomes The primary outcome of this analysis was carbon monoxide (CO)-verified 7-day point prevalence smoking abstinence at 6 months from baseline. Self-reported 7-day point prevalence abstinence (that is, smoking not even a puff in the previous 7 days) was assessed at the 6-month followup. Participants who self-reported 7-day point prevalence abstinence were requested to undergo a CO breath test. Exhaled CO levels were measured using a handheld piCO Smokerlyzer (Bedfont Scientific, Maidstone, UK). CO levels ≤ 6 parts per million (ppm) confirmed abstinence. Participants with missing follow-up data or whose self-reported abstinence was not biochemically validated were considered to be smokers in accordance with the Russell Standard. Secondary outcomes included: the proportion of smokers who self-reported the use of smoking cessation aids or alternative therapies over the 6-month period; changes within groups (from baseline to 6 months) and differences between groups at 6 months in readiness-to-quit score; and CO-validated 7-day point prevalence abstinence at 6 months from baseline in smokers with COPD. Data were collected from participants using validated tools at baseline and at 6 months. This included the readiness-to-quit scale (to assess motivation to quit smoking along a continuum). In addition, self-reported utilisation of smoking cessation pharmacotherapies or alternative products (for example, electronic cigarettes) was explored at the 6-month follow-up. Statistical analysis Baseline demographic characteristics were summarised using counts and proportions, means and standard deviations (SD), or medians and interquartile ranges (IQR), depending on data distribution. The primary analysis was performed according to the intention-to-treat (ITT) principle. Logistic regression models were used to examine the effectiveness of the intervention, with results reported as odds ratios (OR) and 95% confidence intervals (CI). Changes in readiness-to-quit score were compared between treatment groups using linear regression, with results reported as mean difference and 95% CIs. All regression analyses were adjusted for clustering by practice. A subgroup analysis of smokers with COPD was undertaken to analyse the efficacy of the HMR and the HomeBase components of the RADICALS intervention. Statistical significance was set at a two-sided P -value of 0.05. Analyses were conducted using Statistical Package for Social Sciences (SPSS) (version 25.0) and Stata version 14.0).
RADICALS was conducted in Melbourne general practices between March 2015 and January 2018. The RADICALS study protocol and baseline findings have been described in detail elsewhere. , Briefly, group or solo GP clinics in Melbourne with ≥ 1000 patients on their databases were approached. Upon obtaining signed agreement, practices were block randomised (block sizes of four and six) to the control or intervention groups. Eligible participants were those aged ≥ 40 years who had visited the clinic at least twice in the previous year and self-reported being a current or an ex-smoker with a smoking history of ≥ 10 pack years, or those who had a documented diagnosis of COPD on clinic records or were being managed with COPD-specific medications. At each clinic, trained research assistants identified potential participants based on the eligibility criteria and contacted them via mail or telephone. Upon obtaining written informed consent, participants were interviewed at the practice. For the present analysis, the authors excluded participants who were ex-smokers ( n = 350) or never smokers ( n = 10). Only those who reported being a current smoker in baseline interviews were included in this analysis ( n = 690).
All smokers in the RADICALS trial, regardless of their diagnosis, were eligible for the smoking cessation intervention. Copies of the Supporting Smoking Cessation: a Guide For Health Professionals publication were provided to clinic staff in both groups. Intervention group GPs in the intervention clinics continued to provide routine care to their patients. Smoking cessation support at intervention clinics was coordinated by a pharmacist appointed at each site as part of the study. The pharmacist contacted the GP for initiating any prescription medications for smoking cessation. Pharmacists had smoking cessation training through QUIT Victoria (a government funded agency that promotes smoking cessation and offers a range of information, services, and tools for smokers and health professionals), which included an online training module consisting of educational videos and other materials. , Pharmacists provided smoking cessation support guided by a treatment algorithm developed by Thomas et al . Smoking cessation support was tailored to the individual’s readiness to quit and consisted of a counselling session during baseline interviews, telephone follow-up calls at 1 week and 1 month from the initial consultation, and a referral to Quitline, a free telephone support and counselling service to help people quit smoking. Telephone follow-ups re-emphasised the importance of quitting. Over-the-counter and/or prescription medications (through the GP) for smoking cessation were also recommended, if appropriate. Current smokers with spirometry-confirmed COPD were referred for a home medicines review (HMR) and home-based pulmonary rehabilitation (HomeBase). Performed by an accredited consultant pharmacist, the HMR consisted of an interview with the participants in their homes (about 1.5 hours’ duration) to assess and enhance medication use. The pharmacist also provided further individualised smoking cessation support, including recommendations for pharmacotherapy, if relevant. A report including recommendations for optimising medication use (especially for COPD and to assist smoking cessation), and any issues or concerns identified during the interview, was forwarded by the pharmacist to the individual’s GP following completion of the HMR. The 8-week HomeBase programme was conducted by a trained physiotherapist and consisted of one home visit and seven once-weekly follow-up telephone calls. The programme comprised individually prescribed, home-based aerobic and resistance exercise training and telephone calls based on motivational interviewing that included discussions on smoking behaviour and quitting using the 5As approach (ask, advise, assess, assist, arrange). Control group GPs in control clinics continued to provide routine care to their patients. In addition, participants were referred to Quitline.
GPs in the intervention clinics continued to provide routine care to their patients. Smoking cessation support at intervention clinics was coordinated by a pharmacist appointed at each site as part of the study. The pharmacist contacted the GP for initiating any prescription medications for smoking cessation. Pharmacists had smoking cessation training through QUIT Victoria (a government funded agency that promotes smoking cessation and offers a range of information, services, and tools for smokers and health professionals), which included an online training module consisting of educational videos and other materials. , Pharmacists provided smoking cessation support guided by a treatment algorithm developed by Thomas et al . Smoking cessation support was tailored to the individual’s readiness to quit and consisted of a counselling session during baseline interviews, telephone follow-up calls at 1 week and 1 month from the initial consultation, and a referral to Quitline, a free telephone support and counselling service to help people quit smoking. Telephone follow-ups re-emphasised the importance of quitting. Over-the-counter and/or prescription medications (through the GP) for smoking cessation were also recommended, if appropriate. Current smokers with spirometry-confirmed COPD were referred for a home medicines review (HMR) and home-based pulmonary rehabilitation (HomeBase). Performed by an accredited consultant pharmacist, the HMR consisted of an interview with the participants in their homes (about 1.5 hours’ duration) to assess and enhance medication use. The pharmacist also provided further individualised smoking cessation support, including recommendations for pharmacotherapy, if relevant. A report including recommendations for optimising medication use (especially for COPD and to assist smoking cessation), and any issues or concerns identified during the interview, was forwarded by the pharmacist to the individual’s GP following completion of the HMR. The 8-week HomeBase programme was conducted by a trained physiotherapist and consisted of one home visit and seven once-weekly follow-up telephone calls. The programme comprised individually prescribed, home-based aerobic and resistance exercise training and telephone calls based on motivational interviewing that included discussions on smoking behaviour and quitting using the 5As approach (ask, advise, assess, assist, arrange).
GPs in control clinics continued to provide routine care to their patients. In addition, participants were referred to Quitline.
Participants were followed up at 6 months by research assistants blind to group allocation. Follow-up was conducted face-to-face or via telephone, and involved the completion of a structured questionnaire and a carbon monoxide (CO) breath test in participants who self-reported abstinence at the 6-month follow-up.
The primary outcome of this analysis was carbon monoxide (CO)-verified 7-day point prevalence smoking abstinence at 6 months from baseline. Self-reported 7-day point prevalence abstinence (that is, smoking not even a puff in the previous 7 days) was assessed at the 6-month followup. Participants who self-reported 7-day point prevalence abstinence were requested to undergo a CO breath test. Exhaled CO levels were measured using a handheld piCO Smokerlyzer (Bedfont Scientific, Maidstone, UK). CO levels ≤ 6 parts per million (ppm) confirmed abstinence. Participants with missing follow-up data or whose self-reported abstinence was not biochemically validated were considered to be smokers in accordance with the Russell Standard. Secondary outcomes included: the proportion of smokers who self-reported the use of smoking cessation aids or alternative therapies over the 6-month period; changes within groups (from baseline to 6 months) and differences between groups at 6 months in readiness-to-quit score; and CO-validated 7-day point prevalence abstinence at 6 months from baseline in smokers with COPD. Data were collected from participants using validated tools at baseline and at 6 months. This included the readiness-to-quit scale (to assess motivation to quit smoking along a continuum). In addition, self-reported utilisation of smoking cessation pharmacotherapies or alternative products (for example, electronic cigarettes) was explored at the 6-month follow-up.
Baseline demographic characteristics were summarised using counts and proportions, means and standard deviations (SD), or medians and interquartile ranges (IQR), depending on data distribution. The primary analysis was performed according to the intention-to-treat (ITT) principle. Logistic regression models were used to examine the effectiveness of the intervention, with results reported as odds ratios (OR) and 95% confidence intervals (CI). Changes in readiness-to-quit score were compared between treatment groups using linear regression, with results reported as mean difference and 95% CIs. All regression analyses were adjusted for clustering by practice. A subgroup analysis of smokers with COPD was undertaken to analyse the efficacy of the HMR and the HomeBase components of the RADICALS intervention. Statistical significance was set at a two-sided P -value of 0.05. Analyses were conducted using Statistical Package for Social Sciences (SPSS) (version 25.0) and Stata version 14.0).
A total of 690 current smokers were recruited (317 from 18 control clinics, and 373 from 21 intervention clinics); 166 had spirometryconfirmed COPD (82 in the control group, and 84 in the intervention group) ( ). The intervention and control groups were similar at baseline ( ). The majority of the 166 current smokers with COPD (126, 76.0%) had mild COPD, defined as forced expiratory volume in 1 second, 60% ≤ FEV1 < 80% predicted. Primary outcome At the 6-month follow-up, there was no significant difference in CO-verified abstinence rates between the control and intervention groups (OR 1.17, 95% CI = 0.52 to 2.64). In the ITT analysis, the CO-verified 7-day point prevalence abstinence rates were 3.5% and 4.0% in the control and intervention groups, respectively. CO-validated abstinence rates remained unchanged when a higher CO cut-off of < 10 ppm was used (3.8% and 4.3% in the control and intervention groups, respectively), (data not shown). Baseline readiness (OR 1.27, 95% CI = 1.06 to 1.52) and confidence in quitting (OR 1.42, 95% CI = 1.18 to 1.71) were significantly associated with CO-verified 7-day point prevalence abstinence at 6 months. No significant differences in CO-verified abstinence rates were seen after adjusting for baseline readiness and confidence in quitting (adjusted OR 1.04, 95% CI = 0.44 to 2.47), (data not shown). Secondary outcomes Only 177 (25.7%) of all current smokers ( n = 690) reported using a smoking cessation aid or alternative therapy (such as electronic cigarettes, acupuncture, or hypnotherapy) to assist them in quitting over the 6-month period. No significant differences were observed in the proportions of smokers who reported using a smoking cessation aid or alternative therapy during the followup period between the control (24.3%) and intervention groups (28.7%) ( P = 0.5), (data not shown). Over the 6-month period, nicotine replacement therapy (NRT) was the most commonly used smoking cessation aid by smokers in both groups ( n = 118, 66.7%) followed by varenicline ( n = 40, 22.6%). Of the participants who used NRT, seven also used varenicline during the follow up period. Among those who achieved CO-validated abstinence at 6 months, 50% reported the use of smoking cessation aids over that time period. Varenicline was the agent most commonly used by quitters, followed by NRT. Use of smoking cessation aids and alternative therapies by smokers with COPD ( n = 166) was low, with only 42 (25.3%) reporting the use of such aids over the 6-month period. Only 11 (26.2%) of those completing the HMR component ( n = 42) and seven (25.9%) of those completing at least six sessions of HomeBase ( n = 27) reported using a smoking cessation aid or alternative therapy over the follow-up period. No significant differences were observed between the control and intervention groups at 6 months in readiness-to-quit scores (Supplementary Table S1). Improvements seen within groups from baseline to 6 months in readiness-to-quit score did not reach statistical significance. In smokers with COPD, the CO-verified abstinence rate at 6 months was lower in the control group ( n = 3, 3.7%) compared with those who completed HMR and at least six sessions of HomeBase ( n = 2, 9.1%) ( P = 0.29), (data not shown). The low uptake of the HMR and HomeBase components of the intervention limited any further statistical analyses in this subgroup of smokers ( ).
At the 6-month follow-up, there was no significant difference in CO-verified abstinence rates between the control and intervention groups (OR 1.17, 95% CI = 0.52 to 2.64). In the ITT analysis, the CO-verified 7-day point prevalence abstinence rates were 3.5% and 4.0% in the control and intervention groups, respectively. CO-validated abstinence rates remained unchanged when a higher CO cut-off of < 10 ppm was used (3.8% and 4.3% in the control and intervention groups, respectively), (data not shown). Baseline readiness (OR 1.27, 95% CI = 1.06 to 1.52) and confidence in quitting (OR 1.42, 95% CI = 1.18 to 1.71) were significantly associated with CO-verified 7-day point prevalence abstinence at 6 months. No significant differences in CO-verified abstinence rates were seen after adjusting for baseline readiness and confidence in quitting (adjusted OR 1.04, 95% CI = 0.44 to 2.47), (data not shown).
Only 177 (25.7%) of all current smokers ( n = 690) reported using a smoking cessation aid or alternative therapy (such as electronic cigarettes, acupuncture, or hypnotherapy) to assist them in quitting over the 6-month period. No significant differences were observed in the proportions of smokers who reported using a smoking cessation aid or alternative therapy during the followup period between the control (24.3%) and intervention groups (28.7%) ( P = 0.5), (data not shown). Over the 6-month period, nicotine replacement therapy (NRT) was the most commonly used smoking cessation aid by smokers in both groups ( n = 118, 66.7%) followed by varenicline ( n = 40, 22.6%). Of the participants who used NRT, seven also used varenicline during the follow up period. Among those who achieved CO-validated abstinence at 6 months, 50% reported the use of smoking cessation aids over that time period. Varenicline was the agent most commonly used by quitters, followed by NRT. Use of smoking cessation aids and alternative therapies by smokers with COPD ( n = 166) was low, with only 42 (25.3%) reporting the use of such aids over the 6-month period. Only 11 (26.2%) of those completing the HMR component ( n = 42) and seven (25.9%) of those completing at least six sessions of HomeBase ( n = 27) reported using a smoking cessation aid or alternative therapy over the follow-up period. No significant differences were observed between the control and intervention groups at 6 months in readiness-to-quit scores (Supplementary Table S1). Improvements seen within groups from baseline to 6 months in readiness-to-quit score did not reach statistical significance. In smokers with COPD, the CO-verified abstinence rate at 6 months was lower in the control group ( n = 3, 3.7%) compared with those who completed HMR and at least six sessions of HomeBase ( n = 2, 9.1%) ( P = 0.29), (data not shown). The low uptake of the HMR and HomeBase components of the intervention limited any further statistical analyses in this subgroup of smokers ( ).
Summary A pharmacist-coordinated smoking cessation intervention delivered in collaboration with other health professionals in general practice did not influence abstinence rates at 6 months. No differences were noted between groups in readiness-to-quit scores at 6 months. Additionally, 6-month abstinence rates in smokers with COPD were higher in those who completed HMR and at least six sessions of HomeBase compared with those who received usual care plus Quitline referral. However, due to the low uptake of the intervention components, further research is needed to confirm these findings. Strengths and limitations The main strength of this study was its pragmatic nature and the number of clinics and GPs involved in the study. Clinics differed in size and socioeconomic status of patients, increasing the generalisability of the findings. The cluster randomised design minimised the risk of contamination. The interventions tested were readily available and could be implemented in general practice. Outcome assessments were performed by research assistants blinded to group allocation, minimising the risk of bias. Although smoking cessation training was offered to all pharmacists, individual differences may have impacted the nature of support offered to smokers. The dissemination of smoking cessation guidelines to GPs in the control arm may have prompted changes in the support offered to smokers presenting at these clinics, which would not have otherwise occurred. Additionally, some clinics in the control arm were already delivering smoking cessation services to their patients before the trial. Quitline referral was offered to both control and intervention groups. This may have contributed to the lack of a difference between the two arms of the study, as evidence indicates that such telephone-based smoking cessation services are effective at increasing quit rates. Moreover, smokers were recruited into the trial when they were not actively seeking medical help. This recruitment strategy may have impacted on the authors’ findings, as anti-smoking advice is more effective when linked to the patient’s presenting complaint. Low intensity of the smoking cessation intervention, limited follow-up, and poor uptake of smoking cessation pharmacotherapy may also explain the low abstinence rates observed. Comparison with existing literature The results of this study were not consistent with those of Chen et al , who evaluated the efficacy of individual counselling in smokers with or without COPD. The current study reported a significant difference in abstinence rates at 6 months between the intervention and usual-care groups (23.4% versus 10.4%, respectively, P = 0.007). However, the majority of the COPD patients in the study by Chen et al were recruited from pulmonary outpatient clinics and thus represent a population with potentially more severe symptoms and a stronger motivation to quit than the present study participants. When Chen et al removed smokers with COPD from the analysis, the effect of the intervention was no longer statistically significant. The current findings are consistent with those of Zwar et al , who assessed the effectiveness of an interdisciplinary team of general practice nurses and GPs developing and implementing an evidence-based disease management plan for patients newly diagnosed with COPD. Practice nurses and GPs in the intervention clinics received educational material and training on various aspects of COPD disease management and smoking cessation. At 6 months, no significant difference in self-reported abstinence rates were noted between the intervention (22.2%) and control groups (26.0%) (OR 0.92, 95% CI = 0.44 to 1.91). Similar to the findings of the present study, the low uptake of the intervention by participants in the intervention group may have contributed to the lack of effect observed by Zwar et al . Evidence from a qualitative study shows that most smokers view motivation to quit as a factor that is essential for successful smoking abstinence. A majority of smokers believe that the process needs to be initiated by themselves, and is independent of any external motivational factors such as discussions with GPs or family members. The modest level of motivation to quit among the current cohort may be a possible explanation for the lack of effect on abstinence noted in this study. The use of smoking cessation pharmacotherapies and non-pharmacological aids reported in the current study was low, but similar to that observed previously. , Although varenicline is one of the most effective pharmacological agents for smoking cessation, its use was relatively low in this study. – The present study was pragmatic in nature and the intervention provided was less intensive than in other studies. The reported abstinence rate of 4.0% in the intervention group in this study is similar to that observed in spontaneous quitters (3–5%). A Cochrane review has suggested that increasing the intensity of behavioural support for people making a quit attempt with the aid of pharmacotherapy increased the proportion who achieve long-term abstinence (risk ratio [RR] 1.29, 95% CI = 1.09 to 1.53). Another effective strategy to promote quit attempts and increase smoking cessation rates is the provision of pharmacotherapy at no cost to participants. Additionally, increasing the number of contacts between participants and intervention providers may be an effective strategy to help those who relapse during a quit attempt, and allows continuous engagement of smokers on the stage of change continuum — precontemplation, contemplation, preparation, action, and maintenance. Implications for research and practice More than 87% of the Australian population visit a GP at least once each year. An individual makes an average of seven GP visits annually. Similar statistics have been reported in England and Canada. , Therefore, interventions implemented in this setting may present a feasible strategy to improving health outcomes at the population level through behaviour change interventions such as smoking cessation. Although the ITT analysis showed no significant difference in abstinence rates between the control and intervention groups, the results were limited by the poor uptake of the intervention, especially by those with COPD. A pharmacist-coordinated interdisciplinary smoking cessation intervention when integrated in a general practice setting had no advantages over usual care. Further research is needed to evaluate the effect of home medicines review and home-based pulmonary rehabilitation on smoking abstinence in smokers with COPD.
A pharmacist-coordinated smoking cessation intervention delivered in collaboration with other health professionals in general practice did not influence abstinence rates at 6 months. No differences were noted between groups in readiness-to-quit scores at 6 months. Additionally, 6-month abstinence rates in smokers with COPD were higher in those who completed HMR and at least six sessions of HomeBase compared with those who received usual care plus Quitline referral. However, due to the low uptake of the intervention components, further research is needed to confirm these findings.
The main strength of this study was its pragmatic nature and the number of clinics and GPs involved in the study. Clinics differed in size and socioeconomic status of patients, increasing the generalisability of the findings. The cluster randomised design minimised the risk of contamination. The interventions tested were readily available and could be implemented in general practice. Outcome assessments were performed by research assistants blinded to group allocation, minimising the risk of bias. Although smoking cessation training was offered to all pharmacists, individual differences may have impacted the nature of support offered to smokers. The dissemination of smoking cessation guidelines to GPs in the control arm may have prompted changes in the support offered to smokers presenting at these clinics, which would not have otherwise occurred. Additionally, some clinics in the control arm were already delivering smoking cessation services to their patients before the trial. Quitline referral was offered to both control and intervention groups. This may have contributed to the lack of a difference between the two arms of the study, as evidence indicates that such telephone-based smoking cessation services are effective at increasing quit rates. Moreover, smokers were recruited into the trial when they were not actively seeking medical help. This recruitment strategy may have impacted on the authors’ findings, as anti-smoking advice is more effective when linked to the patient’s presenting complaint. Low intensity of the smoking cessation intervention, limited follow-up, and poor uptake of smoking cessation pharmacotherapy may also explain the low abstinence rates observed.
The results of this study were not consistent with those of Chen et al , who evaluated the efficacy of individual counselling in smokers with or without COPD. The current study reported a significant difference in abstinence rates at 6 months between the intervention and usual-care groups (23.4% versus 10.4%, respectively, P = 0.007). However, the majority of the COPD patients in the study by Chen et al were recruited from pulmonary outpatient clinics and thus represent a population with potentially more severe symptoms and a stronger motivation to quit than the present study participants. When Chen et al removed smokers with COPD from the analysis, the effect of the intervention was no longer statistically significant. The current findings are consistent with those of Zwar et al , who assessed the effectiveness of an interdisciplinary team of general practice nurses and GPs developing and implementing an evidence-based disease management plan for patients newly diagnosed with COPD. Practice nurses and GPs in the intervention clinics received educational material and training on various aspects of COPD disease management and smoking cessation. At 6 months, no significant difference in self-reported abstinence rates were noted between the intervention (22.2%) and control groups (26.0%) (OR 0.92, 95% CI = 0.44 to 1.91). Similar to the findings of the present study, the low uptake of the intervention by participants in the intervention group may have contributed to the lack of effect observed by Zwar et al . Evidence from a qualitative study shows that most smokers view motivation to quit as a factor that is essential for successful smoking abstinence. A majority of smokers believe that the process needs to be initiated by themselves, and is independent of any external motivational factors such as discussions with GPs or family members. The modest level of motivation to quit among the current cohort may be a possible explanation for the lack of effect on abstinence noted in this study. The use of smoking cessation pharmacotherapies and non-pharmacological aids reported in the current study was low, but similar to that observed previously. , Although varenicline is one of the most effective pharmacological agents for smoking cessation, its use was relatively low in this study. – The present study was pragmatic in nature and the intervention provided was less intensive than in other studies. The reported abstinence rate of 4.0% in the intervention group in this study is similar to that observed in spontaneous quitters (3–5%). A Cochrane review has suggested that increasing the intensity of behavioural support for people making a quit attempt with the aid of pharmacotherapy increased the proportion who achieve long-term abstinence (risk ratio [RR] 1.29, 95% CI = 1.09 to 1.53). Another effective strategy to promote quit attempts and increase smoking cessation rates is the provision of pharmacotherapy at no cost to participants. Additionally, increasing the number of contacts between participants and intervention providers may be an effective strategy to help those who relapse during a quit attempt, and allows continuous engagement of smokers on the stage of change continuum — precontemplation, contemplation, preparation, action, and maintenance.
More than 87% of the Australian population visit a GP at least once each year. An individual makes an average of seven GP visits annually. Similar statistics have been reported in England and Canada. , Therefore, interventions implemented in this setting may present a feasible strategy to improving health outcomes at the population level through behaviour change interventions such as smoking cessation. Although the ITT analysis showed no significant difference in abstinence rates between the control and intervention groups, the results were limited by the poor uptake of the intervention, especially by those with COPD. A pharmacist-coordinated interdisciplinary smoking cessation intervention when integrated in a general practice setting had no advantages over usual care. Further research is needed to evaluate the effect of home medicines review and home-based pulmonary rehabilitation on smoking abstinence in smokers with COPD.
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A Background Search on the Potential Role of | 023e1d7b-3488-4a59-8882-532eb3b4dbd2 | 9365597 | Pharmacology[mh] | Scutellaria is one of the largest genera within Lamiaceae. Scutellaria is a genus that seems to have 360–469 species that could be obtained in Europe, Latin America, Eastern Europe, and Central America. Scutellaria species have a strong tradition of usage as herbal remedies for chemotherapies, hepatic and intestinal disorders, asthma, neurological and cardiovascular ailments, and infectious diseases. Furthermore, contemporary pharmacotherapy has substantiated the traditional applications of Scutellaria medicinal species, including Scutellaria lateriflora L , Scutellaria barbata D . Don, and Scutellaria baicalensis Georgi . This genus has extensive therapeutic potential, encompassing antioxidative, cytotoxic, anti-inflammation, and antivirus qualities, as well as hepatoprotective and neuroprotective abilities. The ongoing evolution of studies on the genus Scutellaria revealed parallels and variances in its range, pharmaceutical components, phytochemical constituents, and pharmacological usage. The diversity of Scutellaria 's active substance structures and abundant biological properties suggests that illustrative associations between phytochemical analysis, phylogeny, and therapeutic implications (conventional use and advanced pharmacology) are beneficial for investigators to easily recognize the medicinal worth of this genus and investigate and exploit it . The Lamiaceae (mint) family comprises 350 species of perennial flowering plants from the genus Scutellaria , which is endemic to Asian countries, North America, and Europe . This genus has about 300 species, many of which can be found throughout Asia . There are 27 Scutellaria species in Iran, 12 of which are endemic . From ancient times, Scutellaria genus has been utilized to treat hyperlipidemia, hepatitis, inflammation, allergies, arteriosclerosis, and hypertension . Scutellaria has been used for over 2000 years in Asian medicine, notably Chinese medicine, to treat high fever, runny noses, influenza, and high blood pressure . Scutellaria has anticancer, antibacterial, antioxidant, hepatoprotective, anti-inflammatory, and antiviral properties . Scutellaria species are also valuable in the mitigation of nervous system conditions such as phenylethanoid glycosides, insomnia, anxiety, and hysteria . Among the 295 compounds identified in this genus are flavonoids and terpenes (diterpenes, monoterpenes, iridoid glycosides, and triterpenoids) . Scutellaria has a high concentration of flavonoids (nearly flavones), which are beneficial chemicals . S. immaculata Nevski ex Juz., S. ramosissima Popov, and S. schachristanica Juz. aerial parts are frequently used to diagnose hypertension, neurodegenerative disorders, and asthma in Uzbekistan. Secondly, they all contain flavonoids and essential oils. Essential oils are secondary plant metabolites that include a wide spectrum of synthetic compounds as well as therapeutic capabilities . They may be harvested from plants in a variety of ways, both classic and cutting-edge . Hydrodistillation, microwave, organic solvent extraction, steam distillation, supercritical CO 2 , ultrasonic, and high-pressure solvent extraction are some of the procedures used to extract essential oils . The components of essential oils are regulated by extraction processes, geographic and climatic conditions, plant storage, physiological age, harvesting time, and drying type. Please keep in mind that the contents of several parts of the plant vary . Terpenoids, which are classified as monoterpenes, sesquiterpenes, triterpenes, diterpenes, and tetraterpenes, are the most significant essential oil components . Essential oils protect plants from predators, environmental stress, parasites, and illness, and they also attract insects. They also help in attracting insects to provide an effective reproductive phase . Scutellaria baicalensis may be safe to consume by mouth for the vast majority of individuals. It has the ability to induce sleep. Patients who took Scutellaria baicalensis had fever and lung irritation. However, there is insufficient information to determine if Scutellaria baicalensis is the cause of these adverse effects. A few also show that some products containing Scutellaria baicalensis may cause liver issues in some people. Flavocoxid, a unique combination drug, was determined to be safe in 12-week study studies. However, some people may develop liver issues as a result of this or other combination products. This negative impact does not appear to be prevalent, and it may only be felt by people who have an allergic reaction . In this review, we have mentioned the antioxidant, antimicrobial, antifeedant, phytotoxic, acaricidal toxicity, antibacterial, anti-inflammatory, and antianalgesic activities of Scutellaria and its essential oils. The current review was compiled using content from the databases Web of Knowledge, Chemical Abstracts, Scopus, PubMed, ScienceDirect, and Google Scholar.
Per this study, around 50 species, 5 subspecies, and 17 variations of Scutellaria were utilized using natural remedies (aerial portion, rhizome, or whole plant) in countries like China, Nepal, India, North America, Nepal, Turkey, and Uzbekistan . Scutellaria medicinal herbs are being used to treat several diseases, which include peptic diseases (stomach pain, dysentery, bloating), liver function and gall diseases (jaundice, hepatitis), infections (carbuncles, furunculosis), neurological conditions (epilepsy, insomnia, chorea, spasm, hysteria), respiratory problems (respiratory infections, colds, scarlet fever), and traumatic injuries. Also, variability in the pharmacologic portions of Scutellaria may be attributed to morphological differences in Scutellaria and medication usage choices in various places . Conventional herbal remedies in China are created from 32 species and 13 variations, the largest of which are found in the southern region. These medicinal plants' most commonly used sections are the root and, indeed, the entire plant. Scutellaria species with fleshy rhizomes are used as medicine in China including Scutellaria rehderiana , Scutellaria baicalensis , Scutellaria amoena , and Scutellaria viscidula. Additionally, as per traditional Chinese theory, certain species often have the quality of removing heat, moisture, and poisonous materials, as well as having a significant impact on treating upper respiratory tract infections and acute gastroenteritis . Scutellaria plants are used whole as remedies; on the other hand, they often have short roots and little plants, such as Scutellaria barbata , Scutellaria galericulata , Scutellaria indica , and Scutellaria sessilifolia . These species frequently have the qualities of removing heat, wet, and poisonous elements, boosting blood circulation to alleviate blood stasis, and lowering inflammation to reduce pain, according to traditional Chinese medicine theory . Furthermore, certain species, according to traditional Chinese thought, can remove heat, moisture, and harmful elements, as well as have a major influence on curing upper respiratory tract infections and acute gastroenteritis . Scutellaria plants used as medicines contain short root systems as well as little plants, including Scutellaria indica , Scutellaria barbata , Scutellaria galericulata , and Scutellaria sessilifolia . According to the Chinese medicine concept, those species typically get the benefits of eradicating heat, dampness, and poisonous elements, increasing circulation of blood to decrease blood stasis, and decreasing inflammation to ease the pain. They have been shown to treat traumatic injuries, furuncles, and furunculosis and to also reduce inflammation derived from a variety of disorders. Scutellaria baicalensis and Scutellaria barbata D. are both frequently used natural medicines in China, and they are also used in other Asian countries such as Japan and Korea .
Aromatic plants produce natural volatile oil molecules with a strong odor as bioactive compounds. They are primarily twisted with the use of steam or hydro-distillation, which was initiated in the Middle Ages. Because of their antiseptic, i.e., virucidal, bactericidal, fungicidal, and therapeutic aspects, as well as their scent, they are utilized in embalming, food preparation, and as antibacterial, painkiller, sedative, anti-inflammatory, antispasmodic, and topically anesthetic therapies . These characteristics have not altered substantially up to the present day, other than that so much is already understood about all of their modes of action, notably at the antimicrobial level. Essential oils are a crucial component in plant protection throughout nature as antibacterial, antifungal, pesticides, antivirals, and also against herbivores by limiting their hunger for those kinds of plants. They might even invite particular insects to aid in pollen and seed propagation while repelling others. Essential oils are extracted from several fragrant plants that are found in subtropical to warm climates such as those of the Mediterranean and tropical areas when compounds represent a large element of conventional pharmacopeia . These were liquid, volatile, clear, but seldom colored, fat-soluble, and common organic solvents, with a density that is generally lower than water . There are several approaches to extracting essential oils. The usage of liquid carbon dioxide or microwaves, as a greater or lower pressure distillation using boiling water or heated vapor, is an example of this. Healthcare and culinary usage are now becoming increasingly prevalent as compared to synthetic pharmaceutical goods to safeguard the natural balance due to their bactericidal and fungicidal capabilities. Extraction by steam distillation or expression, for instance, is favored in certain circumstances . Extraction with lipid-soluble solvents and, in some cases, supercritical carbon dioxide is preferred for fragrance applications. Thus, the biochemical signature of essential oil products changes not only in the number of molecules extracted but also in the stereochemistry of molecules extracted depending on the mode of extraction, which is decided based on the aim of usage. Climate, age, plant organs, soil composition, and vegetative cycle phase can all improve the level and quantity, as well as proportions of the extracted product. To generate essential oils with a consistent constitution, they must be extracted under such conditions within the same organ of a plant that has grown in the same soil, location, and season. Gas chromatography and mass spectrometry studies are used to chemotype the majority of marketed essential oils. To certify the purity of essential oils, analytical monographs have already been issued (ISO, European pharmacopeia, WHO, Council of Europe) . Essential oils have been used for qualities that have already been found in nature, such as antifungal, antibacterial, and insecticidal effects. Approximately 3000 essential oils are currently known, and approximately 300 of them would be economically relevant, particularly in the cosmetic, medicinal, food, agronomic, sanitary, cosmetic, and aroma sectors. Essential oils with their ingredients are applied in aromas and cosmetics, hygiene goods, medicine, horticulture, food custodians and supplements, and organic cures. D-Limonene, d-carvone, and geranyl acetate, for instance, are used in aromas, moisturizers, cosmetics, as fragrance enhancers in food, odors in-home cleaning chemicals, and as lubricating oils . Further, essential oils are utilized in massaging as a combination with vegetable oil, in spas, and often in aromatherapy. Essential oils appear to have specific therapeutic characteristics that have been proposed to treat some organ dysfunctions or systemic disorders. Due to the high demand for natural, unadulterated substances in many industries, essential oils are utilized widely throughout the world and are continuing to expand in popularity. As a result, a lot of essential oils are produced around the world to support the cosmetics, aromatherapy, and phytomedicine businesses. Most of them have been efficient substitutes or supplements to added compounds used in the chemical process industries but generally do not get the same side effects .
Far more research reports on the essential oils of several Scutellaria species were studied . Even though several assessment reviews on the Scutellaria genus have been performed , knowledge regarding Scutellaria essential oils is lacking. As a result, this study focuses on the chemical components and biological activity of essential oils extracted from the Scutellaria genus.
A review of the most current studies on the essential oils of various Scutellaria species was conducted . While several overview aspects of the Scutellaria genus have been undertaken , there is little research on Scutellaria essential oils. In conclusion, these studies were based on the chemical components and pharmacological effects of essential oils obtained from the genus Scutellaria . The concentration of essential oils varies according to the harvesting season, drying conditions, subspecies type, soil pH, geographic location, subspecies type, plant part, and extraction technique . Essential oil compositions are depicted in supplementary file figures a to d; sesquiterpenes are the most abundant component in Scutellaria essential oils. The bulk of the essential oils in this species includes β -farnesene, hexadecanoic acid, β -caryophyllene, germacrene D, linalool, and eugenol. depicts the structures of these compounds. Scutellaria species have been shown to contain a variety of hydrocarbons and oxygenated terpenoid chemicals . Hexadecanoic acid, a saturated fatty acid, is found in plants, animals, and microbes . Germacrene D is a sesquiterpene pioneer of cadences and selinenes . Germacrene D kills mosquitoes, aphids, and ticks . β -Caryophyllene is a phytocannabinoid-rich sesquiterpene that may help with neuropathic pain, anxiety, endometriosis, ulcerative colitis, and renal safety . Linalool is a monoterpene component found in a wide variety of plants that has antinociceptive, antibacterial, and antihyperalgesic properties, but also antibacterial and antifungal action against a variety of pathogens and fungi . Farnesene is a potent pheromone in the vast majority of aphid species . Considering several publications on the essential oils of Scutellaria species (over 38), a wide variety of species remain unexplored. Additional investigation into the chemical properties of unreported Scutellaria essential oils is thus required . The primary components of S. diffusa oil remained revealed to be hexadecanoic acid with 30% and caryophyllene oxide with 9%. Germacrene D with 21%, hexadecanoic acid with 16%, and β -caryophyllene with 13% were found identified to be critical elements in S. heterophylla oil. Germacrene D with 40% was perhaps the most important element of S. salviifolia oil, preceded by bicyclo germacrene with 14% and β -caryophyllene with 4% . The essential oils extracted by hydrodistillation from extracts of three Scutellaria brevibracteata subspecies (subsp. subverting, subs. brevibracteata, and subsp. Pannosula) from their natural locations in Turkey were all studied simultaneously using gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). Depending on the chromatographic study and data analysis, the main determinants in S. brevibracteata subsp. brevibracteata oil were found to be β -caryophyllene (22.8%) and caryophyllene oxide (22.8%). The major components of S. brevibracteata subsp. subvelutina oil were 28.3% β -caryophyllene, 12.4% linalool, and 10.8% hexadecanoic acid. S. brevibracteata subsp. peninsula oil contains high levels of β -caryophyllene (36.4%), β -cadinol (9.8%), β -cadinene (7.0%), and linalool (5.3%). It was, to the best of our knowledge, the first research on the chemical properties of three Scutellaria brevibracteata essential oils. TLC, LSC, GLC, and GLC-MS methods were employed to analyze the essential oil Scutellaria lateriflora L. (Labiatae) generated by hydrodistillation in northern Iran. In the oil, there were at least 73 different substances. Low quantities of nonterpenoid components were discovered . The Lamiaceae family includes Scutellaria volubilis and Lepechinia paniculata . In Ecuador, they are commonly utilized in the traditional system of medicine. After hydro distillation, the structural activity and chemical characteristics of essential oils derived from aerial parts of Scutellaria volubilis in its foliation-blooming period and Lepechinia paniculata in its propagation season remained explored. Gas chromatography/mass spectrometry (GC/MS) and gas chromatography/flame ionization detection (GC/FID) approaches were used to examine the composition of these essential oils. The essential oil of Scutellaria volubilis was found to have 37 components. Sesquiterpene hydrocarbons are also confirmed to be the primary elements: germacrene D with 20.4%, β -caryophyllene with 17.5%, β -humulene with 14.7%, and β -bisabolene with 5.8%. The essential oil of L. paniculata comprised 34 components, the overwhelming of which were sesquiterpene hydrocarbons such as aromadendrene (24.6%), viridiflorene with 12.4%, β -selinene with 7.4%, and valencene with 6.7%. Monoterpene hydrocarbons were identified in smaller concentrations, as was β -phellandrene with 6.9% and with 7.7%. Including both species, oxygenated monoterpenes and sesquiterpenes constitute less than 5%. This is the first description of this species' chemical characteristics . Scutellaria albida L . subsp. albida, Scutellaria albida L. subsp. Colchica [Rech.f.]J.R.Edm ., Scutellaria albida L. subsp. Condensata [ Rech.f.]J.R.Edm ., and Scutellaria albida L. subsp. Velenovskyi [Rech. Linalool with 20% and 29%, respectively, was found recognized as a prominent compound in the oils of S. albida subsp. albida and S. albida subsp. condensata. Hexadecanoic acid with 13% was discovered to be a significant constituent in the oil of S. albida subsp. colchica. The oil of S. albida subsp. velenovskyi has the highest proportion of -caryophyllene (20%) .
Essential oils are the main raw material for the aroma and fragrance, food, and pharmaceutical industries. Essential oils are concentrated plant extracts that retain the natural smell and flavor, or “essence,” of their source. Some authors investigated the relationship between lavender essential oil production and gene expression during blooming, aiming to determine the optimum period for essential oil harvest . Other researchers came to the conclusion that changes in chemical variety have a mosaic pattern, which is tied to changes in predator activity and may be influenced by geographic factors or natural enemies. In terms of antigenotoxicity, all of the essential oils assessed showed this preventive effect. Moreover, the manner of defense varied according to the mutagens, i.e., the kinds of defects generated and therefore the kinds of enzymatic identification and activation resulting in translational synthesis or late apoptosis/necrosis .
7.1. Antioxidant Capability The antibacterial properties of Scutellaria genus essential oils are quite low relative to the antioxidant potential of Scutellaria extracts . Mamadalieva et al. investigated the antioxidant properties of three Uzbek Scutellaria species' essential oils ( Scutellaria ramosissima , Scutellaria immaculata , and Scutellaria schachristanica ). These Scutellaria essential oils demonstrated significant antioxidant action due to the incorporation of eugenol, thymol, and carvacrol; however, it was less than ascorbic acid . The antioxidant effect of a Scutellaria baicalensis trihydroxyflavone extract on oxidation generated by UV radiation was investigated using a phosphatidylcholine liposome membrane. The antioxidative activity of baicalin, baicalein, wogonin, and butylated hydroxytoluene (BHT) was also examined as standards . The chemical confirmation of essential oils found from aerial sections of Scutellaria immaculata Nevski ex Juz ., Scutellaria ramosissima M. Pop., and Scutellaria schachristanica Juz. (Lamiaceae) rising wild in Uzbekistan was studied using GC and GC–MS. The foremost components of S. immaculata essential oils appear to be acetophenone with 30.39%, eugenol with 20.61%, thymol with 10.04%, but also linalool with 6.92%, whereas S. schachristanica essential oils appear to be acetophenone with 34.74%, linalool with 26.98%, but also eugenol with 6.92%. Germacrene D with 23.96%, β -caryophyllene with 11.09%, linalool with 9.63%, and hexadecanoic acid comprise the oil of S. ramosissima with 8.34%. In DPPH, ABTS, and FRAP experiments, the essential oils of Scutellaria species displayed lesser antioxidant activity. Especially eugenol showed a significant lowering power in the FRAP experiment (IC 50 = 2476.9215.8(mM Fe(II)/g)) . 7.2. Antimicrobial Activity The physiological effects of Scutellaria essential oils have been examined, with the majority of the research focusing on antibacterial activity. Eugenol, linalool, and other long-chain alcohols may be responsible for the antibacterial properties of these oils . Antibacterial action may also be aided by other essential oil components such as thymol and alpha-terpineol . Khotimchenko and Yakovleva explored the antibacterial properties of S. barbata essential oils contrary to 17 microorganisms ( Pseudomonas aeruginosa , Salmonella paratyphi-A , Klebsiella pneumonia , Stenotrophomonas maltophilia , Serratia marcescens , Enterococcus faecalis , Staphylococcus aureus , Serratia liquefaciens , Escherichia coli , Staphylococcus haemolyticus , Candida tropicalis , Staphylococcus simulans , Salmonella typhi , Staphylococcus epidermidis , Citrobacter freundii , Shigella flexneri , and Candida albicans ) utilizing the disc diffusion and broth microdilution approaches. Because the essential oil had such significant bacteriostatic activity, their data indicated that S. epidermidis was perhaps the furthermost sensitive microbe (29 mm inhibition zone and 0.77 mg/mL MBC), whereas C. albicans was possibly the most resistant (7-9 mm and 24.50 mg/mL MBC) . The essential oils of S. strigillosa , according to Zhu et al., are substantially more efficient against Gram-positive bacteria and fungi than against Gram-negative germs . Thus, according to Pant et al., essential oils of S. grossa exhibited antimicrobial properties toward K. pneumonia , E. faecalis , B. subtilis , and S. enterica . As per Skaltsa et al., essential oils of S. rupestris and S. sieberi isolated in Greece had limited potency against S. aureus and B. cereus . Skaltsa et al. discovered that perhaps the essential oil of S. albida subsp albida showed activity against B. subtilis , S. aureus , P. aeruginosa , E. coli , and S. cerevisiae due to the huge amount of linalool and nerolidol . Dereboylu et al. investigated the antibacterial properties of S. aureus , E. coli , S. typhimurium , B. subtilis , E. faecalis , and P. aeruginosa active ingredients against seven bacteria and one fungus ( S. aureus , S. typhimurium , E. coli , P. aeruginosa , E. faecalis , B. subtilis ) . The essential oil of S. repens being tested evaluated antibacterial activity on A. tumefaciens , E. faecalis , K. pneumoniae , X. phaseoli , S. aureus , E. coli , S. enterica , E. chrysanthemi , and P. multocida , where the zone of inhibition for E. coli was 23 mm, accompanied by E. faecalis at 18 millimeters, K. pneumonia at 15 millimeters, and then B. subtilis at 12 mm . The plant Scutellaria barbata D. Don (Lamiaceae) is endemic to south China. This plant, identified as Ban-Zhi-Lian in Chinese traditional medicine, has been recognized as an antitumor, anti-inflammatory, and diuretic ingredient. S. barbata formulations have exhibited leads to growth inhibition in a variety of malignancies. The plant has been applied in the mitigation of digestive system malignancies, lung cancer, breast cancer, hepatoma, and chorioepithelioma in therapy. The plant is expected to possess alkaloids and flavonoids. Polyphenols (apigenin and luteolin) have been identified as bioactive components toward methicillin-resistant Staphylococcus aureus from just a 50% ethanolic leaf extract. E-1-(40-Hydroxyphenyl)-but-1-en-3-one was extracted from a methanolic extraction of the leaves and showed high cytotoxicity in K562 human leukemia cell lines. There is still no published evidence on the chemical components and antibacterial action of S. barbata essential oil. Scutellaria barbata essential oil has been produced by hydrodistillation with a 0.3%( v / w ) yield as well as examined by GC and GCMS. Hexahydrofarnesylacetone with 11.0%, 3,7,11,15-tetramethyl-2-hexadecane-1-ol with 7.8%, menthol with 7.7%, and 1-octen-3-ol with 7.7% were the primary components in the oil with 7.1%. The oil's antibacterial efficacy toward 17 microorganisms has been tested through disc diffusion and broth microdilution techniques. Gram-positive bacteria were just more tolerant to the oil than Gram-negative bacteria and yeasts, notably methicillin-resistant Staphylococcus aureus . The aerial portions of three endemic Scutellaria species from Lamiaceae are being studied for glandular trichomes shape, volatile content, and antibacterial activity. The examined species have two kinds of glandular trichomes that are morphologically unique. Capitate trichomes were found in all three taxa studied. Peltate glandular trichomes featured a large secretory head with one central and three to eight periphery cells. Even in the petiole of S. cypria var. elatior could peltate trichomes found. Steam distillation in a Clevenger type system yielded 0.26-0.47% ( v / w ) volatiles and essential oil combinations from three species. The GC-FID and GC-MS methods were used for their studies. By comparing their relative retention indices, mass spectra, and certain literature records, these chemicals were identified. There was a total of 23 identified components. While overall volatile % ages were found to be 99.99%, essential oil yield varies from 34.64 to 92.25% for three species. Trans-caryophyllene with 22.58% and germacrene D with 42.01% were found to be key components of S. sibthorpii . Eugenol with 23.05% and palmitic acid with 27.00% were found considered to be significant components of S. cypria var. cypria. Furthermore, S. cypria var. elatior has a substantial fraction of linalool and palmitic acid, with 10.92% and 46.76%, respectively, where the MIC values of the volatiles towards Gram-negative and Gram-positive bacteria varied from 10 to 20 mg/mL. C. albicans was shown to be among the furthermost resistant yeast-like fungus, with MIC values found to be high than 20 mg/mL. 7.3. Antifeedant Activity The essential oils of three Scutellaria species ( Scutellaria orientalis ssp. Alpina, Scutellaria brevibracteata , and Scutellaria hastifolia ) were tested in contradiction to the feeding and egg-laying activities of Spodoptera littoralis in research published by Formisano et al. Both S. brevibracteata and S. hastifolia extraction inhibited female moth egg laying on sheets; however, only S. hastifolia essential oil halted Spodoptera littoralis larvae from eating on mitigation discs . As per Giuliani et al., the essential oil of S. rubicunda subsp. linnaeana has antifeedant action in contradiction of Spodoptera littoralis . S. littoralis is a contraction for the letter S. The essential oil of the plant generated a dose-dependent positive feeding response in littoralis larvae. Scutalbin C, Scutecyprol B, and scutecyprol B remained initiate in aerial sections of S. rubicunda subsp. linnaeana . Linnaeana (FI at 100 ppm = 100) was antifeedant to larvae of five Lepidoptera species . 7.4. Phytotoxic Effect Phytochemicals from various Scutellaria species displayed substantial cytotoxic effects on some human tumor cell lines in vitro. Flavonoids, neoclerodan diterpenoids, iridoids, phenyl alcohol glycosides, and alkaloids have all been identified from Scutellaria species. S. strigillosa essential oil has been studied for phytotoxicity to amaranth and bluegrass (amaranthus is a worldwide genus of annual or short-lived perennial plants, while bluegrass refers to numerous species of grasses of the genus Poa). Amaranthus seedling progress was completely inhibited by 3 μ L/mL essential oil, although bluegrass growth was just slightly affected . 7.5. Acaricidal Toxicities The acaricidal toxicities of 1-hydroxynaphthalene from S. barbata oil and its derivatives were determined and compared with those of benzyl benzoate. S. barbata essential oil has potent acaricidal action than the control sample (benzyl benzoate) . 7.6. Antibacterial Activity S. grossa essential oil extracts had potent antibacterial effects on Bacillus subtilis and Enterococcus faecalis (MIC, 31.25–62.5 μ L/mL), along with Klebsiella pneumoniae as well as Salmonella enterica (MIC, 125 μ L/mL). S. lindbergii Rech.f. ethanolic had to have a considerable antibacterial property, with a MIC value of 6.25 mg/mL −1 . The steam volatile oil derived from S. repens aerial parts displayed identified potential towards E. faecalis (the MIC was found to be 125 μ L/mL −1 ), Escherichia coli (MIC, 31.25 μ L/mL −1 ), and Klebsiella pneumoniae (MIC, 250 μ L/mL −1 ) . The chemical constituents of the steam volatile oil produced by steam distillation of this aerial portion of Scutellaria grossa Wall ex Benth. (Lamiaceae) were investigated using capillary GC and GC-MS. Oxygenated monoterpenes were shown to be abundant in the oil (88.6%). There must have been 50 elements discovered, accounting for 94.4% of the overall oil content. Linalool (37.0%) and 1-octen-3-ol (32.0%) were shown to have main components. The oil's antibacterial efficacy towards ten bacterial strains was established by measuring the growth inhibitory zones. The oil had substantial antibacterial action toward Gram-positive Bacillus subtilis and Enterococcus faecalis bacteria as well as Gram-negative Klebsiella pneumoniae but also Salmonella enterica enterica bacteria. The minimal inhibitory concentration against E. faecalis was reported at 31.25 μ L mL –1 . 7.7. Anti-inflammatory Action Many combinations of Scutellaria baicalensis hot water extract (SB-HW) and Chrysanthemum morifolium ethanol extract (CM-E) were tested for anti-inflammatory activity. SB-HW (80 g/mL)/CM-E (120 g/mL) or SB-HW (40 g/mL)/CM-E (160 g/mL) substantially decreased LPS-stimulated NO and IL-6 levels in RAW 264.7 cells. SB-HW (80 g/mL)/CM-E (120 g/mL) was shown to be the most effective combination for suppressing MUC5AC secretion in PMA- and LPS-induced NCI-H292 cells. In PMA-induced A549 cells, the active combination also reduced PGE2 and IL-8 production. According to LC-MS/MS tests, the active combination had a high concentration of flavone glycosides such as baicalin and cynaroside. The active combination inhibited phosphorylation of ERK, JNK, and p38 on Western blots, showing that MAPK signaling was inhibited. The active combination, according to our findings, might be employed as a new anti-inflammatory herbal medication . 7.8. Antianalgesic Activity S. edelbergii crude extract with subfraction analgesic effectiveness was tested in Swiss albino mice at various dosages to treat acetic acid-induced writhes. In this investigation, aspirin was utilized as a control. EtOAc was found to be the most active fraction, with inhibition rates of 37% and 55% at dosages of 50 and 100 mg/kg body weight, respectively, followed by chloroform, with inhibition rates of 29% and 48% at doses of 50 and 100 mg/kg body weight, respectively .
The antibacterial properties of Scutellaria genus essential oils are quite low relative to the antioxidant potential of Scutellaria extracts . Mamadalieva et al. investigated the antioxidant properties of three Uzbek Scutellaria species' essential oils ( Scutellaria ramosissima , Scutellaria immaculata , and Scutellaria schachristanica ). These Scutellaria essential oils demonstrated significant antioxidant action due to the incorporation of eugenol, thymol, and carvacrol; however, it was less than ascorbic acid . The antioxidant effect of a Scutellaria baicalensis trihydroxyflavone extract on oxidation generated by UV radiation was investigated using a phosphatidylcholine liposome membrane. The antioxidative activity of baicalin, baicalein, wogonin, and butylated hydroxytoluene (BHT) was also examined as standards . The chemical confirmation of essential oils found from aerial sections of Scutellaria immaculata Nevski ex Juz ., Scutellaria ramosissima M. Pop., and Scutellaria schachristanica Juz. (Lamiaceae) rising wild in Uzbekistan was studied using GC and GC–MS. The foremost components of S. immaculata essential oils appear to be acetophenone with 30.39%, eugenol with 20.61%, thymol with 10.04%, but also linalool with 6.92%, whereas S. schachristanica essential oils appear to be acetophenone with 34.74%, linalool with 26.98%, but also eugenol with 6.92%. Germacrene D with 23.96%, β -caryophyllene with 11.09%, linalool with 9.63%, and hexadecanoic acid comprise the oil of S. ramosissima with 8.34%. In DPPH, ABTS, and FRAP experiments, the essential oils of Scutellaria species displayed lesser antioxidant activity. Especially eugenol showed a significant lowering power in the FRAP experiment (IC 50 = 2476.9215.8(mM Fe(II)/g)) .
The physiological effects of Scutellaria essential oils have been examined, with the majority of the research focusing on antibacterial activity. Eugenol, linalool, and other long-chain alcohols may be responsible for the antibacterial properties of these oils . Antibacterial action may also be aided by other essential oil components such as thymol and alpha-terpineol . Khotimchenko and Yakovleva explored the antibacterial properties of S. barbata essential oils contrary to 17 microorganisms ( Pseudomonas aeruginosa , Salmonella paratyphi-A , Klebsiella pneumonia , Stenotrophomonas maltophilia , Serratia marcescens , Enterococcus faecalis , Staphylococcus aureus , Serratia liquefaciens , Escherichia coli , Staphylococcus haemolyticus , Candida tropicalis , Staphylococcus simulans , Salmonella typhi , Staphylococcus epidermidis , Citrobacter freundii , Shigella flexneri , and Candida albicans ) utilizing the disc diffusion and broth microdilution approaches. Because the essential oil had such significant bacteriostatic activity, their data indicated that S. epidermidis was perhaps the furthermost sensitive microbe (29 mm inhibition zone and 0.77 mg/mL MBC), whereas C. albicans was possibly the most resistant (7-9 mm and 24.50 mg/mL MBC) . The essential oils of S. strigillosa , according to Zhu et al., are substantially more efficient against Gram-positive bacteria and fungi than against Gram-negative germs . Thus, according to Pant et al., essential oils of S. grossa exhibited antimicrobial properties toward K. pneumonia , E. faecalis , B. subtilis , and S. enterica . As per Skaltsa et al., essential oils of S. rupestris and S. sieberi isolated in Greece had limited potency against S. aureus and B. cereus . Skaltsa et al. discovered that perhaps the essential oil of S. albida subsp albida showed activity against B. subtilis , S. aureus , P. aeruginosa , E. coli , and S. cerevisiae due to the huge amount of linalool and nerolidol . Dereboylu et al. investigated the antibacterial properties of S. aureus , E. coli , S. typhimurium , B. subtilis , E. faecalis , and P. aeruginosa active ingredients against seven bacteria and one fungus ( S. aureus , S. typhimurium , E. coli , P. aeruginosa , E. faecalis , B. subtilis ) . The essential oil of S. repens being tested evaluated antibacterial activity on A. tumefaciens , E. faecalis , K. pneumoniae , X. phaseoli , S. aureus , E. coli , S. enterica , E. chrysanthemi , and P. multocida , where the zone of inhibition for E. coli was 23 mm, accompanied by E. faecalis at 18 millimeters, K. pneumonia at 15 millimeters, and then B. subtilis at 12 mm . The plant Scutellaria barbata D. Don (Lamiaceae) is endemic to south China. This plant, identified as Ban-Zhi-Lian in Chinese traditional medicine, has been recognized as an antitumor, anti-inflammatory, and diuretic ingredient. S. barbata formulations have exhibited leads to growth inhibition in a variety of malignancies. The plant has been applied in the mitigation of digestive system malignancies, lung cancer, breast cancer, hepatoma, and chorioepithelioma in therapy. The plant is expected to possess alkaloids and flavonoids. Polyphenols (apigenin and luteolin) have been identified as bioactive components toward methicillin-resistant Staphylococcus aureus from just a 50% ethanolic leaf extract. E-1-(40-Hydroxyphenyl)-but-1-en-3-one was extracted from a methanolic extraction of the leaves and showed high cytotoxicity in K562 human leukemia cell lines. There is still no published evidence on the chemical components and antibacterial action of S. barbata essential oil. Scutellaria barbata essential oil has been produced by hydrodistillation with a 0.3%( v / w ) yield as well as examined by GC and GCMS. Hexahydrofarnesylacetone with 11.0%, 3,7,11,15-tetramethyl-2-hexadecane-1-ol with 7.8%, menthol with 7.7%, and 1-octen-3-ol with 7.7% were the primary components in the oil with 7.1%. The oil's antibacterial efficacy toward 17 microorganisms has been tested through disc diffusion and broth microdilution techniques. Gram-positive bacteria were just more tolerant to the oil than Gram-negative bacteria and yeasts, notably methicillin-resistant Staphylococcus aureus . The aerial portions of three endemic Scutellaria species from Lamiaceae are being studied for glandular trichomes shape, volatile content, and antibacterial activity. The examined species have two kinds of glandular trichomes that are morphologically unique. Capitate trichomes were found in all three taxa studied. Peltate glandular trichomes featured a large secretory head with one central and three to eight periphery cells. Even in the petiole of S. cypria var. elatior could peltate trichomes found. Steam distillation in a Clevenger type system yielded 0.26-0.47% ( v / w ) volatiles and essential oil combinations from three species. The GC-FID and GC-MS methods were used for their studies. By comparing their relative retention indices, mass spectra, and certain literature records, these chemicals were identified. There was a total of 23 identified components. While overall volatile % ages were found to be 99.99%, essential oil yield varies from 34.64 to 92.25% for three species. Trans-caryophyllene with 22.58% and germacrene D with 42.01% were found to be key components of S. sibthorpii . Eugenol with 23.05% and palmitic acid with 27.00% were found considered to be significant components of S. cypria var. cypria. Furthermore, S. cypria var. elatior has a substantial fraction of linalool and palmitic acid, with 10.92% and 46.76%, respectively, where the MIC values of the volatiles towards Gram-negative and Gram-positive bacteria varied from 10 to 20 mg/mL. C. albicans was shown to be among the furthermost resistant yeast-like fungus, with MIC values found to be high than 20 mg/mL.
The essential oils of three Scutellaria species ( Scutellaria orientalis ssp. Alpina, Scutellaria brevibracteata , and Scutellaria hastifolia ) were tested in contradiction to the feeding and egg-laying activities of Spodoptera littoralis in research published by Formisano et al. Both S. brevibracteata and S. hastifolia extraction inhibited female moth egg laying on sheets; however, only S. hastifolia essential oil halted Spodoptera littoralis larvae from eating on mitigation discs . As per Giuliani et al., the essential oil of S. rubicunda subsp. linnaeana has antifeedant action in contradiction of Spodoptera littoralis . S. littoralis is a contraction for the letter S. The essential oil of the plant generated a dose-dependent positive feeding response in littoralis larvae. Scutalbin C, Scutecyprol B, and scutecyprol B remained initiate in aerial sections of S. rubicunda subsp. linnaeana . Linnaeana (FI at 100 ppm = 100) was antifeedant to larvae of five Lepidoptera species .
Phytochemicals from various Scutellaria species displayed substantial cytotoxic effects on some human tumor cell lines in vitro. Flavonoids, neoclerodan diterpenoids, iridoids, phenyl alcohol glycosides, and alkaloids have all been identified from Scutellaria species. S. strigillosa essential oil has been studied for phytotoxicity to amaranth and bluegrass (amaranthus is a worldwide genus of annual or short-lived perennial plants, while bluegrass refers to numerous species of grasses of the genus Poa). Amaranthus seedling progress was completely inhibited by 3 μ L/mL essential oil, although bluegrass growth was just slightly affected .
The acaricidal toxicities of 1-hydroxynaphthalene from S. barbata oil and its derivatives were determined and compared with those of benzyl benzoate. S. barbata essential oil has potent acaricidal action than the control sample (benzyl benzoate) .
S. grossa essential oil extracts had potent antibacterial effects on Bacillus subtilis and Enterococcus faecalis (MIC, 31.25–62.5 μ L/mL), along with Klebsiella pneumoniae as well as Salmonella enterica (MIC, 125 μ L/mL). S. lindbergii Rech.f. ethanolic had to have a considerable antibacterial property, with a MIC value of 6.25 mg/mL −1 . The steam volatile oil derived from S. repens aerial parts displayed identified potential towards E. faecalis (the MIC was found to be 125 μ L/mL −1 ), Escherichia coli (MIC, 31.25 μ L/mL −1 ), and Klebsiella pneumoniae (MIC, 250 μ L/mL −1 ) . The chemical constituents of the steam volatile oil produced by steam distillation of this aerial portion of Scutellaria grossa Wall ex Benth. (Lamiaceae) were investigated using capillary GC and GC-MS. Oxygenated monoterpenes were shown to be abundant in the oil (88.6%). There must have been 50 elements discovered, accounting for 94.4% of the overall oil content. Linalool (37.0%) and 1-octen-3-ol (32.0%) were shown to have main components. The oil's antibacterial efficacy towards ten bacterial strains was established by measuring the growth inhibitory zones. The oil had substantial antibacterial action toward Gram-positive Bacillus subtilis and Enterococcus faecalis bacteria as well as Gram-negative Klebsiella pneumoniae but also Salmonella enterica enterica bacteria. The minimal inhibitory concentration against E. faecalis was reported at 31.25 μ L mL –1 .
Many combinations of Scutellaria baicalensis hot water extract (SB-HW) and Chrysanthemum morifolium ethanol extract (CM-E) were tested for anti-inflammatory activity. SB-HW (80 g/mL)/CM-E (120 g/mL) or SB-HW (40 g/mL)/CM-E (160 g/mL) substantially decreased LPS-stimulated NO and IL-6 levels in RAW 264.7 cells. SB-HW (80 g/mL)/CM-E (120 g/mL) was shown to be the most effective combination for suppressing MUC5AC secretion in PMA- and LPS-induced NCI-H292 cells. In PMA-induced A549 cells, the active combination also reduced PGE2 and IL-8 production. According to LC-MS/MS tests, the active combination had a high concentration of flavone glycosides such as baicalin and cynaroside. The active combination inhibited phosphorylation of ERK, JNK, and p38 on Western blots, showing that MAPK signaling was inhibited. The active combination, according to our findings, might be employed as a new anti-inflammatory herbal medication .
S. edelbergii crude extract with subfraction analgesic effectiveness was tested in Swiss albino mice at various dosages to treat acetic acid-induced writhes. In this investigation, aspirin was utilized as a control. EtOAc was found to be the most active fraction, with inhibition rates of 37% and 55% at dosages of 50 and 100 mg/kg body weight, respectively, followed by chloroform, with inhibition rates of 29% and 48% at doses of 50 and 100 mg/kg body weight, respectively .
The cytotoxic potential of essential oils found in this prooxidant behavior can make this effective disinfectant and microbial mitigation for personal use, including air purification, personal hygiene, and even internal use via oral ingestion, and also the pesticide approval process for agricultural or supply product preservation . Essential oils have a considerable advantage in that they can be free of long-term genotoxic effects. Furthermore, several of them still have strong antimutagenic potential, which could also be connected to anticarcinogenic action. Current findings have shown that the prooxidant activities of essential oils or certain of their ingredients, as well as those of many polyphenols, are particularly efficient in reducing either tumor volume or tumor growth using apoptotic and/or necrotic activities. Myrica gale essential oil possesses an anticancer effect on lung and colon cancer cell lines, per Carson and Riley . Nigella sativa has been established to have an antiproliferative effect and suppressed 1,2-dimethylhydrazine-induced malignancy in rats by Sun et al. Because essential oils have the potential to interact with mitochondrial activity, they would add prooxidant effects and even become true antitumor agents. Several radical-producing drugs are used in anticancer therapies. In the case of essential oils, oxidative generation may be strictly controlled and tailored while representing no harmful or mutagenic risks to healthy cells . Essential oils or related bioactive constituents might be integrated into vectorized liposomes, allowing for more precise quantification. As a result, essential oils may force their way from the classical to the pharmaceutical sphere . Scutellaria is a genus of seldom shrubs, herbs, or subshrubs, with a broad range of structures. Many plants in this genus are being used as conventional remedies to cure a variety of ailments all over the world, with their most popular medicinal portions including the root, aerial part, and complete plant. As per the reports, aerial parts of around 12 species, 5 subspecies, and 1 variation have been used in conventional ways. The majority of them will be capable of treating the neurological disorder, trauma, allergies, peptic, cerebrovascular illnesses, hepatic cardiovascular and gallbladder disorders, and malignancy. Likewise, the majority of the therapeutic plants of the genus Scutellaria are tiny plants, have short roots, and are present mostly in Europe, Latin America, Asia, and Southwest Asia. The roots of around 16 species and 4 variations are also used to treat a variety of diseases, including respiratory disorders, miscarriage, liver and gall problems, gastric diseases, hypertension, insomnia, and trauma, and are primarily found in China. This species was distinguished by its well-developed rhizome features. Cold symptoms, infectious diseases, snake bites, hepatitis, peptic disorders, gynecologic inflammation, internal injury, renal vacuousness, lumbar discomfort, pyelonephritis, migraine, toothache, major trauma, tinea of the feet and hands, and miscarriage are among the ailments treated with the whole plant. These species, which are mostly perennial plants and subshrubs, are found across East and South Asia. As a result, the identification of therapeutic components may be influenced by vegetation structure and regional medical practices. Moreover, due to its several flavonoids, Scutellaria has been deemed a distinct genus of Scutellarioideae , and while several chemicals, specifically a number of diterpenes, have already been discovered in Scutellaria in recent times. There are also variances in the dispersion of the chemicals based on established chemistry research on these therapeutic plants in the genus Scutellaria . Is there a link between many medical components, organic compounds, and applications? As we investigated S. baicalensis and S. barbata , the two largest studied species in terms of nutrients, we determined the difference in chemical structure, pharmacological components, and therapeutic properties . Scutellaria baicalensis is an herbaceous plant with a dense and meaty rhizome, and the dried root of Scutellaria baicalensis has an abundance of 4′‑deoxyflavones, which lead to Radix Scutellariae 's clarifying warmth and detoxing properties. S. barbata , on hand, is a perennial herb with a small and thick rhizome that comprises flavonoids and is high in neo-clerodane diterpenoids, and the entire plant has been used to treat cancer, major injuries, and carbuncles . Neo-clerodane diterpenoids are recognized to be reflective components of S. barbata . Moreover, they are the existing research area of S. barbata with varied geometries and strong carcinogenic and antifeedant actions. Hence, it is suggested that every species' different molecular components coincide with unique medical value and that their pharmacological purposes correlate with their morphological features. Ignoring the fact that so much research on their chemical characteristics is concentrated on the pharmacological parts, and various bioactive components have been separated from Scutellaria medicinal plants, their impact on the plants' claimed medical benefit or demonstrable pharmacological properties has not yet been satisfactorily studied. Furthermore, phytochemistry research on nearly 50% of those phytochemical constituents has not yet been completed. As a result of insufficiently defined studies on these herbs and shrubs, the links between the therapeutic component chemical characteristics and traditional usage in other medicinal belonging to the genus Scutellaria require future investigation. More studies need to be done to look for particular bioactive components in Scutellaria plants . Scutellaria is a Lamiaceae genus that has been used as medicine for countless generations . Multiple investigations into the essential oils of several Scutellaria species have now been conducted . Nonetheless, because several species of the Scutellaria genus will not be researched, many studies on the composition and biologically active compounds of underresearched Scutellaria essential oils may be completed. The present investigation highlights the chemical characteristics and bioactivities of the Scutellaria genus (antioxidant, antifeedant, antibacterial, phytotoxic, and acaricidal activities). The essential characteristics comprised β -farnesene, hexadecanoic acid, β -caryophyllene, germacrene D, linalool, and eugenol (any of these oil constituents contain therapeutic capabilities). This article can be used as a guide in the disciplines of essential oils and ethnopharmacology.
Essential oils are secondary metabolites with a variety of organic structures that have therapeutic activity depending on their content. With about 250 species, Scutellaria is a Lamiaceae genus of perennial plant species. For a long time, it has been used to treat hypertension, arteriosclerosis, allergies, hyperlipidemia, inflammatory illnesses, hypertension, and hepatitis. Several substances, particularly essential oils, have been discovered in numerous studies on the chemical constituents of the Scutellaria genus. Various compounds have been discovered in studies on the chemical compositions of essential oils from the Scutellaria genus. Chemical constituents and biological activities of Scutellaria essential oils were identified. The main components of this genus' essential oils are hexadecenoic acid, farnesene, caryophyllene, germacrene D, linalool, and eugenol. Although 38 studies on the essential oils of Scutellaria species are still available, there appears to be a large number of species that need to be investigated. As a result, more research is needed into the various elements and pharmacological actions of unstudied Scutellaria essential oils. Based on available data, this study examined studies on the chemistry and biochemical processes of Scutellaria essential oils, including phytotoxic, antioxidant, antimicrobial, antifeedant, and antiparasitic toxic effects.
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A transdisciplinary team approach to scoping reviews: the case of pediatric polypharmacy | b3ac2800-890d-4c05-a82a-c11caa13f6c5 | 6172739 | Pediatrics[mh] | Exposure to multiple medications is common among pediatric patients in both inpatient and outpatient settings [ – ]. Using multiple medications can have benefits such as augmentation, tolerability, and efficacy [ – ], or harms such as adverse drug reactions, drug-drug interactions, difficulty adhering to complex regimens, toxicity, overdose, and increased cost [ – ]. Balancing harms and benefits is challenging for prescribers, especially with limited evidence to guide treatment in pediatric patients, and varying definitions and methodologies for pediatric polypharmacy [ , , ]. In the pediatric literature, the term polypharmacy is commonly used when more than one medication is prescribed for a single disease, despite the reality that it is more common to use multiple medications in patients with comorbid diagnoses [ – ]. In this context, we conducted a transdisciplinary scoping review to map the pediatric polypharmacy literature, identify gaps in literature, clarify the definition, and describe the prevalence of pediatric polypharmacy. Transdisciplinary team science is the most integrated form of collaborative research, after interdisciplinary and multidisciplinary approaches . The three terms refer to the involvement of multiple disciplines interacting in different ways while examining aspects of the same larger question or problem. Multidisciplinary is the most basic level of involvement where each discipline independently applies knowledge and approaches, often in a sequential fashion. Interdisciplinary involves concurrent reciprocal interaction among disciplines, necessitating a degree of blurring of disciplinary boundaries. Transdisciplinary transcends disciplinary boundaries to consider the dynamics of systems in a holistic way . To achieve the highest level of collaboration over the broad topic of pediatric polypharmacy, we selected the transdisciplinary team approach for our scoping review. A scoping review is a form of knowledge synthesis that addresses an exploratory research question aimed at mapping key concepts, types of evidence, and gaps in research related to a defined area or field [ – ]. Like a systematic review, a scoping review uses transparent and reproducible processes to define a research question, search for studies, and synthesize findings. However, a systematic review typically focuses on a well-defined question and aims to provide answers to questions from a relatively narrow range of studies assessed for quality. A scoping study, in contrast, uses the literature to address a broader research question, typically without assessing quality of studies [ , , ]. Scoping reviews seek to reveal patterns that emerge from the literature and are more likely to be hypothesis generating, whereas systematic reviews often are hypothesis testing . We believe that applying a transdisciplinary approach to a scoping review is novel in pediatric literature synthesis. A transdisciplinary team approach is holistic in that team members from different disciplines exchange expertise, knowledge and skills around a complex problem, resulting in integrated insights not easily assigned to a particular discipline . Representatives of different disciplines transcend their separate conceptual, theoretical, and methodological orientations in order to develop a common conceptual framework, in ways that go beyond multidisciplinary and interdisciplinary approaches [ – ]. In multidisciplinary approaches, different disciplines work in parallel or sequentially with the research questions and methods staying within the boundaries of each discipline . Interdisciplinary approaches harmonize links between, typically two, disciplines while mostly maintaining disciplinary identities without a common framework . Success of these collaborative initiatives depends on the extent to which cross disciplinary integrations are actually achieved by research teams . A common feature of scoping studies has been the need to engage researchers from a wide range of academic disciplines . Additionally, authors may find it appropriate to search multiple sources of literature— quantitative, qualitative, text, opinion pieces, or summaries [ – ]. Multidisciplinary approaches have been widely used in scoping studies . A multidisciplinary team provides the required specialist knowledge to map a subject that is not necessarily always found in one field . This approach can, however, create problems as researchers from very different theoretical perspectives often have difficulty in working together . Because of its intentional integrational nature, the transdisciplinary approach may be better suited to handle the broad research questions and types of literature of scoping studies . Similar to the transdisciplinary approach, an integrated knowledge translation approach is a collaborative research process whereby researchers and knowledge users work together from developing the question through designing, completing the literature search, analyzing and interpreting the data and disseminating the results . While multiple research teams have conducted narrative, scoping, and systematic reviews on polypharmacy among adults and the elderly [ – ], we were unable to find transdisciplinary teams that conducted systematic or scoping reviews of studies involving pediatric polypharmacy. In this manuscript, we report the methods of our transdisciplinary scoping review of pediatric polypharmacy. To facilitate potential replication by others, we also describe the key roles of our transdisciplinary team members.
Study design and methodology We used the methodological framework for scoping reviews proposed by Arksey and O’Malley, and enhanced by others [ – , , – ]. We specifically adopted Levac and colleagues’ modifications including the steps outlined below . Our detailed protocol is available from the corresponding author upon request. Articulate the research question in relation to the purpose and rationale of the study. Identify relevant studies while considering human and financial resources, breadth, and comprehensiveness. Select studies using an iteratively developed search strategy, and abstract and full text inclusion and exclusion criteria, applied independently by two reviewers. Chart the data by two reviewers using a collectively and interactively developed extraction form. Collate, summarize, and report the results in relation to study purpose, and implications for policy, practice, or research Conduct ongoing engagement and consultation of experts to further understand the concept of pediatric polypharmacy Transdisciplinary team approach Our transdisciplinary team included core disciplines of pediatrics, pharmacy, evidence synthesis, epidemiology, and library and information science. We developed three sub-teams: the implementation team, the protocol team, and the project stakeholders or consultants. The implementation team was comprised of ten members who developed the protocol and standard operating procedures (SOPs), collected data and drafted the manuscripts. The protocol team - a group of three experts in internal medicine, research implementation, pharmaceutical outcomes research, pediatrics, health services research and policy - oversaw the development and implementation of the research by mentoring and advising the implementation team. Project stakeholders/consultants included experts in content areas critical to our research, including mental health, childhood complex chronic disease conditions, pediatrics, epilepsy, pharmacoepidemiology, and scoping research methodology. We consulted with members of this group during protocol development, data interpretation, and reporting. We identified and recruited members to our team locally from three large hospital systems, a medical school, and a nursing school, and nationally, including authors of seminal manuscripts in the field. Graduate research assistants brought further relevant disciplinary expertise, including biostatistics and public health, into the team. We illustrate our transdisciplinary team in Fig. . The overlapping boxes and fading color depict the merging and fading of the individual disciplines into a new distinct transdisciplinary product. A team leader coordinated the activities of our transdisciplinary team. The implementation team met weekly, in person and via teleconference, while the broader team communication was primarily electronic. Table summarizes the activities of our transdisciplinary implementation team, designed to foster communication and cooperation, and to ensure quality research outputs. We conducted training sessions for the implementation team at critical stages of the study, including when the team was newly created, when new members joined the team, and before the beginning of the pilot and implementation phases. We used weekly meetings to discuss challenging studies and share information about progress, interrater agreement, weekly targets, and quality improvement. The epidemiologist, librarian, pharmacists, pediatric neurologist, and evidence synthesis expert on the implementation team provided disciplinary perspectives during training, SOP development, and review of studies. For example, the epidemiologist helped to incorporate principles of study design; pharmacists guided the classification of medications; clinicians clarified clinical meaning; and the librarian guided the team towards best practices in literature search. Each played an integral role in teaching the team respective disciplines to help in the execution of the project. These experts on our implementation team also screened studies and extracted data (Additional file ), requiring them to learn and apply skills from other disciplines. For example, the librarian participated in conceptualizing the project, screening and extracting data from studies, and drafting abstracts and manuscripts in addition to searching for studies. The incorporation of internal content experts was efficient and informative when faced with the many technical, pharmacological, and clinical data challenges in the literature. Even so, medication classification remained challenging because of the existence of multiple classification systems and the presence of apparent misclassifications in the literature. The ready availability of pharmacists on the team made it possible to complete the work despite this lack of clarity. The team made use of a shared Google Drive account to create and/or store research documents including the protocol, responses to an appreciative inquiry questionnaire , “letters to Mum” (described in Table ), seminal methodological manuscripts, meeting minutes, SOPs, draft abstracts, and manuscripts. We used the tool “letter to Mum” to convey the need to communicate our research to lay people, referring to one of our team member’s mum who is unschooled. Protocol The team leader (PB) conceptualized the research questions and drafted the research protocol in consultation with the evidence synthesis expert (SB) and librarian (JS). The rest of the team, including our stakeholders, reviewed, edited, and approved the protocol before implementation. This iterative process ensured that the experts generated transdisciplinary research questions and approaches. We made a few modifications to the protocol during implementation to refine our inclusion and exclusion criteria in keeping with scoping review methodology. For example, while our search strategy specified children, we decided to retain any resulting studies that included a few young adults up to age 25 when they predominantly studied children below age 19 and were conducted in pediatric facilities. The team leader drafted the initial screening and data extraction forms which, with input from the implementation team, underwent considerable changes during the pilot and implementation phases of the study. This process aligns with the iterative nature of scoping reviews . These modifications were valuable as they were informed by new insights, discoveries, prior omissions, and the need for clarification discovered during study screening and data extraction. As a function of EPPI Reviewer-4 software , our screening and data extraction forms were able to accommodate reference information explaining the meaning of each field and how it should be completed. These SOPs were developed iteratively by our core implementation team. They were also available to team members as stand-alone electronic copies in our shared Google Drive account for reference. The SOPs, screening, and data extraction forms were piloted on 100 studies. Twenty-one of these studies were included in the final data. Eligibility We sought to review original observational studies written in English that assessed polypharmacy in children 18 years of age or younger. Studies must have assessed polypharmacy as an aim, outcome measure, main predictor of outcome, or a covariate. We did not impose any geographical or publication year limits. Neither did we consider study quality, as is common in scoping reviews. We excluded case reports; non-English or non-original studies (reviews, opinion pieces, letters, or abstracts); studies exclusively conducted in adult subjects; those not about polypharmacy; or those that assessed polypharmacy experimentally, prenatally, or during breastfeeding. We excluded experimental research because our study aims involved gaining understanding regarding the practice patterns, definition, and prevalence of pediatric polypharmacy, which cannot be addressed by experimental studies. Search strategy Our librarian developed a search strategy in consultation with the team leader and evidence synthesis expert. The final MEDLINE search strategy is shown in Fig. . First, we searched the following databases from inception to October 2016 using controlled vocabulary and free text terms for the concepts of polypharmacy and children: Ovid Medline, PubMed, EMBASE, CINAHL, Ovid PsycINFO, Cochrane CENTRAL, ProQuest Dissertations & Theses A&I, and the Web of Science Core Collection. We then updated the database search in July 2017. Finally, we hand searched a random sample of 30 studies (10% of included studies from the original search), as well as six relevant review articles to find any studies our database search might have missed. The six review articles were purposively selected by two reviewers, out of 15 identified by the whole review team, prioritizing medications studied (all medications, antipsychotics, antiepileptic), age groups (neonates, older children), and outcomes (e.g. adverse drug reactions). Study selection Once we acquired relevant titles and abstracts, two independent reviewers screened titles and abstracts together using a standardized abstract screening form. Likewise, pairs of independent reviewers screened full text articles using an article screening form. Reviewer pairs met in-person or by telephone to reconcile differences after independently reviewing their studies. Conflicts were resolved by the larger implementation team. Data extraction We iteratively designed a comprehensive data extraction form to collect information pertaining to study and population characteristics, study measures, definition of polypharmacy, diseases and medications evaluated. Sections of the extraction form were initially drafted by members of the relevant disciplines (e.g. medications by pharmacists, disease conditions by pediatricians, and study measures by epidemiologists) then they were discussed and revised by the transdisciplinary team. Data extraction was conducted through two sequential reviews. Our detailed data extraction form is provided in Additional file . We timed both screening and data extraction in order to distribute studies according to each reviewer’s availability and review speed. In addition to computing individual average duration, we computed group average duration of screening and data extraction in order to establish an objective timeline of study activities. This tracking did not take into account the immense amount of time spent on project administration, database searches, article retrieval, data cleaning, and processing. Data synthesis We conducted both qualitative and quantitative synthesis of the data. We performed a qualitative synthesis on the definitions of polypharmacy that assessed text definitions for the presence of components such as number of medications, overlap period of medications, class or drug level, medication or class name, and limitation to one or two medications. Additionally, we conducted descriptive statistics of individual variables and cross-tabulated variables to examine relationships. A pharmacist, an epidemiologist, and a library and information scientist conducted the qualitative synthesis in pairs and among all of them in case of disagreements. The quantitative health scientists (epidemiologist and statisticians) performed the descriptive statistics and shared preliminary results with both the review team and consultants for input before generating the final results. Software We used Clarivate Analytics EndNote (X7) to find studies and remove duplicates. We then imported the titles and abstracts into EPPI-Reviewer 4 (EPPI) . We used EPPI for data management and collaborative review. It aided us in randomly assigning studies to groups, creating screening and data extraction forms, screening studies and reconciling differences, data cleaning, data synthesis, and report generation. We used SAS and Microsoft Excel to compute Kappa statistics, process, and analyze data downloaded from EPPI. Quality control Implementing quality control measures such as training, independent paired reviews and the use of standardized data collection forms reinforced the reliability of our study procedures. We screened titles and abstracts in batches of 120 randomly assigned studies and extracted data from 20 randomly assigned full text studies per pair of reviewers. The team leader purposively assigned these groups to varying review pairs to maximize interactions between team members based on availability, experience, and academic discipline. We measured inter-rater reliability using percent agreement and Kappa statistic ( k ) . Percent agreement for each group of studies was immediately available to the reviewer pair. The team leader also generated cumulative percent agreement on a weekly basis to provide insight on screening uniformity. We discussed strategies for improving agreement during our weekly team meetings. Kappa statistic was computed for a 30% sample of all titles and abstracts screened as well as for all full text studies screened.
We used the methodological framework for scoping reviews proposed by Arksey and O’Malley, and enhanced by others [ – , , – ]. We specifically adopted Levac and colleagues’ modifications including the steps outlined below . Our detailed protocol is available from the corresponding author upon request. Articulate the research question in relation to the purpose and rationale of the study. Identify relevant studies while considering human and financial resources, breadth, and comprehensiveness. Select studies using an iteratively developed search strategy, and abstract and full text inclusion and exclusion criteria, applied independently by two reviewers. Chart the data by two reviewers using a collectively and interactively developed extraction form. Collate, summarize, and report the results in relation to study purpose, and implications for policy, practice, or research Conduct ongoing engagement and consultation of experts to further understand the concept of pediatric polypharmacy
Our transdisciplinary team included core disciplines of pediatrics, pharmacy, evidence synthesis, epidemiology, and library and information science. We developed three sub-teams: the implementation team, the protocol team, and the project stakeholders or consultants. The implementation team was comprised of ten members who developed the protocol and standard operating procedures (SOPs), collected data and drafted the manuscripts. The protocol team - a group of three experts in internal medicine, research implementation, pharmaceutical outcomes research, pediatrics, health services research and policy - oversaw the development and implementation of the research by mentoring and advising the implementation team. Project stakeholders/consultants included experts in content areas critical to our research, including mental health, childhood complex chronic disease conditions, pediatrics, epilepsy, pharmacoepidemiology, and scoping research methodology. We consulted with members of this group during protocol development, data interpretation, and reporting. We identified and recruited members to our team locally from three large hospital systems, a medical school, and a nursing school, and nationally, including authors of seminal manuscripts in the field. Graduate research assistants brought further relevant disciplinary expertise, including biostatistics and public health, into the team. We illustrate our transdisciplinary team in Fig. . The overlapping boxes and fading color depict the merging and fading of the individual disciplines into a new distinct transdisciplinary product. A team leader coordinated the activities of our transdisciplinary team. The implementation team met weekly, in person and via teleconference, while the broader team communication was primarily electronic. Table summarizes the activities of our transdisciplinary implementation team, designed to foster communication and cooperation, and to ensure quality research outputs. We conducted training sessions for the implementation team at critical stages of the study, including when the team was newly created, when new members joined the team, and before the beginning of the pilot and implementation phases. We used weekly meetings to discuss challenging studies and share information about progress, interrater agreement, weekly targets, and quality improvement. The epidemiologist, librarian, pharmacists, pediatric neurologist, and evidence synthesis expert on the implementation team provided disciplinary perspectives during training, SOP development, and review of studies. For example, the epidemiologist helped to incorporate principles of study design; pharmacists guided the classification of medications; clinicians clarified clinical meaning; and the librarian guided the team towards best practices in literature search. Each played an integral role in teaching the team respective disciplines to help in the execution of the project. These experts on our implementation team also screened studies and extracted data (Additional file ), requiring them to learn and apply skills from other disciplines. For example, the librarian participated in conceptualizing the project, screening and extracting data from studies, and drafting abstracts and manuscripts in addition to searching for studies. The incorporation of internal content experts was efficient and informative when faced with the many technical, pharmacological, and clinical data challenges in the literature. Even so, medication classification remained challenging because of the existence of multiple classification systems and the presence of apparent misclassifications in the literature. The ready availability of pharmacists on the team made it possible to complete the work despite this lack of clarity. The team made use of a shared Google Drive account to create and/or store research documents including the protocol, responses to an appreciative inquiry questionnaire , “letters to Mum” (described in Table ), seminal methodological manuscripts, meeting minutes, SOPs, draft abstracts, and manuscripts. We used the tool “letter to Mum” to convey the need to communicate our research to lay people, referring to one of our team member’s mum who is unschooled.
The team leader (PB) conceptualized the research questions and drafted the research protocol in consultation with the evidence synthesis expert (SB) and librarian (JS). The rest of the team, including our stakeholders, reviewed, edited, and approved the protocol before implementation. This iterative process ensured that the experts generated transdisciplinary research questions and approaches. We made a few modifications to the protocol during implementation to refine our inclusion and exclusion criteria in keeping with scoping review methodology. For example, while our search strategy specified children, we decided to retain any resulting studies that included a few young adults up to age 25 when they predominantly studied children below age 19 and were conducted in pediatric facilities. The team leader drafted the initial screening and data extraction forms which, with input from the implementation team, underwent considerable changes during the pilot and implementation phases of the study. This process aligns with the iterative nature of scoping reviews . These modifications were valuable as they were informed by new insights, discoveries, prior omissions, and the need for clarification discovered during study screening and data extraction. As a function of EPPI Reviewer-4 software , our screening and data extraction forms were able to accommodate reference information explaining the meaning of each field and how it should be completed. These SOPs were developed iteratively by our core implementation team. They were also available to team members as stand-alone electronic copies in our shared Google Drive account for reference. The SOPs, screening, and data extraction forms were piloted on 100 studies. Twenty-one of these studies were included in the final data.
We sought to review original observational studies written in English that assessed polypharmacy in children 18 years of age or younger. Studies must have assessed polypharmacy as an aim, outcome measure, main predictor of outcome, or a covariate. We did not impose any geographical or publication year limits. Neither did we consider study quality, as is common in scoping reviews. We excluded case reports; non-English or non-original studies (reviews, opinion pieces, letters, or abstracts); studies exclusively conducted in adult subjects; those not about polypharmacy; or those that assessed polypharmacy experimentally, prenatally, or during breastfeeding. We excluded experimental research because our study aims involved gaining understanding regarding the practice patterns, definition, and prevalence of pediatric polypharmacy, which cannot be addressed by experimental studies.
Our librarian developed a search strategy in consultation with the team leader and evidence synthesis expert. The final MEDLINE search strategy is shown in Fig. . First, we searched the following databases from inception to October 2016 using controlled vocabulary and free text terms for the concepts of polypharmacy and children: Ovid Medline, PubMed, EMBASE, CINAHL, Ovid PsycINFO, Cochrane CENTRAL, ProQuest Dissertations & Theses A&I, and the Web of Science Core Collection. We then updated the database search in July 2017. Finally, we hand searched a random sample of 30 studies (10% of included studies from the original search), as well as six relevant review articles to find any studies our database search might have missed. The six review articles were purposively selected by two reviewers, out of 15 identified by the whole review team, prioritizing medications studied (all medications, antipsychotics, antiepileptic), age groups (neonates, older children), and outcomes (e.g. adverse drug reactions).
Once we acquired relevant titles and abstracts, two independent reviewers screened titles and abstracts together using a standardized abstract screening form. Likewise, pairs of independent reviewers screened full text articles using an article screening form. Reviewer pairs met in-person or by telephone to reconcile differences after independently reviewing their studies. Conflicts were resolved by the larger implementation team.
We iteratively designed a comprehensive data extraction form to collect information pertaining to study and population characteristics, study measures, definition of polypharmacy, diseases and medications evaluated. Sections of the extraction form were initially drafted by members of the relevant disciplines (e.g. medications by pharmacists, disease conditions by pediatricians, and study measures by epidemiologists) then they were discussed and revised by the transdisciplinary team. Data extraction was conducted through two sequential reviews. Our detailed data extraction form is provided in Additional file . We timed both screening and data extraction in order to distribute studies according to each reviewer’s availability and review speed. In addition to computing individual average duration, we computed group average duration of screening and data extraction in order to establish an objective timeline of study activities. This tracking did not take into account the immense amount of time spent on project administration, database searches, article retrieval, data cleaning, and processing.
We conducted both qualitative and quantitative synthesis of the data. We performed a qualitative synthesis on the definitions of polypharmacy that assessed text definitions for the presence of components such as number of medications, overlap period of medications, class or drug level, medication or class name, and limitation to one or two medications. Additionally, we conducted descriptive statistics of individual variables and cross-tabulated variables to examine relationships. A pharmacist, an epidemiologist, and a library and information scientist conducted the qualitative synthesis in pairs and among all of them in case of disagreements. The quantitative health scientists (epidemiologist and statisticians) performed the descriptive statistics and shared preliminary results with both the review team and consultants for input before generating the final results.
We used Clarivate Analytics EndNote (X7) to find studies and remove duplicates. We then imported the titles and abstracts into EPPI-Reviewer 4 (EPPI) . We used EPPI for data management and collaborative review. It aided us in randomly assigning studies to groups, creating screening and data extraction forms, screening studies and reconciling differences, data cleaning, data synthesis, and report generation. We used SAS and Microsoft Excel to compute Kappa statistics, process, and analyze data downloaded from EPPI.
Implementing quality control measures such as training, independent paired reviews and the use of standardized data collection forms reinforced the reliability of our study procedures. We screened titles and abstracts in batches of 120 randomly assigned studies and extracted data from 20 randomly assigned full text studies per pair of reviewers. The team leader purposively assigned these groups to varying review pairs to maximize interactions between team members based on availability, experience, and academic discipline. We measured inter-rater reliability using percent agreement and Kappa statistic ( k ) . Percent agreement for each group of studies was immediately available to the reviewer pair. The team leader also generated cumulative percent agreement on a weekly basis to provide insight on screening uniformity. We discussed strategies for improving agreement during our weekly team meetings. Kappa statistic was computed for a 30% sample of all titles and abstracts screened as well as for all full text studies screened.
Studies reviewed Of 8651 citations, we screened 4398 studies. A total of 363 studies remained for data extraction and synthesis. A full list of the 363 included studies is provided in Additional file . Time investment The pilot phase lasted 3 months, implementation lasted 8 months, data cleaning and processing lasted 2 months. Individual time commitment varied among team members (Additional file ). On average, it took 7 min to screen a study on title and abstract, 13 min to screen on full text, 76 min to conduct a primary data extraction, 52 min to verify the extraction, and 30 min to address queries raised through the verification and data cleaning process. Dividing the total time spent on the reviews by the 363 included studies revealed that it took 7.3 h to produce a record in our analytic database. We required reviewers to time only their uninterrupted reviews which were 61% (220/363) of included studies. Inter-rater concordance The Kappa coefficients ( k ) ranged from fair to excellent (0.41–0.8) for all screening on title and abstract or full text, with/without reason for exclusion (Additional file ). Inter-reviewer agreement was highest when reviewers were similar to one another, for example, between pharmacists or between graduate assistants. The agreement was lowest between dissimilar reviewers, especially during the early phase of the implementation period. Pharmacists tended to go “deeper” when extracting information related to medicines and physicians went “deeper” when extracting information about disease conditions while non clinicians were uniform while extracting information. Inter-reviewer agreement increased as the study progressed, irrespective of reviewer similarity, mainly because we tasked specialists to simplify professional language while training others and writing SOPs.
Of 8651 citations, we screened 4398 studies. A total of 363 studies remained for data extraction and synthesis. A full list of the 363 included studies is provided in Additional file .
The pilot phase lasted 3 months, implementation lasted 8 months, data cleaning and processing lasted 2 months. Individual time commitment varied among team members (Additional file ). On average, it took 7 min to screen a study on title and abstract, 13 min to screen on full text, 76 min to conduct a primary data extraction, 52 min to verify the extraction, and 30 min to address queries raised through the verification and data cleaning process. Dividing the total time spent on the reviews by the 363 included studies revealed that it took 7.3 h to produce a record in our analytic database. We required reviewers to time only their uninterrupted reviews which were 61% (220/363) of included studies.
The Kappa coefficients ( k ) ranged from fair to excellent (0.41–0.8) for all screening on title and abstract or full text, with/without reason for exclusion (Additional file ). Inter-reviewer agreement was highest when reviewers were similar to one another, for example, between pharmacists or between graduate assistants. The agreement was lowest between dissimilar reviewers, especially during the early phase of the implementation period. Pharmacists tended to go “deeper” when extracting information related to medicines and physicians went “deeper” when extracting information about disease conditions while non clinicians were uniform while extracting information. Inter-reviewer agreement increased as the study progressed, irrespective of reviewer similarity, mainly because we tasked specialists to simplify professional language while training others and writing SOPs.
In this project, we established a transdisciplinary team of experts that conducted a large scoping review in order to map the pediatric polypharmacy literature, identify research gaps, clarify the definition of pediatric polypharmacy, and describe the prevalence of pediatric polypharmacy. In addition to reviewing studies, the team also provided internal consultation to one another throughout the project cycle. Study strengths In the past, some scoping reviews have been conducted by multidisciplinary and inter-professional teams while other large scoping reviews have depended on a few individuals to conduct the review . What distinguishes our project from many others is integration of the transdisciplinary approach at every stage of the scoping review . Five out of ten members of our implementation team participated in acquiring studies, nine reviewed studies, and eight were involved in drafting abstracts and manuscripts. Achieving this level of participation required learning about other disciplines and teaching one’s own discipline to each other. We illustrate this integrated effort through the description of activities of our health science librarian, a discipline that has been found lacking among authors of scoping reviews . The librarian was engaged during the whole scoping review cycle: conceptualizing the research question; developing database search strategies; retrieving studies, screening studies; extracting data; training team members; reviewing SOPs; and writing abstracts, posters, and manuscripts. Similar experiences were mirrored among members of the other core disciplines including pharmacists, clinicians, and research methodologists. With a librarian, epidemiologist, two pharmacists, and a clinician reviewing studies, we had internal consultation in our core disciplines. Moreover, we had a knowledge synthesis expert attend our weekly meetings to address pressing issues in real time. The transdisciplinary approach where we constantly worked on establishing a common strategy enabled us to perform internal consultation at least as rigorously as the inter-professional approach used by Daudt and colleagues . The episodic engagement of the project stakeholders provided a second layer of consultation. Time requirement As other authors of scoping reviews have argued previously, a scoping review is not a rapid review as it was initially defined . In our situation, it took thirteen months to complete the project. Lack of published guidance on detailed time frames made it difficult for us to project how much time each stage would take. The detailed extraction form partially explains why it took our group more than 2 h for each study. However, it is not likely that a shorter extraction form would have significantly reduced the amount of time needed to extract a study. Additionally, a shorter form would not have adequately met the needs of our broad research questions. One potential option for time saving could have included utilizing the machine learning capability available in EPPI Reviewer-4 (EPPI) software for screening on title and abstract. By our estimates, automated screening would have reduced our review time by about 800 h or 30% of the total time. This approach, however, would still require manually screening about 1000 random titles and abstracts from which EPPI would learn in order to screen the rest of the studies. In any case, we hope that future researchers planning scoping reviews similar to ours can use the 7 h estimate for an extracted study to plan their own projects. Limitations Our scoping review project had some limitations. As expected in a large team like ours, member involvement varied with time due to competing engagements and the unpredictable time requirements of our study. The team leader ensured that each person was assigned work proportional to their availability during each phase of the study. Setting short-term targets, typically of one to 2 weeks, helped to ensure continuity. Converging our team’s diverse training, experiences, and backgrounds around the concept of pediatric polypharmacy required more time, discussions, and meetings among team members. Whereas we achieved kappa coefficients in the moderate to substantial range of 0.41–0.80 , the coefficients for screening on title and abstract were lower than those for screening on full text. This may be explained by the difference in inclusion proportions at title and abstract screening of 25% and at full text screening of 30%. The opportunity for chance agreement to increase (and for kappa coefficients to decrease) is enhanced with the deviation of inclusion proportion away from 50% . Overall, both percent agreement and kappa coefficients increased as the study progressed, implying mastery of screening guidelines with time and practice. The high agreement we observed between reviewers of the same discipline seems to imply similarity of background knowledge rather than protocol-based decisions. Minimizing the paring of reviewers with similar disciplinary backgrounds and changing reviewer pairs of study batches between the screening phases addressed this problem. Excluding experimental and non-primary observational studies such as review studies may have led to exclusion of some definitions of pediatric polypharmacy, affecting one of the primary aims of this study.
In the past, some scoping reviews have been conducted by multidisciplinary and inter-professional teams while other large scoping reviews have depended on a few individuals to conduct the review . What distinguishes our project from many others is integration of the transdisciplinary approach at every stage of the scoping review . Five out of ten members of our implementation team participated in acquiring studies, nine reviewed studies, and eight were involved in drafting abstracts and manuscripts. Achieving this level of participation required learning about other disciplines and teaching one’s own discipline to each other. We illustrate this integrated effort through the description of activities of our health science librarian, a discipline that has been found lacking among authors of scoping reviews . The librarian was engaged during the whole scoping review cycle: conceptualizing the research question; developing database search strategies; retrieving studies, screening studies; extracting data; training team members; reviewing SOPs; and writing abstracts, posters, and manuscripts. Similar experiences were mirrored among members of the other core disciplines including pharmacists, clinicians, and research methodologists. With a librarian, epidemiologist, two pharmacists, and a clinician reviewing studies, we had internal consultation in our core disciplines. Moreover, we had a knowledge synthesis expert attend our weekly meetings to address pressing issues in real time. The transdisciplinary approach where we constantly worked on establishing a common strategy enabled us to perform internal consultation at least as rigorously as the inter-professional approach used by Daudt and colleagues . The episodic engagement of the project stakeholders provided a second layer of consultation.
As other authors of scoping reviews have argued previously, a scoping review is not a rapid review as it was initially defined . In our situation, it took thirteen months to complete the project. Lack of published guidance on detailed time frames made it difficult for us to project how much time each stage would take. The detailed extraction form partially explains why it took our group more than 2 h for each study. However, it is not likely that a shorter extraction form would have significantly reduced the amount of time needed to extract a study. Additionally, a shorter form would not have adequately met the needs of our broad research questions. One potential option for time saving could have included utilizing the machine learning capability available in EPPI Reviewer-4 (EPPI) software for screening on title and abstract. By our estimates, automated screening would have reduced our review time by about 800 h or 30% of the total time. This approach, however, would still require manually screening about 1000 random titles and abstracts from which EPPI would learn in order to screen the rest of the studies. In any case, we hope that future researchers planning scoping reviews similar to ours can use the 7 h estimate for an extracted study to plan their own projects.
Our scoping review project had some limitations. As expected in a large team like ours, member involvement varied with time due to competing engagements and the unpredictable time requirements of our study. The team leader ensured that each person was assigned work proportional to their availability during each phase of the study. Setting short-term targets, typically of one to 2 weeks, helped to ensure continuity. Converging our team’s diverse training, experiences, and backgrounds around the concept of pediatric polypharmacy required more time, discussions, and meetings among team members. Whereas we achieved kappa coefficients in the moderate to substantial range of 0.41–0.80 , the coefficients for screening on title and abstract were lower than those for screening on full text. This may be explained by the difference in inclusion proportions at title and abstract screening of 25% and at full text screening of 30%. The opportunity for chance agreement to increase (and for kappa coefficients to decrease) is enhanced with the deviation of inclusion proportion away from 50% . Overall, both percent agreement and kappa coefficients increased as the study progressed, implying mastery of screening guidelines with time and practice. The high agreement we observed between reviewers of the same discipline seems to imply similarity of background knowledge rather than protocol-based decisions. Minimizing the paring of reviewers with similar disciplinary backgrounds and changing reviewer pairs of study batches between the screening phases addressed this problem. Excluding experimental and non-primary observational studies such as review studies may have led to exclusion of some definitions of pediatric polypharmacy, affecting one of the primary aims of this study.
In conclusion, we completed a scoping review as a transdisciplinary team. Our team efforts have enabled us to implement a project of considerable magnitude, as well as benefit from all team members’ skills and efforts. Our transdisciplinary review team provided inbuilt expert consultation which complemented that from external stakeholders. We found holding regular meetings, producing SOPs, and continually assessing internal validity to be helpful. We recommend that researchers conducting large scoping reviews consider using a transdisciplinary approach to elevate the breadth and focus of the questions; enhance the scoping review decisions and iterations; and enrich review conclusions. We hope the detailed description provided in this paper will help others conducting future scoping reviews when designing their studies and planning for necessary resource requirements.
Additional file 1: Distribution of Studies Reviewed and Time Spent by the Pediatric Polypharmacy Scoping Review Implementation Team. Reviewer work load and amount of time spent on abstract screening, full text screening, and data extraction. (DOCX 17 kb) Additional file 2: Data Extraction Form. All the questions used for extracting data. (DOCX 24 kb) Additional file 3: Included Studies. List of first author, year of publication, and title of all included studies. (DOCX 54 kb) Additional file 4: Inter-rater Concordance Measures for Screening on Title & Abstract, and Full Text . Details of percent agreement and kappa statistics for screening title & abstracts as well as full texts. (DOCX 19 kb)
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Novel heavily fucosylated glycans as a promising therapeutic target in colorectal cancer | 69fa707e-7496-4aaf-a9f2-a633149d2810 | 10373344 | Anatomy[mh] | In 2020, approximately 1.9 million newly diagnosed colorectal cancer (CRC) cases and more than 900 000 deaths from CRC were reported worldwide, accounting for 10% of cancer incidence and 9.4% of total cancer-related deaths in that year . Clinically, surgery remains the standard treatment for CRC, while radiotherapy, systemic medical treatment, or a combination of both may also be administered according to tumor location and stage . For metastatic CRC (mCRC), oxaliplatin- and irinotecan-based regimens are frequently used as first-line chemotherapy. However, drug resistance and intolerance of the adverse effects (e.g., hair loss, diarrhea, neurotoxicity, and hand-foot syndrome) have been reported . Furthermore, drug resistance is the leading cause of cancer relapse and disease progression, and biological agents have been developed to improve therapeutic responses . Targeted agents against vascular endothelial growth factor (VEGF) or epidermal growth factor receptor (EGFR) are used in combination with cytotoxic therapy as a first-line treatment for mCRC . However, only a few target agents are applied in clinical, and the overall survival rate of patients with distant metastasis is only 14% . Therefore, developing a new drug for treating CRC is a crucial task. Studies have reported that increased sialylation, galactosylation, and fucosylation are correlated with CRC progression . Tumor-associated fucosylated epitopes are a class of carbohydrate molecules and include Lewis a, Lewis y, Lewis x, and sialyl Lewis antigens . Among various features, fucosylation is among the most frequently occurring modifications in glycoproteins and glycolipids, and overexpression of fucosylated epitopes, including certain Lewis antigens, was detected in various epithelial cancers . The activity of fucosyltransferase (FUT) 3 and 6 promotes transforming-growth-factor-ß-mediated CRC cells through the epithelial–mesenchymal transition (EMT) and metastatic tendency, and the tumors in patients with advanced clinical stage CRC and vascular invasion exhibit high levels of fucosylated proteins . The expression of Lewis y was also detected in CRC tumors and revealed to be strongest in stage IV tumors . Among patients with CRC, nonresponders to irinotecan/5-fluorouracil (5-FU)/leucovorin exhibited considerably higher expression of sialyl Lewis X . Therefore, the overexpression of fucosylated epitopes is associated with tumor invasion, metastasis, poor prognosis, and drug resistance . In the present study, a humanized monoclonal antibody (mAb) was designed that specifically binds to novel heavily fucosylated glycans (HFGs). This novel fucosylated epitope, HFG, is a Lewis antigen–related glycan that is characterized by the presence of multiple fucose residues. Immunohistochemistry (IHC) and western blotting were performed to assess the expression level of HFG in tumor tissues and in normal tissues adjacent to tumors (NATs). Furthermore, we assessed the feasibility of chemotherapy drugs combined with anti-HFG mAb in CRC cells and demonstrated that this novel HFG is a potential tumor marker of CRC and a promising therapeutic target.
Human samples The present study was approved by the Institutional Review Board of Taipei Medical University Hospital (N201906007). Thirty patients with CRC and 10 healthy donors were randomly selected and recruited for the present study; their informed consent was obtained. Tumor tissues and NATs were collected between July 2019 and February 2020 during the surgical resection of the 30 patients with CRC at Taipei Medical University Hospital. Each NAT was sampled at least 10 cm from the tumor margin, and NATs were not allowed to exhibit the characteristics of malignant histopathology. All the tissue specimens were fixed with 10% formalin and embedded in paraffin blocks. Blood samples were collected from the 10 healthy donors and 30 patients with CRC before surgery and approximately 1 month after surgery between July 2019 and March 2020. Plasma samples were harvested by centrifuging the blood specimens at 1710 × g for 15 min at ambient temperature; the samples were then stored at − 80 °C until use. IHC and scoring criteria The tissue blocks from CRC patients were cut into 4-μm-thick sections and affixed onto slides. The tissue sections were deparaffinized with xylene, rehydrated using gradient alcohol, and then boiled in antigen retrieval buffer (10 mM citric acid and 0.05% Tween-20, pH 6.0) for 30 min. After three washes with phosphate-buffered saline (PBS), the sections were immersed in PBS containing 3% hydrogen peroxide (Sigma) to quench endogenous peroxidase activity. Anti-HFG mAb developed by GlycoNex Inc. was used to detect the expression of HFG. For the IHC analysis, the tissue slides of CRC patients and the human normal tissue microarray FDA999 (US Biomax) were incubated at 4 °C overnight with the primary antibody anti-HFG mAb at 20 and 2 μg/mL, respectively. Subsequently, after three washes with PBS, the slides were incubated for an hour with a secondary mouse anti-human IgG Fc-HRP antibody (Southern Biotech), at a dilution of 1:2,000 and then visualized using a DAB-Plus Substrate Kit (Dako). The scoring of patients’ tissues included the intensity and percentage of positively stained cells. Staining intensity was denoted as 0 (negative), 1 (weakly positive), 2 (moderately positive), or 3 (strongly positive). Staining percentage was examined based on the estimated percentage of stained tumor cells among the total tumor cells or the estimated percentage of stained epithelial cells among the total epithelial cells. As for the scoring of FDA999, the average staining intensity was presented from + to + + + , while – indicated negative staining. The number of positive stains in all tissues were also present in brackets. Human multiple cancer tissue microarrays BC000120, BC001128, and ST2091 were purchased from US Biomax. The tissue sections were first deparaffinized with xylene, rehydrated through gradient alcohol, and then boiled in antigen retrieval buffer (10 mM citric acid, 0.1% NP-40, pH 6.0) for 30 min. After washing three times with PBS, the sections were immersed in PBS containing 3% hydrogen peroxide (Sigma) to quench endogenous peroxidase activity. For IHC analysis, the slides were incubated with a primary antibody anti-HFG mAb (10 μg/mL) at room temperature for an hour. Then, after washing three times with PBS, the slides were incubated with a secondary mouse anti-human IgG (Fc)-BIOT antibody (Southern Biotech), at a dilution of 1:2,000 for an hour followed by VECTASTAIN® Elite® ABC HRP Kit (Vector Laboratories) and then visualized by DAB-Plus Substrate Kit (Dako). The staining was scored and further calculated as positive rates of staining because the tissue numbers of different cancer types varied. HFG expression on human cancer cell lines by flow cytometry Human cancer cell lines were obtained from the American Type Culture Collection (ATCC), Bioresource Collection and Research Center (BCRC) of the Food Industry Research and Development Institute (FIRDI, Hsinchu, Taiwan), and Japanese Collection of Research Bio-resources Cell Bank (JCRB) and then cultured according to standard mammalian tissue culture protocols and sterile technique. Each human cancer cell line was suspended in PBS with 2% heat-inactivated FBS (Hyclone) and added to a V-shape 96-well plate (Nunc), followed by the addition of equal volume of anti-HFG mAb. The plates were then incubated at 4 °C for an hour. After washing with PBS once, the plates were centrifuged, and the cell pellet was re-suspended in 200-fold PBS-diluted Fluorescein (FITC)-AffiniPure Goat Anti-Human IgG, Fcγ Fragment Specific (Jackson ImmunoResearch Inc) and incubated at 4 °C for 30 min. Then, the plates were centrifuged, and PBS was added to the wells to wash off unbound secondary antibodies. The cell pellet was re-suspended in ice-cold PBS and then analyzed on a FACS Canto cytometer instrument and FACS Diva software (BD Biosciences). Protein extraction and Western blot analysis Tissues were cut into pieces with sterilized scissors and washed three times with saline. They were then lysed using lysis buffer (1% Triton X-100 in 50-mM Tris–HCl and 0.15-M NaCl, pH 7.5), homogenized with TissueRuptor (QIAGEN), and agitated at 4 °C for 1 h. AGS and MKN45 cells were scraped from cell culture flasks and then washed three times with saline. Cells were lysed using lysis buffer and agitated at 4 °C for 30 min. Tissue and cell lysates were centrifuged at 15,521 × g and 4 °C for 15 min to remove debris. The supernatant was collected, and the concentration of lysates was determined using Pierce 660 nm Protein Assay Reagent (Thermo Scientific), MOPS running buffer (M00138, Genescript), ExpressPlus PAGE Gel (M42015, Genescript), and SurePAGE (M00657, Genescript) in sodium dodecyl sulfate–polyacrylamide gel electrophoresis. Tissue lysates (10 μg) or cell lysates (20 μg) were mixed with 1 × NuPAGE LDS sample buffer (NP0007, Invitrogen) and 1 × sample reducing agent (NP0009, Invitrogen). The protein samples were boiled at 100 °C for 10 min before being loaded into 4–20% gel, run at 80 V for 20 min, and then run at 110 V for 90 min. Proteins were transferred to polyvinylidene difluoride membrane (BSP0161, PALL) at 150 mA for 180 min. Immunoblotting was performed by conducting blocking with 5% skim milk at room temperature for 1 h, incubation overnight with 10 μg/mL of primary antibody anti-HFG mAb at 4 °C, and incubation with the secondary antibody mouse anti-human IgG Fc-HRP (1:5000, Southern Biotech) at ambient temperature for 1 h. Subsequently, the membranes were washed four times for 5 min with wash buffer (0.05% Tween-20 in PBS). Signals were visualized with electrochemiluminescence reagent (NEL105001EA, PerkinElmer). Cell culture and treatment DLD-1, SW1116, COLO 201, and COLO 205 cell lines were purchased from the American Type Culture Collection. The DLD-1 cells were maintained in complete RPMI-1640 medium (Gibco) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Hyclone) and cultured at 37 °C in a humidified incubator with 5% CO 2 . The SW1116 cells were maintained in Leibovitz's L-15 medium (Gibco) supplemented with 10% heat-inactivated FBS and cultured at 37 °C in a humidified incubator. All cell lines included in the study was summarized in Additional file : Table S1 with individual mutational status. The chemotherapy drugs used in the present study included 5-FU (Nang Kuang Pharmaceutical), oxaliplatin (Oxalip, TTY Biopharm), and irinotecan (Campto, Pfizer). DLD-1 and SW1116 cells were seeded at 5 × 10 3 and 2 × 10 4 cells/well, respectively, in 96-well culture plates (Greiner Bio-One). After they were incubated overnight, the cells were treated with either vehicle, a combination of 5-FU plus oxaliplatin, or a combination of 5-FU plus irinotecan and then incubated in a 37 °C humidified incubator for 48 h. All drugs were diluted in the aforementioned cell culture medium. Chemotherapy drug treatments were divided into low-concentration and high-concentration groups. Among the cells treated with low concentrations of chemotherapy drugs, the DLD-1 cells were treated with 1 μM 5-FU and 1.5 μM oxaliplatin or 1 μM 5-FU and 20 μM irinotecan, whereas the SW1116 cells were treated with 5 μM 5-FU and 30 μM oxaliplatin or 5 μM 5-FU and 60 μM irinotecan. Among the cells treated with high concentrations of chemotherapy drugs, the DLD-1 cells were treated with 5 μM 5-FU and 6 μM oxaliplatin or 5 μM 5-FU and 60 μM irinotecan, whereas the SW1116 cells were treated with 75 μM 5-FU and 50 μM oxaliplatin or 75 μM 5-FU and 100 μM irinotecan. Complement-dependent cytotoxicity (CDC) assay After the cells were incubated with chemotherapy drugs for 48 h, their supernatant was discarded. Subsequently, 50 μL of the medium, 50 μL of anti-HFG mAb (at the final concentration of 25, 100, or 400 μg/mL), and 50 μL of normal human serum complement (QUIDEL) were added to a 96-well plate sequentially. The plate was incubated at 37 °C for 4 h. The cytolysis of DLD-1 and SW1116 cells was analyzed using the CellTiter-Glo Luminescent Cell Viability Assay (Promega) in accordance with the manufacturer’s instructions. The cell viability of control well–indicated DLD-1 and SW1116 cells not treated with chemotherapy drugs or anti-HFG mAb-induced CDC was evaluated using the following formula: cell viability = (experimental well/control well) × 100%. In vivo CRC xenograft model Animal experiments were performed strictly in accordance with the regulations of the Institutional Animal Care and Use Committee (IACUC) of GlycoNex. Specific-pathogen-free female CB17 severe-combined-immunodeficiency (SCID) mice were purchased from BioLASCO (Taiwan). DLD-1, COLO 201, and COLO 205 cells were resuspended at a cell density of 5 × 10 6 cells per 200 μL of ice-cold serum-free medium. All the mice were injected subcutaneously in the flank region with 200 μL of cell suspension when they were aged 6–8 weeks. Their body weight was measured once weekly, their tumor size was measured weekly with a digital caliper, and their tumor weight was estimated using the following formula: weight in mg = (width 2 × length) mm 3 /2. Because of ethical considerations pertaining to animal experiments, a tumor burden of > 10% of body weight and a body weight loss of > 15% were defined as the humane endpoints. When the tumor weight of the tumor-bearing SCID mice reached 150–200 mg, they were intraperitoneally injected with anti-HFG mAb or saline, which served as a negative control. In the DLD-1 xenograft model, mice (n = 4) were intraperitoneally injected with 50 mg/kg of anti-HFG mAb twice weekly for 5 weeks. In the COLO 205 xenograft model, mice (n = 6) were intraperitoneally injected with 50 mg/kg of anti-HFG mAb twice weekly for 5 weeks. In the COLO 201 xenograft models, mice (n = 6) were intraperitoneally injected with 2, 10, and 50 mg/kg of anti-HFG mAb twice weekly for 6 weeks or 0.008, 0.04, 0.2, and 1 mg/kg of anti-HFG mAb once weekly for 6 weeks. In all the xenograft models, the first dose of anti-HFG mAb was 1.5 times the indicated dose. Antibodies were diluted with saline (20 μL per gram of body weight was intraperitoneally injected). Statistics The collected data were analyzed using the statistics functions of Microsoft Excel. Values are presented as the mean ± standard deviation (SD). Continuous variable data were analyzed with one-way analyses of variance or two-tailed independent t-tests to perform comparisons of two groups. A p -value of < 0.05 was regarded to indicate a statistically significant difference (* = p < 0.05; ** = p < 0.01).
The present study was approved by the Institutional Review Board of Taipei Medical University Hospital (N201906007). Thirty patients with CRC and 10 healthy donors were randomly selected and recruited for the present study; their informed consent was obtained. Tumor tissues and NATs were collected between July 2019 and February 2020 during the surgical resection of the 30 patients with CRC at Taipei Medical University Hospital. Each NAT was sampled at least 10 cm from the tumor margin, and NATs were not allowed to exhibit the characteristics of malignant histopathology. All the tissue specimens were fixed with 10% formalin and embedded in paraffin blocks. Blood samples were collected from the 10 healthy donors and 30 patients with CRC before surgery and approximately 1 month after surgery between July 2019 and March 2020. Plasma samples were harvested by centrifuging the blood specimens at 1710 × g for 15 min at ambient temperature; the samples were then stored at − 80 °C until use.
The tissue blocks from CRC patients were cut into 4-μm-thick sections and affixed onto slides. The tissue sections were deparaffinized with xylene, rehydrated using gradient alcohol, and then boiled in antigen retrieval buffer (10 mM citric acid and 0.05% Tween-20, pH 6.0) for 30 min. After three washes with phosphate-buffered saline (PBS), the sections were immersed in PBS containing 3% hydrogen peroxide (Sigma) to quench endogenous peroxidase activity. Anti-HFG mAb developed by GlycoNex Inc. was used to detect the expression of HFG. For the IHC analysis, the tissue slides of CRC patients and the human normal tissue microarray FDA999 (US Biomax) were incubated at 4 °C overnight with the primary antibody anti-HFG mAb at 20 and 2 μg/mL, respectively. Subsequently, after three washes with PBS, the slides were incubated for an hour with a secondary mouse anti-human IgG Fc-HRP antibody (Southern Biotech), at a dilution of 1:2,000 and then visualized using a DAB-Plus Substrate Kit (Dako). The scoring of patients’ tissues included the intensity and percentage of positively stained cells. Staining intensity was denoted as 0 (negative), 1 (weakly positive), 2 (moderately positive), or 3 (strongly positive). Staining percentage was examined based on the estimated percentage of stained tumor cells among the total tumor cells or the estimated percentage of stained epithelial cells among the total epithelial cells. As for the scoring of FDA999, the average staining intensity was presented from + to + + + , while – indicated negative staining. The number of positive stains in all tissues were also present in brackets. Human multiple cancer tissue microarrays BC000120, BC001128, and ST2091 were purchased from US Biomax. The tissue sections were first deparaffinized with xylene, rehydrated through gradient alcohol, and then boiled in antigen retrieval buffer (10 mM citric acid, 0.1% NP-40, pH 6.0) for 30 min. After washing three times with PBS, the sections were immersed in PBS containing 3% hydrogen peroxide (Sigma) to quench endogenous peroxidase activity. For IHC analysis, the slides were incubated with a primary antibody anti-HFG mAb (10 μg/mL) at room temperature for an hour. Then, after washing three times with PBS, the slides were incubated with a secondary mouse anti-human IgG (Fc)-BIOT antibody (Southern Biotech), at a dilution of 1:2,000 for an hour followed by VECTASTAIN® Elite® ABC HRP Kit (Vector Laboratories) and then visualized by DAB-Plus Substrate Kit (Dako). The staining was scored and further calculated as positive rates of staining because the tissue numbers of different cancer types varied.
Human cancer cell lines were obtained from the American Type Culture Collection (ATCC), Bioresource Collection and Research Center (BCRC) of the Food Industry Research and Development Institute (FIRDI, Hsinchu, Taiwan), and Japanese Collection of Research Bio-resources Cell Bank (JCRB) and then cultured according to standard mammalian tissue culture protocols and sterile technique. Each human cancer cell line was suspended in PBS with 2% heat-inactivated FBS (Hyclone) and added to a V-shape 96-well plate (Nunc), followed by the addition of equal volume of anti-HFG mAb. The plates were then incubated at 4 °C for an hour. After washing with PBS once, the plates were centrifuged, and the cell pellet was re-suspended in 200-fold PBS-diluted Fluorescein (FITC)-AffiniPure Goat Anti-Human IgG, Fcγ Fragment Specific (Jackson ImmunoResearch Inc) and incubated at 4 °C for 30 min. Then, the plates were centrifuged, and PBS was added to the wells to wash off unbound secondary antibodies. The cell pellet was re-suspended in ice-cold PBS and then analyzed on a FACS Canto cytometer instrument and FACS Diva software (BD Biosciences).
Tissues were cut into pieces with sterilized scissors and washed three times with saline. They were then lysed using lysis buffer (1% Triton X-100 in 50-mM Tris–HCl and 0.15-M NaCl, pH 7.5), homogenized with TissueRuptor (QIAGEN), and agitated at 4 °C for 1 h. AGS and MKN45 cells were scraped from cell culture flasks and then washed three times with saline. Cells were lysed using lysis buffer and agitated at 4 °C for 30 min. Tissue and cell lysates were centrifuged at 15,521 × g and 4 °C for 15 min to remove debris. The supernatant was collected, and the concentration of lysates was determined using Pierce 660 nm Protein Assay Reagent (Thermo Scientific), MOPS running buffer (M00138, Genescript), ExpressPlus PAGE Gel (M42015, Genescript), and SurePAGE (M00657, Genescript) in sodium dodecyl sulfate–polyacrylamide gel electrophoresis. Tissue lysates (10 μg) or cell lysates (20 μg) were mixed with 1 × NuPAGE LDS sample buffer (NP0007, Invitrogen) and 1 × sample reducing agent (NP0009, Invitrogen). The protein samples were boiled at 100 °C for 10 min before being loaded into 4–20% gel, run at 80 V for 20 min, and then run at 110 V for 90 min. Proteins were transferred to polyvinylidene difluoride membrane (BSP0161, PALL) at 150 mA for 180 min. Immunoblotting was performed by conducting blocking with 5% skim milk at room temperature for 1 h, incubation overnight with 10 μg/mL of primary antibody anti-HFG mAb at 4 °C, and incubation with the secondary antibody mouse anti-human IgG Fc-HRP (1:5000, Southern Biotech) at ambient temperature for 1 h. Subsequently, the membranes were washed four times for 5 min with wash buffer (0.05% Tween-20 in PBS). Signals were visualized with electrochemiluminescence reagent (NEL105001EA, PerkinElmer).
DLD-1, SW1116, COLO 201, and COLO 205 cell lines were purchased from the American Type Culture Collection. The DLD-1 cells were maintained in complete RPMI-1640 medium (Gibco) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Hyclone) and cultured at 37 °C in a humidified incubator with 5% CO 2 . The SW1116 cells were maintained in Leibovitz's L-15 medium (Gibco) supplemented with 10% heat-inactivated FBS and cultured at 37 °C in a humidified incubator. All cell lines included in the study was summarized in Additional file : Table S1 with individual mutational status. The chemotherapy drugs used in the present study included 5-FU (Nang Kuang Pharmaceutical), oxaliplatin (Oxalip, TTY Biopharm), and irinotecan (Campto, Pfizer). DLD-1 and SW1116 cells were seeded at 5 × 10 3 and 2 × 10 4 cells/well, respectively, in 96-well culture plates (Greiner Bio-One). After they were incubated overnight, the cells were treated with either vehicle, a combination of 5-FU plus oxaliplatin, or a combination of 5-FU plus irinotecan and then incubated in a 37 °C humidified incubator for 48 h. All drugs were diluted in the aforementioned cell culture medium. Chemotherapy drug treatments were divided into low-concentration and high-concentration groups. Among the cells treated with low concentrations of chemotherapy drugs, the DLD-1 cells were treated with 1 μM 5-FU and 1.5 μM oxaliplatin or 1 μM 5-FU and 20 μM irinotecan, whereas the SW1116 cells were treated with 5 μM 5-FU and 30 μM oxaliplatin or 5 μM 5-FU and 60 μM irinotecan. Among the cells treated with high concentrations of chemotherapy drugs, the DLD-1 cells were treated with 5 μM 5-FU and 6 μM oxaliplatin or 5 μM 5-FU and 60 μM irinotecan, whereas the SW1116 cells were treated with 75 μM 5-FU and 50 μM oxaliplatin or 75 μM 5-FU and 100 μM irinotecan.
After the cells were incubated with chemotherapy drugs for 48 h, their supernatant was discarded. Subsequently, 50 μL of the medium, 50 μL of anti-HFG mAb (at the final concentration of 25, 100, or 400 μg/mL), and 50 μL of normal human serum complement (QUIDEL) were added to a 96-well plate sequentially. The plate was incubated at 37 °C for 4 h. The cytolysis of DLD-1 and SW1116 cells was analyzed using the CellTiter-Glo Luminescent Cell Viability Assay (Promega) in accordance with the manufacturer’s instructions. The cell viability of control well–indicated DLD-1 and SW1116 cells not treated with chemotherapy drugs or anti-HFG mAb-induced CDC was evaluated using the following formula: cell viability = (experimental well/control well) × 100%.
Animal experiments were performed strictly in accordance with the regulations of the Institutional Animal Care and Use Committee (IACUC) of GlycoNex. Specific-pathogen-free female CB17 severe-combined-immunodeficiency (SCID) mice were purchased from BioLASCO (Taiwan). DLD-1, COLO 201, and COLO 205 cells were resuspended at a cell density of 5 × 10 6 cells per 200 μL of ice-cold serum-free medium. All the mice were injected subcutaneously in the flank region with 200 μL of cell suspension when they were aged 6–8 weeks. Their body weight was measured once weekly, their tumor size was measured weekly with a digital caliper, and their tumor weight was estimated using the following formula: weight in mg = (width 2 × length) mm 3 /2. Because of ethical considerations pertaining to animal experiments, a tumor burden of > 10% of body weight and a body weight loss of > 15% were defined as the humane endpoints. When the tumor weight of the tumor-bearing SCID mice reached 150–200 mg, they were intraperitoneally injected with anti-HFG mAb or saline, which served as a negative control. In the DLD-1 xenograft model, mice (n = 4) were intraperitoneally injected with 50 mg/kg of anti-HFG mAb twice weekly for 5 weeks. In the COLO 205 xenograft model, mice (n = 6) were intraperitoneally injected with 50 mg/kg of anti-HFG mAb twice weekly for 5 weeks. In the COLO 201 xenograft models, mice (n = 6) were intraperitoneally injected with 2, 10, and 50 mg/kg of anti-HFG mAb twice weekly for 6 weeks or 0.008, 0.04, 0.2, and 1 mg/kg of anti-HFG mAb once weekly for 6 weeks. In all the xenograft models, the first dose of anti-HFG mAb was 1.5 times the indicated dose. Antibodies were diluted with saline (20 μL per gram of body weight was intraperitoneally injected).
The collected data were analyzed using the statistics functions of Microsoft Excel. Values are presented as the mean ± standard deviation (SD). Continuous variable data were analyzed with one-way analyses of variance or two-tailed independent t-tests to perform comparisons of two groups. A p -value of < 0.05 was regarded to indicate a statistically significant difference (* = p < 0.05; ** = p < 0.01).
Higher levels of HFGs exist in tumor tissues of patients with CRC To identify the expression of HFG in NATs and CRC tumor tissues, the tissue sections from 30 patients with CRC were stained with anti-HFG mAb (i.e., a mAb for recognizing HFGs) through IHC. Table lists the scores for each patient’s NAT and tumor tissue. The clinical and pathological characteristics were summarized in Additional file : Table S2. A score could not be obtained for the tumor tissue of patient-1 because of a lack of tumor cells in the tumor tissue. High levels of HFGs were expressed in all patients except patient-11 and patient-24, in whom HFG expression was higher in their NAT than in their CRC tumor tissue. Furthermore, the IHC staining results for patient-19, patient-5, and patient-21, presented in Fig. , highlight three conditions, namely positive HFG staining in NAT and tumor tissue (Fig. a, b), negative HFG staining in NAT and positive HFG staining in tumor tissue (Fig. c, d), and negative HFG staining in both tumor tissue and NAT (Fig. e, f). For patient-19 and patient-5, HFGs were revealed to be mainly localized in the cell membrane and in the cytoplasm of tumor cells (Fig. ). Among the patients, 90% (26/29) of the tumor tissues from 29 patients expressed HFGs and that only 30% (9/30) of these patients’ NATs expressed HFGs. The IHC results for paired NAT and tumor tissue are listed in Table ; they indicate that positive staining of tumor tissue and negative staining of NAT were discovered in 59% of the patients, positive staining of both tumor tissue and NAT in 31%, and negative staining of both tumor tissue and NAT in 10%. No negative staining of tumor tissue and positive staining of NAT were found in any of the patients' samples. The IHC results revealed that HFGs were detected in 90% of CRC tumor tissues; the HFG expression of 18 patients was further verified through western blotting. Tissue lysates from the 18 selected patients were analyzed with anti-HFG mAb; Fig. presents the adjoined results (for NAT and tumor tissue) for each selected patient. The western blot results indicated higher levels of heavily fucosylated glycoproteins in tumor tissue than in NAT for 13 patients. Furthermore, a strong major band near 185 kDa was observed in the tumor tissue of seven patients (patient-4, patient 7, patient-9, patient-16, patient-18, patient-24, and patient-29). By contrast, a stronger HFG signal was detected in the NAT of patient-11, which was compatible with the patient’s IHC staining score. For patient-5, patient-14, and patient-15, neither their NAT nor their tumor tissue produced signals of heavily fucosylated glycoproteins. The western blot and IHC results were mostly consistent except for those pertaining to the tumor tissue of patient-5 (IHC score, 2; Western blot, negative) and the NATs of patient-8, patient-19, and patient-24 (IHC score, 3; Western blot, negative). These differences could have been caused by the heterogeneous expression of HFGs in tissues. The use of different tissue parts for the two methods could have led to different expression levels. On the basis of the IHC and western blot analysis results, HFG was recognized by the anti-HFG mAb to be overexpressed in the tumor tissue of patients with CRC in comparison to that in their NAT. Overexpression of fucosylated antigens in human CRC cells instead of normal colonic epithelial cells A study indicated that Lewis antigens are expressed at moderate levels in healthy human tissues (e.g., reproductive and digestive epithelial cells) but overexpressed on the cell surface of various cancers (e.g., lymphoma or malignant neoplasm of the breast, lung, liver, pancreas, kidney, bladder, or prostate) . To determine the fucosylated antigen levels in normal and cancerous tissue, the anti-HFG mAb was used to perform immunostaining of both healthy and cancerous samples. The staining results revealed higher levels of fucosylated antigen in the salivary glands, larynx, esophagus, stomach, pancreas, and small intestine. However, the results indicated low levels of fucosylated antigens in normal colon tissue (Table ). By contrast, strong anti-HFG mAb signaling was produced by CRC tissues, especially in adenocarcinoma of the colon (Table ). These findings are consistent with our IHC staining results for HFGs. In subsequent experiments, several adenocarcinoma CRC cell lines—COLO 205, COLO 201, SW1116, DLD-1, LS 174 T, and HT-29—were evaluated through anti-HFG mAb epitope expression (Table ). Strong binding affinity was detected in SW1116 and DLD-1 cells, whereas no binding affinity was detected in HT-29 or COLO 205 cells. Collectively, fucosylated antigens were overexpressed in human CRC cells rather than normal colonic epithelial cells. CRC tumor growth is inhibited by anti-HFG mAb in a xenograft model The tumor-bearing SCID mice were given intraperitoneal anti-HFG mAb injections at doses from 2 to 50 mg/kg twice weekly for 6 weeks. Xenograft experiments were conducted to assess DLD-1, COLO 205, and COLO 201 tumor growth. The results indicated that anti-HFG mAb effectively reduced the growth rate of DLD-1 cells relative to the control (Fig. a) but did not inhibit growth of the COLO 205 cells (Fig. b); these findings are consistent with the binding ability of anti-HFG mAb (Table ). Furthermore, a dose-dependent effect of anti-HFG mAb on COLO 201 cell growth was observed. The results obtained from the tumor-bearing SCID mice given intraperitoneal injections of anti-HFG mAb at doses from 2 to 50 mg/kg twice weekly for 6 weeks revealed significant tumor growth inhibition relative to the control group. Tumor volumes shrank rapidly and had completely remitted 2 weeks after tumor inoculation (Fig. c). We further reduced the treatment dose to 0 to 1-mg/kg anti-HFG mAb. The inhibitory effects were favorable when the concentration was > 0.2 mg/kg. Collectively, the results indicated that the antibody-based treatments specifically targeted fucosylated antigens to inhibit tumor growth. Thus, antifucosylation is a crucial mechanism, and developing an effective agent to target fucosylated antigens is a promising method for treating CRC. Combined chemotherapy and anti-HFG mAb cause synergistic cytotoxicity in CRC The combinatory effect of chemotherapy drugs with the CDC activity of anti-HFG mAb was induced in DLD-1 and SW1116 human colorectal adenocarcinoma cell lines that expressed HFGs recognized by anti-HFG mAb. We found that 100 μg/mL anti-HFG mAb applied to DLD-1 cells resulted in approximately 40% inhibition of cell growth (Fig. a). The maximal cell-killing effect was produced when the DLD-1 cells were first treated with a low concentration of 5-FU plus oxaliplatin followed by anti-HFG mAb-induced CDC. In addition, the combination treatment exhibited higher killing capacity than the treatment of only a high concentration of 5-FU plus oxaliplatin. Similarly, a low concentration of 5-FU with irinotecan combined with anti-HFG mAb-induced CDC also produced the maximal cytotoxicity (Fig. b). The results of the experiments involving SW1116 cells were consistent with those of the experiments involving DLD-1 cells (Fig. c, d). SW1116 cells treated with a low concentration of 5-FU plus oxaliplatin or a low concentration of 5-FU plus irinotecan followed by anti-HFG mAb-induced CDC exhibited the maximal cell growth inhibition. The cytotoxic assay results suggested that the combination of chemotherapy drugs with anti-HFG mAb resulted in the maximal cytotoxicity in DLD-1 and SW1116 cells relative to the use of either chemotherapy drugs or anti-HFG mAb alone. At present, these chemotherapy drugs are used clinically to treat CRC, and anti-HFG mAb can recognize the HFGs expressed in CRC. Therefore, anti-HFG mAb can be a potent treatment adjunct to these chemotherapy agents in future combination therapy regimens.
To identify the expression of HFG in NATs and CRC tumor tissues, the tissue sections from 30 patients with CRC were stained with anti-HFG mAb (i.e., a mAb for recognizing HFGs) through IHC. Table lists the scores for each patient’s NAT and tumor tissue. The clinical and pathological characteristics were summarized in Additional file : Table S2. A score could not be obtained for the tumor tissue of patient-1 because of a lack of tumor cells in the tumor tissue. High levels of HFGs were expressed in all patients except patient-11 and patient-24, in whom HFG expression was higher in their NAT than in their CRC tumor tissue. Furthermore, the IHC staining results for patient-19, patient-5, and patient-21, presented in Fig. , highlight three conditions, namely positive HFG staining in NAT and tumor tissue (Fig. a, b), negative HFG staining in NAT and positive HFG staining in tumor tissue (Fig. c, d), and negative HFG staining in both tumor tissue and NAT (Fig. e, f). For patient-19 and patient-5, HFGs were revealed to be mainly localized in the cell membrane and in the cytoplasm of tumor cells (Fig. ). Among the patients, 90% (26/29) of the tumor tissues from 29 patients expressed HFGs and that only 30% (9/30) of these patients’ NATs expressed HFGs. The IHC results for paired NAT and tumor tissue are listed in Table ; they indicate that positive staining of tumor tissue and negative staining of NAT were discovered in 59% of the patients, positive staining of both tumor tissue and NAT in 31%, and negative staining of both tumor tissue and NAT in 10%. No negative staining of tumor tissue and positive staining of NAT were found in any of the patients' samples. The IHC results revealed that HFGs were detected in 90% of CRC tumor tissues; the HFG expression of 18 patients was further verified through western blotting. Tissue lysates from the 18 selected patients were analyzed with anti-HFG mAb; Fig. presents the adjoined results (for NAT and tumor tissue) for each selected patient. The western blot results indicated higher levels of heavily fucosylated glycoproteins in tumor tissue than in NAT for 13 patients. Furthermore, a strong major band near 185 kDa was observed in the tumor tissue of seven patients (patient-4, patient 7, patient-9, patient-16, patient-18, patient-24, and patient-29). By contrast, a stronger HFG signal was detected in the NAT of patient-11, which was compatible with the patient’s IHC staining score. For patient-5, patient-14, and patient-15, neither their NAT nor their tumor tissue produced signals of heavily fucosylated glycoproteins. The western blot and IHC results were mostly consistent except for those pertaining to the tumor tissue of patient-5 (IHC score, 2; Western blot, negative) and the NATs of patient-8, patient-19, and patient-24 (IHC score, 3; Western blot, negative). These differences could have been caused by the heterogeneous expression of HFGs in tissues. The use of different tissue parts for the two methods could have led to different expression levels. On the basis of the IHC and western blot analysis results, HFG was recognized by the anti-HFG mAb to be overexpressed in the tumor tissue of patients with CRC in comparison to that in their NAT.
A study indicated that Lewis antigens are expressed at moderate levels in healthy human tissues (e.g., reproductive and digestive epithelial cells) but overexpressed on the cell surface of various cancers (e.g., lymphoma or malignant neoplasm of the breast, lung, liver, pancreas, kidney, bladder, or prostate) . To determine the fucosylated antigen levels in normal and cancerous tissue, the anti-HFG mAb was used to perform immunostaining of both healthy and cancerous samples. The staining results revealed higher levels of fucosylated antigen in the salivary glands, larynx, esophagus, stomach, pancreas, and small intestine. However, the results indicated low levels of fucosylated antigens in normal colon tissue (Table ). By contrast, strong anti-HFG mAb signaling was produced by CRC tissues, especially in adenocarcinoma of the colon (Table ). These findings are consistent with our IHC staining results for HFGs. In subsequent experiments, several adenocarcinoma CRC cell lines—COLO 205, COLO 201, SW1116, DLD-1, LS 174 T, and HT-29—were evaluated through anti-HFG mAb epitope expression (Table ). Strong binding affinity was detected in SW1116 and DLD-1 cells, whereas no binding affinity was detected in HT-29 or COLO 205 cells. Collectively, fucosylated antigens were overexpressed in human CRC cells rather than normal colonic epithelial cells.
The tumor-bearing SCID mice were given intraperitoneal anti-HFG mAb injections at doses from 2 to 50 mg/kg twice weekly for 6 weeks. Xenograft experiments were conducted to assess DLD-1, COLO 205, and COLO 201 tumor growth. The results indicated that anti-HFG mAb effectively reduced the growth rate of DLD-1 cells relative to the control (Fig. a) but did not inhibit growth of the COLO 205 cells (Fig. b); these findings are consistent with the binding ability of anti-HFG mAb (Table ). Furthermore, a dose-dependent effect of anti-HFG mAb on COLO 201 cell growth was observed. The results obtained from the tumor-bearing SCID mice given intraperitoneal injections of anti-HFG mAb at doses from 2 to 50 mg/kg twice weekly for 6 weeks revealed significant tumor growth inhibition relative to the control group. Tumor volumes shrank rapidly and had completely remitted 2 weeks after tumor inoculation (Fig. c). We further reduced the treatment dose to 0 to 1-mg/kg anti-HFG mAb. The inhibitory effects were favorable when the concentration was > 0.2 mg/kg. Collectively, the results indicated that the antibody-based treatments specifically targeted fucosylated antigens to inhibit tumor growth. Thus, antifucosylation is a crucial mechanism, and developing an effective agent to target fucosylated antigens is a promising method for treating CRC.
The combinatory effect of chemotherapy drugs with the CDC activity of anti-HFG mAb was induced in DLD-1 and SW1116 human colorectal adenocarcinoma cell lines that expressed HFGs recognized by anti-HFG mAb. We found that 100 μg/mL anti-HFG mAb applied to DLD-1 cells resulted in approximately 40% inhibition of cell growth (Fig. a). The maximal cell-killing effect was produced when the DLD-1 cells were first treated with a low concentration of 5-FU plus oxaliplatin followed by anti-HFG mAb-induced CDC. In addition, the combination treatment exhibited higher killing capacity than the treatment of only a high concentration of 5-FU plus oxaliplatin. Similarly, a low concentration of 5-FU with irinotecan combined with anti-HFG mAb-induced CDC also produced the maximal cytotoxicity (Fig. b). The results of the experiments involving SW1116 cells were consistent with those of the experiments involving DLD-1 cells (Fig. c, d). SW1116 cells treated with a low concentration of 5-FU plus oxaliplatin or a low concentration of 5-FU plus irinotecan followed by anti-HFG mAb-induced CDC exhibited the maximal cell growth inhibition. The cytotoxic assay results suggested that the combination of chemotherapy drugs with anti-HFG mAb resulted in the maximal cytotoxicity in DLD-1 and SW1116 cells relative to the use of either chemotherapy drugs or anti-HFG mAb alone. At present, these chemotherapy drugs are used clinically to treat CRC, and anti-HFG mAb can recognize the HFGs expressed in CRC. Therefore, anti-HFG mAb can be a potent treatment adjunct to these chemotherapy agents in future combination therapy regimens.
Lewis antigens are fucose-containing carbohydrates that are present in blood cells and normal epithelial cells, and they have been reported to be overexpressed on the surface of cancer cells . The levels of Lewis antigens associated with tumor-related fucosylated epitopes (e.g., Lewis y, Lewis x, and sialyl Lewis X ) are increased in various cancers (e.g., gastrointestinal cancers), and several Lewis antigens are related to survival and metastasis . In the present study, HFG, a new fucosylated epitope, was assessed in an initial examination of 30 Taiwanese patients with CRC. Our results indicate significantly higher expression of HFGs in CRC tumor tissues than in normal tissues. The IHC staining and protein level analysis results also consistently indicate a high level of HFG expression in CRC tumor tissues and a low level of HFG expression in NATs. HFG appears to be a potential marker of CRC. Additional in vitro and/or in vivo investigations are required to clarify the treatment effectiveness and adverse effects of HFG targeting. Importantly, this research proposes a novel therapeutic target, and initially proves that it is feasible and convincing. FUTs are key regulators of glycosylation and essential for the terminal fucosylation of glycans, including Lewis antigens . One review summarized a series of studies that examined the correlations of fucosylation with tumor initiation, distant metastases, and disease progression; the review suggested that overexpression of fucosylated epitopes strengthens FUT expression in various cancers. Alterations of FUTs are also associated with the formation of various tumor antigens, with this formation promoting the EMT properties of tumor cells and, thus, contributing to hematogenous metastasis . An early study also demonstrated that the mRNA expression of FUT1 and FUT4 is increased in CRC tissues . In the present study, HFG antigens were discovered in most CRC tumor tissues but were only detected in 30% of NATs. The glycans recognized by the anti-HFG mAb as requiring multiple fucoses in their structure appeared less frequently in normal tissues than in tumor tissues, and the altered expression of FUT is a possible reason for this phenomenon. Therefore, further explorations of FUTs and HFGs in CRC are warranted. Various reports have revealed that aberrant glycosylation is involved in multiple human diseases, including cancer . The results of our in vitro CDC experiments indicate that antibody therapies can inhibit tumor growth. Complement-dependent cytotoxicity is considered as a forceful defense mechanism of innate immunity, and activation of the classical complement cascade is triggered by the binding of C1q to the Fc region of a cell-bound antibody . In our animal experiments, although DLD-1 cell line had a stronger binding ability to anti-HFG than COLO 201 in IHC staining, anti-HFG mAb exhibited more prominent cytotoxic effects in COLO 201 compared with those in DLD-1. The disparity might be due to the inconsistency of binding affinity between antibodies and complements. It was reported that the kinetic pathway of IgG oligomerization and complement activation might remarkably be altered by the cell surface antigen density and membrane mobility . In addition, low affinity of Fc to C1q and the structural intricacy of the IgG1-C1q complex primarily cause the enhancement of antibody-mediated complement activation challenging . Systemic therapies (e.g., chemotherapy, targeted therapy, and immunotherapy) are clinically used to relieve symptoms and prolong the lives of patients with mCRC. The use of targeted agents against tumor angiogenesis and EGFR is approved by the European Medicines Agency and US Food and Drug Administration (FDA) for the first- or second-line treatment of mCRC . However, rat sarcoma virus (RAS) and B-Raf proto-oncogene serine/threonine kinase (BRAF) gene mutations, which occur in approximately 50% and 10% of mCRC cases, respectively, are predictors of resistance to EGFR inhibitors . Thus, anti-EGFR therapy is only allowed for patients with mCRC with wild-type RAS and BRAF genes . However, other mechanisms of resistance to anti-EGFR drugs have been observed in these patients . Angiogenesis is a key modulator involved in tumor cell proliferation, migration, and invasion; therefore, the antiangiogenesis strategy can also be applied as a targeted therapy for mCRC . Because VEGF plays a crucial role in cancer angiogenesis , the FDA approved bevacizumab as the first anti-VEGF agent for mCRC in 2004 . Anti-VEGF drugs are used in first or subsequent lines of mCRC treatment, and they are recommended for patients with mCRC with mutant RAS or BRAF genes . However, several adverse effects contribute to VEGR blockades; they include hypertension, bleeding, and arterial thromboembolic events . Immunotherapy is another emerging therapeutic option for mCRC, but it is only beneficial for tumors with mismatch repair deficiency or high microsatellite instability, which only comprise approximately 5% of mCRC cases . In fact, patients suitable for anti-EGFR, anti-VEGF, or immunotherapy only comprise of small portion of patients with CRC, whereas our results indicate significantly higher expression of HFG in most CRC tumor tissue than in normal tissue. These findings suggest a greater percentage of patients will be eligible for this novel treatment. Moreover, the low frequency of HFG expression in normal tissue suggests anti-HFG mAb may produce few side effects. The antigen presentation of cancer cells in HFG is diverse, and the physiological significance of HFG is still unclear. Some studies have pointed out that colon-like cell lines like COLO 205, COLO 201, LS 174 T, and SW1116 might express Lewis-like antigen, and also upregulate the gene encoding glycosyltransferase, while undifferentiated cell line such as DLD-1 is less likely to express fucosylated antigens . Another highly glycosylated protein, mucin, represents the major secreted substance of the gastrointestinal tract, and major secreted product of colorectal cancer cells. Mucin family contains 22 characterized glycosylated macromolecules in human . Some studies have also pointed out that patients with mucinous colorectal cancer have poorer prognosis, higher invasiveness and metastatic ability . Although genetic alterations and tumorigenesis processes remain unclear, mucinous differentiation of colorectal cancers are associated with high frequency of mutations in KRAS or BRAF . Among mucin protein family, MUC1 was reported to exhibit a role in tumorigenesis by cell death inhibition and metastasis promotion . One study combined monoclonal antibodies against MUC1 with chemotherapeutic agents and showed combined therapy applied in DLD-1 cells induced more apoptosis compared with monotherapy . This report is partly consistent with the current IHC staining result in DLD-1 cells. Although detailed causes of HFG expression and mucinous differentiation in colorectal cancer cells remain indistinct, the current study reveals a novel treatment strategy. We assessed the cytotoxicity of anti-HFG mAb and revealed the synergistic cytotoxic effects of anti-HFG mAb combined with chemotherapy. Another well-known mechanism of antibody-related drugs, namely antibody-dependent cellular cytotoxicity , should also be explored in future studies to assess the cytotoxicity of anti-HFG mAb in combination with chemotherapy or other FDA-approved drugs. We performed only in vitro assays in the present study; however, pharmacokinetics, pharmacodynamics, immunological interactions of antibodies, and other factors in a tumor microenvironment can influence the effects of therapeutic drugs . Thus, additional ex vivo or in vivo investigations are required to clarify the therapeutic effectiveness of HFG targeting. For extensive applications involving the targeting of HFG antigens in cancer, antibody–drug conjugates and bispecific antibodies can also be developed to improve the effectiveness of treatments . The high tumor-specific antigen, HFG, can also be used as a cancer target in chimeric antigen receptor T-cell therapy . It is difficult to evaluate the correlation between the expression levels of HFG and clinical features due to the small sample size. However, a preliminary analysis of our data reveals no correlation of IHC intensity with cancer stage, cancer type, differentiation of tumor, or CEA levels. Addressing the heterogeneity of HFG expression in cancer tissues and identifying possible biomarkers are crucial for the translation of HFGs' use as markers or targets into clinical practice. One possible approach is to analyze the gene expression of FUTs, which play a significant role in HFG biosynthesis, in tumor tissues. By identifying the major regulator of HFG overexpression, it becomes possible to use it as a biomarker for selecting an appropriate subgroup of patients who are more likely to benefit from HFG-targeted therapy. Moreover, in addition to IHC staining of tumor tissues to evaluate individuals with high HFG expression, assessing FUT gene expression can help further refine the patient population for targeted HFG therapy. Overall, these additional studies and subgroup identification efforts are crucial to provide evidence supporting the clinical utility and applicability of the current findings, facilitating the development of new targeted therapies, and extending the use of HFGs in cancer treatments. In conclusion, we revealed that HFG is a cancer-associated antigen that is overexpressed in CRC tumor tissues. Our results demonstrated the CDC activity of anti-HFG mAb against CRC cell lines and revealed the higher cytotoxicity that is achieved when anti-HFG mAb is combined with clinical chemotherapy regimens. In clinical situation, if it is confirmed by pathological examination and IHC staining from the patient's tumor tissue that the tumor has high expression of HFG, it will be suitable for anti-HFG treatment. Furthermore, our findings serve as a basis for developing a new targeted therapy or extending the applicability of HFGs in other cancer therapies.
Additional file 1: Table S1. Summary of colorectal cancer cell lines included in the study with mutational status. Table S2. Clinical and pathological parameters in the colorectal cancer patient cohort.
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Prevention of Malaria in Pregnancy with Intermittent Preventive Treatment and Insecticide Treated Nets in Mali: A Quantitative Health Systems Effectiveness Analysis | fa6816d6-9f7d-4cb1-b2a8-2c20bb64624e | 3695962 | Preventive Medicine[mh] | Malaria in pregnancy due to Plasmodium falciparum is associated with maternal anaemia and low birth weight , . Low birth weight due to malaria is preventable with intermittent preventive treatment with sulphadoxine-pyrimethamine (IPTp-SP) , . IPTp-SP and insecticide treated nets (ITNs) are the currently recommended tools for prevention of malaria in pregnancy in sub-Saharan Africa (SSA) . IPTp-SP is delivered to pregnant women primarily through antenatal clinics (ANC), and ITNs are delivered through ANC together with a variety of other systems. Based on the findings of a randomised controlled trial in 2001 , WHO now recommend focussed ANC (fANC) . As part of fANC it is recommended that a pregnant woman visits ANC four times and during these visits receive a number of interventions. These interventions aim to identify risk factors and provide prevention against the major infections causing poor outcomes in pregnancy. In areas of stable malaria transmission, until October 2012 WHO recommended that pregnant women were given 2–3 courses of IPTp-SP after the onset of foetal movement with each course at least one month apart . New WHO guidelines now recommend a dose of IPTp-SP at each scheduled visit beginning as early as possible in the second trimester, and with each dose at least one month apart . Despite one to two decades of implementation of IPTp-SP and ITNs within national programmes in SSA, coverage of both of these essential tools for protecting pregnant women are still low , . As attendance at ANC at least once is high in many countries of SSA , explanations are required as to the reason for the differences in these estimates. The most recent national level data for Mali estimated that 6.0% of pregnant women received at least one dose of SP during an ANC visit, and 4.0% received 2 doses while 71% of women attended ANC at least once and 63% attended twice . Disparities across socio-economic quintiles of receipt of SP during an ANC visit were extremely high, as were attendance at ANC. This same survey estimated that 28.9% of pregnant women slept under an ITN the previous night. It is important therefore to understand the reasons that women who attend ANC do not receive IPTp-SP, so that interventions can be designed to target specific processes and to increase the effectiveness of the health system to deliver this efficacious intervention. There have been a multitude of studies on the delivery of ITNs through the public and private sectors, through continuous and campaign delivery strategies, and on their use by target groups. However, despite delivery of ITNs through ANC being the primary continuous delivery strategy recommended by Roll Back Malaria (RBM) , there is very little evidence of the effectiveness of this delivery strategy. Studies have evaluated the effectiveness of delivery of ITNs through ANC via voucher schemes where the voucher subsidy is delivered in ANC and the ITN in the private retail sector , but to our knowledge there have been no evaluations of the effectiveness of the direct delivery of ITNs themselves, through ANC. The objectives of the study were to evaluate the health system effectiveness of ANC for delivering a dose of IPTp-SP and an ITN for women attending during eligible gestation as defined by the national policy guidelines, and to identify the predictors of systems effectiveness.
Ethics The study was approved by the ethics committees of the Faculty of Medicine, Pharmacy, and Odonto-stomatology, University of Bamako, the London School of Hygiene and Tropical Medicine, and the Liverpool School of Tropical Medicine. Health workers gave signed consent at the initial meeting for structured questionnaires and for structured observations. Pregnant women gave signed consent for observations and exit interviews immediately prior to beginning the ANC process. Study Site The study was conducted in Segou region located 240 kilometers East of Bamako in Mali. The region is composed of 7 districts including the district of Segou where the study took place. Segou District has a total population of 448,552 projected from the 1998 census, with more than 60% of this population living in rural areas. The climate of Segou is typical of the Sahel with an average annual precipitation of 400 mm, with a wet season of about three months (July–September) corresponding to the highest malaria transmission period . There is also a ‘cold’ dry season (November–February) and a hot dry season (March–May/June) Malaria in Segou Region is seasonal ranging from holo-endemic in the southern part of the district and meso-endemic to the north. The district has a total of 29 functioning health structures comprising 1 hospital, 1 district level health facility ( Centre de santé de reference ), and 27 community health centres (CSComs). At the time of the study there were 8 non-functional CSComs. The hospital serves as the regional referral centre and the Centre de Santé de Reference (CSRef) for district level referrals. The CSComs are situated between 5 km and 150 km from the CSRef. ANC services are available Monday to Friday (8.00 am–5.00 pm) in Segou District, but attendance varies by day of the week, with highest attendance often linked to market days in the closest town. Since the early 1980s a health sector reform programme facilitated the development of community-financed health centres, in a move away from a highly centralised urban bias in the health system. These community-financed health centres rely on cost recovery for the financing of most wage and non-wage recurrent costs, rather than being government financed. This means that a limited number of health staff are government funded. Study Design and Data Collection A cross sectional observational study was conducted in 10 health facilities of Segou District. A dual frame sampling scheme was used to purposively select the CSRef and a representative sample of CSComs . The CSRef was purposively selected as this serves as the referral centre for the district, thus sharing the total population of the district cross the CSComs. A further 9 health facilities were randomly selected using probability proportional to size from the composite list of health facilities. Structured non-participant observations of 780 ANC visits were undertaken between 2 nd October and 26 th November 2009. The sample size was calculated using a standard method for health facility surveys to estimate proportion of women with specific service delivery endpoints . The endpoints estimated were the proportion of women that were given a dose of IPTp-SP on the day of the visit, the proportion who were given SP by DOT, and the proportion that were given an ITN. A total of 305 women were needed to achieve a 5.5% precision, assuming the prevalence of the specified endpoints is 40%. The sample size was increased in order to enable the assessment of predictors of a range of processes in the delivery of IPTp-SP and ITNs, this was done by hypothetically estimating the proportion of pregnant women attending ANC who would be offered IPTp-SP, the proportion who would take the IPTp-SP when offered and the proportion who would attend a second time and therefore have the possibility of receiving a second dose. Based upon the catchment population of the CSRef being the total population of Segou District and upon the operational feasibility, one third of the sample was collected from the CSRef, with the remaining two thirds from the 9 CSComs proportional to their catchment population according to district records. After gaining the consent of the head of each health facility, a meeting was held with all staff to inform them of the study and to collect background information from each health worker using a structured questionnaire. Written consent to be observed was obtained from health workers at this point. Five fieldworkers and three supervisors conducted the observations and interviews by approaching a woman as she entered the health facility, they then introduced the study, gained the consent of the woman, observed her ANC visit, and interviewed her on exit. On completion of the process with the first woman they then approached the next woman to enter the facility and repeated the process. The facility observation schedule was based upon local market days, and numbers of observations required at each facility. Facilities were visited by the study team mainly on the busiest ANC day, coinciding with local market day. Each facility was visited by the team until the required sample size was achieved. Fieldworkers followed pregnant women from their entry to the health facility until their completion of the visit including various scenarios amongst registration, health education, history and vital signs, consultation, prevention of mother to child transmission of HIV (PMTCT), laboratory, post-laboratory consultation and dispensary. During these observations, fieldworkers used a structured checklist to record actions, and communications between the health provider and pregnant woman. An exit interview was conducted with the woman when ready to leave the facility with direct questions on the events during the ANC visit, observation of drugs received, and knowledge of the woman on leaving the facility. Interviews were conducted in Bambara which is the most predominant local language in Segou District. Several different types of information were collected during the observations which included responses of pregnant women to a question by a fieldworker, responses of pregnant women to questions from a health worker during the ANC visit, actions of the pregnant women or the health worker observed by the fieldworker, communications heard by a fieldworker during observations and written information or data observed by a fieldworker. Health facility audits were undertaken at each of the ten health facilities to assess the context within which ANC is delivered including departmental structure of the facility, size in terms of ANC attendance, numbers cadres of staff, and source of funding. Study Definitions A health system effectiveness algorithm was developed based upon the WHO and national policy documents on IPTp-SP and delivery of ITNs through ANC which were in place at the time of data collection. Women should be given IPTp-SP twice during pregnancy in the second and third trimesters with the first dose after quickening and each dose at least one month apart . According to the Malian national policy at the time of the study, IPTp-SP should be given free of charge, but should not be given to women in their ninth month of pregnancy . Each of the two doses of IPTp-SP consists of 3 tablets of SP, each containing 500 mg sulpha drug and 25 mg pyrimethamine and should be taken in the facility by directly observed treatment (DOT) by the health provider. The intermediate processes required for effective delivery of IPTp-SP per policy were therefore defined as: Intermediate process 1: attend ANC consultation between 4 and 8 months pregnant; Intermediate process 2: be given any SP; Intermediate process 3: be given 3 tablets of SP; Intermediate process 4: be given SP by DOT; Intermediate process 5: told when to return for the next visit; and Intermediate process 6 told to return in 4 to 5 weeks. The data source for each of these processes was observation of the ANC visit. In order to include the situation where a woman was not given IPTp-SP by DOT but may still have been given and taken SP, in a second analysis process 4 was defined as took the SP by DOT or left the facility with 3 tablets of SP and was able to report correctly how they would be taken. The data for these processes was obtained at exit interview. As the policy is that 2 doses of IPTp-SP should be given, full effectiveness requires that those pregnant women for whom IPTp-SP is successfully delivered once, should attend ANC a second time and progress effectively a second time through the first 4 defined processes. It is important to note that pregnant women with symptoms of malaria were not excluded from the effectiveness denominator as there is no direction on this in the national guidelines and the diagnosis of malaria in pregnancy within these health facilities needed more study. The case management of malaria in pregnancy in these health facilities will be presented elsewhere. According to the national policy, every pregnant woman should be given an ITN on her first visit to ANC . The health systems effectiveness algorithm for ITNs as included in is relatively simple consisting of just 3 processes: Process 1 attend ANC; Process 2 be offered an ITN; and Process 3 take the ITN. Intermediate processes for systems effectiveness of the delivery of IPTp-SP and ITNs were described as ineffective if less that 80% of pregnant women were reached by the process . Cumulative systems effectiveness represents successful coverage of women for each of the intermediate processes up to the designated point in the effectiveness algorithm. Analyses Data were double entered and validated using EpiData version 3.1 , and Stata 11.0 was used for data processing and analysis. Analyses accounted for the survey design, adjusting for clustering within health facilities. Sample weights for observations were estimated based upon the sampling probability of each selected health facility . Analyses were stratified by CSRef and collated CSCom as we hypothesised that the systems effectiveness and the predictors of the intermediate processes involved in delivery of IPTp-SP would differ at these different levels of the health system. Two systems effectiveness analyses were undertaken for IPTp-SP: 1) a cumulative analysis of the overall effectiveness of the intermediate processes for women who reported during exit interview that they were 4 to 8 months pregnant for their 1 st and for their 2 nd visit to ANC, and 2) an assessment of the effectiveness of each individual intermediate process for women 4 to 8 months pregnant for their 1 st , and 2 nd visits to ANC. The effectiveness of each intermediate process in the delivery system effectiveness algorithm was calculated by estimating the proportion of women who successfully reached each step from the previous step . Two cumulative delivery system effectiveness estimates were calculated 1) a ‘per policy’ estimate of receiving 3 tablets of SP by directly observed therapy (DOT) on first, and second visits to ANC; 2) a with or without DOT inclusive estimate of the proportion of women either receiving 3 tablets of SP by DOT, or leaving the health facility with 3 tablets of SP and able to report on questioning that they would take all 3 tablets at one time. For ITNs the cumulative effectiveness included only 3 steps which were attend ANC (with no restrictions on gestation), offered an ITN, and given an ITN during ANC consultation. Principal components analysis (PCA) was used to create an asset index , based upon household characteristics such as source of drinking water, type of toilet facilities, and a range of household assets. All assets were included in the PCA as binary variables . The asset index was then used to construct socio-economic quintiles from the poorest households through to the least poor. This method has been validated in household surveys with information on both assets and income or expenditure . In this study these socio-economic quintiles are not representative of the population level, but are a relative score amongst women who attend ANC in Segou District, and a greater proportion of pregnant women from less poor households attend ANC in Mali . Potential predictors of intermediate processes for pregnant women 4 to 8 months pregnant (for IPTp-SP) on their first visit to ANC were assessed using a univariate (unadjusted) logistic regression model. Categories of potential predictors included: socio-demographic; pregnancy factors; health facility factors; and 3 types of process factors which were departments and time; illness or suspected illness; and payments. Individual potential predictors within each of these categories were measured during the structured observations by fieldworkers observing actions, listening to communications, or observing written information . Potential predictors were analysed for those intermediate processes that were found to be ineffective, that is for which less than 80% of women who should have completed the process, did so. These analyses were restricted to women 4 to 8 months pregnant, but gestation was included as a potential predictor. Adjusted Wald tests were used to assess the association between each potential predictor and the outcome of each intermediate process. Predictors with Odds Ratios (ORs) significant at the 10% level (p-values<0.1) were included in multi-variable (adjusted) logistic regression models for each intermediate process outcome in order to determine which potential predictors remained associated with each of the outcomes when adjusted for other predictors. ORs were estimated rather than Relative Risk (RR) due to clustering and stratification of the sample, and therefore our outcomes not being truly representative of the district level population. In the multi-variable models, predictors were considered significant at the 10% level at all stages of model building except for the final model where p<0.05 was used . The design effect (DE) and intra-cluster correlation coefficients (ICC) were calculated for 6 systems effectiveness intermediate processes defined in the health systems effectiveness algorithm for aggregated CSRef and CSComs, and for aggregated CSComs alone. The design effect was calculated as the difference between the variance based on the clusters used compared with a modelled variance if a simple random sample was used. A design effect of 1 means that variance is unaffected by clustering and is equivalent to that of a simple random sample. An ICC of 0 equates to a DE of 1 where the variance is equivalent to that of a simple random sample.
The study was approved by the ethics committees of the Faculty of Medicine, Pharmacy, and Odonto-stomatology, University of Bamako, the London School of Hygiene and Tropical Medicine, and the Liverpool School of Tropical Medicine. Health workers gave signed consent at the initial meeting for structured questionnaires and for structured observations. Pregnant women gave signed consent for observations and exit interviews immediately prior to beginning the ANC process.
The study was conducted in Segou region located 240 kilometers East of Bamako in Mali. The region is composed of 7 districts including the district of Segou where the study took place. Segou District has a total population of 448,552 projected from the 1998 census, with more than 60% of this population living in rural areas. The climate of Segou is typical of the Sahel with an average annual precipitation of 400 mm, with a wet season of about three months (July–September) corresponding to the highest malaria transmission period . There is also a ‘cold’ dry season (November–February) and a hot dry season (March–May/June) Malaria in Segou Region is seasonal ranging from holo-endemic in the southern part of the district and meso-endemic to the north. The district has a total of 29 functioning health structures comprising 1 hospital, 1 district level health facility ( Centre de santé de reference ), and 27 community health centres (CSComs). At the time of the study there were 8 non-functional CSComs. The hospital serves as the regional referral centre and the Centre de Santé de Reference (CSRef) for district level referrals. The CSComs are situated between 5 km and 150 km from the CSRef. ANC services are available Monday to Friday (8.00 am–5.00 pm) in Segou District, but attendance varies by day of the week, with highest attendance often linked to market days in the closest town. Since the early 1980s a health sector reform programme facilitated the development of community-financed health centres, in a move away from a highly centralised urban bias in the health system. These community-financed health centres rely on cost recovery for the financing of most wage and non-wage recurrent costs, rather than being government financed. This means that a limited number of health staff are government funded.
A cross sectional observational study was conducted in 10 health facilities of Segou District. A dual frame sampling scheme was used to purposively select the CSRef and a representative sample of CSComs . The CSRef was purposively selected as this serves as the referral centre for the district, thus sharing the total population of the district cross the CSComs. A further 9 health facilities were randomly selected using probability proportional to size from the composite list of health facilities. Structured non-participant observations of 780 ANC visits were undertaken between 2 nd October and 26 th November 2009. The sample size was calculated using a standard method for health facility surveys to estimate proportion of women with specific service delivery endpoints . The endpoints estimated were the proportion of women that were given a dose of IPTp-SP on the day of the visit, the proportion who were given SP by DOT, and the proportion that were given an ITN. A total of 305 women were needed to achieve a 5.5% precision, assuming the prevalence of the specified endpoints is 40%. The sample size was increased in order to enable the assessment of predictors of a range of processes in the delivery of IPTp-SP and ITNs, this was done by hypothetically estimating the proportion of pregnant women attending ANC who would be offered IPTp-SP, the proportion who would take the IPTp-SP when offered and the proportion who would attend a second time and therefore have the possibility of receiving a second dose. Based upon the catchment population of the CSRef being the total population of Segou District and upon the operational feasibility, one third of the sample was collected from the CSRef, with the remaining two thirds from the 9 CSComs proportional to their catchment population according to district records. After gaining the consent of the head of each health facility, a meeting was held with all staff to inform them of the study and to collect background information from each health worker using a structured questionnaire. Written consent to be observed was obtained from health workers at this point. Five fieldworkers and three supervisors conducted the observations and interviews by approaching a woman as she entered the health facility, they then introduced the study, gained the consent of the woman, observed her ANC visit, and interviewed her on exit. On completion of the process with the first woman they then approached the next woman to enter the facility and repeated the process. The facility observation schedule was based upon local market days, and numbers of observations required at each facility. Facilities were visited by the study team mainly on the busiest ANC day, coinciding with local market day. Each facility was visited by the team until the required sample size was achieved. Fieldworkers followed pregnant women from their entry to the health facility until their completion of the visit including various scenarios amongst registration, health education, history and vital signs, consultation, prevention of mother to child transmission of HIV (PMTCT), laboratory, post-laboratory consultation and dispensary. During these observations, fieldworkers used a structured checklist to record actions, and communications between the health provider and pregnant woman. An exit interview was conducted with the woman when ready to leave the facility with direct questions on the events during the ANC visit, observation of drugs received, and knowledge of the woman on leaving the facility. Interviews were conducted in Bambara which is the most predominant local language in Segou District. Several different types of information were collected during the observations which included responses of pregnant women to a question by a fieldworker, responses of pregnant women to questions from a health worker during the ANC visit, actions of the pregnant women or the health worker observed by the fieldworker, communications heard by a fieldworker during observations and written information or data observed by a fieldworker. Health facility audits were undertaken at each of the ten health facilities to assess the context within which ANC is delivered including departmental structure of the facility, size in terms of ANC attendance, numbers cadres of staff, and source of funding.
A health system effectiveness algorithm was developed based upon the WHO and national policy documents on IPTp-SP and delivery of ITNs through ANC which were in place at the time of data collection. Women should be given IPTp-SP twice during pregnancy in the second and third trimesters with the first dose after quickening and each dose at least one month apart . According to the Malian national policy at the time of the study, IPTp-SP should be given free of charge, but should not be given to women in their ninth month of pregnancy . Each of the two doses of IPTp-SP consists of 3 tablets of SP, each containing 500 mg sulpha drug and 25 mg pyrimethamine and should be taken in the facility by directly observed treatment (DOT) by the health provider. The intermediate processes required for effective delivery of IPTp-SP per policy were therefore defined as: Intermediate process 1: attend ANC consultation between 4 and 8 months pregnant; Intermediate process 2: be given any SP; Intermediate process 3: be given 3 tablets of SP; Intermediate process 4: be given SP by DOT; Intermediate process 5: told when to return for the next visit; and Intermediate process 6 told to return in 4 to 5 weeks. The data source for each of these processes was observation of the ANC visit. In order to include the situation where a woman was not given IPTp-SP by DOT but may still have been given and taken SP, in a second analysis process 4 was defined as took the SP by DOT or left the facility with 3 tablets of SP and was able to report correctly how they would be taken. The data for these processes was obtained at exit interview. As the policy is that 2 doses of IPTp-SP should be given, full effectiveness requires that those pregnant women for whom IPTp-SP is successfully delivered once, should attend ANC a second time and progress effectively a second time through the first 4 defined processes. It is important to note that pregnant women with symptoms of malaria were not excluded from the effectiveness denominator as there is no direction on this in the national guidelines and the diagnosis of malaria in pregnancy within these health facilities needed more study. The case management of malaria in pregnancy in these health facilities will be presented elsewhere. According to the national policy, every pregnant woman should be given an ITN on her first visit to ANC . The health systems effectiveness algorithm for ITNs as included in is relatively simple consisting of just 3 processes: Process 1 attend ANC; Process 2 be offered an ITN; and Process 3 take the ITN. Intermediate processes for systems effectiveness of the delivery of IPTp-SP and ITNs were described as ineffective if less that 80% of pregnant women were reached by the process . Cumulative systems effectiveness represents successful coverage of women for each of the intermediate processes up to the designated point in the effectiveness algorithm.
Data were double entered and validated using EpiData version 3.1 , and Stata 11.0 was used for data processing and analysis. Analyses accounted for the survey design, adjusting for clustering within health facilities. Sample weights for observations were estimated based upon the sampling probability of each selected health facility . Analyses were stratified by CSRef and collated CSCom as we hypothesised that the systems effectiveness and the predictors of the intermediate processes involved in delivery of IPTp-SP would differ at these different levels of the health system. Two systems effectiveness analyses were undertaken for IPTp-SP: 1) a cumulative analysis of the overall effectiveness of the intermediate processes for women who reported during exit interview that they were 4 to 8 months pregnant for their 1 st and for their 2 nd visit to ANC, and 2) an assessment of the effectiveness of each individual intermediate process for women 4 to 8 months pregnant for their 1 st , and 2 nd visits to ANC. The effectiveness of each intermediate process in the delivery system effectiveness algorithm was calculated by estimating the proportion of women who successfully reached each step from the previous step . Two cumulative delivery system effectiveness estimates were calculated 1) a ‘per policy’ estimate of receiving 3 tablets of SP by directly observed therapy (DOT) on first, and second visits to ANC; 2) a with or without DOT inclusive estimate of the proportion of women either receiving 3 tablets of SP by DOT, or leaving the health facility with 3 tablets of SP and able to report on questioning that they would take all 3 tablets at one time. For ITNs the cumulative effectiveness included only 3 steps which were attend ANC (with no restrictions on gestation), offered an ITN, and given an ITN during ANC consultation. Principal components analysis (PCA) was used to create an asset index , based upon household characteristics such as source of drinking water, type of toilet facilities, and a range of household assets. All assets were included in the PCA as binary variables . The asset index was then used to construct socio-economic quintiles from the poorest households through to the least poor. This method has been validated in household surveys with information on both assets and income or expenditure . In this study these socio-economic quintiles are not representative of the population level, but are a relative score amongst women who attend ANC in Segou District, and a greater proportion of pregnant women from less poor households attend ANC in Mali . Potential predictors of intermediate processes for pregnant women 4 to 8 months pregnant (for IPTp-SP) on their first visit to ANC were assessed using a univariate (unadjusted) logistic regression model. Categories of potential predictors included: socio-demographic; pregnancy factors; health facility factors; and 3 types of process factors which were departments and time; illness or suspected illness; and payments. Individual potential predictors within each of these categories were measured during the structured observations by fieldworkers observing actions, listening to communications, or observing written information . Potential predictors were analysed for those intermediate processes that were found to be ineffective, that is for which less than 80% of women who should have completed the process, did so. These analyses were restricted to women 4 to 8 months pregnant, but gestation was included as a potential predictor. Adjusted Wald tests were used to assess the association between each potential predictor and the outcome of each intermediate process. Predictors with Odds Ratios (ORs) significant at the 10% level (p-values<0.1) were included in multi-variable (adjusted) logistic regression models for each intermediate process outcome in order to determine which potential predictors remained associated with each of the outcomes when adjusted for other predictors. ORs were estimated rather than Relative Risk (RR) due to clustering and stratification of the sample, and therefore our outcomes not being truly representative of the district level population. In the multi-variable models, predictors were considered significant at the 10% level at all stages of model building except for the final model where p<0.05 was used . The design effect (DE) and intra-cluster correlation coefficients (ICC) were calculated for 6 systems effectiveness intermediate processes defined in the health systems effectiveness algorithm for aggregated CSRef and CSComs, and for aggregated CSComs alone. The design effect was calculated as the difference between the variance based on the clusters used compared with a modelled variance if a simple random sample was used. A design effect of 1 means that variance is unaffected by clustering and is equivalent to that of a simple random sample. An ICC of 0 equates to a DE of 1 where the variance is equivalent to that of a simple random sample.
Characteristics of the Health Facilities The sample included 1 CSRef, 8 CSComs and 1 Dispensary for ease of presentation we included the dispensary amongst the CSComs in this paper . Eight facilities had at least one staff member funded by the government. Cadres of staff with government salaries included: doctors, midwives, nurses, public health nurses, health technicians, and auxillaries. The number of ANC attendees during 2008 ranged from 165 in the Dispensary to 2,811 in the CSRef. The number of staff usually in ANC ranged from 2 to 7. The CSRef and two of the CSComs had a functioning laboratory, with malaria microscopy performed in the CSRef and one of the CSComs. All facilities had a pharmacy with the exception of one CSCom and the Dispensary. Numbers of structured observations by facility are presented in . There were no stock-outs of SP in any of the sampled health facilities during the period of data collection. The CSRef and two of the CSComs had a stock-out of ITNs during the data collection period. Characteristics of Health Workers A median of 4 (range 1–10) health workers was interviewed per facility, with a total of 68 across all 10 facilities. The health workers were 32.4% male and 67.6% female, had a mean age of 34 (range 20–57) and were from 12 ethnic groups: 41.0% Bambara, 14.7% Malinke, 11.8% Peuhl (Fulani), 10.0% Minianka, and less that 10.0% Senoufo, Bobo, Arabe, Bozo, Dogon, Maure, Sarakole and Sonrhai. A total of 61.8% of health workers were from Segou Province, 52.9% from Segou District, and 32.4% were from the town or village within which they were providing health care. Nearly a quarter (23.5%) of those interviewed had worked in the current health facility for less that 1 year, 23.5% for 1 to 3 years, and 53.0% for more than 3 years. All health workers interviewed support the care of pregnant women and 57.4% worked in ANC. Amongst the ANC consultations observed, 47.7% were conducted by a ‘ matrone ’ (an under qualified nurse), 35.4% by trainee/non-permanent cadres (midwives or obstetric nurses), 10.4% by qualified obstetric nurses (trained in nursing and obstetrics), and 6.5% by qualified midwives (not trained in nursing). Characteristics of Pregnant Women A total of 780 ANC visits were observed, and 770 pregnant women interviewed on exiting the health facility. The population of pregnant women attending ANC in the CSRef varied in several indicators compared with those attending the CSComs . Women attending the CSRef were generally younger, had a higher level of education, were more ethnically diverse, of higher socio-economic status, had lesser number of children or were primigravidae and were more likely to be attending ANC for a routine visit together with an illness. Systems Effectiveness of Delivery of IPTp-SP The cumulative systems effectiveness for receiving one dose of IPTp-SP by DOT (processes 1 to 4), for women attending CSRef was 0% on their first visit to ANC and 2.1% on their second visit . Amongst pregnant women attending CSComs for their first ANC and second ANC visits 24.5% and 25.4% received IPTp-SP by DOT, respectively . For women on their third visit to ANC the systems effectiveness of receiving one dose of IPTp-SP by DOT for women attending the CSRef was 0% and 8.5% for women attending the CSComs. Where the definition of systems effectiveness was broadened to include both those women who received IPTp-SP by DOT, and those who have 3 tablets on exiting the health facility and are able to report correctly how to take them, then the systems effectiveness was increased. For pregnant women attending the CSRef cumulative systems effectiveness for processes 1 to 4 increased to 55.7% for those on their 1 st visit, 45.8% for those on their 2 nd visit, and 37.9% for those on their third visit; for the CSComs 66.7% on the 1 st visit, 68.1% on the 2 nd visit and 45.7% on the third visit. These are likely to be overestimates as they assume that 100% of pregnant women adhere to taking all 3 doses outside of the health facility. Estimating the intermediate process systems effectiveness in delivery of one dose of IPTp-SP based upon the algorithm presented in , two intermediate processes in the delivery of IPTp-SP per policy were ineffective which were 1) being given SP in ANC, and 2) being given SP in ANC by DOT. Approximately two thirds of pregnant women (63.9%) who were between 4 and 8 months pregnant when they attended the CSRef for their first ANC visit were given SP, whilst three quarters of eligible pregnant women (74.0%; 95% CI 62.0, 83.3) were given SP on their 1 st visit to the CSCom . The majority of women at the CSRef and CSComs who were given SP, correctly were given 3 tablets on their first visit. Amongst pregnant women attending ANC and receiving SP at the CSRef none were given the SP under DOT, whilst amongst those attending a CSCom 34.3% (95% CI: 10.5, 69.8) were given the SP by DOT. On completing ANC consultation, pregnant women on their 1 st and 2 nd visits should be told that they need to return to ANC, and they should be told when to return. The intermediate process of being told to return was ineffective, with 23.5% and 4.5% of those attending the CSRef, and 18.8% and 8.6% of those attending the CSComs being told to return at the close of their 1 st and 2 nd visits, respectively. For those on their 1 st visits to both CSRef and the CSComs who were told to return, the time within which they were told to return was correct for greater than 80% in both categories of facility, and therefore an effective intermediate process according to the definition adopted for this study. Systems Effectiveness of Delivery of ITNs The CSRef did not have ITNs in stock during the period of data collection, therefore none of the pregnant women attending the CSRef for their ANC visit of any gestation were given an ITN during the survey and the health systems effectiveness was 0%. Eight women reported that they were offered an ITN even though there were stock-outs. The cumulative effectiveness of delivery of ITNs through the CSComs for women of any gestation on their 1 st visit was 72.4%, and amongst those on their 2 nd visit 5.6% . The systems effectiveness algorithm for delivery of ITNs used in this study included only 3 intermediate processes the first of which, attendance at ANC provided the denominator for the estimates of other intermediate processes. For women attending ANC in the CSComs the offer of an ITN by health workers was just below the defined effectiveness target of 80% . The uptake of ITNs amongst those women offered it on a 1 st ANC visit was effective in this group of women, 91.2%. Predictors of being given SP In the unadjusted logistic regression analyses for women attending the CSRef predictors of being given SP included 2 pregnancy related and 9 process related factors . In the multivariate analysis only three predictors remained significantly associated with the systems effectiveness of being given SP. They were gestational age, had no symptoms of malaria, and the total expenditure in the health facility. A final model including these 3 indicators alone found that women who attended ANC at the CSRef were more likely to be given SP if the total expenditure they reported during the visit to ANC was between CFA 500 to 999 (adjusted OR 3.1 95% CI 1.4, 7.2; p = 0.006) compared to CFA <500 spent; and less likely to receive IPTp-SP if they were 7 to 8 months pregnant (adjusted OR 0.23 95% CI 0.11, 0.5; p = 0.002) than if they were 4 to 6 months pregnant. Women were less likely to receive IPTp-SP if they reported symptoms of malaria during ANC consultation (adjusted OR 0.27 95% CI 0.09, 0.84; p = 0.02). The predictors of being given SP in the CSComs differed from those of the CSRef . In the univariate analyses, there was 1 socio-demographic, 2 pregnancy related and 5 process predictors of being given SP in a CSCom. When adjusted for other univariate predictors, those multivariate predictors remaining significant were the education level of the pregnant woman, gestational age, the reason for the visit, palpation, and any expenditure during the visit. A final model (data not shown) including these 5 indicators showed that women who attended ANC at the CSComs were more likely to be given SP if they were palpated in ANC consultation (adjusted OR 1.77 95% CI 1.0, 3.12; p = 0.05) or had any expenditure in the health facility during the visit (adjusted OR 2.27 95% CI 0.99, 5.2; p = 0.05); and less likely to be given IPTp-SP if they were educated above primary level (adjusted OR 0.28 95% CI 0.18, 0.45; p = 0.0001) were 7 to 8 months pregnant (adjusted OR 0.25 95% CI 0.11, 0.6; p = 0.005), or attended ANC for a routine visit and because they were ill (adjusted OR 0.4 95% CI 0.17,0.97; p = 0.04). Predictors of being given SP by DOT Women who attended ANC at the CSRef were not given SP by DOT. Amongst pregnant women who were given SP at ANC in a CSComs, unadjusted predictors of being given SP by DOT included 1 socio-demographic factor, and 5 process factors . When adjusted for other univariate predictors, the only multivariate predictors remaining significant were socio-economic group of the pregnant woman, and the total expenditure in the health facility on the day of the visit. In the final model (data not shown), pregnant women were more likely to be given SP by DOT if they spent 500 to 999CFA (adjusted OR 9.87 95% CI 1.28, 75.71; p = 0.01) or ≥1,000 CFA (adjusted OR 12.17 95% CI 3.14, 47.16; p = 0.01) than if they spent less than 500CFA. Predictors of Receiving an ITN Women who attended ANC at the CSRef for their first ANC visit were not offered and were not given an ITN as there was a stock-out at the time of the study. Amongst women attending ANC at the CSComs there was 1 socio-demographic, and 7 process factors that were predictive of being offered an ITN in ANC in univariate analyses . When adjusted for other univariate predictors, those multivariate predictors remaining significant were the socio-economic status of the pregnant woman’s household, symptoms of malaria, palpation, paying money during consultation, and the total expenditure at the health facility. A final model (data not shown) including these adjusted predictors of being offered an ITN in ANC showed that pregnant women were more likely to be offered an ITN if they were palpated (adjusted OR 5.0 95% CI 1.3, 19.5 p = 0.03); and if the total expenditure in the health facility was ≥CFA1,000 (adjusted OR 10.3 95% CI 2.7,39.5; p = 0.004). They were less likely to be offered an ITN if they were from the 4 th socio-economic quintile (adjusted OR 0.08 95%CI 0.04, 0.16), that is less poor households; and if they paid money for consultation (adjusted OR 0.05 95% CI 0.007, 0.41; p = 0.01). Design Effect and Intra-cluster Correlation The within cluster correlation was low for being told to return for their next visit in 4 to 5 weeks amongst pregnant women in the CSComs who were told to return at all (DE 0.58, ICC −0.007), for this indicator the sample therefore resembled that of a simple random sample . For indicators of relatively effective processes such as being given 3 tablets of SP amongst those given any SP (97.1%; DE 1.49, ICC 0.009), being told to take 3 tablets (93.4%; DE 1.07, ICC 0.001) and being able to report on exit that they would take 3 tablets at one time, amongst those with 3 tablets (98.5% DE 0.83, ICC −0.003) as would be expected due to the high coverage across facilities clustering within health facilities was low. Amongst the ineffective processes being given SP by DOT was found to cluster more by health facility (33.1% DE 21.11, ICC 0.353) than receiving any SP during consultation (68.0% DE 2.86, ICC 0.033) and being told when to return for the next dose (14.8% DE 2.53, ICC 0.027). The design effect and intra-cluster variation were generally higher for the CSRef plus CSComs than for the CSComs alone but the pattern was similar across the indicators of intermediate process effectiveness.
The sample included 1 CSRef, 8 CSComs and 1 Dispensary for ease of presentation we included the dispensary amongst the CSComs in this paper . Eight facilities had at least one staff member funded by the government. Cadres of staff with government salaries included: doctors, midwives, nurses, public health nurses, health technicians, and auxillaries. The number of ANC attendees during 2008 ranged from 165 in the Dispensary to 2,811 in the CSRef. The number of staff usually in ANC ranged from 2 to 7. The CSRef and two of the CSComs had a functioning laboratory, with malaria microscopy performed in the CSRef and one of the CSComs. All facilities had a pharmacy with the exception of one CSCom and the Dispensary. Numbers of structured observations by facility are presented in . There were no stock-outs of SP in any of the sampled health facilities during the period of data collection. The CSRef and two of the CSComs had a stock-out of ITNs during the data collection period.
A median of 4 (range 1–10) health workers was interviewed per facility, with a total of 68 across all 10 facilities. The health workers were 32.4% male and 67.6% female, had a mean age of 34 (range 20–57) and were from 12 ethnic groups: 41.0% Bambara, 14.7% Malinke, 11.8% Peuhl (Fulani), 10.0% Minianka, and less that 10.0% Senoufo, Bobo, Arabe, Bozo, Dogon, Maure, Sarakole and Sonrhai. A total of 61.8% of health workers were from Segou Province, 52.9% from Segou District, and 32.4% were from the town or village within which they were providing health care. Nearly a quarter (23.5%) of those interviewed had worked in the current health facility for less that 1 year, 23.5% for 1 to 3 years, and 53.0% for more than 3 years. All health workers interviewed support the care of pregnant women and 57.4% worked in ANC. Amongst the ANC consultations observed, 47.7% were conducted by a ‘ matrone ’ (an under qualified nurse), 35.4% by trainee/non-permanent cadres (midwives or obstetric nurses), 10.4% by qualified obstetric nurses (trained in nursing and obstetrics), and 6.5% by qualified midwives (not trained in nursing).
A total of 780 ANC visits were observed, and 770 pregnant women interviewed on exiting the health facility. The population of pregnant women attending ANC in the CSRef varied in several indicators compared with those attending the CSComs . Women attending the CSRef were generally younger, had a higher level of education, were more ethnically diverse, of higher socio-economic status, had lesser number of children or were primigravidae and were more likely to be attending ANC for a routine visit together with an illness.
The cumulative systems effectiveness for receiving one dose of IPTp-SP by DOT (processes 1 to 4), for women attending CSRef was 0% on their first visit to ANC and 2.1% on their second visit . Amongst pregnant women attending CSComs for their first ANC and second ANC visits 24.5% and 25.4% received IPTp-SP by DOT, respectively . For women on their third visit to ANC the systems effectiveness of receiving one dose of IPTp-SP by DOT for women attending the CSRef was 0% and 8.5% for women attending the CSComs. Where the definition of systems effectiveness was broadened to include both those women who received IPTp-SP by DOT, and those who have 3 tablets on exiting the health facility and are able to report correctly how to take them, then the systems effectiveness was increased. For pregnant women attending the CSRef cumulative systems effectiveness for processes 1 to 4 increased to 55.7% for those on their 1 st visit, 45.8% for those on their 2 nd visit, and 37.9% for those on their third visit; for the CSComs 66.7% on the 1 st visit, 68.1% on the 2 nd visit and 45.7% on the third visit. These are likely to be overestimates as they assume that 100% of pregnant women adhere to taking all 3 doses outside of the health facility. Estimating the intermediate process systems effectiveness in delivery of one dose of IPTp-SP based upon the algorithm presented in , two intermediate processes in the delivery of IPTp-SP per policy were ineffective which were 1) being given SP in ANC, and 2) being given SP in ANC by DOT. Approximately two thirds of pregnant women (63.9%) who were between 4 and 8 months pregnant when they attended the CSRef for their first ANC visit were given SP, whilst three quarters of eligible pregnant women (74.0%; 95% CI 62.0, 83.3) were given SP on their 1 st visit to the CSCom . The majority of women at the CSRef and CSComs who were given SP, correctly were given 3 tablets on their first visit. Amongst pregnant women attending ANC and receiving SP at the CSRef none were given the SP under DOT, whilst amongst those attending a CSCom 34.3% (95% CI: 10.5, 69.8) were given the SP by DOT. On completing ANC consultation, pregnant women on their 1 st and 2 nd visits should be told that they need to return to ANC, and they should be told when to return. The intermediate process of being told to return was ineffective, with 23.5% and 4.5% of those attending the CSRef, and 18.8% and 8.6% of those attending the CSComs being told to return at the close of their 1 st and 2 nd visits, respectively. For those on their 1 st visits to both CSRef and the CSComs who were told to return, the time within which they were told to return was correct for greater than 80% in both categories of facility, and therefore an effective intermediate process according to the definition adopted for this study.
The CSRef did not have ITNs in stock during the period of data collection, therefore none of the pregnant women attending the CSRef for their ANC visit of any gestation were given an ITN during the survey and the health systems effectiveness was 0%. Eight women reported that they were offered an ITN even though there were stock-outs. The cumulative effectiveness of delivery of ITNs through the CSComs for women of any gestation on their 1 st visit was 72.4%, and amongst those on their 2 nd visit 5.6% . The systems effectiveness algorithm for delivery of ITNs used in this study included only 3 intermediate processes the first of which, attendance at ANC provided the denominator for the estimates of other intermediate processes. For women attending ANC in the CSComs the offer of an ITN by health workers was just below the defined effectiveness target of 80% . The uptake of ITNs amongst those women offered it on a 1 st ANC visit was effective in this group of women, 91.2%.
In the unadjusted logistic regression analyses for women attending the CSRef predictors of being given SP included 2 pregnancy related and 9 process related factors . In the multivariate analysis only three predictors remained significantly associated with the systems effectiveness of being given SP. They were gestational age, had no symptoms of malaria, and the total expenditure in the health facility. A final model including these 3 indicators alone found that women who attended ANC at the CSRef were more likely to be given SP if the total expenditure they reported during the visit to ANC was between CFA 500 to 999 (adjusted OR 3.1 95% CI 1.4, 7.2; p = 0.006) compared to CFA <500 spent; and less likely to receive IPTp-SP if they were 7 to 8 months pregnant (adjusted OR 0.23 95% CI 0.11, 0.5; p = 0.002) than if they were 4 to 6 months pregnant. Women were less likely to receive IPTp-SP if they reported symptoms of malaria during ANC consultation (adjusted OR 0.27 95% CI 0.09, 0.84; p = 0.02). The predictors of being given SP in the CSComs differed from those of the CSRef . In the univariate analyses, there was 1 socio-demographic, 2 pregnancy related and 5 process predictors of being given SP in a CSCom. When adjusted for other univariate predictors, those multivariate predictors remaining significant were the education level of the pregnant woman, gestational age, the reason for the visit, palpation, and any expenditure during the visit. A final model (data not shown) including these 5 indicators showed that women who attended ANC at the CSComs were more likely to be given SP if they were palpated in ANC consultation (adjusted OR 1.77 95% CI 1.0, 3.12; p = 0.05) or had any expenditure in the health facility during the visit (adjusted OR 2.27 95% CI 0.99, 5.2; p = 0.05); and less likely to be given IPTp-SP if they were educated above primary level (adjusted OR 0.28 95% CI 0.18, 0.45; p = 0.0001) were 7 to 8 months pregnant (adjusted OR 0.25 95% CI 0.11, 0.6; p = 0.005), or attended ANC for a routine visit and because they were ill (adjusted OR 0.4 95% CI 0.17,0.97; p = 0.04).
Women who attended ANC at the CSRef were not given SP by DOT. Amongst pregnant women who were given SP at ANC in a CSComs, unadjusted predictors of being given SP by DOT included 1 socio-demographic factor, and 5 process factors . When adjusted for other univariate predictors, the only multivariate predictors remaining significant were socio-economic group of the pregnant woman, and the total expenditure in the health facility on the day of the visit. In the final model (data not shown), pregnant women were more likely to be given SP by DOT if they spent 500 to 999CFA (adjusted OR 9.87 95% CI 1.28, 75.71; p = 0.01) or ≥1,000 CFA (adjusted OR 12.17 95% CI 3.14, 47.16; p = 0.01) than if they spent less than 500CFA.
Women who attended ANC at the CSRef for their first ANC visit were not offered and were not given an ITN as there was a stock-out at the time of the study. Amongst women attending ANC at the CSComs there was 1 socio-demographic, and 7 process factors that were predictive of being offered an ITN in ANC in univariate analyses . When adjusted for other univariate predictors, those multivariate predictors remaining significant were the socio-economic status of the pregnant woman’s household, symptoms of malaria, palpation, paying money during consultation, and the total expenditure at the health facility. A final model (data not shown) including these adjusted predictors of being offered an ITN in ANC showed that pregnant women were more likely to be offered an ITN if they were palpated (adjusted OR 5.0 95% CI 1.3, 19.5 p = 0.03); and if the total expenditure in the health facility was ≥CFA1,000 (adjusted OR 10.3 95% CI 2.7,39.5; p = 0.004). They were less likely to be offered an ITN if they were from the 4 th socio-economic quintile (adjusted OR 0.08 95%CI 0.04, 0.16), that is less poor households; and if they paid money for consultation (adjusted OR 0.05 95% CI 0.007, 0.41; p = 0.01).
The within cluster correlation was low for being told to return for their next visit in 4 to 5 weeks amongst pregnant women in the CSComs who were told to return at all (DE 0.58, ICC −0.007), for this indicator the sample therefore resembled that of a simple random sample . For indicators of relatively effective processes such as being given 3 tablets of SP amongst those given any SP (97.1%; DE 1.49, ICC 0.009), being told to take 3 tablets (93.4%; DE 1.07, ICC 0.001) and being able to report on exit that they would take 3 tablets at one time, amongst those with 3 tablets (98.5% DE 0.83, ICC −0.003) as would be expected due to the high coverage across facilities clustering within health facilities was low. Amongst the ineffective processes being given SP by DOT was found to cluster more by health facility (33.1% DE 21.11, ICC 0.353) than receiving any SP during consultation (68.0% DE 2.86, ICC 0.033) and being told when to return for the next dose (14.8% DE 2.53, ICC 0.027). The design effect and intra-cluster variation were generally higher for the CSRef plus CSComs than for the CSComs alone but the pattern was similar across the indicators of intermediate process effectiveness.
This cross sectional health facility survey enabled an in-depth investigation of the ANC experience and interactions with health providers of pregnant women attending ANC at two levels of the health system in Segou District. Using a structured checklist it was possible to quantify these processes and interactions for all women attending ANC on the day of the survey. This quantification of processes plus information collected on characteristics of pregnant women and the health facilities enabled an assessment of a wide range of possible predictors of the effectiveness of these delivery processes. Delivery of IPTp-SP by DOT was found to be ineffective amongst pregnant women attending ANC for their first or second visit during the current pregnancy, who were of eligible gestation according to national policy. When the requirement of DOT was excluded from the definition of effective delivery of IPTp-SP in a second analysis (a pregnant woman was given the correct number of tablets and had knowledge on how to take them, thus giving the opportunity for her to take an effective dose) the proportion of pregnant women being given a course of IPTp-SP (first or second dose) was higher than for delivery by DOT alone (55.6% and 66.7%) for the CSRef and CSComs respectively, close to the previous Abuja target (60% of 2-dose in 2005) , and way below the 100% target for universal coverage . In addition, this was the maximum effectiveness possible as it assumed that 100% of women who had the tablets and the knowledge complied with the instructions given. In practice, this is unlikely to be the case and these are likely to be substantial overestimates. We are not aware, however of any empirical data on the proportion of women who, given tablets of SP for IPTp to take at home, comply with this preventive treatment regimen. Although there is a wealth of data available on the lack of adherence to anti-malarial treatment regimens in the household, as this data is primarily for treatment of symptomatic malaria cases, it is not appropriate to draw parallels here. After determining that delivery of IPTp-SP was ineffective overall, we were able to identify the specific ineffective processes through an intermediate process analysis. The first of these ineffective processes was that of a pregnant woman being given any SP in ANC consultation. The adjusted predictors of being given SP, with the exception of being second or third trimester, differed between the CSRef and the CSComs. Visit number did not remain predictive of being given SP in the CSRef after adjusting for other potential predictors. The relationship between number of visits and being given SP may have been influenced by attendance of women at more than one health facility. Although we did not assess parity directly we found number of children was not a predictor of being given SP in this setting. Parity has previously been reported as a predictor of receiving IPTp-SP , . The finding from other studies which were population based rather than amongst attendees at health facilities, may have been due to lack of adjustment for factors influencing attendance at ANC. More specifically the findings from these studies may have been confounded by earlier attendance at ANC by primigravidae and a greater proportion of primigravidae attending ANC twice. In the CSRef, having symptoms of malaria, including fever, shivers, or chills reported by the pregnant woman, reduced the odds of being given SP. This may account for visit number not being predictive of being given SP in this health facility. According to the national policy at the time of this study pregnant women with malaria should be treated with quinine, and therefore not being given IPTp-SP was appropriate. Perhaps the most important factor to note here is that as mentioned in the methods, treatment of pregnant women for malaria was not accounted for in the indicator for being given a dose of IPTp-SP used in this study, as we based the analysis on national guidelines which are in-line with the global indicator for assessing coverage with IPTp-SP as measured through the DHS, MIS and other national household surveys. These findings suggest that in Segou District it was important to take pregnant women treated for malaria out of the denominator when assessing effectiveness of delivery of IPTp-SP. According to the structure of the health system in Mali, the main role of the CSRef within the district is to function as a referral centre for patients from the CSComs . It is not surprising therefore that a high proportion of pregnant women attending ANC at the CSRef complained of an illness at the time of their routine ANC attendance (20%). However, the proportion of pregnant women attending ANC with symptoms of malaria in the CSComs was also quite high at approximately 13%. There is a need to assess whether adjustment to the denominator of the delivery and coverage indicator for IPTp-SP is necessary in other settings, and in order to do this the proportion of pregnant women accessing ANC who are treated for malaria should be estimated. The proportion of pregnant women treated for malaria upon attendance at ANC is not currently included in the standard survey tool for the DHS or MIS ( http://www.measuredhs.com/What-We-Do/Survey-Types/DHS-Questionnaires.cfm ; http://www.measuredhs.com/What-We-Do/Survey-Types/MIS.cfm ) however the proportion of pregnant women who took any anti-malarial drug is often included. More work is needed to understand the relationship between taking anti-malarials for treatment during pregnancy, receiving the required number of doses of IPTp-SP, and how to combine or interpret both indicators. A further predictor of being given SP in the CSRef after adjusting for other potential predictors was having paid at least CFA 500 whilst in the facility. According to the national policy IPTp-SP should be delivered to eligible pregnant women free of charge , however on first visit to ANC there is a fee of CFA 500 for registration. In the CSRef 93% of first visit pregnant women paid CFA500 at registration, 8% of pregnant women on their second visit also paid this fee and 1% of women on their 3 rd visit. In addition to registration fees all women attending the CSRef paid CFA 300 for ANC consultation. Both paying CFA 500 in registration and paying for consultation were perfectly predictive of getting SP. For pregnant women attending the CSComs, educational level together with gestation and visit number was predictive of their being given IPTp-SP. Higher levels of education have been reported as predictive of receiving IPTp-SP , ; however these studies were population based cross sectional surveys, where this finding may be confounded by increased attendance at ANC amongst those with higher education levels. In such surveys although predictors are adjusted for the influence of other potential predictors these analyses are usually conducted with a denominator of all pregnant or recently pregnant women sampled, rather than amongst women who attended ANC. This access factor may also contribute to parity being reported as a predictor of being given IPTp-SP in population based studies, as mentioned above. It is important in future studies that access to health services and delivery of interventions are disaggregated in predictor analyses. Unlike the CSRef, paying for registration and paying for consultation were not predictive of getting SP at CSComs; though having spent any money during the visit was a predictor. These findings suggest differences in the way payments are made by women for different procedures and drugs within the CSRef and the CSComs which may in turn relate to the government rather than community funding of the CSRef. However, it is clear that if we are to improve delivery of IPTp-SP in an equitable manner then these cost issues need addressing so that delivery is truly free at all levels of the health system. This predictor offers direct action for a solution to systems ineffectiveness where as other predictors such as palpation do not provide a clear course of action as there are many reasons why this should be predictive of being given IPTp-SP and qualitative data would be useful to provide clarity. The second ineffective process was giving IPTp-SP by DOT. Delivery of IPTp-SP by DOT was not generally practised in the CSRef. Just one pregnant woman was given a dose of IPTp-SP as directed by the national policy guidelines when attending the CSRef and just one third of those who attended the CSComs were given IPTp-SP by DOT. Amongst pregnant women who were given IPTp-SP in ANC it is not clear why the total amount of money spent in the health facility was a predictor of DOT after adjusting for other potential predictors. This finding suggests that additional approaches are needed to gain a deeper understanding of the processes within health facilities and factors that influence giving treatment by DOT. It has previously been shown that giving IPTp-SP by DOT is influenced by the availability of clean drinking water . Such factors are not easily captured using quantitative approaches and require the addition of qualitative methods to further elucidate and explain quantitative findings. These findings are explored and presented in the companion paper (Webster et al Unpublished). The delivery of ITNs was ineffective in the CSRef because ITNs were out of stock, and relatively effective in the CSComs. In the CSRef the ineffectiveness was due to a stock-out of ITNs during the period of the survey. Although still below 80% in the CSComs if the 2 CSCom with stock-outs of ITNs during the survey are excluded from the analysis, the proportion of pregnant women who were given an ITN on their first visit to a CSCom was 81.7% and therefore using our definition of 80% of women completing the process, the delivery was effective where ITNs were in-stock. These data suggest that in this setting, if the health facilities have stock of ITNs then, the delivery of them is effective. This assumes that effectiveness of delivery of ITNs in the CSRef would mirror that of the CSComs. This is the first time as far as we are aware that the process effectiveness of direct delivery of ITNs through ANC has been assessed, despite the acknowledged strategic importance of this delivery channel for ITNs . Other studies have evaluated the outcomes at the population level of delivery of ITNs through ANC , but have not assessed whether women who attend ANC are offered or are given ITNs. The estimations of design effect and intra-cluster correlation were important in this study for reasons which can be divided into those relating to internal validity of the study, and those relating to interpretation of the findings for prioritising interventions, and for optimising the design and targeting of these interventions. With this study design and in this setting, clustering by health facility varies greatly by indicator, elevated design effects have been reported in other studies from Benin and Ghana . With a high level of clustering the precision of the estimate for each indicator is reduced as is the power to identify predictors of these indicators. This may have resulted in some predictors being missed in this study. Where the design effect and intra-cluster correlation are high it would not be feasible in terms of the resources required, to achieve the sample sizes needed for high precision on the estimates using this study design. Increasing the number of clusters, that is health facilities, and reducing the number of observations within each facility would be a more operationally feasible approach. However, given the magnitude of the design effect on some of the indicators in this study, the increase in clusters required would also not be achievable. The calculation of design effects and intra-cluster correlation however, provide some insight into the variability in implementation between health facilities which itself is important and potentially useful information. For example, the two main ineffective processes identified in this study, being given any SP in ANC, and being given SP by DOT are very different in terms of clustering by health facility, with clustering much higher for DOT. This translates to there being a problem in pregnant women being given any SP for some women in many of the health facilities, whilst for being given SP by DOT; the problem is for most women in some health facilities. The study had several limitations. Non-participant structured observations were the main tool for identifying ineffective processes in this study. The Hawthorne effect is a well recognised limitation of studies where behaviours are observed , and it is possible that both the health workers and the pregnant women involved in this study may have changed their behaviours. We assumed that any change in behaviours was towards ‘best behaviour’. The number of observations of some of the health workers involved would have been sufficient for any behaviour change to be likely to revert back to normal during the period of the study , but not for the pregnant women. However, given the poor findings on the cumulative and intermediate delivery processes we do not believe that the Hawthorne effect is a substantial worry in interpreting the findings of the study . The method used for enrolling pregnant women was based upon feasibility of implementation of the study and was not technically random. It is possible that the study was biased towards women attending at certain times of day. However, this potential bias did not impact upon the findings as time of attendance was not a significant predictor in univariate analyses of receipt of being given SP or an ITN. It is also possible that health worker behaviour on the busy days chosen for implementation of this study may have differed on less busy days. The study did not include data on the timing since the last dose of IPTp-SP. International and national guidelines state that there should be at least one month between doses of IPTp-SP. In this study therefore we may have over-estimated the health systems effectiveness of delivery of IPTp-SP if women re-attended for a second dose less than one month after receiving the first dose. The inclusion of pregnant women with symptoms of malaria in the denominator may have resulted in an under-estimate of the effectiveness of delivery of IPTp-SP where it is reasonable that these women should be treated for malaria using the national case management guidelines. Assessment of predictors of effectiveness may have been compromised where there were stock-outs of ITNs. Although we collected information on the health workers involved in the delivery of ANC in the health facilities involved in the study, the individual health workers observed at each stage of ANC were not recorded, only the cadre. This was a limitation to the inclusion of health worker factors in the assessment of predictors of the effectiveness of intermediate processes. However, cadre was not a significant predictor of being given IPTp-SP or an ITN in the univariate analyses. The strength of this study design is in allowing the in-depth study of health systems delivery processes on the day that a pregnant woman or patient attends the facility. It is not an appropriate study design for providing estimates of the proportion of pregnant women who are given one or more doses of IPTp-SP, during their pregnancy, at the population level. Household surveys are the most appropriate method for this. However, unlike in our health facility study, household surveys rely on self reports from pregnant women. A recent study from Uganda on the validity of pregnant women’s reported behaviour on taking doses of IPTp-SP showed such data to be inaccurate when assessed against plasma levels of sulphadoxine . The fieldworkers in this study were rigorously trained. There are potential limitations to the use of this structured observation method for assessing the effectiveness of delivery of interventions if fieldworkers are not given rigorous training and the tools are not extensively piloted. The two main reasons that the implementation of this method is difficult are firstly that observers need to both look and listen to what is happening in real time. And secondly, unlike the administration of a questionnaire, observers are not able to control the pace of the process if they are unsure of either an action or a verbal interaction between the health provider and the pregnant woman. Rigorous training and extensive piloting are key to achieving quality implementation, together with tailored structuring of the checklists to match the order of processes within the health facilities. The ultimate use of the findings of this study is to identify reasons for reduced effectiveness in order to improve programme delivery. Quantitative approaches however, are limited in their ability to provide explanations of why a process is not working or behaviour is not happening. These quantitative approaches are also limited by their structured nature for example in the CSRef whilst 39 women were observed to have been given tablets of SP during consultation 4 of these women did not have the tablets on exiting the health facility. The reasons for this may be either that the women had taken the tablets after leaving ANC consultation but before exiting the health facility, or that they disposed of the tablets in the health facility. However, as these behaviours were not pre-empted and included in the checklist or exit interview questionnaire, the explanations were not captured. The limited number of predictors of receiving IPTp-SP by DOT in this study is another example where qualitative approaches are needed to understand why this intermediate process was ineffective. For this reason a qualitative study of the reasons for ineffective delivery was explored from the perspectives of health workers involved and the quantitative and qualitative findings used together to identify disorders in implementation and offer practical solutions. These findings are presented in a companion paper (Webster et al Unpublished). The time-frame and the resources required for such a research study mean that whilst important for identifying implementation problems and for identifying the areas which need further illumination, this kind of approach is not applicable for routine feedback to inform programme implementation and adjustments required to improve its effectiveness. This requires the application of findings from such research studies as this one to adapt routine programmatic monitoring data at the district level for improving the effectiveness of national and sub-national programmes. In conclusion, in Segou District, the delivery of IPTp-SP was ineffective whilst ITN delivery was ineffective at the district level where ITNs were out of stock and effective in the community level health facilities where ITNs were in stock. The specific intermediate processes which are effective may be identified through quantitative analyses. Regression analyses may be used to successfully identify major predictors of the effectiveness of these processes, but requires additional qualitative analyses to further illuminate factors influencing the delivery processes. Adaptation of this methodology to routine monitoring systems is required to use the opportunity presented by this approach to influence successful uptake of IPT-SP and other interventions at the programmatic level.
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Registro SBR-AF: Preditores de Recorrência de Taquiarritmia Atrial após Primeira Ablação por Cateter na Fibrilação Atrial | acd6d06e-8d44-4f65-b0ec-c41233d40017 | 11809865 | Surgical Procedures, Operative[mh] | A prevalência global estimada de Fibrilação Atrial (FA) foi de 44 milhões de pessoas em 2016. - Pacientes com FA têm um risco maior de desenvolverem eventos tromboembólicos, disfunção ventricular esquerda progressiva, e pior qualidade de vida. , Ensaios clínicos contemporâneos apoiam o controle precoce do ritmo cardíaco para melhorar os desfechos clínicos e a qualidade de vida em comparação a um controle tardio. , A Ablação por Cateter é superior a Drogas Antiarrítmicas (DAA) em manter o ritmo sinusal e retardar a progressão da FA paroxística para FA persistente. , Assim, a ablação por cateter tem sido cada vez mais realizada como terapia de primeira linha no controle do ritmo cardíaco em paciente com diagnóstico recente de FA. - Apesar de evidência crescente à favor do controle do ritmo em Ensaios Clínicos Randomizados (ECRs), cenários no mundo real podem não replicar os mesmos níveis de eficácia de estudos em que centros de alto volume com operadores experientes são muito representados. Além disso, a eficácia promissora da ablação da FA precisa alinhar-se com o perfil igualmente atraente de segurança, principalmente à medida que esse procedimento é adotado por operadores e hospitais com diferentes experiência e expertise ao redor do mundo. O risco de complicações relacionadas ao procedimento pode diminuir o benefício das técnicas de ablação para controle do ritmo em pacientes com FA. Nesse sentido, muitas evidências tem se originado de ECRs e registros desenvolvidos ou em países de alta renda ou em centros de referência/acadêmicos de Países de Renda Baixa e Média (PRBM). - No Brasil, o registro oficial mais recente sobre desfechos de ablação por cateter, financiado pela Sociedade Brasileira de Arritmias Cardíacas, é do ano de 2007. Mais recentemente, os primeiros resultados do estudo RECALL (Registro Brasileiro Cardiovascular de Fibrilação Atrial) mostraram que, no basal, somente 4,4% da população foram submetidos à ablação por cateter. Durante o seguimento, ocorreu 1,8 ablação por 100 pacientes-ano. Contudo, a eficácia da ablação por cateter não foi avaliada no estudo. Assim, a fim de esclarecer o distanciamento que existe entre as recomendações de diretrizes e dados da via real sobre o manejo da FA em PRBM, há uma necessidade urgente de se desenvolver registros estruturados para rastrear, sistematicamente, pacientes com FA, e coletar desfechos perioperatórios e de longo prazo da ablação por cateter. O estudo Southern Brazilian Registry of Atrial Fibrillation (SBR-AF) é atualmente o maior estudo prospectivo multicêntrico do tipo coorte da América Latina cujo objetivo é avaliar a segurança, a eficácia, e os desfechos clínicos de longo prazo de ablações consecutivas. Delineamento do estudo e critérios de eligibilidade Conduzimos um estudo multicêntrico do tipo coorte com 1043 pacientes consecutivos com idade ≥ 18 anos, com FA paroxística, persistente, ou de longa duração, que se submeteram pela primeira vez à ablação por cateter por radiofrequência (RF) entre janeiro de 2009 e janeiro de 2024. O estudo incluiu pacientes com FA sintomática e documentada em três centros no Brasil (SOS Cardio, Florianopolis, SC; Hospital Unimed, Chapecó, SC; e Hospital Moinhos de Vento, Porto Alegre, RS). Características basais sociodemográficas e clínicas dos participantes foram coletadas antes de cada procedimento, juntamente com o escore canadense de gravidade da FA (CCS-SAF, Canadian Cardiovascular Society Severity of AF ) e o escore de sintomas relacionados à FA da European Heart Rhythm Association (EHRA). , Todos os dados foram armazenados no programa Syscardio ® , preservando a identidade do paciente. O Comitê de Ética local aprovou o estudo, e se obteve consentimento de todos os pacientes, seguindo-se a declaração de Helsinki. Protocolo de procedimento e seguimento Todos os pacientes foram submetidos à ablação por cateter de RF sob anestesia geral. Todos os procedimentos foram realizados com diferentes versões de um EnSite Navx - Abbott ® . A ilustra a abordagem de ablação para FA paroxística e não paroxística. Em resumo, foi realizado somente o isolamento das veias pulmonares (IVP) em pacientes com FA paroxística, enquanto a parede posterior foi incluída na maioria dos pacientes com FA não paroxística. Nos pacientes com FA paroxística, a parede posterior também foi isolada traçando-se uma linha oposta ao esôfago, quando as temperaturas desse órgão eram consideradas arriscadas para se realizar IVP. A parede posterior foi incluída em todos os pacientes com áreas de baixa voltagem em ritmo sinusal ou quando o ritmo sinusal não foi restaurado após três tentativas de cardioversão. Nos pacientes em que as áreas de baixa voltagem não estavam presentes, a ablação da parede posterior do átrio esquerdo foi realizada a critério do operador. A temperatura esofágica foi monitorada continuamente em todos os casos usando sensores Circa®, e ablação foi imediatamente interrompida se a temperatura esofágica excedesse 38 o C. Após junho de 2016, os procedimentos de ablação foram realizados utilizando-se um cateter com sensor de força e contato. RF foi aplicada por 8-12 segundos ao longo da parede posterior e por 15-30 segundos nos demais locais, com uma corrente variando entre 650 e 700 m Amperes. Quando disponível, essa abordagem tipicamente resultaria em um índice de ablação de 3,5-4 para a parede posterior e de 4,5 a 5,5 ao longo da parede anterior e topo do átrio esquerdo. Infusão de isoproterenol (até 20 mcg/minuto) ou de adenosina foi usada a critério do operador até 2018. A detecção de bloqueio bidirecional da veia pulmonar (VP) e da parede posterior (quando realizada) foi o marco final do procedimento. Após a ablação por cateter, os pacientes foram mantidos em drogas antiarrítmicas por 30 dias. A amiodarona foi prescrita ou mantida para pacientes com fração de ejeção ventricular esquerda (FEVE) ≤40% e/ou doença arterial coronariana. Para pacientes com uma FEVE normal, foi prescrito 25 mg de metroprolol uma vez ao dia e 150 mg de profanenona duas vezes ao dia. Medicamentos anticoagulantes foram recomendadas por no mínimo três meses. Após os três meses iniciais, a anticoagulação oral foi usada como função do escore CHA 2 DS 2 -VASc, mas realizada a critério do médico. O acompanhamento foi conduzido por visitas pessoais 30, 160 e 360 dias após a ablação. Subsequentemente, os pacientes foram indicados a visitas anuais. Quando o paciente não pôde estar presente nas visitas anuais, outros contatos por telefone foram feitos durante o período do estudo, usando um questionário pré-definido para avaliar sintomas de arritmia. Quando casos de arritmia sintomática eram identificados em contatos telefônicos, os pacientes foram solicitados a apresentarem um eletrocardiograma e se submeterem a um exame Holter 24 horas. Desfecho primário O desfecho primário foi definido como a recorrência de qualquer Taquiarritmia Atrial (TAA) avaliada por um ECG, exame de Holter ou teste de estresse cardíaco mostrando FA ou flutter atrial. Eventos que ocorreram em menos de 60 dias após o procedimento índice não foram incluídos na análise. Os pacientes foram contabilizados no último contato disponível, seja por telefone ou por escore, e considerados livres de TAA se nenhum registro de arritmia tiver sido feito após a ablação por cateter. Análise estatística Os dados foram expressos em média ± desvio padrão, mediana e Intervalo Interquartil (IIQ), ou números absolutos e porcentagens. A normalidade dos dados foi avaliada usando o teste de Shapiro-Wilk, e as variáveis foram consideradas com distribuição normal quando apresentaram um valor de p > 0,05. Comparações entre os grupos (com e sem recorrência de TAA) foram realizadas pelo teste t de Student para variáveis com distribuição normal ou os testes de Wilcoxon-Mann-Whitney e de Kruskal-Wallis para variáveis sem distribuição normal. O teste do qui-quadrado foi usado para avaliar a significância da associação entre frequências das variáveis. Preditores univariados de eventos arrítmicos recorrentes (valor de p <0,10) e características basais foram avaliados com o modelo de riscos proporcionais de Cox. Valores médios foram inseridos em caso de valores faltantes de Índice de massa corporal (IMC), taxa de filtração glomerular (TFG), e diâmetro do átrio esquerdo (AE) para permitir um modelamento estatístico adequado para análise multivariada. Pacientes com FA persistente de longa duração foram incluídos no grupo de pacientes com FA persistente. Análises de sobrevida foram realizadas usando curvas de Kaplan-Meier e o teste de log-rank. Todas as análises estatísticas foram realizadas usando o Stata (versão 18). Um p-valor bicaudal de 0,05 foi considerado estatisticamente significativo. Conduzimos um estudo multicêntrico do tipo coorte com 1043 pacientes consecutivos com idade ≥ 18 anos, com FA paroxística, persistente, ou de longa duração, que se submeteram pela primeira vez à ablação por cateter por radiofrequência (RF) entre janeiro de 2009 e janeiro de 2024. O estudo incluiu pacientes com FA sintomática e documentada em três centros no Brasil (SOS Cardio, Florianopolis, SC; Hospital Unimed, Chapecó, SC; e Hospital Moinhos de Vento, Porto Alegre, RS). Características basais sociodemográficas e clínicas dos participantes foram coletadas antes de cada procedimento, juntamente com o escore canadense de gravidade da FA (CCS-SAF, Canadian Cardiovascular Society Severity of AF ) e o escore de sintomas relacionados à FA da European Heart Rhythm Association (EHRA). , Todos os dados foram armazenados no programa Syscardio ® , preservando a identidade do paciente. O Comitê de Ética local aprovou o estudo, e se obteve consentimento de todos os pacientes, seguindo-se a declaração de Helsinki. Todos os pacientes foram submetidos à ablação por cateter de RF sob anestesia geral. Todos os procedimentos foram realizados com diferentes versões de um EnSite Navx - Abbott ® . A ilustra a abordagem de ablação para FA paroxística e não paroxística. Em resumo, foi realizado somente o isolamento das veias pulmonares (IVP) em pacientes com FA paroxística, enquanto a parede posterior foi incluída na maioria dos pacientes com FA não paroxística. Nos pacientes com FA paroxística, a parede posterior também foi isolada traçando-se uma linha oposta ao esôfago, quando as temperaturas desse órgão eram consideradas arriscadas para se realizar IVP. A parede posterior foi incluída em todos os pacientes com áreas de baixa voltagem em ritmo sinusal ou quando o ritmo sinusal não foi restaurado após três tentativas de cardioversão. Nos pacientes em que as áreas de baixa voltagem não estavam presentes, a ablação da parede posterior do átrio esquerdo foi realizada a critério do operador. A temperatura esofágica foi monitorada continuamente em todos os casos usando sensores Circa®, e ablação foi imediatamente interrompida se a temperatura esofágica excedesse 38 o C. Após junho de 2016, os procedimentos de ablação foram realizados utilizando-se um cateter com sensor de força e contato. RF foi aplicada por 8-12 segundos ao longo da parede posterior e por 15-30 segundos nos demais locais, com uma corrente variando entre 650 e 700 m Amperes. Quando disponível, essa abordagem tipicamente resultaria em um índice de ablação de 3,5-4 para a parede posterior e de 4,5 a 5,5 ao longo da parede anterior e topo do átrio esquerdo. Infusão de isoproterenol (até 20 mcg/minuto) ou de adenosina foi usada a critério do operador até 2018. A detecção de bloqueio bidirecional da veia pulmonar (VP) e da parede posterior (quando realizada) foi o marco final do procedimento. Após a ablação por cateter, os pacientes foram mantidos em drogas antiarrítmicas por 30 dias. A amiodarona foi prescrita ou mantida para pacientes com fração de ejeção ventricular esquerda (FEVE) ≤40% e/ou doença arterial coronariana. Para pacientes com uma FEVE normal, foi prescrito 25 mg de metroprolol uma vez ao dia e 150 mg de profanenona duas vezes ao dia. Medicamentos anticoagulantes foram recomendadas por no mínimo três meses. Após os três meses iniciais, a anticoagulação oral foi usada como função do escore CHA 2 DS 2 -VASc, mas realizada a critério do médico. O acompanhamento foi conduzido por visitas pessoais 30, 160 e 360 dias após a ablação. Subsequentemente, os pacientes foram indicados a visitas anuais. Quando o paciente não pôde estar presente nas visitas anuais, outros contatos por telefone foram feitos durante o período do estudo, usando um questionário pré-definido para avaliar sintomas de arritmia. Quando casos de arritmia sintomática eram identificados em contatos telefônicos, os pacientes foram solicitados a apresentarem um eletrocardiograma e se submeterem a um exame Holter 24 horas. O desfecho primário foi definido como a recorrência de qualquer Taquiarritmia Atrial (TAA) avaliada por um ECG, exame de Holter ou teste de estresse cardíaco mostrando FA ou flutter atrial. Eventos que ocorreram em menos de 60 dias após o procedimento índice não foram incluídos na análise. Os pacientes foram contabilizados no último contato disponível, seja por telefone ou por escore, e considerados livres de TAA se nenhum registro de arritmia tiver sido feito após a ablação por cateter. Os dados foram expressos em média ± desvio padrão, mediana e Intervalo Interquartil (IIQ), ou números absolutos e porcentagens. A normalidade dos dados foi avaliada usando o teste de Shapiro-Wilk, e as variáveis foram consideradas com distribuição normal quando apresentaram um valor de p > 0,05. Comparações entre os grupos (com e sem recorrência de TAA) foram realizadas pelo teste t de Student para variáveis com distribuição normal ou os testes de Wilcoxon-Mann-Whitney e de Kruskal-Wallis para variáveis sem distribuição normal. O teste do qui-quadrado foi usado para avaliar a significância da associação entre frequências das variáveis. Preditores univariados de eventos arrítmicos recorrentes (valor de p <0,10) e características basais foram avaliados com o modelo de riscos proporcionais de Cox. Valores médios foram inseridos em caso de valores faltantes de Índice de massa corporal (IMC), taxa de filtração glomerular (TFG), e diâmetro do átrio esquerdo (AE) para permitir um modelamento estatístico adequado para análise multivariada. Pacientes com FA persistente de longa duração foram incluídos no grupo de pacientes com FA persistente. Análises de sobrevida foram realizadas usando curvas de Kaplan-Meier e o teste de log-rank. Todas as análises estatísticas foram realizadas usando o Stata (versão 18). Um p-valor bicaudal de 0,05 foi considerado estatisticamente significativo. Características dos pacientes De janeiro de 2009 a janeiro de 2024, 1043 pacientes foram submetidos pela primeira vez à ablação por cateter por FA paroxística (n=788), FA persistente (n=230), e FA persistente de longa duração (n=25). A idade média foi de 67,3 ± 11,3 anos, e 27,9% eram mulheres. A maioria dos pacientes (79,0%) relataram sintomas relacionados à FA, com 23,8% classificados com escore EHRA classe III ou IV. A maioria dos pacientes apresentou escore CHA 2 DS 2 -VASc ≥2, e 79,1% usavam anticoagulantes. A descreve características clínica basais dos pacientes, estratificados por recorrência de TAA durante o acompanhamento. Características do procedimento IVP foi realizada em todos os pacientes usando ablação por cateter de RF, com um tempo médio de fluoroscopia de 10,6 ± 7,3 minutos e dose de radiação de 93 ± 121 mSv (dados disponíveis para 639 e 622 pacientes, respectivamente). A variação anatômica da veia pulmonar esquerda (VPE) foi determinada em casos em que duas VPEs se fundiam pelo menos 10 mm antes de sua inserção no óstio comum para desembocar no AE , com 26,6% (n=277) dos pacientes exibindo essa característica. O isolamento da parede posterior (IPP) adjunto (199 pacientes, 19,1%) foi realizado em pacientes com FA não paroxística e naqueles pacientes com FA paroxística que apresentavam temperatura esofágica que impossibilitava o IVP. Acompanhamento e recorrência de TAA O tempo médio de acompanhamento foi de 2,5 ± 2,3 anos (mediana 1,4 [IIQ 1,0 – 3,4]. No geral, 223 (21,4%) pacientes apresentaram recorrência de TAA, 67,3% dos quais (n=150) ocorreram no primeiro ano após o procedimento. A ilustra a taxa de recorrência de TAA 12 meses após uma primeira ablação por cateter para FA de acordo com o ano do procedimento. Observamos uma redução gradual na recorrência de TAA na análise temporal [Hazard Ratio [HR] 0,94, intervalo de confiança (IC) de 95% de 0,90 a 0,99; p = 0,01), alcançando uma taxa reduzida após um ano de 7,5% em 2017. A Figura Suplementar 1 apresenta os números absolutos de ablações da FA e as taxas de recorrência de TAA de acordo com o ano em que o procedimento foi realizado. Pacientes com FA paroxística apresentaram uma taxa de recorrência de 12,8% em um ano e uma taxa global de 18,6%. A taxa de recorrência para paciente com FA persistente foi de 19,2% em um ano e de 29,8% durante o acompanhamento em longo prazo. Uma análise de sobrevida comparando FA paroxística versus FA não paroxística revelou uma maior ausência de TAA na FA paroxística como mostrado na tanto aos 12 meses (A) como no seguimento global. Pacientes com variação anatômica da VPE apresentaram uma liberdade de 81,6% de TAA (226/277, p=0,08). Liberdade de TAA nos pacientes com FA paroxística e não paroxística, que receberam IPP adjunto, foi de 87,2% (82/94, p = 0,11) e 77,1% (81/105, p = 0,04), respectivamente. Análise de sobrevida comparando técnicas de ablação com e sem cateteres com sensor de força e contato, ilustrada na , mostrou uma taxa de liberdade mais alta de TAA durante o seguimento em pacientes que se submeteram à ablação usando esses cateteres (log-rank p=0,03). Análise univariada e multivariada Análise univariada e modelo de riscos proporcionais de Cox para avaliar preditores de recorrência de TAA após ablação da FA estão apresentados na . Preditores independentes de recorrência de TAA após primeira ablação incluíram FA persistente no basal (HR 1,57; IC95% 1,15 – 2,13; p = 0,004), maior diâmetro do AE (em milímetros) (HR 1,03; IC95% CI 1,00 – 1,05; p = 0,033), e paciente com um escore EHRA classe III ou IV (HR 1,60, IC95% 1,18 – 2,18; p = 0,003) (Figura Central). O ano do procedimento foi um fator protetor independente, com uma redução relativa de 9% na recorrência para cada novo ano do calendário do programa de ablação ( e ). Esses achados foram consistentes em uma análise restrita a pacientes com FA paroxística, como apresentado na Tabela Suplementar 1 . Uma análise de subgrupos de recorrência de TAA entre diferentes faixas etárias, sexo, categorias de IMC, hipertensão, diabetes tipo 2, TFG, fração de ejeção ventricular esquerda, e diâmetro do AE está apresentada na . Ente os subgrupos, os pacientes com idade superior a 75 anos (HR 1,77, IC95% 1,28 – 2,45; p = 0,001) e um diâmetro atrial esquerdo mais alto (45-49mm, p = 0,020; >50mm, p = 0,003) apresentaram desfechos estatisticamente significativos em relação à TAA (HR 1,55, IC95% 1,15-2,10, p = 0,004). A análise multivariada identificou apenas a idade (HR 1,03; IC95% 1,00 – 1,05, p = 0,01) como um preditor independente de recorrência de TAA quando restrita a pacientes com FA persistente ( Tabela Suplementar 2 ). A ilustra a análise de sobrevida em pacientes com FA persistente com e sem alteração da TCE-VPs (log-rank p=0,30). Segurança e eventos adversos Ao longo de 15 anos, entre as 1043 ablações consecutivas realizadas, a taxa de complicação durante a admissão índice foi de 2,1% ( Tabela Suplementar 3 ). Vale notar que os pacientes com idade superior a 75 anos representaram apenas 0,8% das complicações totais. Eventos adversos graves incluíram dois casos de tamponamento cardíaco (um caso tratado com sucesso durante o procedimento e um necessitou de cirurgia cardíaca), um acidente vascular cerebral não fatal durante a admissão para o procedimento índice, e uma perfuração esofágica sem fístula tratada com sucesso de maneira conservadora. Não foi observada lesão de nervo frênico, estenose da veia pulmonar clinicamente relevante, ou mortes relacionadas ao procedimento . De janeiro de 2009 a janeiro de 2024, 1043 pacientes foram submetidos pela primeira vez à ablação por cateter por FA paroxística (n=788), FA persistente (n=230), e FA persistente de longa duração (n=25). A idade média foi de 67,3 ± 11,3 anos, e 27,9% eram mulheres. A maioria dos pacientes (79,0%) relataram sintomas relacionados à FA, com 23,8% classificados com escore EHRA classe III ou IV. A maioria dos pacientes apresentou escore CHA 2 DS 2 -VASc ≥2, e 79,1% usavam anticoagulantes. A descreve características clínica basais dos pacientes, estratificados por recorrência de TAA durante o acompanhamento. IVP foi realizada em todos os pacientes usando ablação por cateter de RF, com um tempo médio de fluoroscopia de 10,6 ± 7,3 minutos e dose de radiação de 93 ± 121 mSv (dados disponíveis para 639 e 622 pacientes, respectivamente). A variação anatômica da veia pulmonar esquerda (VPE) foi determinada em casos em que duas VPEs se fundiam pelo menos 10 mm antes de sua inserção no óstio comum para desembocar no AE , com 26,6% (n=277) dos pacientes exibindo essa característica. O isolamento da parede posterior (IPP) adjunto (199 pacientes, 19,1%) foi realizado em pacientes com FA não paroxística e naqueles pacientes com FA paroxística que apresentavam temperatura esofágica que impossibilitava o IVP. O tempo médio de acompanhamento foi de 2,5 ± 2,3 anos (mediana 1,4 [IIQ 1,0 – 3,4]. No geral, 223 (21,4%) pacientes apresentaram recorrência de TAA, 67,3% dos quais (n=150) ocorreram no primeiro ano após o procedimento. A ilustra a taxa de recorrência de TAA 12 meses após uma primeira ablação por cateter para FA de acordo com o ano do procedimento. Observamos uma redução gradual na recorrência de TAA na análise temporal [Hazard Ratio [HR] 0,94, intervalo de confiança (IC) de 95% de 0,90 a 0,99; p = 0,01), alcançando uma taxa reduzida após um ano de 7,5% em 2017. A Figura Suplementar 1 apresenta os números absolutos de ablações da FA e as taxas de recorrência de TAA de acordo com o ano em que o procedimento foi realizado. Pacientes com FA paroxística apresentaram uma taxa de recorrência de 12,8% em um ano e uma taxa global de 18,6%. A taxa de recorrência para paciente com FA persistente foi de 19,2% em um ano e de 29,8% durante o acompanhamento em longo prazo. Uma análise de sobrevida comparando FA paroxística versus FA não paroxística revelou uma maior ausência de TAA na FA paroxística como mostrado na tanto aos 12 meses (A) como no seguimento global. Pacientes com variação anatômica da VPE apresentaram uma liberdade de 81,6% de TAA (226/277, p=0,08). Liberdade de TAA nos pacientes com FA paroxística e não paroxística, que receberam IPP adjunto, foi de 87,2% (82/94, p = 0,11) e 77,1% (81/105, p = 0,04), respectivamente. Análise de sobrevida comparando técnicas de ablação com e sem cateteres com sensor de força e contato, ilustrada na , mostrou uma taxa de liberdade mais alta de TAA durante o seguimento em pacientes que se submeteram à ablação usando esses cateteres (log-rank p=0,03). Análise univariada e modelo de riscos proporcionais de Cox para avaliar preditores de recorrência de TAA após ablação da FA estão apresentados na . Preditores independentes de recorrência de TAA após primeira ablação incluíram FA persistente no basal (HR 1,57; IC95% 1,15 – 2,13; p = 0,004), maior diâmetro do AE (em milímetros) (HR 1,03; IC95% CI 1,00 – 1,05; p = 0,033), e paciente com um escore EHRA classe III ou IV (HR 1,60, IC95% 1,18 – 2,18; p = 0,003) (Figura Central). O ano do procedimento foi um fator protetor independente, com uma redução relativa de 9% na recorrência para cada novo ano do calendário do programa de ablação ( e ). Esses achados foram consistentes em uma análise restrita a pacientes com FA paroxística, como apresentado na Tabela Suplementar 1 . Uma análise de subgrupos de recorrência de TAA entre diferentes faixas etárias, sexo, categorias de IMC, hipertensão, diabetes tipo 2, TFG, fração de ejeção ventricular esquerda, e diâmetro do AE está apresentada na . Ente os subgrupos, os pacientes com idade superior a 75 anos (HR 1,77, IC95% 1,28 – 2,45; p = 0,001) e um diâmetro atrial esquerdo mais alto (45-49mm, p = 0,020; >50mm, p = 0,003) apresentaram desfechos estatisticamente significativos em relação à TAA (HR 1,55, IC95% 1,15-2,10, p = 0,004). A análise multivariada identificou apenas a idade (HR 1,03; IC95% 1,00 – 1,05, p = 0,01) como um preditor independente de recorrência de TAA quando restrita a pacientes com FA persistente ( Tabela Suplementar 2 ). A ilustra a análise de sobrevida em pacientes com FA persistente com e sem alteração da TCE-VPs (log-rank p=0,30). Ao longo de 15 anos, entre as 1043 ablações consecutivas realizadas, a taxa de complicação durante a admissão índice foi de 2,1% ( Tabela Suplementar 3 ). Vale notar que os pacientes com idade superior a 75 anos representaram apenas 0,8% das complicações totais. Eventos adversos graves incluíram dois casos de tamponamento cardíaco (um caso tratado com sucesso durante o procedimento e um necessitou de cirurgia cardíaca), um acidente vascular cerebral não fatal durante a admissão para o procedimento índice, e uma perfuração esofágica sem fístula tratada com sucesso de maneira conservadora. Não foi observada lesão de nervo frênico, estenose da veia pulmonar clinicamente relevante, ou mortes relacionadas ao procedimento . Este estudo prospectivo multicêntrico do tipo coorte avaliou mais de mil pacientes consecutivos com FA submetidos pela primeira vez à ablação no Brasil, e apresenta dados de longo prazo sobre eficiência, segurança, e preditores de recorrência de arritmia. Os principais achados da análise presente incluem: (i) eficácia e segurança global foram comparáveis às descritas em ensaios clínicos e registros de países de alta renda na Europa e na América do Norte; , (ii) a eficácia em longo prazo aumentou ao decorrer do tempo, com uma redução de 9% no risco relativo de recorrência de TAA para cada ano consecutivo em que a ablação foi realizada; (iii) a adoção de catéteres com sensores de força e contato melhorou os desfechos após a primeira ablação; (iv) a maioria das recorrências de TAA ocorreu em um ano após a ablação; e (v) a recorrência de TAA foi mais frequentemente observada em procedimentos realizados em pacientes com doença avançada (escore de EHRA grave de sintomas de FA, AE maior e FA persistente). Além disso, nossos achados destacam a baixa taxa de complicações de ablações consecutivas em um estudo prospectivo do tipo coorte conduzido na América Latina. Registros internacionais exercem um papel crucial em compreender disparidades entre diretrizes e o manejo da FA na prática clínica diária. Um relatório inicial da Atrial Fibrillation Ablation Pilot Registry of the European Society (EORP-AF) demonstrou taxas de sucesso de um ano após a ablação variando entre 69% e 74,7% em diferentes países. O EORP-AF também contribuiu significativamente para o entendimento de dados da vida real relacionados à FA. No EORP-AF Long-Term Registry, os desfechos foram documentados de 9663 pacientes com FA com base no seu tratamento antitrombótico. Enquanto 42% e 33% dos pacientes do EORP-AF usaram Antagonistas de Vitamina-K (AVK) e Anticoagulantes Orais Diretos (DOAC), respectivamente, nossa coorte exibiu um padrão diferente, com 15% usando AVK e 64% DOACs. Desfechos da ablação baseados no gênero também foram relatados nessa colaboração europeia, com uma representação similar de gênero à observada em nosso estudo, onde cerca de somente 30% dos pacientes eram do gênero feminino. No basal, pacientes do sexo feminino eram mais sintomáticas em comparação ao gênero masculino, com escores EHRA médios de 2,6 vs. 2,4 na Europa (p<0,001) e 2,2 vs. 2,0 no Brasil (p<0,001). Um dado importante é que nenhum dos estudos relatou diferenças baseadas no gênero estatisticamente significativas nas taxas de recorrência em 12 meses (34,4% vs. 34,2% na Europa; 16,1% vs. 13,7% no Brasil, p=0,3), destacando a necessidade de acesso igualitário como uma opção terapêutica para as mulheres. Este estudo representa o maior estudo do tipo coorte até o momento delineado para avaliar desfechos da ablação em pacientes com FA na América Latina. Dados de pacientes brasileiros com FA foram recentemente descritos no estudo RECALL, embora desfechos de ablação não tenham sido avaliados. O último registro multicêntrico dedicado a desfechos de ablação publicado no Brasil foi conduzido pela Sociedade Brasileira de Arritmias Cardíacas entre 2005 e 2006. Nesse registro, 755 pacientes com FA foram incluídos, e uma taxa de complicação de 14,3% foi relatada, que incluiu 1,4% de eventos isquêmicos neurológicos transientes, 0,4% de estenose na veia pulmonar, 3,8% de hematomas na região inguinal, e 2,3% de outras complicações. A taxa de 2,1% de complicações observadas na coorte atual destaca a curva de aprendizagem associada com procedimentos de ablação e demonstra como avanços tecnológicos, principalmente cateteres com sensores de força e contato, tornaram esses procedimentos mais seguros e mais confiáveis na prática clínica. Resultados similares foram observados no maior estudo do tipo coorte, o NCDR AFib Ablation Registry , com uma taxa de complicação de 2,5% nos 76219 pacientes com FA ao longo de cinco anos. Estudos prévios abordaram preditores de recorrência após ablação da FA. A análise presente demonstra que FA persistente e um AE maior foram consistentemente relatados como fatores de risco independentes. , Vários escores foram desenvolvidos para predizer desfechos de ritmo após ablação da FA. O escore APPLE (um ponto para idade > 65 anos, FA persistente, TFG estimada < 60 mL/min/1,73 m , diâmetro do AE ≥43mm, FEVE < 50%) mostrou um desempenho subótimo (AUC = 0,64), enquanto a calculadora da web AFA-Recur, que se baseia em um modelo random forest de 19 variáveis alcançou um desempenho discriminatório aceitável (AUC 0,72). Nosso modelo de Cox também incorporou o escore EHRA de sintomas de FA classes III-IV como um preditor independente de risco. O escore EHRA AF é comumente usado para avaliar a resposta clínica após a ablação, e pode também sinalizar a gravidade e a duração mais longa da doença. Em comparação a registros anteriores, nossa coorte também mostrou taxas mais altas de TAA após a ablação em pacientes mais velhos, embora não houve diferença significativa nos desfechos entre as categorias de IMC. , É razoável considerar que pacientes com FA paroxística expostos a cargas mais longas de arritmia sofram um remodelamento progressivo do átrio. Essa possibilidade leva a uma piora da atriopatia subjacente e progressão a formas mais graves e persistentes da doença. Por fim, essa progressão esperada da FA leva a piores desfechos clínicos em procedimentos realizados em estágios mais tardios da história natural da arritmia. Essa proposta foi sustentada no ensaio EARLY-AF, em que pacientes com FA paroxística foram acompanhados por três anos. Esse estudo revelou que pacientes submetidos à ablação inicial apresentaram menor progressão à FA persistente e menos recorrências de TAA em comparação a pacientes tratados somente com drogas antiarrítmicas. Embora pareça evidente que ablações mais precoces poderiam levar a melhores resultados, atingir uma eficácia elevada em ablações de FA persistente continua um desafio. Locais adjuntivos de ablação, tais como IPP, foram recentemente sugeridos como uma estratégia potencial no manejo dessa condição desafiadora. , Em nossa coorte, o IPP foi realizado em aproximadamente um quinto dos pacientes incluídos segundo critérios do operador, mas não foi um preditor independente de recorrência de TAA. Pontos fortes e limitações do estudo Nossa coorte é constituída de pacientes consecutivos com FA submetidos à ablação pela primeira vez, o que a torna o maior conjunto de dados da América Latina destinado a avaliar a segurança e a eficácia da ablação da FA. Esses achados são particularmente relevantes no contexto das alterações do TCE-VPs, fornecendo insights valiosos à segurança clínica no mundo real. Fatores de confusão residuais são uma preocupação potencial, uma vez que faltaram dados para o ajuste quanto à duração da FA. Não analisamos os desfechos de ablações repetidas neste estudo. Este estudo multicêntrico do tipo coorte foi conduzido somente em centros privados e pode não refletir a realidade de centros públicos no Brasil. A maioria dos pacientes eram brancos e não representaram a população da América Latina. Ainda, os pacientes foram contabilizados no último acompanhamento, o que pode ter subestimado a taxa de recorrência de TAA. Nossa coorte é constituída de pacientes consecutivos com FA submetidos à ablação pela primeira vez, o que a torna o maior conjunto de dados da América Latina destinado a avaliar a segurança e a eficácia da ablação da FA. Esses achados são particularmente relevantes no contexto das alterações do TCE-VPs, fornecendo insights valiosos à segurança clínica no mundo real. Fatores de confusão residuais são uma preocupação potencial, uma vez que faltaram dados para o ajuste quanto à duração da FA. Não analisamos os desfechos de ablações repetidas neste estudo. Este estudo multicêntrico do tipo coorte foi conduzido somente em centros privados e pode não refletir a realidade de centros públicos no Brasil. A maioria dos pacientes eram brancos e não representaram a população da América Latina. Ainda, os pacientes foram contabilizados no último acompanhamento, o que pode ter subestimado a taxa de recorrência de TAA. No maior estudo coorte da América Latina de pacientes consecutivos com FA submetidos à primeira ablação, a recorrência de TAA foi associada a intervenções realizadas em estágios mais avançados da doença, destacando a importância da intervenção precoce para melhores desfechos clínicos. Complicações do procedimento e taxas de recorrência da TAA foram comparáveis às de países de alta renda, destacando a aplicabilidade global da ablação por cateter para o manejo da FA. Assim, esses dados reforçam o excelente desempenho da ablação no manejo da FA em centros da América Latina, sugerindo que essa opção terapêutica deveria ser expandida ao sistema público no Brasil |
Short‐term surgical outcomes of open, laparoscopic, and robot‐assisted pancreatoduodenectomy: A comparative, single‐center, retrospective study | 396ffd6b-b7eb-4bb6-bf2b-acf9b058efcb | 11669441 | Robotic Surgical Procedures[mh] | INTRODUCTION Pancreatoduodenectomy (PD), also known as Whipple's procedure, was first successfully performed by Whipple in 1935. In 1994, a less invasive laparoscopic approach (laparoscopic PD [LPD]) was introduced by Gagner and Pomp, and by 2003, robot‐assisted PD (RPD), first conducted by Giulianotti, further improved surgical precision through advanced features such as three‐dimensional, motion‐scaled, and tremor‐filtered articulated functions. In 2008, Gumbs et al. presented the first comparative study of LPD and open PD (OPD) and demonstrated the potential of LPD. Since then, many studies have compared the safety and efficacy of LPD and OPD. One meta‐analysis of over 40 000 patients has found that LPD offers comparable short‐term outcomes and oncologic adequacy to OPD, with reduced postoperative complications and blood loss but longer operative times. Several meta‐analyses have compared RPD and OPD. , , One comprehensive meta‐analysis has found that RPD typically takes longer than OPD but results in less blood loss, fewer postoperative complications, and shorter hospital stays. Another meta‐analysis of over 3500 patients has found similar postoperative outcomes between LPD and RPD; however, RPD resulted in less blood loss, a lower conversion rate, and more retrieved lymph nodes. This comparative analysis is significant because it provides insights into the effectiveness and safety of three surgical approaches, viz. OPD, LPD, and RPD. By evaluating short‐term surgical outcomes, such as operative time, postoperative complications, length of hospital stay, and hospitalization cost, this study can help determine which method offers the best balance of benefits and risks. This information is crucial for surgical decision‐making and improving patient care during pancreatic surgery.
MATERIALS AND METHODS 2.1 Patients LPD was introduced at our institution in April 2020 and performed on 16 patients until July 2021. RPD was introduced in April 2021 and performed in 41 patients up to May 2024, excluding two patients who required portal vein reconstruction and reconstruction due to pancreatic cancer invasion, one patient who developed intraoperative bleeding, and one patient in whom a stent was lost in the main pancreatic duct. To eliminate selection bias, 36 consecutive patients with a history of laparotomy without pancreatic ductal adenocarcinoma (PDAC) who underwent OPD between January 2019 and December 2020 were included in this comparison. Patients who underwent portal venous and/or arterial resection were excluded (Figure ). Clinical and follow‐up information was extracted from a prospectively maintained database at the Department of Hepatobiliary Pancreatic and Transplant Surgery, Mie University Hospital. All information was verified by reviewing patients' medical records. This study was approved by the Institutional Review Board of Mie University, Japan (approval number: 2857) and conducted in accordance with the ethical principles outlined in the 1964 Declaration of Helsinki and its later amendments. 2.2 Transition of surgical indications for LPD and RPD The following surgical indications were established for safe induction of LPD in April 2020: benign and borderline malignant pancreatic tumor, ampullary adenoma/carcinoma (T1–T3), distal cholangiocarcinoma (T1–T2), duodenal tumor without another organ invasion, metastatic pancreatic tumor, and PDAC. The exclusion criteria were as follows: age >80 years, body mass index (BMI) >30 kg/m 2 , patients with severe chronic obstructive pulmonary disease or interstitial pneumonia, history of severe pancreatitis within the past year, and history of laparotomy. RPD was introduced in April 2021 with the same criteria as LPD; that is, it was restricted to patients aged <60 years with a BMI <25 kg/m 2 ; however, the age‐ and BMI‐related exclusion criteria were abolished in November 2021, and PDAC (T1–T3) has also been included as a surgical indication for RPD since January 2024. 2.3 Surgical procedure of OPD Surgical procedures for OPD of periampullary tumors other than PDAC and advanced distal cholangiocarcinoma are briefly described in Table . An upper midline incision was made. The omental bursa was opened first, and the transverse colon was mobilized from the head of the pancreas and duodenum (Step 2). The Kocher maneuver was performed by elevating the duodenum and the head of the pancreas out of the retroperitoneum until the left renal vein could be identified (Step 3). The superior mesenteric vein (SMV) was exposed at the inferior border of the pancreas, and the gastrocolic trunk of Henle was divided (Step 4). The stomach was divided into the proximal antrum using a linear stapler for the subtotal stomach‐preserving PD approach (Step 5). The pancreas was separated, and regional lymph nodes were dissected, allowing careful dissection along the common hepatic artery until the origin of the gastroduodenal artery was reached. The division of the gastroduodenal artery exposes the anterior aspect of the portal vein (PV), facilitating dissection of the common bile duct after detachment from the gallbladder bed and lymph node dissection surrounding the hepatic artery and PV (Step 6). After completing the retropancreatic tunneling from the SMV/PV, the pancreas was divided using an ultrasonically activated device (Step 7). The jejunum was then divided. Finally, the head of the pancreas was separated from the SMV/PV and superior mesenteric artery (SMA) by dividing the pancreatic head nerve plexus, including the inflow and outflow vascular branches, and dissection was continued until PhPLI, culminating in specimen removal (Step 8: Right SMA approach). For reconstruction, the jejunum was elevated through the antecolic route. Our end‐to‐side pancreatojejunostomy consists of two‐layer anastomosis, viz. duct‐to‐mucosa anastomosis and pancreatic parenchymal to jejunal seromuscular anastomosis (Step 9). Duct‐to‐mucosa anastomosis was achieved using 12 interrupted sutures with an external stent, and second‐layer anastomosis was achieved using interrupted sutures, similar to a previous study. The end‐to‐side hepaticojejunostomy was performed using continuous sutures for the posterior wall and interrupted sutures for the anterior wall with an external stent (Step 10). A loop of the jejunum was brought in an antecolic fashion, and a side‐to‐side gastrojejunostomy was performed with Brawn anastomosis (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems (J‐VAC drainage system; Ethicon, Inc., Somerville, NJ, USA) were placed near the sites of the pancreaticojejunostomy and hepaticojejunostomy (Step 12). 2.4 Surgical procedure of LPD The surgical procedures for LPD are described in Table . Patients were placed with their legs apart in the reverse Trendelenburg position at 10°–15° with a right‐side tilt of 5°–10°. The trocar settings for the LPD are shown in Figure . As to OPD, PD was performed laparoscopically from Steps 1 to 8. For reconstruction during LPD, the jejunum was elevated through the mesocolic window. The end‐to‐side hepaticojejunostomy was first performed with continuous sutures for the anterior and posterior walls with internal stents (Step 10). The end‐to‐side pancreatojejunostomy was performed under a small laparotomy. Duct‐to‐mucosa anastomosis was achieved using eight interrupted sutures with an internal stent. Second‐layer anastomosis was also achieved using the modified Blumgart method (Step 9). The loop of the jejunum was brought in an antecolic fashion, and side‐to‐side gastrojejunostomy was performed with Brawn anastomosis (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems, as well as the OPD, were placed (Step 12). 2.5 Surgical procedure of RPD The surgical procedures for the RPD are briefly described in Table . Patients were placed with their legs apart in the reverse Trendelenburg position at 10°–15° with a right‐side tilt of 5°–10°. The trocar settings using the da Vinci Xi system (Intuitive Surgical, Sunnyvale, CA, USA) are shown in Figure . The Treitz ligament was first dissected after exposing the inferior vena cava, followed by exposure of the left side of the SMA (Step 1: left SMA approach). After Step 2 was performed, Steps 4 through 7 were performed, followed by the Kocher maneuver in Step 3 after changing the camera from port 3 to port 2, and the tumor was resected after Step 8. During the RPD reconstruction, the jejunum was elevated through the mesocolic window. In end‐to‐side pancreatojejunostomy, duct‐to‐mucosa anastomosis was achieved using continuous sutures with an internal stent. A second‐layer anastomosis was achieved using the modified Blumgart method (Step 9). The end‐to‐side hepaticojejunostomy was performed in the same procedure as for LPD (Step 10). The loop of the jejunum was brought in an antecolic fashion, and end‐to‐side duodenojejunostomy was also performed (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems, as well as the OPD and LPD (Step 12), were placed. 2.6 Postoperative management Three drains were scheduled to be removed on the fourth postoperative day or later, provided that the amylase and bilirubin concentrations in the drainage fluid did not exceed three times their respective normal upper limits. Otherwise, the drain was replaced once with a closed, non‐suction drain within 2 weeks. The drain was removed after fistulography confirmed the absence of a residual space along the fistula tract. 2.7 Postoperative complications Postoperative complications were graded according to the Clavien–Dindo (CD) classification. Postoperative pancreatic fistula (POPF), bile leakage, postoperative pancreatic hemorrhage (PPH), and delayed gastric emptying were defined according to the classification formulated by the International Study Group on Pancreatic Surgery. , , , 2.8 Statistical analysis Continuous variables are expressed as median (range) and were compared using the Mann–Whitney U test for two groups. Categorical variables were summarized as numbers (percentages) and compared using Pearson's Chi‐square/Fisher's exact test. A two‐tailed significance level of p < .05 was established. All the statistical analyses were performed using SPSS v28 (IBM Corp., Armonk, NY, USA).
Patients LPD was introduced at our institution in April 2020 and performed on 16 patients until July 2021. RPD was introduced in April 2021 and performed in 41 patients up to May 2024, excluding two patients who required portal vein reconstruction and reconstruction due to pancreatic cancer invasion, one patient who developed intraoperative bleeding, and one patient in whom a stent was lost in the main pancreatic duct. To eliminate selection bias, 36 consecutive patients with a history of laparotomy without pancreatic ductal adenocarcinoma (PDAC) who underwent OPD between January 2019 and December 2020 were included in this comparison. Patients who underwent portal venous and/or arterial resection were excluded (Figure ). Clinical and follow‐up information was extracted from a prospectively maintained database at the Department of Hepatobiliary Pancreatic and Transplant Surgery, Mie University Hospital. All information was verified by reviewing patients' medical records. This study was approved by the Institutional Review Board of Mie University, Japan (approval number: 2857) and conducted in accordance with the ethical principles outlined in the 1964 Declaration of Helsinki and its later amendments.
Transition of surgical indications for LPD and RPD The following surgical indications were established for safe induction of LPD in April 2020: benign and borderline malignant pancreatic tumor, ampullary adenoma/carcinoma (T1–T3), distal cholangiocarcinoma (T1–T2), duodenal tumor without another organ invasion, metastatic pancreatic tumor, and PDAC. The exclusion criteria were as follows: age >80 years, body mass index (BMI) >30 kg/m 2 , patients with severe chronic obstructive pulmonary disease or interstitial pneumonia, history of severe pancreatitis within the past year, and history of laparotomy. RPD was introduced in April 2021 with the same criteria as LPD; that is, it was restricted to patients aged <60 years with a BMI <25 kg/m 2 ; however, the age‐ and BMI‐related exclusion criteria were abolished in November 2021, and PDAC (T1–T3) has also been included as a surgical indication for RPD since January 2024.
Surgical procedure of OPD Surgical procedures for OPD of periampullary tumors other than PDAC and advanced distal cholangiocarcinoma are briefly described in Table . An upper midline incision was made. The omental bursa was opened first, and the transverse colon was mobilized from the head of the pancreas and duodenum (Step 2). The Kocher maneuver was performed by elevating the duodenum and the head of the pancreas out of the retroperitoneum until the left renal vein could be identified (Step 3). The superior mesenteric vein (SMV) was exposed at the inferior border of the pancreas, and the gastrocolic trunk of Henle was divided (Step 4). The stomach was divided into the proximal antrum using a linear stapler for the subtotal stomach‐preserving PD approach (Step 5). The pancreas was separated, and regional lymph nodes were dissected, allowing careful dissection along the common hepatic artery until the origin of the gastroduodenal artery was reached. The division of the gastroduodenal artery exposes the anterior aspect of the portal vein (PV), facilitating dissection of the common bile duct after detachment from the gallbladder bed and lymph node dissection surrounding the hepatic artery and PV (Step 6). After completing the retropancreatic tunneling from the SMV/PV, the pancreas was divided using an ultrasonically activated device (Step 7). The jejunum was then divided. Finally, the head of the pancreas was separated from the SMV/PV and superior mesenteric artery (SMA) by dividing the pancreatic head nerve plexus, including the inflow and outflow vascular branches, and dissection was continued until PhPLI, culminating in specimen removal (Step 8: Right SMA approach). For reconstruction, the jejunum was elevated through the antecolic route. Our end‐to‐side pancreatojejunostomy consists of two‐layer anastomosis, viz. duct‐to‐mucosa anastomosis and pancreatic parenchymal to jejunal seromuscular anastomosis (Step 9). Duct‐to‐mucosa anastomosis was achieved using 12 interrupted sutures with an external stent, and second‐layer anastomosis was achieved using interrupted sutures, similar to a previous study. The end‐to‐side hepaticojejunostomy was performed using continuous sutures for the posterior wall and interrupted sutures for the anterior wall with an external stent (Step 10). A loop of the jejunum was brought in an antecolic fashion, and a side‐to‐side gastrojejunostomy was performed with Brawn anastomosis (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems (J‐VAC drainage system; Ethicon, Inc., Somerville, NJ, USA) were placed near the sites of the pancreaticojejunostomy and hepaticojejunostomy (Step 12).
Surgical procedure of LPD The surgical procedures for LPD are described in Table . Patients were placed with their legs apart in the reverse Trendelenburg position at 10°–15° with a right‐side tilt of 5°–10°. The trocar settings for the LPD are shown in Figure . As to OPD, PD was performed laparoscopically from Steps 1 to 8. For reconstruction during LPD, the jejunum was elevated through the mesocolic window. The end‐to‐side hepaticojejunostomy was first performed with continuous sutures for the anterior and posterior walls with internal stents (Step 10). The end‐to‐side pancreatojejunostomy was performed under a small laparotomy. Duct‐to‐mucosa anastomosis was achieved using eight interrupted sutures with an internal stent. Second‐layer anastomosis was also achieved using the modified Blumgart method (Step 9). The loop of the jejunum was brought in an antecolic fashion, and side‐to‐side gastrojejunostomy was performed with Brawn anastomosis (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems, as well as the OPD, were placed (Step 12).
Surgical procedure of RPD The surgical procedures for the RPD are briefly described in Table . Patients were placed with their legs apart in the reverse Trendelenburg position at 10°–15° with a right‐side tilt of 5°–10°. The trocar settings using the da Vinci Xi system (Intuitive Surgical, Sunnyvale, CA, USA) are shown in Figure . The Treitz ligament was first dissected after exposing the inferior vena cava, followed by exposure of the left side of the SMA (Step 1: left SMA approach). After Step 2 was performed, Steps 4 through 7 were performed, followed by the Kocher maneuver in Step 3 after changing the camera from port 3 to port 2, and the tumor was resected after Step 8. During the RPD reconstruction, the jejunum was elevated through the mesocolic window. In end‐to‐side pancreatojejunostomy, duct‐to‐mucosa anastomosis was achieved using continuous sutures with an internal stent. A second‐layer anastomosis was achieved using the modified Blumgart method (Step 9). The end‐to‐side hepaticojejunostomy was performed in the same procedure as for LPD (Step 10). The loop of the jejunum was brought in an antecolic fashion, and end‐to‐side duodenojejunostomy was also performed (Step 11). After completion of the reconstruction, three closed vacuum‐drainage systems, as well as the OPD and LPD (Step 12), were placed.
Postoperative management Three drains were scheduled to be removed on the fourth postoperative day or later, provided that the amylase and bilirubin concentrations in the drainage fluid did not exceed three times their respective normal upper limits. Otherwise, the drain was replaced once with a closed, non‐suction drain within 2 weeks. The drain was removed after fistulography confirmed the absence of a residual space along the fistula tract.
Postoperative complications Postoperative complications were graded according to the Clavien–Dindo (CD) classification. Postoperative pancreatic fistula (POPF), bile leakage, postoperative pancreatic hemorrhage (PPH), and delayed gastric emptying were defined according to the classification formulated by the International Study Group on Pancreatic Surgery. , , ,
Statistical analysis Continuous variables are expressed as median (range) and were compared using the Mann–Whitney U test for two groups. Categorical variables were summarized as numbers (percentages) and compared using Pearson's Chi‐square/Fisher's exact test. A two‐tailed significance level of p < .05 was established. All the statistical analyses were performed using SPSS v28 (IBM Corp., Armonk, NY, USA).
RESULTS Table presents the demographics and short‐term outcomes of the patients who underwent OPD, LPD, and RPD. The patients in the RPD group were significantly younger (65 years) than those in the OPD (73 years, p = .029) and LPD (72 years, p = .044) groups. Distal cholangiocarcinoma was more commonly diagnosed in the OPD group, whereas ampullary tumors were less common than in the RPD group ( p < .001). The distribution of diagnoses between the LPD and RPD groups was similar. In terms of intraoperative findings, the operative time for RPD (553 min) was significantly longer than those for OPD (446 min, p < .001) and LPD (453 min, p < .001). However, the RPD group had a significantly lower estimated blood loss (150 mL) than the OPD group (400 mL, p < .001). The time for hepaticojejunostomy was shorter for RPD (26 min) than for LPD (43 min, p < .001). The size of the main pancreatic duct and texture of the pancreatic parenchyma were similar across the three groups. However, the common bile duct diameter was significantly more dilated in the OPD group (12 mm) than in the RPD group (8 mm, p = .001). Postoperative complications (CD3 or higher) were significantly less common in the RPD group (26.8%) than in the OPD (50.0%, p = .032) and LPD (68.8%, p = .005) groups. Looking at the details of each postoperative CD3 or higher complication, of the 18 cases (50.0%) in the OPD group, the most common were 10 cases of POPF, followed by four cases of intra‐abdominal abscess requiring drainage, three cases of PPH with POPF, and one case of regastrojejunostomy. In the LPD group (11 patients, 68.8%), the most common were five cases of POPF, followed by four cases of bile leakage, one case of PPH with POPF, and one case of peritonitis surgery due to small bowel perforation. In the RPD group (10 patients, 24.4%), the most common complication was four cases of POPF, followed by four cases of bile leakage, one case of PPH with POPF, and one case of PPH. The incidence of grade ≥B POPF was also significantly lower in the RPD group (14.6%) than in the OPD (38.9%, p = .020) and LPD (43.8%, p = .033) groups. The incidence of grade ≥B delayed gastric emptying was significantly lower in the RPD group (0%) than in the OPD (11.1%, p = .044). The length of hospital stay was the shortest in the RPD group at 11 days, followed by 21 days in the LPD group ( p < .001) and 28 days in the OPD group ( p < .001). However, hospitalization costs were higher for RPD (20 109 USD) than for OPD (18 487 USD, p < .001) and LPD (20 496 USD) and RPD costs were similar.
DISCUSSION The short‐term outcomes of the first 41 patients who underwent RPD were compared with those of the first set of patients who underwent LPD ( n = 16) or OPD ( n = 36). RPD possessed advantages in terms of reduced estimated blood loss and lower postoperative complication rates, resulting in a shorter postoperative hospital stay, despite a longer operative time and higher hospitalization costs. These findings suggest that RPD may be more beneficial than OPD or LPD. Many studies have clarified the utility and limitations of the newly developed LPD relative to the OPD, which has been the standard procedure for pancreatic and periampullary tumors for several years. Four randomized trials comparing LPD and OPD have been reported. , , , Overall, while LPD has shown some advantages, such as shorter hospital stays, these trials often reported longer operative times and highlighted the importance of the operator's experience and patient selection in achieving optimal outcomes. The LEOPARD‐2 Trial had to be terminated early because of the higher postoperative mortality in the LPD group. These findings underscore the potential benefits of LPD but also highlight significant risks and the need for careful consideration of operator expertise and patient characteristics in determining the best surgical approach. In our study, although the sample size of the LPD group was small during the initial phase, it had a higher incidence of postoperative complications with a grade of CD3 or greater than that of the OPD group. In particular, the higher postoperative complications associated with reconstruction of the pancreatic and bile ducts suggest that OPD and LPD are equivalent until the tumor is removed. However, practice and proficiency are required to overcome the limitations of forceps movement required for reconstruction. Several studies have compared RPD performed using the latest surgical technologies with conventional OPD. In 2024, two randomized trials comparing RPD and OPD were reported. , Liu et al. showed that surgeons who had passed the learning curve could extract benefits from RPD, including a shorter hospital stay. In contrast, the EUROPA trial, which was conducted at a very high‐volume center, found no significant difference in the overall complication rate between the two groups. Additionally, RPD was associated with longer surgical duration and higher hospitalization costs. In our study, RPD clearly reduced blood loss, although the operative time was prolonged compared with OPD. In addition, although the RPD was in its initial phase, the incidence of postoperative complications of CD3 or higher had already decreased, resulting in significantly shorter hospital stays. The unique technologies of the RPD, such as three‐dimensional motion‐scaled and tremor‐filtered articulated functions, contribute to its ability to facilitate sophisticated surgical procedures. To date, no randomized trials have compared LPD with RPD. Several multicenter, retrospective studies have compared LPD and RPD. , , In 2023, a study using the American College of Surgeons National Sample Quality Improvement Program (ACS NSQIP) dataset showed that the incidences of conversion surgery and postoperative complications were lower with RPD than with LPD. In contrast, in 2024, a multicenter European study performed by the European Consortium on Minimally Invasive Pancreatic Surgery (E‐MIPS) reported that LPD was associated with a lower rate of postoperative complications, shorter duration of hospitalization, and a higher R0 resection rate compared with RPD. , In contrast, RPD was associated with a lower conversion rate and a higher number of retrieved lymph nodes than LPD. However, the utility and superiority of RPD and LPD remain controversial. In our study, RPD required a significantly longer operative time than LPD, similar to previous studies; however, the former was significantly superior in terms of blood loss, postoperative complication rate, and length of hospital stay. Additionally, hospitalization costs were comparable, suggesting that RPD could replace LPD as the driving force behind MIPS in the future. The incidence of postoperative complications (CD3 or higher) in the LPD/OPD groups were notably high compared to that in the RPD group. First, it cannot be denied that the reason for the high incidence of CD3 or higher complications in the OPD group was that many procedures were performed by relatively young, still‐trained hepatobiliary surgeons. In the LPD group, there were 16 cases of initial induction, and since approximately 40–50 cases were required to overcome this in the LPD, , the impact of the learning curve may have influenced the high frequency of complications. In contrast, in the RPD group, a low frequency of clinically relevant POPF was considered to indicate complications. These results suggest that RPD may be particularly useful in pancreaticojejunostomies. This study had some limitations. First, this was a retrospective cohort study conducted at a single institution in the process of transitioning from OPD to LPD and then to RPD, which introduced bias associated with the transition of surgical indications; therefore, the results need to be confirmed in prospective clinical trials. Second, all LPD and RPD procedures were performed by a single experienced hepatobiliary and pancreatic surgeon, and the effects of the learning curve could not be evaluated. A comparative analysis of OPD, LPD, and RPD conducted at a single center revealed that RPD offers significant benefits over both OPD and LPD. This study highlights the evolving role of robotic surgery in PD, a complex pancreatic procedure, and emphasizes the potential of RPD in improving patient care during pancreatic surgery.
Conception and design of work : Naohisa Kuriyama, Masashi Kishiwada, and Shugo Mizuno. Acquisition of data : Naohisa Kuriyama, Takehiro Fujii, Benson Kaluba, Tatsuya Sakamoto, Haruna Komatsubara, Daisuke Noguchi, Takahiro Ito, Aoi Hayasaki, Yusuke Iizawa, Yasuhiro Murata, and Akihiro Tanemura.
This study was not supported by any external funding source.
The authors declare no conflicts of interest.
|
Effects on lymph node size, staging and primary tumor histology on diagnostic accuracy of axillary lymph node aspirate of breast cancers | 2c486bc2-37ac-4b8c-8fd0-afc8a5390785 | 11785652 | Surgical Procedures, Operative[mh] | In the assessment of axillary lymph node status for breast cancers, fine-needle aspiration cytology is the preferred diagnostic modality with a low cost and minimal risk of complications . Although it has been widely accepted that lymph node aspiration cytology, for detection of metastasis, is highly specific with slight limitations on sensitivity , the application of aspiration cytology for breast cancer metastasis is different. Clinical, radiological and histopathological findings of the lymph node and primary tumor are usually available before aspiration is performed, unlike in the assessment of lymphadenopathies of unknown nature . In this study, a large cohort of axillary lymph node aspirates in pre-operative assessment for breast cancer patients were reviewed for lymph node and histopathological parameters affecting the adequacy rate and accuracy of cytologic diagnosis.
Computerized searches of the three involved institutions for axillary node fine-needle aspirate cytology specimens were performed (Alice Ho Miu Ling Nethersole Hospital and North District Hospital: from the year 2000 to 2022; Prince of Wales Hospital from the year 1997 to 2022). Cytologic diagnoses were reclassified into a five-tiered system—inadequate/unsatisfactory (C1), benign (C2), atypia (C3), suspicious for malignancy (C4) and malignant (C5). Case notes and pathology reports of each patient was reviewed, and those with corresponding sentinel lymph node core or excision biopsy and/or axillary lymph node dissection performed were included (Fig. ). Radiology reports, pathology reports and clinical notes were reviewed in sequence for the greatest diameter of the target lymph node (i.e., clinical dimensions taken when radiological and pathological sizing were not present). Histological parameters of the primary breast tumor, including histological type, histological grade and presence of in situ components were recorded from corresponding breast biopsy and/or surgical excision reports. Case notes, cytology reports and/or slides with a false positive result (no histologic evidence of lymph node metastasis but a cytologic diagnosis of C3, C4 or C5) were further reviewed for possible causes including but not limited to interval neoadjuvant treatment, other neoplasms involving the axilla and cytologic interpretation. Statistical analysis was performed using SPSS (version 26.0). The chi-squared test and t-test were used to compare lymph node parameters including the size of the targeted lymph node, number of positive and total number of lymph nodes excised, and histological parameters of the primary tumor. Comparisons were made between inadequate (C1) and adequate (C2-C5) specimens, and between concordant and discordant cases at binary cutoffs considering atypia or higher-grade cytologic diagnoses (C3 +) or suspicious or higher-grade cytologic diagnoses (C4 +) as positive and excluding C1 specimens. A p -value of < 0.05 was considered as significant. The study was approved by The Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee.
A total of 1361 fine-needle aspiration cytology specimens were included, with 697 from the left and 664 from the right axilla. The primary breast tumor was invasive ductal carcinoma (invasive breast carcinoma, no special type) ( n = 1094/1361 80.38%), followed by ductal carcinoma in situ ( n = 68/1361, 5.00%) and invasive lobular carcinoma ( n = 43/1361, 3.16%) (Table ). The risk of malignancy for the C1 to C5 categories were 53.39%, 27.45%, 70.97%, 83.33% and 88.00%, increasing to 75.86%, 94.59% and 99.28% for the C3, C4 and C5 categories when cases with neoadjuvant therapy were excluded (Table ). Comparison of inadequate and adequate specimens demonstrated that the greatest diameter of the target lymph node (i.e., size) ( p < 0.001) and the histologic grade ( p = 0.003) of the primary tumor were positively correlated with an adequate cytologic diagnosis. The presence of an in situ component in the primary breast tumor showed a trend towards an inadequate cytologic diagnosis ( p = 0.069). The number of positive lymph nodes, total number of lymph nodes, percentage of positive nodes and surrogate molecular subtype did not correlate with specimen adequacy ( p > 0.05) (Table ). The greatest diameter of the target lymph node remained a strong predictor of concordance in two cytologic diagnosis categorical cut-offs, with a p-value of less than 0.001. A higher percentage of involved lymph node ( p = 0.006) and HER2 overexpressed breast cancers ( p = 0.027) were associated greater concordance rates, considering C4 and C5 as a positive diagnostic result. Other parameters compared did not show statistical significance, and except for lymph node diameter, no other parameter was significantly correlated with concordance when cytologic diagnoses of C3 or above were taken as positive (Table ). The concordance rates for cases with at least one positive lymph node compared to all lymph nodes negative were lower (C3 + : 82.11% vs. 94.76%; C4 + : 76.63% vs. 98.43%). However, the difference in concordance rates were reversed at higher cut-offs. Aspirates in cases with at least 4 or more (and at least 10 or more) positive lymph nodes were more likely to be concordant ( p = 0.009–< 0.001), with differences in concordance rates at 8.27% to 12.37%. As for the greatest diameter of the target lymph node, a greater diameter was associated with higher concordance rates consistently, with significant differences at cut-offs of ≥ 5 mm ( p = 0.001 and p = 0.006) and ≥ 10 mm (p < 0.001) and statistical trends at ≥ 20 mm ( p = 0.090 and p = 0.051) (Table ).
Axillary lymph node metastasis is a strong prognostic indicator in breast cancer . The treatment options are axillary lymph node dissection, radiotherapy and/or combinations with other systemic therapy . Axillary recurrence is associated with significant morbidity and mortality , with nearly half of the patients further developing distant metastases . On the other hand, axillary dissection and regional radiotherapy are associated with risks of functional morbidities such as lymphedema, paresthesia and other forms of impairment . Both overtreatment and undertreatment should be avoided. Accurate pre-operative diagnosis is necessary in preventing inadequate treatment. The triple assessment also applies to the axilla . Fine-needle aspiration is highly suited for breast and axillary lymph node biopsy . With the superficial and palpable location of the axillary nodes, the need of puncture in multiple directions to adequately sample a lymph node, and a relatively favorable cost and complication profile of fine-needle aspiration over core biopsy , axillary lymph node aspiration is often used in primary tissue diagnosis for axillary nodal status. Despite extensive literature highlighting the specificity of axillary lymph node aspiration cytology , two caveats must be addressed – the diagnostic accuracy of cytology depends on how the diagnostic categories are attributed (in particular the atypia group) , and cytology results are not interpreted in isolation but with clinical and radiological findings. In this study, the histologic correlation of axillary lymph node aspiration from a cohort including multiple centers and collected through an extended period, were reviewed in correlation with clinical and radiological parameters to detail the diagnostic performance and possible effects of clinical and radiological features. In line with the literature, the sensitivity of axillary lymph node aspiration cytology was modest, with a 27.45% ROM, equivalent to the false negative rate . The ROMs of the C3 to C5 categories were initially slightly low, ranging from 70% to less than 90%, but when cases with neoadjuvant therapy were excluded, the ROMs of C4 and C5 categories improved to 94.50% and 99.28%. There were 16, 2, and 4 false positives in the C3, C4 and C5 categories, respectively. Review of the cases found one with primary sarcoma involving the axillary region, and one case with ductal carcinoma in situ involving the axillary tail, without invasion nor lymph node involvement. The remaining 18 were all attributed to interpretative errors (Table ). Inadequate aspiration necessitates repeat biopsy and leads to delay in management and increased resources consumption . It should be noted that the risk of malignancy for inadequate specimens is significantly higher than C2 and cannot be considered as a “provisionally” benign diagnosis. There were also 68 cases of ductal carcinoma in situ included for analysis, of which 10 had histologic evidence of lymph node metastasis. Ductal carcinoma in situ with metastasis is a well reported phenomenon that is largely attributed to sampling error and minute undetected or undetectable invasive foci , as such the cases were included for analysis. Two inadequate diagnosis that had positive lymph node histology were also present in the group of ductal carcinoma in situ, indicating that even in low-risk cases, inadequate aspirates necessitate further workup. Excisional or sentinel node biopsy may be preferable when pre-operative diagnostic yield is expected to be low, such as in cases of classical lobular carcinoma . Low-grade histology and small lymph node size were associated with an increased inadequacy rate in the current cohort. Omission of substitution of fine-needle aspiration by other biopsy modalities such be considered for these cases. Of note, only the size of the target, node demonstrated correlation, whereas the total number of positive nodes does not affect adequacy rate, suggesting that targeting the largest node is necessary even when there are multiple suspicious lymph nodes. The limitations of the study includes the heterogeneity of cases over a long collection period, with different clinical guidelines and protocols adopted, and its retrospective design. Clinically and radiologically low-risk cases, particularly those with benign or inadequate aspirates, may not be subjected to further axillary lymph node dissection or even core or excisional biopsy. On the other hand, patients with advanced disease also may not be treated surgically and thus not captured in the cohort. The requirement of histological correlation skewed the composition of breast cancer cases and would not match the composition histological or molecular typing in the breast cancers of the general population. As for clinical and radiological parameters affecting the diagnostic performance of lymph node aspiration, lymph node size was identified as a consistent predictor of concordance regardless of cut-off adopted in cytologic diagnostic category. Cases with higher percentage of involved lymph node and HER2 overexpressed breast cancers showed higher concordance at the C4 or above cut-off but not for C3 or above. Further analysis pertaining to these significant parameters showed that for size, lymph nodes with greatest dimension of greater or equal to 5 mm and 10 mm statistically significantly improved diagnostic accuracy, and a trend was observed for the cut-off at least 20 mm. The concordance rate also increased with the number of positive nodes, reaching statistical significance at the threshold of greater or equal to 4 positive nodes. These figures can serve as a reference in deciding whether fine-needle aspiration should be proceeded, or in cases where there is discrepancy between cytologic diagnosis, clinical impression and radiological findings, further investigation is needed for clarification.
Fine-needle aspiration is specific but suffers from a lower sensitivity in detecting lymph node metastasis. As such, it is critical that clinical and radiological findings be examined together with cytologic results. Smaller lymph nodes are more likely to be non-informative on aspiration cytology, irrespective of whether other suspicious lymph nodes are present, or if the primary lesion if of a high histologic grade. In axillae with less than 4 suspicious lymph nodes and/or a target lymph node of less than 5–10 mm, the diagnostic accuracy of axillary lymph node aspiration decreases and should be interpreted with caution.
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Human exposure to air contaminants under the far-UVC system operation in an office: effects of lamp position and ventilation condition | ed888ed0-a3fd-4b2a-a6fe-8b8768a5ccf7 | 11489401 | Microbiology[mh] | The germicidal ultraviolet (GUV) system is a prominent solution for effectively controlling airborne pathogens. Traditionally, ultraviolet C (UVC) at 254 nm has been used to irradiate the upper part of rooms, primarily due to its known adverse effects on human skin cells – . In recent times, there has been a growing preference for utilizing shorter wavelengths, known as far-UVC, which involves KrCl excimer lamps emitting UVC at a peak wavelength of 222 nm , . Far-UVC has demonstrated the capability to inactivate airborne pathogens by degrading their genetic material and impeding their reproductive capacity – . Notably, its minimal impact on human tissues positions it as a viable method for comprehensive indoor disinfection , , . However, concerns have been raised regarding the potential of the far-UVC system to act as an indoor O 3 source – . The photolysis of O 2 by the wavelength range of 175–242 nm, inherent to this system, results in O 3 generation. O 3 itself poses risks and initiates indoor chemical reactions, leading to the formation of air pollutants such as oxidants and secondary organic aerosols (SOA) , – . The market offers various configurations of far-UVC lamps, including ceiling-mounted, wall-mounted, and stand-alone types. Given UV intensity is high near the lamp but decreases rapidly with distance, the positioning of the far-UVC lamp significantly affects the distribution of UV intensity within an indoor space , , . This distribution could not only impact the removal efficiency of pathogens but also influence the rate constant of O 2 photolysis by UVC at 222 nm , . Therefore, the placement of the far-UVC system is intricately linked to human exposure to airborne pathogens and secondary contaminants. Based on this background, our study investigates detailed airborne pathogen disinfection and indoor O 3 chemistry associated with far-UVC system in an office environment, using computational fluid dynamics (CFD) simulations. By examining impacts of six different positions of the far-UVC lamp irradiating occupants with four ventilation conditions, our investigation elucidates the implications of far-UVC lamps for human exposure to airborne pathogens and secondary contaminants.
CFD model description To analyze the disinfection of airborne pathogens and the formation of secondary contaminant associated with the far-UVC system operation, we carried out the CFD simulation using the commercial solver STAR-CCM+ (version 2021.03) . In the CFD model, airborne pathogen and chemical reactions were simulated simultaneously. The Eulerian model was employed to simulate airborne pathogens, whereas the multi-component gas model was utilized for modeling chemical reactions. The incompressible ideal gas model was applied to solve buoyancy-driven convection flow near occupants. We created the simulation domain with dimensions of 7.0 m × 5.8 m × 3.1 m (length × width × height) and included four occupants (see Fig. ) based on the experimental setup outlined by Liu et al. . Airborne pathogens are released through coughing, talking, and breathing . Considering the worst-case scenario where an infector is talking continuously, we simulated the talking mode for one hour, as it aligns with the typical maximum duration of staying focused and results in the highest cumulative emission . Preliminary analysis indicated that the highest airborne pathogen concentration occurred when the occupant 4 (P4) was infected and speaking (see Figure S7), we designated P4 as a constant source of airborne pathogens. Thus, P4 was designated as a constant source of airborne pathogens, emitting from a 1.2 cm 2 mouth opening with at a horizontal air speed of 4 m·s −1 – . Our study focused specifically on 1 μm with a density of 1000 kg·m −3 , as this size is predominant during talking, and particles in the 1–4 μm range exhibit similar behavior in the air , , . The emission concentration was maintained at 1 µg·m 3 . Airborne pathogens were removed by ventilation and deposition onto the floor, with a deposition velocity of 0.003 cm·s −1 . The susceptibility constant of airborne pathogens to UVC at 222 nm was set to 1.4 × 10 −3 cm 2 ·µW −1 ·s −1 , simulating SARS-CoV-2 . Each occupant generates a metabolic heat of 99 W in seating mode . Under these conditions, the disinfection of airborne pathogen was modeled as the first order decay rate in the CFD model, based on the survival rate of pathogens (Eq. ) – . 1 [12pt]{minimal}
$$\:Survival\:rate=\:{10}^{-kIt}$$ Where, [12pt]{minimal}
$$\:k$$ is the susceptibility constant of airborne pathogens (cm 2 ·µW −1 ·s −1 ), [12pt]{minimal}
$$\:I$$ is the UV fluence rate (µW· cm −2 ), and [12pt]{minimal}
$$\:t$$ is time (s). Chemistry modeling Chemical reactions associated with far-UVC system were modeled based on Barber et al. , incorporating a total of 12 chemical reactions in the CFD simulation (see Table S2). In the simulation of chemical reactions, we assumed that there was no indoor O 3 source and no UV radiation through windows. The outdoor O 3 concentration was set to 40 ppb, typical for urban environments . Indoor O 3 was removed from room surfaces at a deposition rate of 2.8 h −1 and from human surfaces at a deposition velocity of 6.8 m·h −1 . VOCs emissions from indoor surfaces and occupants were set at 150 µg·m −2 ·h −1 and 1 µg·s −1 ·person −1 , respectively, based on typical indoor conditions , . The simulations assumed atmospheric conditions of 1 atm pressure, 35–40% relative humidity, and a temperature of 25 °C, reflecting indoor environments at sea level , . Further details on boundary conditions and the CFD simulation setup are provided in Sections S1 and S2 of the Supporting Information. Spatial distribution of UV fluence rate To investigate the effect of the far-UVC lamp position relative to the occupant area, we modeled six different positions (Fig. ): ceiling-mounted type, wall-mounted type, and stand-alone type 1–4. The ceiling-mounted far-UVC lamp emits a 120-degree beam, while other types produce a beam in all directions. The power of each lamp was adjusted to achieve a room average UV fluence rate of 3 µW·cm −2 – (see Fig. S8), with spatial distributions of UV fluence rates obtained using the Visual Software . The average UV fluence rate within the human envelope zone for all lamp types remained below 1.1 µW·cm −2 , in compliance with the eye exposure limit standards set by the American Conference of Governmental Industrial Hygienists (ACGIH) eye limit (0.3–1.5 µW·cm −2 ) . Note that the human envelope zone is defined as a 0.8 m 3 box air volume near the human body (see Fig. S9) . We also assumed that the UV fluence rate and susceptibility of pathogens to UV were unaffected by environmental conditions, ensuring that both the disinfection performance and the rate constant of chemical reactions remained constant over time. Parametric analysis Along with evaluating six lamp positions, four distinct ventilation conditions were examined: mixing ventilation at rates of 0.7 h −1 , 2 h −1 , and 4 h −1 , and infiltration at a rate of 0.7 h −1 . Note that the 0.7 h −1 is the minimum requirements by ASHRAE , and 4 h −1 is considered good according to The Lancet COVID-19 commission . To enhance the credibility of our CFD model, we conducted a thorough validation and substantiation of our CFD model to assess its accuracy in predicting airborne transmission and indoor chemical reactions. This involved validating the airflow field, particle transport within a room, time-series airborne pathogen concentrations, O 3 generation by indoor chemical reactions, and O 3 deposition. Validation was achieved by comparing CFD results with experimental data and a well-mixed mass balance model. Further details on the CFD model validation and substantiation are provided in Sect. S3. To analyze human exposure related to the inhalation of airborne pathogens, we examined “intake faction” within the ASHRAE breathing zone and the human breathing box over a one-hour period (Eq. ) . Note that the ASHRAE breathing zone is defined as the air volume extending from 8 cm to 180 cm above 60 cm away from walls , and the human breathing box is defined as a 500 cm 3 air volume below the nose tip . 2 [12pt]{minimal}
$$\:Intake\:fraction=\:_{0}^{T}{Q}_{b}C(t)dt}{{\:}_{0}^{T}E(t)dt}$$ Where, [12pt]{minimal}
$$\:{Q}_{b}$$ is the breathing flow rate of occupants (rest mode − 0.6 m 3 ·h −1 ) , [12pt]{minimal}
$$\:C(t)$$ is the contaminant concentration, [12pt]{minimal}
$$\:E(t)$$ is the emission rate, and [12pt]{minimal}
$$\:T$$ is the total emission time. Similarly, we presented the results of O 3 , OH, and products as a one-hour integrated exposure within the ASHRAE breathing zone and the human breathing box (Eq. ). 3 [12pt]{minimal}
$$\:Exposure=\:{\:}_{0}^{T}tC(t)dt$$
To analyze the disinfection of airborne pathogens and the formation of secondary contaminant associated with the far-UVC system operation, we carried out the CFD simulation using the commercial solver STAR-CCM+ (version 2021.03) . In the CFD model, airborne pathogen and chemical reactions were simulated simultaneously. The Eulerian model was employed to simulate airborne pathogens, whereas the multi-component gas model was utilized for modeling chemical reactions. The incompressible ideal gas model was applied to solve buoyancy-driven convection flow near occupants. We created the simulation domain with dimensions of 7.0 m × 5.8 m × 3.1 m (length × width × height) and included four occupants (see Fig. ) based on the experimental setup outlined by Liu et al. . Airborne pathogens are released through coughing, talking, and breathing . Considering the worst-case scenario where an infector is talking continuously, we simulated the talking mode for one hour, as it aligns with the typical maximum duration of staying focused and results in the highest cumulative emission . Preliminary analysis indicated that the highest airborne pathogen concentration occurred when the occupant 4 (P4) was infected and speaking (see Figure S7), we designated P4 as a constant source of airborne pathogens. Thus, P4 was designated as a constant source of airborne pathogens, emitting from a 1.2 cm 2 mouth opening with at a horizontal air speed of 4 m·s −1 – . Our study focused specifically on 1 μm with a density of 1000 kg·m −3 , as this size is predominant during talking, and particles in the 1–4 μm range exhibit similar behavior in the air , , . The emission concentration was maintained at 1 µg·m 3 . Airborne pathogens were removed by ventilation and deposition onto the floor, with a deposition velocity of 0.003 cm·s −1 . The susceptibility constant of airborne pathogens to UVC at 222 nm was set to 1.4 × 10 −3 cm 2 ·µW −1 ·s −1 , simulating SARS-CoV-2 . Each occupant generates a metabolic heat of 99 W in seating mode . Under these conditions, the disinfection of airborne pathogen was modeled as the first order decay rate in the CFD model, based on the survival rate of pathogens (Eq. ) – . 1 [12pt]{minimal}
$$\:Survival\:rate=\:{10}^{-kIt}$$ Where, [12pt]{minimal}
$$\:k$$ is the susceptibility constant of airborne pathogens (cm 2 ·µW −1 ·s −1 ), [12pt]{minimal}
$$\:I$$ is the UV fluence rate (µW· cm −2 ), and [12pt]{minimal}
$$\:t$$ is time (s).
Chemical reactions associated with far-UVC system were modeled based on Barber et al. , incorporating a total of 12 chemical reactions in the CFD simulation (see Table S2). In the simulation of chemical reactions, we assumed that there was no indoor O 3 source and no UV radiation through windows. The outdoor O 3 concentration was set to 40 ppb, typical for urban environments . Indoor O 3 was removed from room surfaces at a deposition rate of 2.8 h −1 and from human surfaces at a deposition velocity of 6.8 m·h −1 . VOCs emissions from indoor surfaces and occupants were set at 150 µg·m −2 ·h −1 and 1 µg·s −1 ·person −1 , respectively, based on typical indoor conditions , . The simulations assumed atmospheric conditions of 1 atm pressure, 35–40% relative humidity, and a temperature of 25 °C, reflecting indoor environments at sea level , . Further details on boundary conditions and the CFD simulation setup are provided in Sections S1 and S2 of the Supporting Information.
To investigate the effect of the far-UVC lamp position relative to the occupant area, we modeled six different positions (Fig. ): ceiling-mounted type, wall-mounted type, and stand-alone type 1–4. The ceiling-mounted far-UVC lamp emits a 120-degree beam, while other types produce a beam in all directions. The power of each lamp was adjusted to achieve a room average UV fluence rate of 3 µW·cm −2 – (see Fig. S8), with spatial distributions of UV fluence rates obtained using the Visual Software . The average UV fluence rate within the human envelope zone for all lamp types remained below 1.1 µW·cm −2 , in compliance with the eye exposure limit standards set by the American Conference of Governmental Industrial Hygienists (ACGIH) eye limit (0.3–1.5 µW·cm −2 ) . Note that the human envelope zone is defined as a 0.8 m 3 box air volume near the human body (see Fig. S9) . We also assumed that the UV fluence rate and susceptibility of pathogens to UV were unaffected by environmental conditions, ensuring that both the disinfection performance and the rate constant of chemical reactions remained constant over time.
Along with evaluating six lamp positions, four distinct ventilation conditions were examined: mixing ventilation at rates of 0.7 h −1 , 2 h −1 , and 4 h −1 , and infiltration at a rate of 0.7 h −1 . Note that the 0.7 h −1 is the minimum requirements by ASHRAE , and 4 h −1 is considered good according to The Lancet COVID-19 commission . To enhance the credibility of our CFD model, we conducted a thorough validation and substantiation of our CFD model to assess its accuracy in predicting airborne transmission and indoor chemical reactions. This involved validating the airflow field, particle transport within a room, time-series airborne pathogen concentrations, O 3 generation by indoor chemical reactions, and O 3 deposition. Validation was achieved by comparing CFD results with experimental data and a well-mixed mass balance model. Further details on the CFD model validation and substantiation are provided in Sect. S3. To analyze human exposure related to the inhalation of airborne pathogens, we examined “intake faction” within the ASHRAE breathing zone and the human breathing box over a one-hour period (Eq. ) . Note that the ASHRAE breathing zone is defined as the air volume extending from 8 cm to 180 cm above 60 cm away from walls , and the human breathing box is defined as a 500 cm 3 air volume below the nose tip . 2 [12pt]{minimal}
$$\:Intake\:fraction=\:_{0}^{T}{Q}_{b}C(t)dt}{{\:}_{0}^{T}E(t)dt}$$ Where, [12pt]{minimal}
$$\:{Q}_{b}$$ is the breathing flow rate of occupants (rest mode − 0.6 m 3 ·h −1 ) , [12pt]{minimal}
$$\:C(t)$$ is the contaminant concentration, [12pt]{minimal}
$$\:E(t)$$ is the emission rate, and [12pt]{minimal}
$$\:T$$ is the total emission time. Similarly, we presented the results of O 3 , OH, and products as a one-hour integrated exposure within the ASHRAE breathing zone and the human breathing box (Eq. ). 3 [12pt]{minimal}
$$\:Exposure=\:{\:}_{0}^{T}tC(t)dt$$
Airborne pathogen transmission Figure illustrates the time-series airborne pathogen concentration within the ASHRAE breathing zone over one hour under four different ventilation conditions. Additional details on airborne pathogen distributions at one-hour are provided in Figs. S10 and S11. Far-UVC systems demonstrate a reduction in airborne pathogen concentration by 50–85% compared to scenarios without far-UVC. The ceiling-mounted type is the most effective, consistently showing the lowest concentration for all ventilation conditions. The effectiveness of stand-alone types varies with their position and ventilation conditions. For example, type 1 (closest to the infector) consistently achieves the highest reduction under mixing ventilation, while under infiltration, types 3 (3 m away from the infector) results in the lowest concentration among stand-alone types. Figure illustrates the intake fraction over one hour. Far-UVC systems reduce the intake fraction by approximately 40–80% compared to scenarios without far-UVC. Although stand-alone types exhibit a higher UV fluence rate within the breathing zone (see Fig. S8), the ceiling-mounted type shows a more pronounced reduction effect, up to 80% across all types. Specifically, at a ventilation rate of 0.7 h −1 , the ceiling-mounted type lowers the intake fraction from 2.12 to 0.46 under mixing ventilation and from 2.24 to 0.63 under the infiltration condition. This greater effectiveness is primarily due to airborne pathogens emitted from an infector tending to rise with the room airflow, reaching the upper region near a ceiling-mounted UVC lamp (Fig. S12). In addition to the far-UVC lamp position, ventilation conditions play a crucial role in determining human exposure to airborne pathogens. Increased ventilation not only dilutes airborne pathogens but also influences pathogen transport near occupants, as reflected by the intake fraction within the breathing box. At a ventilation rate of 0.7 h −1 under mixing ventilation, P1 (facing the infector, P4) is exposed to airborne pathogens at more than twice the level of P2 and P3 (see Fig. a). Under infiltration conditions, the intake fraction within the breathing box for P1 can be up to nine times higher than for P2 and P3 (see Fig. d). This is primarily due to the reduced air mixing effect under infiltration, which allows the air jet emitted from the infector’s mouth to travel a longer distance toward the occupant directly in front of the infector , , . On the other hand, at ventilation rates of 2 h −1 and 4 h −1 , the increased air mixing results in more uniform exposure to airborne pathogens among all occupants (see Fig. b and c). This finding suggests that higher ventilation rates can help reduce human exposure to airborne pathogens. Exposure to secondary contaminants Figure illustrates one-hour human exposure to O 3 within the ASHRAE breathing zone under four different ventilation conditions. Due to the O 3 deposition on indoor and human surfaces, the breathing zone O 3 concentration is 40–60% lower than the outdoor concentration (40 ppb) when the far-UVC system is not in operation, consistent with a previous study . The calculated O 3 generation rate for all far-UVC types, based on the well-mixed mass balance model , is 7.0 (± 1.5) ppb·h −1 ·(µW·cm −2 ) −1 , aligning with findings from previous studies – . During one hour of the far-UVC system operation, the breathing zone O 3 concentration increases by 4–6 ppb compared to scenarios without far-UVC. This impact is more pronounced at lower ventilation rates (see Fig. ). For instance, at a ventilation rate of 0.7 h −1 , far-UVC operation increases O 3 concentration by 40–60%. However, as the ventilation rate increases to 2 h −1 and 4 h −1 , indoor O 3 concentration without the far-UVC system is 20–25 ppb due to higher ventilation bringing more outdoor O 3 indoors. Consequently, the impact of the far-UVC system operation on indoor O 3 concentration becomes less noticeable with increased ventilation. Figure depicts the one-hour exposure to O 3 . Unlike airborne pathogens, all occupants experience a similar level of O 3 across different far-UVC types. However, it is important to note that a zone with relatively high O 3 concentration is created in the vicinity of the far-UVC lamp when it is turned on (> 25 ppb) (Figs. S13–S16). As a result, positioning the far-UVC lamp near occupants is likely to increase human exposure to O 3 and secondary contaminants , . The OH concentration mirrors the pattern observed for O 3 , with a relatively higher concentration near the far-UVC lamp. This trend is because the primary reaction generating OH is the reaction of O 3 with VOCs (see Figs. S17–S19). As the ventilation rate increases from 0.7 h −1 to 2 h −1 , the breathing zone OH concentration rises due to the increased introduction of O 3 indoors. However, at a ventilation rate of 4 h −1 , the OH concentration decreases from 4.5 [12pt]{minimal}
$$\:\:$$ 10 5 to 3 [12pt]{minimal}
$$\:\:$$ 10 5 molec·cm −3 after one hour, owing to the enhanced removal facilitated by ventilation (see Fig. S20). In contrast, reaction products show a well-mixed distribution regardless of the far-UVC lamp’s position (see Fig. ). Moreover, the ventilation condition is important in reducing human exposure to products; increasing ventilation rate from 0.7 h −1 to 4 h −1 decreases the breathing zone product concentrations by 90% (see Fig. ). Also, the upward airflow pattern created by the buoyancy-driven convective thermal plume under infiltration results in a product concentration within the breathing zone about 20% lower than a well-mixed airflow (see Figs. , ) , . Implications Our findings suggest that the ceiling-mounted far-UVC type is most effective at reducing airborne pathogen concentration in a small, occupied office. Moreover, this configuration may be considered safer than stand-alone types, which have the potential to create a high O 3 concentration near the occupants. We anticipate that this trend likely extends to highly occupied environments for the following reasons: First, the position and number of infectors are random, making it challenging to position far-UVC lamps in the path of airborne pathogens. Second, airborne pathogens emitted by infectors tend to rise due to occupant thermal plumes and remain suspended in the air , , . Therefore, efficient disinfection can be achieved when a high UV fluence rate is directed above occupants by the ceiling-mounted type far-UVC lamp. Ventilation also plays an important role in removing airborne pathogens as well as secondary contaminants associated with the far-UVC operation. Increasing the amount of fresh air indoors is essential for reducing human exposure to harmful air contaminants. However, it should be noted that in regions where outdoor O 3 concentration is high (> 40 ppb), the O 3 treatment is necessary to mitigate its adverse health impacts. Limitations Some limitations should be noted. First, this study modeled the transport and disinfection of airborne pathogens with a fixed particle size of 1 μm, without considering particle size distribution. Second, the effects of evaporation of exhaled droplets were not simulated because they are negligible for the continuous phase and droplets less than 80 μm, which evaporate almost immediately after emission , . Third, the spatial UV fluence rate was derived from the lighting simulation that was developed based on the experimental data. Lastly, the chemistry modeling included twelve major chemical reactions without encompassing comprehensive chemical reactions, such as O 3 and OH reaction with human skin oil. Future studies are warranted to address these limitations by validating UV fluence rate distributions and considering a broader range of chemical reactions.
Figure illustrates the time-series airborne pathogen concentration within the ASHRAE breathing zone over one hour under four different ventilation conditions. Additional details on airborne pathogen distributions at one-hour are provided in Figs. S10 and S11. Far-UVC systems demonstrate a reduction in airborne pathogen concentration by 50–85% compared to scenarios without far-UVC. The ceiling-mounted type is the most effective, consistently showing the lowest concentration for all ventilation conditions. The effectiveness of stand-alone types varies with their position and ventilation conditions. For example, type 1 (closest to the infector) consistently achieves the highest reduction under mixing ventilation, while under infiltration, types 3 (3 m away from the infector) results in the lowest concentration among stand-alone types. Figure illustrates the intake fraction over one hour. Far-UVC systems reduce the intake fraction by approximately 40–80% compared to scenarios without far-UVC. Although stand-alone types exhibit a higher UV fluence rate within the breathing zone (see Fig. S8), the ceiling-mounted type shows a more pronounced reduction effect, up to 80% across all types. Specifically, at a ventilation rate of 0.7 h −1 , the ceiling-mounted type lowers the intake fraction from 2.12 to 0.46 under mixing ventilation and from 2.24 to 0.63 under the infiltration condition. This greater effectiveness is primarily due to airborne pathogens emitted from an infector tending to rise with the room airflow, reaching the upper region near a ceiling-mounted UVC lamp (Fig. S12). In addition to the far-UVC lamp position, ventilation conditions play a crucial role in determining human exposure to airborne pathogens. Increased ventilation not only dilutes airborne pathogens but also influences pathogen transport near occupants, as reflected by the intake fraction within the breathing box. At a ventilation rate of 0.7 h −1 under mixing ventilation, P1 (facing the infector, P4) is exposed to airborne pathogens at more than twice the level of P2 and P3 (see Fig. a). Under infiltration conditions, the intake fraction within the breathing box for P1 can be up to nine times higher than for P2 and P3 (see Fig. d). This is primarily due to the reduced air mixing effect under infiltration, which allows the air jet emitted from the infector’s mouth to travel a longer distance toward the occupant directly in front of the infector , , . On the other hand, at ventilation rates of 2 h −1 and 4 h −1 , the increased air mixing results in more uniform exposure to airborne pathogens among all occupants (see Fig. b and c). This finding suggests that higher ventilation rates can help reduce human exposure to airborne pathogens.
Figure illustrates one-hour human exposure to O 3 within the ASHRAE breathing zone under four different ventilation conditions. Due to the O 3 deposition on indoor and human surfaces, the breathing zone O 3 concentration is 40–60% lower than the outdoor concentration (40 ppb) when the far-UVC system is not in operation, consistent with a previous study . The calculated O 3 generation rate for all far-UVC types, based on the well-mixed mass balance model , is 7.0 (± 1.5) ppb·h −1 ·(µW·cm −2 ) −1 , aligning with findings from previous studies – . During one hour of the far-UVC system operation, the breathing zone O 3 concentration increases by 4–6 ppb compared to scenarios without far-UVC. This impact is more pronounced at lower ventilation rates (see Fig. ). For instance, at a ventilation rate of 0.7 h −1 , far-UVC operation increases O 3 concentration by 40–60%. However, as the ventilation rate increases to 2 h −1 and 4 h −1 , indoor O 3 concentration without the far-UVC system is 20–25 ppb due to higher ventilation bringing more outdoor O 3 indoors. Consequently, the impact of the far-UVC system operation on indoor O 3 concentration becomes less noticeable with increased ventilation. Figure depicts the one-hour exposure to O 3 . Unlike airborne pathogens, all occupants experience a similar level of O 3 across different far-UVC types. However, it is important to note that a zone with relatively high O 3 concentration is created in the vicinity of the far-UVC lamp when it is turned on (> 25 ppb) (Figs. S13–S16). As a result, positioning the far-UVC lamp near occupants is likely to increase human exposure to O 3 and secondary contaminants , . The OH concentration mirrors the pattern observed for O 3 , with a relatively higher concentration near the far-UVC lamp. This trend is because the primary reaction generating OH is the reaction of O 3 with VOCs (see Figs. S17–S19). As the ventilation rate increases from 0.7 h −1 to 2 h −1 , the breathing zone OH concentration rises due to the increased introduction of O 3 indoors. However, at a ventilation rate of 4 h −1 , the OH concentration decreases from 4.5 [12pt]{minimal}
$$\:\:$$ 10 5 to 3 [12pt]{minimal}
$$\:\:$$ 10 5 molec·cm −3 after one hour, owing to the enhanced removal facilitated by ventilation (see Fig. S20). In contrast, reaction products show a well-mixed distribution regardless of the far-UVC lamp’s position (see Fig. ). Moreover, the ventilation condition is important in reducing human exposure to products; increasing ventilation rate from 0.7 h −1 to 4 h −1 decreases the breathing zone product concentrations by 90% (see Fig. ). Also, the upward airflow pattern created by the buoyancy-driven convective thermal plume under infiltration results in a product concentration within the breathing zone about 20% lower than a well-mixed airflow (see Figs. , ) , .
Our findings suggest that the ceiling-mounted far-UVC type is most effective at reducing airborne pathogen concentration in a small, occupied office. Moreover, this configuration may be considered safer than stand-alone types, which have the potential to create a high O 3 concentration near the occupants. We anticipate that this trend likely extends to highly occupied environments for the following reasons: First, the position and number of infectors are random, making it challenging to position far-UVC lamps in the path of airborne pathogens. Second, airborne pathogens emitted by infectors tend to rise due to occupant thermal plumes and remain suspended in the air , , . Therefore, efficient disinfection can be achieved when a high UV fluence rate is directed above occupants by the ceiling-mounted type far-UVC lamp. Ventilation also plays an important role in removing airborne pathogens as well as secondary contaminants associated with the far-UVC operation. Increasing the amount of fresh air indoors is essential for reducing human exposure to harmful air contaminants. However, it should be noted that in regions where outdoor O 3 concentration is high (> 40 ppb), the O 3 treatment is necessary to mitigate its adverse health impacts.
Some limitations should be noted. First, this study modeled the transport and disinfection of airborne pathogens with a fixed particle size of 1 μm, without considering particle size distribution. Second, the effects of evaporation of exhaled droplets were not simulated because they are negligible for the continuous phase and droplets less than 80 μm, which evaporate almost immediately after emission , . Third, the spatial UV fluence rate was derived from the lighting simulation that was developed based on the experimental data. Lastly, the chemistry modeling included twelve major chemical reactions without encompassing comprehensive chemical reactions, such as O 3 and OH reaction with human skin oil. Future studies are warranted to address these limitations by validating UV fluence rate distributions and considering a broader range of chemical reactions.
Below is the link to the electronic supplementary material. Supplementary Material 1
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A Delphi-based needs assessment to identify and prioritise procedural skills through consensus for simulation-based learning in neurosurgery | 8527f058-f0ff-47e6-8929-7a2f99de5968 | 11871727 | Surgical Procedures, Operative[mh] | Modern neurosurgical trainees face significant challenges in acquiring the necessary technical competencies required at appropriate stages of their training . Factors such as contemporary patient safety expectations and governance , the fallout from COVID-19 , reduced operative exposure due to working hour restrictions , and fewer complex cases due to advances in alternative treatments contribute to this difficulty . As a result, many trainees experience reduced operative autonomy, particularly in the earlier years of training , which may delay their seamless progression to independent surgical practice. Given the importance of safe and effective surgery in achieving positive patient outcomes , this issue is a cause for concern. To address these challenges, she Joint Committee on Surgical Training (JCST) has emphasised the role of simulation-based education (SBE) in aiding the recovery of surgical training post COVID-19 . It is a useful tool for learning in neurosurgery, as it is an exceptionally demanding surgical specialty in technical terms, with shallow learning curves . Identifying key procedural skills for SBE—particularly in early to mid-training—can significantly impact surgical performance in the operating room . SBE can support the introduction of the competency versus time based neurosurgical curriculum rolled out by the intercollegiate surgical curriculum programme (ISCP) in recent years . Following Kern’s Six Step Approach to Curriculum Development, the first step in designing an SBE curriculum is a problem identification and general needs assessment . Other curricula have demonstrated the benefits of SBE, including enhanced understanding of surgical instruments, technology and equipment in a safe learning environment. The selection of skills for inclusion should be guided not only by the quality of simulation modalities , but also by their relevance to trainee needs. There are now many affordable, accessible training models and modalities (Fig. ) available for neurosurgical training, including porcine cadavers (Fig. ). Fresh frozen cadaveric tissue, although significantly more expensive, provide high fidelity. Ethical considerations must be observed to ensure the proper use of biological models, including obtaining review board approval and adhering to laboratory protocols, to guarantee that these modalities are utilised in a respectful and responsible manner during training. The primary focus should be on meeting learning objectives through effective SBE . To date, no consensus-driven assessment specific to neurosurgery has systematically prioritised skills for SBE training. To address this gap, this study aimed to develop a prioritised list of technical skills through multijurisdictional consensus with key opinion leaders (KOL) in Ireland and the United Kingdom (UK). The findings will inform the development of a technical skills framework for a neurosurgical simulation-based learning curriculum.
This study employed a modified Delphi method employing the Copenhagen Academy for Medical Education and Simulation (CAMES) Needs Assessment Formula (NAF), consisting of three iterative survey rounds, to reach consensus. This approach is well established and aligns with several comparable studies reported in the literature . The research and data synthesising process was overseen by a steering committee comprising five people: consultant neurosurgeons (DC, GZ), senior neurosurgical trainee (VH), director of simulation education (CC), and a surgical education researcher (AR). Participants KOLs in this study were recruited using a convenience and snowball sampling technique. They are defined as senior neurosurgical trainees in years 7 and 8 of an 8-year training programme, those in temporary consultant roles post-Certificate of Completion of Surgical Training (CCST) and full-time consultants in neurosurgery, all of whom are actively working in public practice. KOLs are registered with the following training bodies in the UK and Ireland: Royal College of Surgeons Edinburgh (RCSEd), Royal College of Surgeons England (RCSEng), and Royal College of Surgeons Ireland (RCSI), as having completed or are currently completing Fellowship of Royal College of Surgeons (FRCS) examinations. Multi-jurisdiction consensus was attainable as these training bodies collectively utilise the JCST curriculum . Furthermore, several studies report the management of various neurosurgical conditions in these jurisdictions jointly , which reinforces the general parallels in patient demographics and clinical practices. Intervention design The SurveyMonkey Enterprise version™ (Europe) was used to host the surveys, and information relevant to each survey was collated for distribution via the Quality Enhancement Office in RCSI. Surveys were subsequently distributed to participants via three gatekeepers: RCSI Neurosurgical Programme Administrator, British Neurosurgical Trainees’ Association (BNTA) and Society of British Neurological Surgeons (SBNS) relevant mailing lists. Surveys were distributed iteratively using 5-point nominal data scales to calculate responses. Particular questioning criteria applied to each domain. The data collection protocol was followed to ensure that all data was gathered accurately, completely, and systematically, minimizing the risk of errors or inconsistencies. Round 1: brainstorming and ranking of importance using NAF Two authors (AR, VH), extracted procedural competencies from all phases of neurosurgical training outlined in the ISCP curriculum. Further procedures were added and existing ones removed through participant brainstorming. In the first round, we utilised component A.1 of the CAMES-NAF formula “Doctors”, and requested participants to rank procedures based on the statement, "All neurosurgery trainees at the end of training certification should be competent to perform the following procedures at the level expected of a day-1 consultant," on a 5-point scale (Appendix 1). After thorough deliberation, the steering committee determined that procedures with a mean score of 2.95 or lower in this round would be excluded from subsequent rounds. This decision was made to reduce the burden of lengthy, repetitive surveys on participants and to allow them to focus more effectively on procedures that are critical for newly appointed neurosurgical consultants to demonstrate competence. Round 2. rating using NAF Results from the first round were aggregated, with procedures arising from round one redistributed to all participants in round two for the purpose of ranking each procedure's perceived “Frequency” and “Risk” (Appendix 1, components A.2 and A.3). In this case, frequency refers to the procedure’s prevalence, while risk refers to the patient's risk if a neurosurgical trainee with insufficient experience performs the procedure. The steering group was assigned to complete the last section of the CAMES-NAF survey, which sought to quantify the “Feasibility” of training neurosurgical doctors in these procedures in a simulation-based environment (Appendix 1, components B.1, B.2, B.3); specifically, the factors related to cost, availability, and suitability. A total score was obtained by calculating the means for each of the NAF's four domains (Doctors + Frequency + Risk + Feasibility). Each domain was given an equal weighting of 25%. A revised list of procedures was produced as a result, which could be sent to all participants for final prioritisation. Round 3. feasibility using NAF In the final round, participants were permitted to remove any procedures that they thought were inappropriate for simulation-based learning, merge and reorder the rankings of the procedures that remained. A 75% majority would determine that the results of this round were the final prioritised ranking list. In order to evaluate the measure of rank correlation between the NAF score in round two and the final majority decision from KOLs in round three, we performed a Pearson correlation (r) coefficient test. Statistical analysis was performed using Stata Version 17.0 (StataCorp, College Station, TX, USA). In general for absolute for absolute values of r, 0 – 0.19 is regarded as very weak, 0.2 – 0.39 as weak, 0.40 – 0.59 as moderate, 0.6 – 0.79 as strong and 0.8 – 1 as very strong correlation. A high correlation reflects a high degree of consensus.
KOLs in this study were recruited using a convenience and snowball sampling technique. They are defined as senior neurosurgical trainees in years 7 and 8 of an 8-year training programme, those in temporary consultant roles post-Certificate of Completion of Surgical Training (CCST) and full-time consultants in neurosurgery, all of whom are actively working in public practice. KOLs are registered with the following training bodies in the UK and Ireland: Royal College of Surgeons Edinburgh (RCSEd), Royal College of Surgeons England (RCSEng), and Royal College of Surgeons Ireland (RCSI), as having completed or are currently completing Fellowship of Royal College of Surgeons (FRCS) examinations. Multi-jurisdiction consensus was attainable as these training bodies collectively utilise the JCST curriculum . Furthermore, several studies report the management of various neurosurgical conditions in these jurisdictions jointly , which reinforces the general parallels in patient demographics and clinical practices.
The SurveyMonkey Enterprise version™ (Europe) was used to host the surveys, and information relevant to each survey was collated for distribution via the Quality Enhancement Office in RCSI. Surveys were subsequently distributed to participants via three gatekeepers: RCSI Neurosurgical Programme Administrator, British Neurosurgical Trainees’ Association (BNTA) and Society of British Neurological Surgeons (SBNS) relevant mailing lists. Surveys were distributed iteratively using 5-point nominal data scales to calculate responses. Particular questioning criteria applied to each domain. The data collection protocol was followed to ensure that all data was gathered accurately, completely, and systematically, minimizing the risk of errors or inconsistencies. Round 1: brainstorming and ranking of importance using NAF Two authors (AR, VH), extracted procedural competencies from all phases of neurosurgical training outlined in the ISCP curriculum. Further procedures were added and existing ones removed through participant brainstorming. In the first round, we utilised component A.1 of the CAMES-NAF formula “Doctors”, and requested participants to rank procedures based on the statement, "All neurosurgery trainees at the end of training certification should be competent to perform the following procedures at the level expected of a day-1 consultant," on a 5-point scale (Appendix 1). After thorough deliberation, the steering committee determined that procedures with a mean score of 2.95 or lower in this round would be excluded from subsequent rounds. This decision was made to reduce the burden of lengthy, repetitive surveys on participants and to allow them to focus more effectively on procedures that are critical for newly appointed neurosurgical consultants to demonstrate competence. Round 2. rating using NAF Results from the first round were aggregated, with procedures arising from round one redistributed to all participants in round two for the purpose of ranking each procedure's perceived “Frequency” and “Risk” (Appendix 1, components A.2 and A.3). In this case, frequency refers to the procedure’s prevalence, while risk refers to the patient's risk if a neurosurgical trainee with insufficient experience performs the procedure. The steering group was assigned to complete the last section of the CAMES-NAF survey, which sought to quantify the “Feasibility” of training neurosurgical doctors in these procedures in a simulation-based environment (Appendix 1, components B.1, B.2, B.3); specifically, the factors related to cost, availability, and suitability. A total score was obtained by calculating the means for each of the NAF's four domains (Doctors + Frequency + Risk + Feasibility). Each domain was given an equal weighting of 25%. A revised list of procedures was produced as a result, which could be sent to all participants for final prioritisation. Round 3. feasibility using NAF In the final round, participants were permitted to remove any procedures that they thought were inappropriate for simulation-based learning, merge and reorder the rankings of the procedures that remained. A 75% majority would determine that the results of this round were the final prioritised ranking list. In order to evaluate the measure of rank correlation between the NAF score in round two and the final majority decision from KOLs in round three, we performed a Pearson correlation (r) coefficient test. Statistical analysis was performed using Stata Version 17.0 (StataCorp, College Station, TX, USA). In general for absolute for absolute values of r, 0 – 0.19 is regarded as very weak, 0.2 – 0.39 as weak, 0.40 – 0.59 as moderate, 0.6 – 0.79 as strong and 0.8 – 1 as very strong correlation. A high correlation reflects a high degree of consensus.
Two authors (AR, VH), extracted procedural competencies from all phases of neurosurgical training outlined in the ISCP curriculum. Further procedures were added and existing ones removed through participant brainstorming. In the first round, we utilised component A.1 of the CAMES-NAF formula “Doctors”, and requested participants to rank procedures based on the statement, "All neurosurgery trainees at the end of training certification should be competent to perform the following procedures at the level expected of a day-1 consultant," on a 5-point scale (Appendix 1). After thorough deliberation, the steering committee determined that procedures with a mean score of 2.95 or lower in this round would be excluded from subsequent rounds. This decision was made to reduce the burden of lengthy, repetitive surveys on participants and to allow them to focus more effectively on procedures that are critical for newly appointed neurosurgical consultants to demonstrate competence.
Results from the first round were aggregated, with procedures arising from round one redistributed to all participants in round two for the purpose of ranking each procedure's perceived “Frequency” and “Risk” (Appendix 1, components A.2 and A.3). In this case, frequency refers to the procedure’s prevalence, while risk refers to the patient's risk if a neurosurgical trainee with insufficient experience performs the procedure. The steering group was assigned to complete the last section of the CAMES-NAF survey, which sought to quantify the “Feasibility” of training neurosurgical doctors in these procedures in a simulation-based environment (Appendix 1, components B.1, B.2, B.3); specifically, the factors related to cost, availability, and suitability. A total score was obtained by calculating the means for each of the NAF's four domains (Doctors + Frequency + Risk + Feasibility). Each domain was given an equal weighting of 25%. A revised list of procedures was produced as a result, which could be sent to all participants for final prioritisation.
In the final round, participants were permitted to remove any procedures that they thought were inappropriate for simulation-based learning, merge and reorder the rankings of the procedures that remained. A 75% majority would determine that the results of this round were the final prioritised ranking list. In order to evaluate the measure of rank correlation between the NAF score in round two and the final majority decision from KOLs in round three, we performed a Pearson correlation (r) coefficient test. Statistical analysis was performed using Stata Version 17.0 (StataCorp, College Station, TX, USA). In general for absolute for absolute values of r, 0 – 0.19 is regarded as very weak, 0.2 – 0.39 as weak, 0.40 – 0.59 as moderate, 0.6 – 0.79 as strong and 0.8 – 1 as very strong correlation. A high correlation reflects a high degree of consensus.
The first round survey was completed by 32 KOLs and respondents from this round provided baseline demographic data (Table ). This table reflects the diverse sub-specialty interests of multiple participants. This round incurred a KOL response rate of 4% of the total participant population that were invited to respond. A total of 71 surgical procedures were included for analysis, which were categorised into seven domains (Appendix 2). Thirty KOLs completed the second round survey, which was a response rate of 3.8%. Following the elimination of 17 procedures based on the first round's results, 54 procedures were included in this round (Table ). The most important procedural skill for SBE in neurosurgery at this stage was patient positioning, pinning positions and flap design, according to the NAF's assessment. There was significant disagreement on the requirement of sub-specialist procedures, such as cerebral arteriovenous malformation (AVM) microsurgery and deep brain stimulation, as well as uncommon procedural skills such as microvascular anastomosis. As a result, these were removed from consideration for selection in this and subsequent rounds. Thirty-one KOLs completed round three, resulting in a response rate of 3.9%. This round resulted in a final list of 47 procedures, which also highlights the changes in ranking based on analysis from rounds 2 to 3.(Table ). Two procedures were eliminated, and a further five merged with other procedures as they were deemed inherently similar or used cohesively with other procedural skills. For example, anterior cervical discectomy and fusion (ACDF) are two separate sequential components of the same surgical operation; they were merged here as they address a single operative workflow. Patient positioning, pinning positions and flap design, ICP probe insertion, EVD insertion, burr hole evacuation of chronic subdural haematoma and lumbar puncture and lumbar drain insertion were the highest-ranking prioritised procedures. The excision of convexity meningioma, pterional craniotomy, and elevation of compound depressed skull fracture procedures underwent the most significant shift in rankings due to differing consensus from the steering committee regarding their “feasibility” in round 3. As a result, all procedures were re-ranked based on KOL input during the subjective re-ranking phase at the end. There were no additional unexpected shifts in the rankings; consequently, the consistency across rounds strengthens the collective agreement among the experts on the prioritisation of these neurosurgical procedures. Syringopleural shunt insertion and myelomeningocele repair were the lowest priority procedures, but were nonetheless included in the list. Myelomeningocele, commonly referred to as "spina bifida," is a serious condition involving the spinal cord and its protective coverings. Due to its rarity and association with a niche subspecialty in neurosurgery, KOLs assigned this procedure lower priority. However, it received sufficient support in the first round, to warrant inclusion in subsequent rounds. As the data was normally distributed, a Pearson correlation coefficient was the appropriate test to evaluate the correlational linkages between the round two NAF and the final KOL opinion in the third round. A Pearson’s co-efficient of r = 0.97 (95% confidence interval 0.96, 0.99; p < 0.01) showed a very strong correlation between both rounds, and adds rigour associated with the NAF analysis (Fig. ).
In this study, we conducted a three-round modified Delphi general needs assessment with KOLs to identify which technical procedural skills in neurosurgery should be prioritised for inclusion into SBE curricula. KOLs in this regard were senior trainees and consultants in neurosurgery. This is the first comprehensive multi-jurisdiction general SBE needs assessment carried out in this domain of surgery. A prioritised list of 47 neurosurgical procedures that should be supported by SBE was produced, with an emphasis placed on acute cranial trauma, degenerative spine, neuro-oncology and CSF diversion procedures as the categorical themes of highest priority. Patient positioning, pinning positions and flap design, ICP probe insertion and EVD insertion were the top three ranking skills all throughout the Delphi process. This signifies the importance placed on these procedural skills by KOLs, as their top tier status was maintained throughout our objective quantitative analysis in rounds one and two, and in the subjective re-ranking of skills by KOLs after round three. Trainees in neurosurgery are expected to have competence in performing these procedures early in their training, in addition to burr hole evacuation of chronic subdural haematomas (ranked fourth) and lumbar drain insertion (ranked fifth). Currently, these skills are taught through SBE, but there is a notable lack of consistency in how these skills are identified, prioritised and integrated into training programmes. Where possible, considerations should be made to ensure junior neurosurgical trainees are afforded the opportunity to practice these skills in a safe learning simulation environment prior to real patient encounters. For the purpose of immobilisation, the Mayfield skull clamp is utilised in many cases of cranial and cervical spine surgery. Improper application-related adverse effects are uncommon; however, improper fixation can lead to vascular perforation, pin site infection and instances of bone fracture in particularly thin skull areas . After patient immobilisation, flap design—linear, bicoronal, etc.—usually occurs. It is unsurprising that these procedural skills ranked with highest priority in this study given their prevalence in neurosurgery and the potential harm to patients that could result from inadequate pin placement and / or flap design. Incorrect pin placement, even by a few millimetres, can have implications on ergonomics associated with task execution for the neurosurgeon. Furthermore, if due care is taken during initial head fixation, it can reduce unnecessary case time. These clinical presentations can be replicated through SBE, one suggestion is to use a cost effective synthetic-based manikin for patient positioning and pinning practice component. Anonymized magnetic resonance imaging (MRI) or computed tomography (CT) images from real patients with cranial or spinal pathologies can accompany the modalities outlined in Fig. to support practice of flap design and discussion on surface anatomy. ICP probe insertion and EVD insertion also featured prominently on this list. This is also unsurprising as both these skills are frequently performed life-saving index procedures. In some centres in the UK and Ireland, the two procedures are performed independent of one another; however, other centres combine both approaches by transducing an EVD to obtain an ICP reading . Given both procedures ranked second and third in our study, this suggests there is a degree of generalisability in our list. From a skill execution perspective using SBE, both procedures are typically performed via right frontal burr hole, following identification of Kocher's point. Therefore, a single simulation model perhaps may be used to accommodate practice of both procedures. The most common emergency pathology that requires EVD placement is acute hydrocephalus, which is typically associated with sizable ventricles , thus meaning the procedure is usually straightforward. However, EVD placement can be a hazardous procedure, and consistent practice during early training years through SBE can help accelerate the initial gradual skill acquisition phase in a safe learning environment . Repeated practice during early training years goes some way to increasing fluency and ensuring trainees require fewer attempts to perform appropriate ventricular drain placement on patients, thus reducing the likelihood of repeated mispositioning and subsequent complications such as infection and intraparenchymal hemorrhage . A myriad of simulator modalities exist to accommodate practice of these techniques such as perfused cadaveric models , or commercial synthetic based models , and models that are deemed impactful but haven't yet undergone rigorous validity evaluation (Fig. ). Certain spinal and oncological procedures, including laminotomy, laminectomy, lumbar microdiscectomy, and excision of convexity meningiomas, ranked highly on the list and are considered appropriate for inclusion in advanced neurosurgical training. These tend to be more difficult cases, which are typically performed under supervision by mid-level trainees. Spinal anatomy is complex with high levels of surgical precision required in order to prevent dural, nerve and spinal cord injury (SCI). Complication rates, which encompassed open, microendoscopic (ME) and percutaneous approaches, varied from 10.8% to 12.5% in lumbar microdiscectomy patients . Nerve root damage and exploratory work that started at the incorrect vertebral level are two of the contributory root causes. Intraoperative error may be reduced through the practice of these techniques on pig cadavers, as the anatomy is not too dissimilar to human, and can allow for practice of many of the steps involved in spinal surgical cases (Fig. ). Its disadvantages include the lack of realistic muscle groups and fascicle to accurately portray separation of muscle through dissection for anterior approaches, as well as the requirement for bespoke licenced wet labs to allow practice. Synthetic simulation options exist, which are cost effective and have collated sufficient validation metrics to deem them useful in teaching and learning . Supratentorial convexity meningioma resection is a common procedure on elective neurosurgical theatre lists, requiring the full breadth of competent microsurgical dissection skills to ensure full tumour devascularisation and detachment . Trainees at the later stages of their training are likely to be proficient in performing convexity craniotomies, so the development of high-fidelity task trainers should focus on simulating pre-existing cranial access where necessary, thereby omitting the craniotomy component, and simulating the remaining anatomy, such as the dura, associated vascular structures and the meningioma itself, for example. This would avoid learner cognitive overload and maximise the impact of these SBE sessions. This procedure climbed 10 places in the final subjective re-ranking phase, as the KOLs prioritised more prevalent potentially technically demanding neurological pathologies over less common ones. There is still a need for newly appointed neurosurgical consultants in tertiary centres to perform fundamental generalist procedural lists even in the face of the expanding tendency of sub-specialisation . Our research findings are reflective of this. While simulation models and modalities exist for every procedure on the final list, their effective integration into neurosurgical training requires a holistic approach that goes beyond mere availability. SBE should be strategically Integrated into existing neurosurgery curricula , making it mandatory and scheduling it alongside clinical rotations with protected time to attend. Without this, SBE may be deprioritised due to clinical duties. Training bodies must recognise SBE as essential and work with health service administration to balance service demands with educational needs, ensuring sustainable integration. Multi-institutional support is essential for overcoming barriers and integrating SBE into neurosurgical training . Remote or virtual platforms , low cost educational tools and simulation models and obtaining equipment loans through collaborations with industry partners can mitigates issues faced with cost and subsequently improve access in resource-limited programmes. Faculty training in simulation pedagogy is key for delivering quality performance feedback, targeted instruction and objective assessment . Although many educators are experts in their clinical fields, effective simulation facilitation requires specialised pedagogical skills and instructional design expertise . Conducting a general needs assessment of procedural skills for SBE in neurosurgery is the first step in curriculum development. SBE curricula will require some flexibility as neurosurgery training in the UK and Ireland is outcomes-based, meaning that some trainees reach particular competency milestones ahead of others. Further research is needed to complete targeted needs assessments , align training goals and objectives, and further refine educational strategies for SBE in neurosurgery. Researchers should leverage multi-jurisdictional approaches to develop standardised simulation-based training frameworks, enabling broader applicability across neurosurgical training programmes. For instance, curriculum developers aiming to thematically develop a trauma-related SBE programme for junior neurosurgical trainees, might consider some procedural skills such as positioning, pinning and flap design (1), burr hole haematoma evacuation (4), trauma flap craniotomy (7), EVD insertion (3) and ICP probe insertion (2). This sequence generally prioritises life-saving decompression first (burr hole or craniotomy), followed by CSF drainage through an EVD, and finally ICP monitoring to guide ongoing treatment. Strengths and limitations One strength is the methodology used in this study, which is a widely recognised and utilised framework for obtaining consensus in the sphere of surgical simulation training. A multi-jurisdiction consensus approach also allowed us to obtain a broader institutional level view from KOLs. However, our study has several limitations. We captured demographic data only from respondents of the first survey, and not from the remaining rounds. Snowballing sampling was used to recruit participants, due to the small and highly specialised target group, although this approach carries the risk of bias. Participants from 12 neurosurgical subspecialties were included, but epilepsy was not represented. Additionally, spinal and general neurosurgery made up significant contributions, which may have influenced the procedures prioritised in our final list. Although a sizable pool of participants was identified, the response rate remained low across all three rounds of the Delphi process. While this reflects the inherent challenges of recruiting neurosurgical experts, it may affect the generalisability of the findings. However, the consistency of responses across rounds suggests that consensus had stabilised, reinforcing the reliability of the expert opinions collected.. Lastly, the focus of this study was on acquiring technical skills. Postgraduate surgical education universally acknowledges the need of training surgeons in non-technical skills, a comparable study methodology should seek to identify the crucial soft skills needed by neurosurgery trainees at key junctures throughout training.
One strength is the methodology used in this study, which is a widely recognised and utilised framework for obtaining consensus in the sphere of surgical simulation training. A multi-jurisdiction consensus approach also allowed us to obtain a broader institutional level view from KOLs. However, our study has several limitations. We captured demographic data only from respondents of the first survey, and not from the remaining rounds. Snowballing sampling was used to recruit participants, due to the small and highly specialised target group, although this approach carries the risk of bias. Participants from 12 neurosurgical subspecialties were included, but epilepsy was not represented. Additionally, spinal and general neurosurgery made up significant contributions, which may have influenced the procedures prioritised in our final list. Although a sizable pool of participants was identified, the response rate remained low across all three rounds of the Delphi process. While this reflects the inherent challenges of recruiting neurosurgical experts, it may affect the generalisability of the findings. However, the consistency of responses across rounds suggests that consensus had stabilised, reinforcing the reliability of the expert opinions collected.. Lastly, the focus of this study was on acquiring technical skills. Postgraduate surgical education universally acknowledges the need of training surgeons in non-technical skills, a comparable study methodology should seek to identify the crucial soft skills needed by neurosurgery trainees at key junctures throughout training.
In this study, we utilised the CAMES-NAF to identify through consensus 47 neurosurgical procedures that should be prioritised for SBE. An emphasis was placed on more commonly occurring procedures, with a particular priority placed on acute cranial trauma care, degenerative spine, neuro-oncology and CSF diversion procedures.
Supplementary Material 1: Appendix 1. Description of each phase of the CAMES-NAF utilised in this study. Supplementary Material 2: Appendix 2. Raw list of procedures derived from JCST curriculum and brainstorming phase. Supplementary Material 3.
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Wastewater Target Pathogens of Public Health Importance for Expanded Sampling, Houston, Texas, USA | 7a3738e0-cc8e-4c12-bf77-5d709e1eadca | 11286076 | Microbiology[mh] | The National Academies of Sciences, Engineering, and Medicine recommends selection of targets to expand wastewater surveillance beyond SARS-CoV-2 be based on 3 criteria: 1) public health significance, 2) analytical feasibility, and 3) usefulness of the wastewater surveillance data to inform public health action . The HHD, working with an existing advisory committee of local infectious disease doctors and public health specialists, conducted a hypothesis-generating study whereby infectious disease subject matter experts (SMEs) suggested a list of pathogens or diseases (hereafter referred to as targets) to be considered for surveillance with respect to criteria 1 and 3 above, considering feasibility for assessment outside the scope of the study .
Study Development and Implementation The survey on which the study is based provides its intended purpose, indicates that de-identified results would be publicly shared in aggregate, and asks for consent to participate . Upon consent, the participants provided contact information, academic credentials, and rankings of the 74 targets in terms of the public health importance and actionability for public health intervention (e.g., education, outreach, testing, vaccination). The target options were compiled from the HHD’s database of reportable diseases monitored in Houston, Texas . SARS-CoV-2 virus, required by the National Wastewater Surveillance System, was excluded from this list. Participants classified public health importance by most important, important, or less important, and actionability for public health intervention by actionable, somewhat actionable, not actionable, and don’t know. Finally, participants were asked to identify the top 3 most important targets from the list; they were also invited to provide comments and suggest additional targets not listed. The study population was selected by using nonprobability methods, without use of quotas or incentives. Following recommendations from the advisory committee, the study team distributed invitations to participate in the study by using email listservs, newsletters, and online forums, including those affiliated with the Infectious Diseases Society of America, Big Cities Heath Coalition, and the Council of State and Territorial Epidemiologists, to encourage self-identified infectious disease SMEs to participate. The study period was February 28–August 31, 2023. Rice University’s Institutional Review Board reviewed and approved all study procedures. The study adheres to accepted public opinion research guidelines . Data Analysis We exported survey responses from the Qualtrics platform ( https://www.qualtrics.com ) into Excel software. We checked survey responses for duplicates, using the participant’s name and organization, and completeness. We excluded responses with only the consent portion filled out but without any further completion of personal information or classification of targets. We tallied response counts by category for each possible classification option and assigned numerical weights. In the Public Health Importance category, most important = 3 points, important = 2 points, and less important = 1 point. In the Actionable for Public Health Intervention category, actionable = 3 points, somewhat actionable = 2 points, not actionable option = 1 point, and don’t know = 0 points. We assigned don’t know responses 0 points to differentiate from nonresponses. We multiplied weights by the number of participant responses for each option and then totaled for each target in both categories. Category totals provided an overall total score for each target. We also calculated averages, total divided by the number of participant responses for each target (including don’t know responses), to better interpret results for targets when not all participants submitted responses for each of the 74 targets on the target list. We added the average scores for each category to obtain an overall average score for each target. We sorted the overall total scores and overall average scores from highest to lowest to generate top 10 lists for suggested targets. We ranked targets 1–10 based on their score in each category (ranking tied scores equally) . Because >1 target can have the same score, >10 suggested targets could be obtained.
The survey on which the study is based provides its intended purpose, indicates that de-identified results would be publicly shared in aggregate, and asks for consent to participate . Upon consent, the participants provided contact information, academic credentials, and rankings of the 74 targets in terms of the public health importance and actionability for public health intervention (e.g., education, outreach, testing, vaccination). The target options were compiled from the HHD’s database of reportable diseases monitored in Houston, Texas . SARS-CoV-2 virus, required by the National Wastewater Surveillance System, was excluded from this list. Participants classified public health importance by most important, important, or less important, and actionability for public health intervention by actionable, somewhat actionable, not actionable, and don’t know. Finally, participants were asked to identify the top 3 most important targets from the list; they were also invited to provide comments and suggest additional targets not listed. The study population was selected by using nonprobability methods, without use of quotas or incentives. Following recommendations from the advisory committee, the study team distributed invitations to participate in the study by using email listservs, newsletters, and online forums, including those affiliated with the Infectious Diseases Society of America, Big Cities Heath Coalition, and the Council of State and Territorial Epidemiologists, to encourage self-identified infectious disease SMEs to participate. The study period was February 28–August 31, 2023. Rice University’s Institutional Review Board reviewed and approved all study procedures. The study adheres to accepted public opinion research guidelines .
We exported survey responses from the Qualtrics platform ( https://www.qualtrics.com ) into Excel software. We checked survey responses for duplicates, using the participant’s name and organization, and completeness. We excluded responses with only the consent portion filled out but without any further completion of personal information or classification of targets. We tallied response counts by category for each possible classification option and assigned numerical weights. In the Public Health Importance category, most important = 3 points, important = 2 points, and less important = 1 point. In the Actionable for Public Health Intervention category, actionable = 3 points, somewhat actionable = 2 points, not actionable option = 1 point, and don’t know = 0 points. We assigned don’t know responses 0 points to differentiate from nonresponses. We multiplied weights by the number of participant responses for each option and then totaled for each target in both categories. Category totals provided an overall total score for each target. We also calculated averages, total divided by the number of participant responses for each target (including don’t know responses), to better interpret results for targets when not all participants submitted responses for each of the 74 targets on the target list. We added the average scores for each category to obtain an overall average score for each target. We sorted the overall total scores and overall average scores from highest to lowest to generate top 10 lists for suggested targets. We ranked targets 1–10 based on their score in each category (ranking tied scores equally) . Because >1 target can have the same score, >10 suggested targets could be obtained.
The HHD received 47 unique and complete survey responses affiliated with 42 unique organizations (19 university or hospital systems, 21 public health departments, 2 others) from 21 different states, primarily in large cities or counties. Of the participants from public health departments, 19 worked at the city or county level and 2 worked at state-level agencies. There was significant consistency across both categories. The suggested targets based on the 10 highest score values in either category were influenza A (novel or variant), measles (rubeola), hepatitis A, carbapenem-resistant Enterobacterales, monkeypox virus, Neisseria meningitidis (invasive [meningococcal disease]), Candida auris , West Nile virus, rabies (human), anthrax, legionellosis, pertussis, and cholera. Participants suggested several additional targets of concern to include in expanded wastewater monitoring, including norovirus, rotavirus, Marburg virus, and multidrug-resistant pathogens. Suggested target lists from academic, healthcare, and public health participants included measles, influenza A, hepatitis A, and Neisseria meningitidis , with an expected variance between lists relevant to each participant group’s healthcare focus.
The results of this study cannot be used to represent opinions regarding the prioritization of these suggested targets and cannot be generalized to a broader population, but they can be used to suggest a list of targets that could be considered for surveillance. As such, results from the study identified a list of 13 targets to be considered for expanded wastewater sampling based on public health importance and actionability. The results also can be used as the basis of a questionnaire for a future population-based study, with the intent of homing in on recommendations for target prioritization on a broader scale. Furthermore, supplementing these results with additional data based on local needs might favor the inclusion of different targets for a specific region. A critical first step in expanding a wastewater surveillance program is to understand the pathogens that infectious disease SMEs consider to be the greatest threat to public health. A previous study ranked targets for wastewater surveillance prioritization by using binary and quantitative parameters based in empirical disease data . Other disease prioritization studies that incorporated feedback from SMEs were not focused specifically on rankings for wastewater surveillance and had narrower scopes focusing on specific events or types of targets . The methods used in this study complement those approaches by bringing in perspectives from infectious disease SMEs with a first-hand view of how these targets affect disease in the broader community, whose responses were provided with the express intent of translating the collective data to wastewater monitoring. We believe that these study results can be used to suggest an expanded target list for the National Wastewater Surveillance System and serve as pilot information for future studies.
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Genetic testing in psychiatry, the perceptions of healthcare workers and patients: a mini review | 9c155c85-aad3-46f1-8a1e-ddc1a6d74129 | 11499203 | Psychiatry[mh] | Modern medicine is constantly improving its tools and modernizing its methods to be able to provide patients with the most effective and personalized treatment and genetic testing is in the frontline of precision medicine. The Center for Disease Control and Prevention, defines “genetic testing” as the process of scanning a person’s genetic sequence in search of alterations (mutations, variants) in DNA that may have clinical relevance ( ). A variety of clinical conditions in different fields of medicine are associated with genetic abnormalities and genetic testing is gaining ground in clinical praxis in different specialties ( ). Genetic testing helps to identify the genetic component of some disorders, can be used in diagnosis, to guide treatment and for genetic counseling of the patient’s relatives. Additionally, monitoring of genetic markers during treatment can guide clinicians adjust treatment plans according to one’s genetic variations ( ). Psychiatry is a promising field for the application of genetic testing as, in comparison with other medical specialties, is still well behind in identifying biomarkers for diagnosis, prognosis and treatment response. However, epidemiological and genetic studies have shown a strong association between certain genetic alterations and psychiatric diseases, with expanding research in genetic causality and familial inheritance models ( ). Due to the high prevalence of psychiatric disorders attributable to genetic alterations, the medical community has increased its interest in researching the genetic etiology of these disorders through genetic testing and familial risk classification ( ). Considering the major impact of psychiatric diseases on society, investigation from such a revolutionary perspective could be crucial ( ). Psychiatric genetic testing can be helpful in unraveling the pathophysiology of common mental disorders such as schizophrenia, depression, bipolar disorders, and autism spectrum disorder. For instance, in schizophrenia, genetic testing examines variations in genes impacting functions like brain development, neurotransmission, and immune homeostasis ( ). Information derived from genetic testing can be used as predictors and thus enable early interventions and empower individuals to make informed decisions about their health. Overall, psychiatric genetic testing serves as a crucial advancement in addressing complex psychiatric disorders and enhancing personalized healthcare strategies ( ). In addition to Mendelian models, genes-diseases correlation, and prenatal screening for genotypic abnormalities, the application of pharmacogenomics is increasing. Pharmacogenomics can revolutionize drug prescribing through tailoring treatments to each genetic profile, optimizing efficacy and minimizing unfavorable outcomes ( ). It can reduce the trial-and-error period of treatment and provide actionable information in special populations ( ). Variations in metabolic enzymes, including cytochrome P450 and especially within the CYP2D6 enzyme can impact the metabolism of antipsychotics and antidepressants, affecting treatment response. The use of diagnostic genetic tests remains relatively rare in current clinical practice, largely due to the complex polygenic nature of psychiatric disorders, which complicates direct genetic diagnosis ( ). In contrast, pharmacogenomic tests are used more often, can help tailor medication, with growing evidence suggesting that they can improve both the tolerability and effectiveness of treatment. This has been shown in randomized clinical trials, systematic reviews and meta-analyses especially in managing mood disorders and schizophrenia ( ). Thus, this distinction between the two test types is crucial, as their roles in psychiatric practice differs significantly. Although there is increasing utility of genetic testing in medicine, the existing literature on the perceptions of healthcare professionals and patients regarding this practice is still growing. Initial studies report skepticism from both the medical community and patients regarding the efficacy and utility of these tests, and ethical concerns have been raised related to privacy, security of patient data, confidentiality, economic impact and possible harms such as psychological impact, stigmatization and discrimination ( , ). Preliminary studies reported that the type of genetic condition can influence the mental health of patients when genetic testing is applied, with neurodegenerating disorders such as Huntington’s disease having a profound impact ( ). At present, there is a lack of comprehensive studies on the perspectives of healthcare professionals and patients regarding the utilization of genetic tests in psychiatry. Given the stigma often associated with psychiatric disorders and the vulnerability of psychiatric patients, it is important to investigate the perspectives of those directly involved. Additional concerns might include the capacity of psychiatric patients and their relatives to consent to genetic testing and whether they understand the implications and possible benefits. Also, questions arise about the necessity of such tests in severely mentally ill patients and the usefulness of the results ( ). Therefore, the identification of perceptions of healthcare professionals and patients has important implications in the application of genetic testing in psychiatric clinical praxis. Thus, the aim of this systematic review was to identify, categorize and discuss the perceptions, opinions and concerns of patients and healthcare workers in psychiatry regarding the use of genetic testing.
The systematic review was based on the Preferred Reporting Items for Systematic reviews and Meta-Analysis statement (Prisma) guidelines ( ). Data sources and searches The research of the medical literature was executed in PubMed and Embase and was confined to the preceding decade encompassing the timeframe of 1/12014 to 1/1/2024. The selection of this research timeframe was based on the recognition that while genetic testing in psychiatric applications had been apparent earlier, more advanced applications including pharmacogenetics, were developed in recent years ( ). Published articles were collected using a standard search strategy search query: (“Genetic testing” OR “Genetic screening” OR “Molecular diagnostics”) AND (“Psychiatry” OR “Mental health” OR “Psychiatric disorders” OR “Mental illness”) AND (“Perceptions” OR “Attitudes” OR “Beliefs” OR “Opinions”) AND (“Healthcare workers” OR “Clinicians” OR “Healthcare professionals” OR “Medical staff”) AND (“Patients” OR “Individuals” OR “Participants” OR “Subjects”). Study selection This systematic overview encompassed articles that investigated the attitudes, perspectives, beliefs, and views of healthcare providers and patients concerning genetic testing in psychiatry. Research articles on Alzheimer’s disease ( n = 2) were excluded due to the primary characteristics of this disease including memory and cognitive dysfunctions. Νo other exclusion criteria referring to gender, age, or ethnicity have been applied. Only articles written in English were considered for inclusion. The PRISMA 2009 checklist guided any similarly restrictions that were imposed on the articles. Data extraction, study quality assessment and analysis The systematic search resulted in the identification of 50 articles in total. Out of the 50 articles, 12 were excluded as duplicates resulting in 38 articles for further screening. After careful full-text article assessment for eligibility and applying the inclusion and exclusion criteria, only 20 ( n = 20) of the articles were deemed eligible to be further assessed in full study. Three ( n = 3) articles were excluded as identified as a review while two ( n = 2) more articles were excluded as being out of the scope of this systematic review since they did not include opinions or beliefs for genetic testing in psychiatry but in another specialties. All the references of the identified review articles were also checked for eligibility. Thus, finally, 15 studies reporting on the patients’ and healthcare provider’s perspectives regarding genetic testing in psychiatry were included. The Prisma Flowchart for exclusion/inclusion criteria is presented in . All included studies were thematically analyzed for identifying themes related to genetic testing in psychiatry. The thematic analysis was performed separately on healthcare professionals and patients’ opinion/perspectives regarding the topic. Data were retrieved from each study and classified through thematic analysis first in subthemes and subsequently into the different themes.
The research of the medical literature was executed in PubMed and Embase and was confined to the preceding decade encompassing the timeframe of 1/12014 to 1/1/2024. The selection of this research timeframe was based on the recognition that while genetic testing in psychiatric applications had been apparent earlier, more advanced applications including pharmacogenetics, were developed in recent years ( ). Published articles were collected using a standard search strategy search query: (“Genetic testing” OR “Genetic screening” OR “Molecular diagnostics”) AND (“Psychiatry” OR “Mental health” OR “Psychiatric disorders” OR “Mental illness”) AND (“Perceptions” OR “Attitudes” OR “Beliefs” OR “Opinions”) AND (“Healthcare workers” OR “Clinicians” OR “Healthcare professionals” OR “Medical staff”) AND (“Patients” OR “Individuals” OR “Participants” OR “Subjects”).
This systematic overview encompassed articles that investigated the attitudes, perspectives, beliefs, and views of healthcare providers and patients concerning genetic testing in psychiatry. Research articles on Alzheimer’s disease ( n = 2) were excluded due to the primary characteristics of this disease including memory and cognitive dysfunctions. Νo other exclusion criteria referring to gender, age, or ethnicity have been applied. Only articles written in English were considered for inclusion. The PRISMA 2009 checklist guided any similarly restrictions that were imposed on the articles.
The systematic search resulted in the identification of 50 articles in total. Out of the 50 articles, 12 were excluded as duplicates resulting in 38 articles for further screening. After careful full-text article assessment for eligibility and applying the inclusion and exclusion criteria, only 20 ( n = 20) of the articles were deemed eligible to be further assessed in full study. Three ( n = 3) articles were excluded as identified as a review while two ( n = 2) more articles were excluded as being out of the scope of this systematic review since they did not include opinions or beliefs for genetic testing in psychiatry but in another specialties. All the references of the identified review articles were also checked for eligibility. Thus, finally, 15 studies reporting on the patients’ and healthcare provider’s perspectives regarding genetic testing in psychiatry were included. The Prisma Flowchart for exclusion/inclusion criteria is presented in . All included studies were thematically analyzed for identifying themes related to genetic testing in psychiatry. The thematic analysis was performed separately on healthcare professionals and patients’ opinion/perspectives regarding the topic. Data were retrieved from each study and classified through thematic analysis first in subthemes and subsequently into the different themes.
Studies characteristics The studies included ( n = 15) had a total population of 3,156 participants including 2,347 healthcare professionals and 809 patients. The studies were carried out in diverse locations, most common the United States ( n = 8). The mental healthcare professionals included were psychiatrists, psychiatric pharmacists, child and adolescent psychiatrists, psychiatric genetics researchers and general practitioners working in mental health clinics. The patients included in the studies suffered from depression, bipolar disorder, schizophrenia, and patients receiving treatment for a mental health condition. The studies are shown in . Healthcare professionals’ perspectives on genetic testing in psychiatry Four themes and fifteen subthemes were identified, the most common theme was Organizational-Implementation concerns, including six subthemes: cost, limited knowledge and training, lack of clear guidelines, lack of funding, limited availability and accessibility, and lack of collaborations among clinicians and researchers. The second theme, Ethical Considerations, encompasses subthemes such as informed consent, patient-doctor relationship, psychological distress, stigma, and inappropriate treatment decisions or changes. The third theme, Concerns on changes in clinical praxis, includes three subthemes: threat to clinical expertise, accuracy of tests, and managing patient expectations. The final theme, Legal Implications, includes concerns related to employment. All themes, subthemes, and studies identifying them are shown in . Patients’ perspectives on genetic testing in psychiatry Four main categories, with a total of 11 subcategories were identified. These primary categories mirror those identified in the case of healthcare professionals including organizational-implementation concerns, ethical considerations, implications for clinical practice, and legal implications. A more comprehensive overview of the themes observed in each individual study is presented in . What was the general sentiment among healthcare providers and patients? Out of the eleven ( n = 11) studies where mental health providers were involved, seven ( n = 7) studies suggested that the consensus among psychiatry professionals was that genetic testing is a valuable tool in psychiatry. However, in four ( n = 4) studies, mental health professionals have expressed mixed perspectives on the matter. Regarding the patients’ perspective, positive opinions regarding genetic tests in psychiatry were expressed, in two ( n = 2) studies, while in two ( n = 2) studies, patients had mixed perspectives. It is important to note that among the studies included in this systematic review, there was no indication of a general negative opinion regarding genetic tests among healthcare providers in psychiatry and psychiatric patients.
The studies included ( n = 15) had a total population of 3,156 participants including 2,347 healthcare professionals and 809 patients. The studies were carried out in diverse locations, most common the United States ( n = 8). The mental healthcare professionals included were psychiatrists, psychiatric pharmacists, child and adolescent psychiatrists, psychiatric genetics researchers and general practitioners working in mental health clinics. The patients included in the studies suffered from depression, bipolar disorder, schizophrenia, and patients receiving treatment for a mental health condition. The studies are shown in .
Four themes and fifteen subthemes were identified, the most common theme was Organizational-Implementation concerns, including six subthemes: cost, limited knowledge and training, lack of clear guidelines, lack of funding, limited availability and accessibility, and lack of collaborations among clinicians and researchers. The second theme, Ethical Considerations, encompasses subthemes such as informed consent, patient-doctor relationship, psychological distress, stigma, and inappropriate treatment decisions or changes. The third theme, Concerns on changes in clinical praxis, includes three subthemes: threat to clinical expertise, accuracy of tests, and managing patient expectations. The final theme, Legal Implications, includes concerns related to employment. All themes, subthemes, and studies identifying them are shown in .
Four main categories, with a total of 11 subcategories were identified. These primary categories mirror those identified in the case of healthcare professionals including organizational-implementation concerns, ethical considerations, implications for clinical practice, and legal implications. A more comprehensive overview of the themes observed in each individual study is presented in .
Out of the eleven ( n = 11) studies where mental health providers were involved, seven ( n = 7) studies suggested that the consensus among psychiatry professionals was that genetic testing is a valuable tool in psychiatry. However, in four ( n = 4) studies, mental health professionals have expressed mixed perspectives on the matter. Regarding the patients’ perspective, positive opinions regarding genetic tests in psychiatry were expressed, in two ( n = 2) studies, while in two ( n = 2) studies, patients had mixed perspectives. It is important to note that among the studies included in this systematic review, there was no indication of a general negative opinion regarding genetic tests among healthcare providers in psychiatry and psychiatric patients.
To our knowledge, this is the first systematic review to investigate the perspectives of patients and healthcare workers associated with genetic testing in psychiatry with the findings contributing to a deeper understanding of the utilization of genetic testing in psychiatry and shed light on ethical considerations and potential risks from various perspectives. The theme that was most frequently identified was the concerns expressed by professionals regarding the limited education, training, and professional experience on genetic testing and genetic information. Indeed, although genetic testing and counseling have many applications in medicine, are still not included as part of the fundamental curriculum in the majority of medical schools across the world ( ). Consequently, this leads to a dearth of professional education and specific training in clinical settings that directly impacts the perspectives of healthcare providers with regards to the utilization of these technologies and techniques in their daily practice. Thus, it is imperative that practitioners receive adequate training to be able to fully utilize newer technologies in clinical praxis such as pharmacogenetic testing ( ). The concern ranking second in frequency among professionals was the cost associated with genetic testing. The cost was deemed a prominent barrier hindering the implementation of pharmacogenomics testing. Physicians expressed concerns regarding the affordability of these tests suggesting that enhancing accessibility and affordability, potentially through the public health sector, would be of utmost importance ( ). Given the novelty and innovative nature of genetic counseling applications, it becomes evident that the public health sectors are ill-prepared to handle the demand and coverage for such tests, resulting in an unfortunate situation where patients bear the economic burden and their perspective on genetic testing becomes adversely affected. Especially in the field of Psychiatry with vulnerable patients of often poor socioeconomic status and services underfunded, it is crucial to advocate for cost coverage of new technology. Nevertheless, in order for genetic testing to truly become a routine practice in the field of medicine and to be fully covered by insurance companies or public health sectors, it is imperative that it provides the scientific community with more clear and consistent results, as well as a wider range of applications. One of the most prevalent concerns among healthcare providers related to the potential mental health stigma experienced by their patients, which, if left unaddressed, could result in discrimination and self-stigmatization for individuals identified as having risk variants. To mitigate the potential negative consequences on participants and their families, clinicians who integrate genetic counseling into their daily practice must actively consider strategies for alleviating such impacts. Furthermore, an extended educational approach targeting both patients and the general public could play a pivotal role in eradicating the stigmatization endured by these patients, as the limited knowledge surrounding genetics has been identified as the primary factor influencing such behavior ( ). By equipping individuals with a comprehensive understanding of the genetic components underlying mental health, it becomes possible to combat the stigma associated with it, fostering an environment of inclusivity and support. This comprehensive approach ensures that patients receive the necessary care without facing unnecessary barriers or prejudice stemming from a lack of awareness or understanding. Special concerns were raised regarding the potential psychological impact of genetic testing in psychiatry. Indeed, it was previously reported that mental health professionals expressed concerns regarding the possible influence of genetic testing on the mental well-being of patients ( ). The characteristics of psychiatric disorders affecting the cognitive function of patients, together with the stigma of psychiatric disorders has the risk for increased misunderstandings and negative psychological impact from genetic testing results. In addition, patients may undergo distress regarding their condition, alterations in treatment, or anxiety regarding possible consequences such as employability. Such concerns, subsequently, tend to overshadow the consideration of the delicate equilibrium associated with the “right to know.” As previous studies have suggested, clinicians are confronted with the task of meticulously evaluating the patients’ entitlement to access their genetic information against the potential psychosocial detriments that may emerge from receiving certain outcomes, including heightened stress, anxiety, stigma, and discrimination ( ). However, it is reasonable to mention that, to the best of our knowledge, there is currently no evidence supporting a high risk of psychological harm related to genetic testing among psychiatric patients, and previous studies suggest that the severity of psychological risks posed by genetic testing is not substantial ( , ). At this juncture, further research is necessary to identify specific patient groups, such as individuals with mental health conditions, who may have a heightened susceptibility to psychological harm. It is possible that some patients might assert that knowledge of genetics and genetic testing could dampen the hopes of individuals afflicted with mental disorders. The awareness of patients regarding their genetic predisposition could potentially engender a sense of fatalism or hopelessness regarding their condition. Alongside the possible psychological impact of genetic testing results, the uncertainty surrounding the outcomes of the tests is also important. Certain patients express worries regarding the efficacy of genetic testing in the event of inconclusive or non-actionable results. In such cases, patients believe that genetic testing would offer limited benefits. It is widely acknowledged that not all genes that can predict the response to psychiatric treatment have been discovered ( ). While there is strong evidence and available guidelines for genes associated with drug metabolism, such as CYP2C19 and CYP2D6, as well as other pharmacokinetic implications, the evidence for other genes is still limited ( ). This lack of comprehensive identification of genes can potentially hinder the effectiveness of pharmacogenetic testing and raise concerns within the medical community regarding the accuracy and applicability of such tests. In the context of the two aforementioned concerns, clinicians have a valid and justifiable concern about effectively managing patient expectations. It is imperative to emphasize that pharmacogenetic testing serves as a clinical decision-making instrument utilized by healthcare providers alongside other pertinent factors to facilitate the process of medication selection. It is crucial for healthcare providers to adeptly handle patients’ expectations in terms of acknowledging the limitations of pharmacogenetic testing as well as the varying degrees of evidence associated with the genes being tested ( ). Considering the unique concerns of professionals, psychiatrists expressed concerns regarding an excessive reliance on genetic tests, as it may undermine their clinical expertise and experience. There were concerns that this reliance may replace clinical judgment and impact the patient-doctor rapport, ultimately leading to the dehumanization of the therapeutic alliance and psychiatric care. Furthermore, psychiatrists also expressed worries about the feasibility of incorporating discussions about testing and patient education within the time constraints of routine care visits. Conversely, some professionals believed that genetic testing could streamline the process by identifying the most appropriate medication for each patient, potentially reducing the trial-and-error approach. These varying perspectives among professionals highlight concerns surrounding the actual utility and potentials of genetic counseling. This study has several limitations. A key limitation of this review is the use of the vote-counting method, which treats all studies equally, regardless of differences in sample size, quality, or bias control. This approach can oversimplify findings, as it does not account for the weight or statistical significance of individual studies, potentially leading to skewed conclusions. Given these limitations, the findings presented should be interpreted cautiously. Future research would benefit from qualitative or meta-analytic approaches to better capture the complexity and variation across studies on genetic testing in psychiatry. As the literature search was conducted in PubMed and Embase only in the English language, possible bias cannot be excluded. Also, the timeframe of the study, including the last decade, might have resulted in missing earlier studies in the subject. However, genetic testing in psychiatry has mainly been used the most recent years. Also, a bias toward healthcare professionals in psychiatry from developed countries, especially USA was evident. As there was a large variation in the methodology of the included studies, including interviews, focus groups, questionnaires and surveys in different patient populations and settings, a meta-analysis was not possible. Finally, as a selection bias cannot be excluded, in combination with the small number of studies, with some themes derived from a small number of studies, the results should be viewed with caution. Although within the studies, the review reached thematic saturation, further research might illuminate new aspects contributing new themes. The relatively emerging nature of this field may have contributed to the lack of research on this topic, thereby limiting the range of insights that could be obtained from existing literature. In this review diagnostic and pharmacogenomic tests were grouped together as a separate analysis was not feasible due to lack of data and data heterogeneity. While both are forms of genetic testing, diagnostic genetic testing is rarely employed due to the complexity of psychiatric disorders, while pharmacogenomic testing has an increasing role in clinical praxis ( ). Future research should focus more specifically on the evolving evidence surrounding pharmacogenomic testing, which holds greater relevance to current psychiatric practice. Despite these limitations, this study provides valuable insights into the current landscape of attitudes and perceptions toward genetic testing in psychiatry, highlighting the need for further research to address these gaps in understanding. In conclusion, this review systematically examined the perceptions of healthcare providers and patients regarding genetic testing in psychiatry highlighting concerns, including the limited knowledge, training and the high costs of genetic tests. This study also emphasizes the importance of establishing clear and updated guidelines to minimize errors, improve test accuracy, and enhance patient confidence in genetic testing. To achieve these goals, increased funding and further investigation into this subject are imperative.
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患者导航模式对我国医联体背景下肺癌全程管理的应用启示 | 1a6d6e28-b7e5-4cf4-9a24-34b7c5f621a1 | 10752780 | Patient-Centered Care[mh] | 患者导航的起源与发展 患者导航是一种以患者为中心的医疗卫生服务提供的干预措施，其主要目的是消除整个医疗连续体中可能出现的障碍，以便及时诊断和治疗癌症和其他慢性病 。患者导航通过在医院和社区设置导航员，导航员担任“经纪人”角色，与患者互动以确定照护障碍，通过及时沟通和协调，将患者与医疗资源联系起来，消除跨越疾病全程的照护障碍，有助于改善跨学科、环境、医疗水平和部门之间的照护整合，对解决具有复杂医疗需求的个体的碎片化照护方面具有重要作用 [ - ] 。1990年，FREEMAN等在美国纽约哈雷姆中心医院首次开展了“患者导航”项目，以应对黑人社区高比例的乳腺癌发病率和死亡率；2010年美国政府颁布的《平价医疗法案》扩大了患者导航员的作用，并要求在健康保险市场建立导航员计划；2012年，美国外科医生学会要求所有癌症项目都必须有一个患者导航计划；截至2015年，美国1600家医院提供患者导航服务 。瑞典政府紧随其后，将患者导航者角色确立为瑞典国家癌症战略的一部分 。在澳大利亚，昆士兰州政府于2015年建立了第一个患者导航计划，并将其作为永久性角色 。印度 、尼日利亚 、印度尼西亚 等越来越多的中低收入国家也相继开展患者导航项目。患者导航近年来已成为连接整合医疗和全生命周期概念的一个全新研究热点，在全球范围内获得了广泛关注。
患者导航的模式 患者导航的核心功能是针对脆弱人群消除医疗保健连续体所有环节及时照护的障碍，及时照护的常见障碍包括：医疗系统障碍、财务障碍、沟通和信息障碍、不信任和情感障碍等 。患者导航员执行的关键任务如 所示。患者导航与国内常采用的个案管理模式的区别是：虽然两者都能为患者提供整体性、持续性照护，但个案管理是围绕医疗服务提供方需求，以实现服务质量、医疗资源的优化利用和成本降低为目标导向；而患者导航以围绕患者需求而不是服务提供者的需求来整合碎片化服务，帮助患者从他们自己的角度理解照护轨迹，减少在获得连续照护服务方面的延误 。患者导航被广泛认可为癌症照护连续体（预防-筛查-诊断-治疗-随访全程阶段）中最常用且推荐的协调性管理模式 [ - ] 。 根据导航员角色的不同，可以划分为专业导航、同伴/非专业导航和患者矩阵导航模型：①专业导航通常由护士主导（又称“导航护士”），侧重解决具有复杂健康和社会需求的患者群体，以医院为中心。这一类导航应用较为广泛，如澳大利亚昆士兰护士导航项目 ；②同伴/非专业导航包括社会工作者、照顾者等，针对健康状况更稳定的人口，以社区为中心，例如新西兰农村地区的健康导航 ；③随着医疗服务体系整合和协同，逐渐延伸出患者导航矩阵模型 ，即专业导航和同伴/非专业导航协同工作，该模型是更为综合的纵向模型，将不同功能的导航员安置在全流程关键的环节上，贯穿纵向多层级多机构，有助于在医院网络里连接医疗保健服务和资源。该模型已成为整合医疗理念下前沿热点研究话题，亟须更多真实世界研究中的案例实践证据。
患者导航的国内外应用现状 患者导航项目，最初是为了提高服务不足人群的癌症筛查率，随着医疗卫生服务系统的动态变化，对患者导航的需求更加趋向于应对医疗服务提供的日益复杂、人口老龄化、多病发病率增加以及人口健康方面的社会不平等 。因此，患者导航项目的服务场所从最初的以社区和初级保健为主到以医院为主，再延伸到覆盖整个医院服务网络。美国拉丁裔癌症研究网络提供的患者导航项目于社区、诊所和医院开展跨癌症连续体的服务，其导航员4年间已帮助 300 多名患者进行癌症筛查、诊断和治疗 。由美国国家癌症研究所中6个癌症中心（癌症照护联盟）开展的一项为期5年（2017–2021年）的患者导航项目，其结果反映了联盟内合作的重要性以及癌症中心合作在进行干预开发、实施和扩展时分享跨学科观点的有用性 。世界卫生组织（WHO）政策简报推荐了患者导航，它可以有效促进整合医疗，有效性维度体现在可及性、照护协调性和连续性、效益、健康结果 。具有最高循证证据的随机对照系统评价研究表明 [ - ] ，患者导航在癌症照护连续体中具有较好的成本效益，可以提高癌症筛查的接受度和依从性，减少检查结果异常后的治疗等待时间，改善及时随访和患者满意度。 国内对患者导航总体处于刚刚开始关注的阶段，主要聚焦于对导航模式的分析探索和案例研究，尚未有高质量的患者导航实践及效果评价的报道。研究中的患者导航仅在单一机构内开展，导航员均为护士，同伴/非专业导航尚未见涉及。如徐虹霞等 报道了在浙江大学附属邵逸夫医院设立导航护士的经验，提出加速康复外科实施过程中导航护士角色的设立及实践；方芳等 通过质性研究探讨了日间手术管理设置导航护士的必要性及管理方法；金培莉等 报道了复旦大学附属中山医院胃癌专病导航护士介导的单家医院内“门诊-住院-出院”全程管理模式，认为导航护士角色的引入和应用能推动胃癌全程管理模式的建立与发展，提高患者满意度及治疗依从性。 总的来说，患者导航在国际上已发展较为成熟，但国内关于患者导航的研究和实践尚处于起步和探索阶段。首先，现有案例研究多为单个医院内部导航模式，而在医联体背景下存在跨机构协作的需求，如何打通全程管理流程，实现区域内不同医疗机构之间的有效衔接，需要进一步探索患者导航在医联体的应用模式。其次，现有研究的导航员角色较单一，我国基层医疗资源比较匮乏，如何发挥社区资源作用，建立起医院、社区导航员之间的跨层级协作，也是未来实践需要探索的问题。最后，国内仍缺乏可推广、可持续的患者导航干预模式，以及缺乏高质量的实施评价研究证据，未来可以开展符合我国国情的患者导航模式的实施科学研究，采用实施科学理论框架来设计、实施和评估患者导航项目，为国内患者导航的建立和发展提供更有力和高质量的实证和理论依据。
将患者导航引入我国医联体背景下肺癌全程管理的思考 4.1 为什么引入患者导航 从国家政策导向来看，2022年4月，《国务院办公厅关于印发“十四五”国民健康规划的通知》提出，要推动预防、治疗、护理、康复有机衔接，形成“病前主动防，病后科学管，跟踪服务不间断”的一体化健康管理服务；鼓励医疗机构采取多种方式设置服务协调员，在患者诊疗过程中予以指导协助和跟踪管理。2023年5月，国家卫生健康委、国家中医药管理局印发了《关于开展改善就医感受提升患者体验主题活动的通知》，提出要改善人民群众全过程就医感受，提升患者体验。因此，有必要创新以患者为中心的医疗服务模式，为老百姓提供可获得、连续性、协调性医疗卫生服务，提升就医获得感、幸福感、安全感。 从现实困境和需求来看，肺癌相对于其他疾病，具有起病隐匿、病期发展时间长、易反复、重症多等特点，肺癌的诊断与治疗是一个非常复杂与困难的过程。常常需要在多个医疗机构层级之间、在不同医疗机构之间、在不同诊疗团队之间、在疾病各个阶段之间经历许多健康照护的转换和过渡，对许多患者来说是极具挑战性的。全程管理是一个具有动态性、多阶段性、多方协同性的复杂管理项目，亟须以一个枢纽为抓手，以患者为中心去协调和衔接多个相关服务主体，推动全程管理的实施，以满足患者的需求。而患者导航是突破肺癌全程管理跨层级跨机构“碎片化”服务困境的新路径。 4.2 如何引入患者导航 目前全国发展趋于成熟的医联体，为开展多层级、多机构协作下肺癌全程管理的患者导航模式提供了良好的实施环境。医联体是我国建设整合型医疗卫生服务体系的具体表现形式之一，是指由不同级别、类别医疗机构之间，通过纵向或横向整合医疗资源所形成的医疗机构联合组织。截至2022年9月，我国已组建了各种形式的医联体1.5万个 。医联体开展患者导航模式具备以下几点优势：第一，医联体可以通过合作与整合共享资源，强化团队协作和综合护理，提供更综合、协调的医疗、护理和社会支持服务；第二，医联体内通过共享患者的健康档案、诊疗信息等数据，可以实现患者信息的无缝对接；第三，通过医联体建立协调机制和信息共享平台，可以实现不同医疗机构之间的顺畅转诊，满足患者需求。 医联体背景下的肺癌全程管理的患者导航概念模型如 所示，该模型涉及医联体内基层医疗机构/社区、医院等纵向多层级机构，提供从预防到随访的各个阶段的一体化、连续性管理，其导航员包括专业人员和经培训的非专业人士。对于如何开发肺癌全程管理的患者导航模型，则需要确定以下核心内容 ：①目标患者群体和识别策略，如选择癌症连续体哪个阶段的患者群体，通过有关患者社会状况和支持需求的问卷调查识别弱势患者；②患者导航员的角色和任务，可以通过考虑患者访谈的结果收集导航员的各种具体任务；③导航员的专业背景和教育程度，可以通过教育模块化方式组织导航员培训；④疾病特点，可以根据疾病类型和地区调整导航员的专业知识；⑤患者与导航员互动的模式，如地点、时间、会面时长和会面间隔；⑥患者导航模式整合到医联体医疗服务系统中；⑦模型开发完成后，将其提交给利益相关者进行最终评估。 4.3 面临的潜在挑战及应对策略 在医联体内开展肺癌全程管理的患者导航模式，突破了单个医疗机构，可能会面临以下实际挑战 [ - ] ：第一，不同医疗机构之间的信息系统不兼容，导致患者信息共享困难；第二，不同医疗机构之间的协作和沟通不畅，导致患者在转诊和治疗过程中遇到困难；第三，医疗机构的人力、物力和财力资源有限，难以满足患者导航服务内容的需求。因此，我们提出了以下相应的应对策略建议：第一，建议推动医联体内医疗信息化建设，建立统一的电子健康记录系统，促进各医疗机构之间数据的互通和共享；第二，建立医联体内的协调沟通机制和利益分配机制，明确责任和角色分工，通过定期会议、团队培训等形式加强合作与沟通；第三，争取政府和社会资金支持，增加投入，开展成本效益评估，优化资源利用。
为什么引入患者导航 从国家政策导向来看，2022年4月，《国务院办公厅关于印发“十四五”国民健康规划的通知》提出，要推动预防、治疗、护理、康复有机衔接，形成“病前主动防，病后科学管，跟踪服务不间断”的一体化健康管理服务；鼓励医疗机构采取多种方式设置服务协调员，在患者诊疗过程中予以指导协助和跟踪管理。2023年5月，国家卫生健康委、国家中医药管理局印发了《关于开展改善就医感受提升患者体验主题活动的通知》，提出要改善人民群众全过程就医感受，提升患者体验。因此，有必要创新以患者为中心的医疗服务模式，为老百姓提供可获得、连续性、协调性医疗卫生服务，提升就医获得感、幸福感、安全感。 从现实困境和需求来看，肺癌相对于其他疾病，具有起病隐匿、病期发展时间长、易反复、重症多等特点，肺癌的诊断与治疗是一个非常复杂与困难的过程。常常需要在多个医疗机构层级之间、在不同医疗机构之间、在不同诊疗团队之间、在疾病各个阶段之间经历许多健康照护的转换和过渡，对许多患者来说是极具挑战性的。全程管理是一个具有动态性、多阶段性、多方协同性的复杂管理项目，亟须以一个枢纽为抓手，以患者为中心去协调和衔接多个相关服务主体，推动全程管理的实施，以满足患者的需求。而患者导航是突破肺癌全程管理跨层级跨机构“碎片化”服务困境的新路径。
如何引入患者导航 目前全国发展趋于成熟的医联体，为开展多层级、多机构协作下肺癌全程管理的患者导航模式提供了良好的实施环境。医联体是我国建设整合型医疗卫生服务体系的具体表现形式之一，是指由不同级别、类别医疗机构之间，通过纵向或横向整合医疗资源所形成的医疗机构联合组织。截至2022年9月，我国已组建了各种形式的医联体1.5万个 。医联体开展患者导航模式具备以下几点优势：第一，医联体可以通过合作与整合共享资源，强化团队协作和综合护理，提供更综合、协调的医疗、护理和社会支持服务；第二，医联体内通过共享患者的健康档案、诊疗信息等数据，可以实现患者信息的无缝对接；第三，通过医联体建立协调机制和信息共享平台，可以实现不同医疗机构之间的顺畅转诊，满足患者需求。 医联体背景下的肺癌全程管理的患者导航概念模型如 所示，该模型涉及医联体内基层医疗机构/社区、医院等纵向多层级机构，提供从预防到随访的各个阶段的一体化、连续性管理，其导航员包括专业人员和经培训的非专业人士。对于如何开发肺癌全程管理的患者导航模型，则需要确定以下核心内容 ：①目标患者群体和识别策略，如选择癌症连续体哪个阶段的患者群体，通过有关患者社会状况和支持需求的问卷调查识别弱势患者；②患者导航员的角色和任务，可以通过考虑患者访谈的结果收集导航员的各种具体任务；③导航员的专业背景和教育程度，可以通过教育模块化方式组织导航员培训；④疾病特点，可以根据疾病类型和地区调整导航员的专业知识；⑤患者与导航员互动的模式，如地点、时间、会面时长和会面间隔；⑥患者导航模式整合到医联体医疗服务系统中；⑦模型开发完成后，将其提交给利益相关者进行最终评估。
面临的潜在挑战及应对策略 在医联体内开展肺癌全程管理的患者导航模式，突破了单个医疗机构，可能会面临以下实际挑战 [ - ] ：第一，不同医疗机构之间的信息系统不兼容，导致患者信息共享困难；第二，不同医疗机构之间的协作和沟通不畅，导致患者在转诊和治疗过程中遇到困难；第三，医疗机构的人力、物力和财力资源有限，难以满足患者导航服务内容的需求。因此，我们提出了以下相应的应对策略建议：第一，建议推动医联体内医疗信息化建设，建立统一的电子健康记录系统，促进各医疗机构之间数据的互通和共享；第二，建立医联体内的协调沟通机制和利益分配机制，明确责任和角色分工，通过定期会议、团队培训等形式加强合作与沟通；第三，争取政府和社会资金支持，增加投入，开展成本效益评估，优化资源利用。
结语 患者导航顺应目前健康中国战略背景下提供公平可及、系统连续的一体化慢病防治的服务需求，能够弥补国内医联体背景下肺癌患者全程管理连续性和协调性不足的问题，为患者和复杂的医疗保健服务体系之间架起沟通的桥梁，克服患者在全程就医过程中的障碍，提高医疗服务及医疗保健信息的可及性。然而，在跨层级跨机构的医联体中引入患者导航模式可能遇到机构之间信息系统不兼容、协作和沟通不畅、资源有限等方面的挑战，尚需进一步完善医联体内医疗信息化建设、协调沟通机制和利益分配机制等问题，探索构建适用于我国国情的患者导航模式，有助于进一步完善我国医联体建设和发展，形成医防融合背景下一体化的慢病管理网络体系。 * * * 作者贡献声明 陶文娟负责论文构思、经费获取和初稿写作，文进负责审读与编辑写作，李为民负责经费获取、监督指导和审读与编辑写作。所有作者已经同意将文章提交给本刊，且对将要发表的版本进行最终定稿，并同意对工作的所有方面负责。 利益冲突 所有作者均声明不存在利益冲突
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Chromogranin a: Its Known and Possible Roles in Obstetrics and Gynecology | c843a0dc-dfc3-454c-a088-f89bb5af2034 | 8522818 | Gynaecology[mh] | When a group of scientists, Blaschko et al., for the first time isolated a group of proteins from the adrenal medulla and labelled them granins over 50 years ago , they probably did not anticipate that two decades later another team of researchers would categorize them into 3 separate subtypes: chromogranin A (CgA), chromogranin B (or, secretogranin I), and secretogranin II . Chromogranins have a widespread distribution in human and animal polypeptide hormone producing tissues, including adrenal medulla chromaffin cells, parathyroid chief cells, thyroid parafollicular C cells, pancreatic islet cells, gut enteroendocrine cells, and anterior pituitary cells [ , , ]. They are believed to play a role in hormone packaging within intracellular secretory granules, in hormone secretion, and serve as prohormones for a variety of proteolytic cleavage products . A widely recognized role of CgA is that of a marker for neuroendocrine tumors, also known as NETs. However, at present it is acknowledged that increased quantities of CgA are produced and secreted by a wide array of human tissues in the course of various disorders . Consequently, the aim of this brief review is to indicate a number of the possible involvements of CgA in the mechanisms of health and disease which are of concern to obstetrics and gynecology.
This glycoprotein with a molecular weight of 49 kDa is composed of 439 amino acids . The gene coding for the particle is localized on chromosome 14. CgA belongs to the family of granins, or acidic glycoproteins universally present in all the secretory granules of the cells included in the diffuse neuroendocrine system, or DNES . CgA functions are not fully understood yet. However, some intracellular and extracellular functions of CgA have been elucidated. The intracellular functions comprise the initiation and regulation of dense-core granule biogenesis and sequestration of hormones synthesized by given cells at the trans -Golgi network. Interestingly, CgA is co-stored and co-released by exocytosis with secreted hormones . The extracellular functions of the prohormone include the generation of bioactive peptides of endocrine nature. Specifically, depending on where a particular sequence of amino acids was interrupted, CgA can break down into a number of active substances, such as vasostatin, chromostatin, and pancreastatin ( ) . The converting enzymes of the prohormone are cathepsin L, plasmin, and kallikrein . The resultant peptides exert their actions locally, mostly in an autocrine and paracrine manner . As it is shown in , several of the CgA-derived peptides present with opposing counter-regulatory effects, for example vasostatin I and catestatin are antiadrenergic, whereas serpinin is proadrenergic. Vasostatin I inhibits endothelial cell proliferation and migration while catestatin supports these phenomena. Vasostatin I demonstrates proapoptotic properties and serpinin is a cell death inhibitor, etc. Thus, tissue-specific modifications of the CgA chain length result in different bioactive compounds that warrant varied, possibly also tissue-specific physiological effects. It is useful to keep in mind that, as a negative regulator, pancreastatin causes e.g.: insulin resistance due to its inhibitory effect on glucose-stimulated insulin secretion, inhibition of glucose uptake by various cells, and inhibition of lipogenesis in adipocytes . In contrast, catestatin mediates direct vasodilation by histamine-induced production of nitric oxide and is a potent endogenous inhibitor of catecholamine secretion and of catecholamine-mediated arterial hypertension. Another beneficial effect of catestatin is that it decreases obesity by both promoting lipid flux from the adipose tissue (or, lipolysis) and enhancing leptin receptor signaling . It is of interest and in line with the principle of CgA’s co-storage and co-release with secreted endocrine regulatory substances that the prohormone is a major cargo in insulin secretory vesicles within pancreatic β-cells, where it is processed mainly to vasostatin- and catestatin-containing fragments . A recent review indicated a new role of CgA as a potential marker for diabetes .
During pregnancy, intrauterine tissues express and synthesize CgA mRNA and protein and secrete it into the biologic fluids of pregnancy . Consequently, during pregnancy new sources of CgA are present, such as placental tissue , and hence CgA concentrations in the maternal and fetal blood may be subject to modification. There have been several efforts to explore this. In one study, maternal blood CgA concentrations were found not to change significantly throughout pregnancy, whereas the activity of pancreastatin, as studied by its immunoreactivity, did increase as pregnancy advanced . Maternal salivary CgA concentrations increase in the second and the early third trimesters to decrease thereafter . Interestingly, CgA was confirmed to be present in the amniotic fluid, decidual cells, and in trophoblasts. A comparison of double immunofluorescence results from term placentas demonstrated that there is a remarkable colocalization of CgA and human placental lactogen and human chorionic gonadotropin in trophoblast cells. Since the latter two hormones are synthesized by syncytiotrophoblasts, the interpretation of such an outcome was that CgA should specifically be a product of syncytiotrophoblasts . For us, this observation is another interesting example of CgA’s co-storage and co-release with other secreted hormones. Furthermore, presents an image from the archive of the Department of Histology and Cytophysiology, Medical University of Białystok, demonstrating that, indeed, human syncytiotrophoblast cells do positively stain for CgA. Italian researchers looked at CgA levels during parturition, either via elective Cesarean section, or spontaneous vaginal delivery, at term. CgA levels were highest in umbilical cord blood; umbilical cord plasma and amniotic fluid CgA levels were significantly higher at vaginal delivery than at C-sections, while maternal plasma levels remained virtually unchanged throughout labor and a 2-hour postpartum period . Also a French study found that CgA and noradrenaline plasma concentrations were significantly higher in infants born by vaginal delivery than by elective C-sections. It is of note that no particular difference was observed for adrenaline concentrations. Since a significant correlation was found between CgA and noradrenaline levels, an elegant suggestion arises from this investigation: in the human fetus, the co-release of CgA with stress is connected with noradrenaline and not with adrenaline secretory granules . Furthermore, the combined data support an association of CgA with the intrapartum fetal stress during vaginal delivery. Somewhat in line, Belgian authors found a trend associating the CgA concentration in the umbilical cord blood sampled at birth with a history of maternal smoking . These data suggest that it is justified to further explore the associations of CgA with intrapartum fetal stress and such disorders of placental dysfunction, as preeclampsia , intrauterine growth restriction , or early pregnancy loss , to name a few.
When studied histologically, both CgA and secretogranin II are commonly found to be associated with luteinizing hormone (LH) and/or follicle-stimulating hormone within specialized secretory granules in pituitary gonadotropic cells and, therefore, it is anticipated that they play an important role in the differential secretion of gonadotropins. Studies in rats before and after ovariectomy demonstrated that estrogens decrease anterior pituitary CgA mRNA, whereas ovariectomy increases CgA mRNA levels . Thus, estrogens are one factor negatively influencing the CgA biosynthesis. In contrast, as studied in a mouse pituitary gonadotropic cell line, adrenal corticosteroids (dexamethasone in particular) exert a positive effect on pituitary CgA, in a similar way as the gonadotropin-releasing hormone from the hypothalamus . Secretoneurin, which is a functional secretogranin II-derived peptide, was shown to stimulate the production and release of LH in this cell model , possibly by facilitating LH trafficking into secretory granules . Interestingly, women of reproductive age with a high degree of premenstrual psychoemotional symptoms have increased salivary CgA concentrations in the late-luteal phase . Moreover, we would like to draw attention to the need for verification of the involvement of both CgA and pancreastatin in the pathomechanism(s) of endometrioid endometrial cancer. Two serious arguments support this suggestion. Over the past decades, there has been a tremendous increase in the incidence of overweight and obesity worldwide, which are established risk factors for this most prevalent gynecological malignancy nowadays. As indicated above, pancreastatin causes insulin resistance. Second, a proportion of endometrioid adenocarcinomas demonstrate neuroendocrine features of which CgA is an established marker. Initial studies of this topic clearly require further exploration.
The presented account of the possible roles and involvements of CgA in obstetrics and gynecology warrants further interest in launching research on the prohormone’s clinical significance, apart from its application as a NETs marker. In particular, our account indicates the need to verify its association with intrapartum fetal stress and the involvement in the pathomechanisms of obstetric disorders related to placental dysfunction, as well as in the pathogenesis of endometrioid endometrial cancer as a hormonally regulated malignancy.
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Bonding Efficacy of Universal Adhesives to Fluorotic Enamel after Pre-conditioning with EDTA | 178a039f-8cf5-44db-9748-0611b6a17156 | 11734296 | Dentistry[mh] | Tooth Selection and Preparation This study used 448 extracted maxillary and mandibular caries-free human molars. The teeth used were classified according to the Thylstrup and Fejerskov (TFI) index to diagnose dental fluorosis according to severity. Before selection of teeth, two examiners were calibrated as described by Ermis et al. This study used 224 teeth with a TFI score of 0 (without fluorosis) and 224 teeth with a TFI score of 4 from individuals living in the endemic fluorosis areas of Ecuador (Chimborazo City) with 2 ppm fluoride in drinking water. , Informed consent was obtained from the individuals under a protocol approved by the Ethics Committee Review Board (#3.183.007) before collecting the teeth. The teeth were disinfected in 0.5% chloramine, stored at 4°C in distilled water, and used within 6 months of extraction. The roots of all teeth were removed by sectioning at the cementoenamel junction. Following this, 128 teeth were used to evaluate the μSBS (n = 8 teeth per group), 128 teeth were used to evaluate in situ DC (n = 8 teeth per group) at the resin-enamel interfaces, and 192 teeth (n = 8 teeth per group) were used to evaluate the etching pattern. Each dental crown was then sectioned diagonally across the long axis of the tooth to produce four enamel specimens (buccal, lingual, and two proximal) with an area of approximately 5 mm 2 . Experimental Design The teeth were then randomly assigned to 16 experimental groups according to the combination of the independent variables: (1) enamel surface: sound enamel and fluorotic enamel; (2) adhesive: Clearfil Universal Bond (CUB) (Kuraray Noritake; Tokyo, Japan), Futurabond U (FBU) (VOCO; Cuxhaven, Germany), iBond Universal (IBU) (Heraeus Kulzer; Hanau, Germany), and Scotchbond Universal (SBU) (3M Oral Care; St Paul, MN, USA); (3) enamel treatment: 37% PA (Condac 37%, FGM; Joinville, SC, Brazil; PA etch-and-rinse) as the control and 17% EDTA (Biodinâmica; Ibiporã, PR, Brazil; EDTA etch-and-rinse). For enamel etching pattern, a control group with no treatment was added. Randomization of the teeth for all testing was performed for each substrate (sound enamel and fluorotic enamel). A person not involved in the research protocol performed this procedure using computer-generated numbers. Sample Size Calculation The main outcome of the present study was enamel bond strength. The mean bond strengths of universal adhesives obtained with PA etch-and-rinse conditioning of the enamel was considered in the sample size calculation. According to the literature, the mean bond strength (± standard deviation) of several universal adhesives evaluated was 20.4 ± 3.0 MPa. In order to detect a difference of 8 MPa among the tested groups, using α = 0.05, a power of 80%, and a two-sided test, the estimated minimal sample size was 8 teeth per group. The same number of teeth per group (n = 8) were used for the other tests (in situ DC at the resin-enamel interfaces and etching pattern). Microshear Bond Strength Test All specimens from one tooth were embedded together in a polyvinyl chloride tube, 10 mm in height and 13 mm in diameter, using a chemically curing acrylic resin (Jet Clássico; São Paulo, SP, Brazil), leaving the enamel surface exposed at the top of the cylinder. The protocol suggested by Shimaoka et al was used to isolate the bonding area. Five to six perforations with an internal diameter of 0.8 mm were made in an acid-resistant, double-faced adhesive tape (Adelbras Ind e Com Adesivos; São Paulo, SP, Brazil) that was adapted to the enamel surface. This procedure was performed using a hygienic Ainsworth-style rubber-dam punch (Coltene Whaledent; Altstätten, Switzerland). The number of perforations on each enamel surface depended on the dimensions of the enamel specimens. The universal adhesives were applied to the enamel surface in accordance with the manufacturer’s instructions, as described in . A single operator performed all bonding procedures as follows: PA etch-and-rinse conditioning (control group): Before adhesive application, the enamel surface was etched with 37% PA gel for the time recommended by each manufacturer. The surface was then water rinsed with an air-water syringe for 15 s. The adhesive was applied, and the manual pressure exerted on the microbrush (Microbrush International; Grafton, WI, USA) during application was equivalent to 35 g . , EDTA etch-and-rinse conditioning: Before adhesive application, the enamel surface was actively etched with 17% EDTA applied on the enamel surface for 30 s. The surface was then rinsed with an air-water syringe for 15 s, followed by adhesive application as described for PA. After application of the adhesive, transparent polyethylene Tygon tubes (Tygon Medical Tubing Formulations 54-HL, Saint Gobain Performance Plastics; Akron, OH, USA), with the same internal diameter as the perforations and a height of 0.5 mm, were positioned on the perforations over the double-faced tape, ensuring that their lumen were congruent with the circular areas exposed by the perforations. Resin composite (Opallis, FGM) was carefully packed inside each tube, and a clear Mylar matrix strip was placed over the filled Tygon tube and pressed gently into place. The resin composite was light cured for 20 s using a light-emitting diode light-curing unit unit at 1200 mW/cm 2 (Radii-cal, SDI; Bayswater, Victoria, Australia). A radiometer (Demetron LED Radiometer, Kerr Sybron Dental Specialties; Middleton, WI, USA) was used to check the light intensity for every five specimens. These procedures were carried out using 10X magnifying loupes and with controlled temperature (23°C ± 2°C) and humidity (50% ± 5% relative humidity). After storing the specimens in distilled water for 24 h at 37°C, the Tygon tubes and the double-faced adhesive tape were carefully removed using a blade to expose the composite cylinders. Each specimen was examined under a stereomicroscope at 10X magnification. The bonded cylinder was discarded if there was any evidence of porosities or gaps at the interface. The specimens were attached to a shear-testing fixture (Odeme Biotechnology; Joaçaba, SC, Brazil) and positioned in a universal testing machine (Instron; Enfield, CT, USA). A thin wire (0.2 mm diameter) was looped around the base of each composite cylinder. The wire contacted the composite resin cylinder along half of its circumference. The setup of resin-enamel interface, wire loop, and center of the load cell was maintained in alignment to ensure the correct orientation of the shear forces. The crosshead speed was set at 1 mm/min until failure. The μSBS (MPa) was calculated by dividing the load at failure by the surface area (mm 2 ). After testing, the specimens were examined under an optical microscope (SZH-131, Olympus; Tokyo, Japan) at 100X magnification to define the location of bond failure. The type of failure was determined based on the percentage of substrate-free material: adhesive/mixed (A/M) failure at the resin/enamel interface or failure at the resin/enamel interface with partial cohesive failure of the neighboring substrates; cohesive (CE) failure exclusively within the enamel or failure exclusively within resin composite (CR); pre-test failures (PF). Enamel-etching Pattern The etching pattern (n = 8 teeth per group) of the enamel surface was evaluated using an SEM (Vega 3 Tescan, Shimadzu; Tokyo, Japan). After teeth were prepared as previously described, the enamel surface for each type of enamel substrate (96 specimens of sound and 96 specimens of fluorotic enamel) was randomly assigned to be tested according to each group. For this purpose, in the PA and EDTA groups, enamel specimens with an area of approximately 5 mm 2 were previously etched according to the different experimental conditions , rinsed for 15 s, air dried, the adhesives were applied but not light cured. The enamel surfaces were immediately stored in acetone for 24 h to dissolve the monomer resins on the enamel surface. The specimens were then rinsed in deionized water for 5 min, immersed in a 96% alcohol bath for 5 min, followed by deionized water again for 5 min to dissolve and remove the SE primer and adhesive resins. Eight specimens of each substrate were used to evaluate the unetched enamel surfaces constituted the control group. All specimens were dried and dehydrated in a desiccator for 12 h, and the conditioned enamel surfaces were sputter-coated with gold/palladium in a vacuum evaporator (SCD 050, Balzers; Schaan, Liechtenstein). The entire surface of the treated enamel was examined using SEM (Vega 3 Tescan, Shimadzu). Photomicrographs of the representative surface areas were captured at 5000X magnification by a technician responsible for the SEM, who was blinded to all adhesive procedures. In Situ Degree of Conversion The in situ DC (n = 8 teeth per group) was evaluated as per the protocol outlined by Cardenas et al and Loguercio et al. Enamel specimens with areas of approximately 5 mm 2 were prepared as previously described. After that, the enamel specimens for each enamel substrate (96 specimens of sound and 96 specimens of fluorotic enamel) were randomly assigned for testing according to each group (12 enamel surfaces per group). After adhesive application, composite resin buildups were constructed on the bonded enamel using the same materials and protocols described for the μSBS test. After storage of the restored teeth in distilled water at 37°C for 24 h, the resin-enamel specimens were longitudinally sectioned across the bonded interface with a low-speed diamond saw (Isomet, Buehler) to obtain three resin-enamel slices. The resin-enamel slices were wet polished with 1500-, 2000-, and 2500-grit silicon carbide paper for 15 s each. They were then ultrasonically cleaned for 20 min in distilled water and stored in water for 24 h at 37°C. The micro-Raman microscope (XploRA ONE Raman microscope, Horiba Scientific; Piscataway, NJ, USA) was first calibrated for zero and then for coefficient values using a silicon sample. The samples were analyzed using a 638-nm diode laser with a 100X air objective. The Raman signal was acquired using 600 lines/mm grating centered between 500 and 2000 cm -1 , and the employed parameters were 100 mW, accumulation time 30 s, with 5 co-additions, spatial resolution 3 µm, and spectral resolution 5 cm -1 . Spectra were captured at the resin-enamel adhesive interface at three random sites for each specimen. Post-processing of the spectra was performed using LabSpec 6 Spectroscopy suite software. Additionally, the spectra of uncured adhesives were used as references. The ratio of the double-bond content of monomer to polymer in the adhesive was quantified by calculating the ratio derived from the aliphatic C=C (vinyl) absorption (1638 cm -1 ) to the aromatic C=C absorption (1608 cm -1 ) signals for both polymerized and unpolymerized samples (n = 8). The DC was calculated according to the following formula: DC = (1: [R-cured/R-uncured]) x 100 where “R” is the ratio of aliphatic and aromatic peak intensities at 1639 cm -1 and 1609 cm -1 in cured and uncured adhesives, respectively. In addition, the more intense peaks observed for all materials and the corresponding chemical bonding were recorded. All these procedures were performed by a technician responsible for the micro-Raman device, who was blinded to all adhesive procedures. Statistical Analysis The average μSBS of all resin-enamel specimens showing A/M failure mode from the same enamel specimens and tooth were obtained for statistical purposes. Specimens with cohesive and pre-test failures were not included in the data analysis. The same procedure was performed for the DC measurements. Therefore, the experimental unit of this study was the enamel specimen. The Kolmogorov-Smirnov test was employed to assess the data distribution for normality. Barlett’s test was performed to determine the validity of the assumption of equal variances. The μSBS data were analyzed using three-way ANOVA (enamel surface vs adhesive vs enamel treatment). The in situ DC data were analyzed using two-way ANOVA (enamel surface vs enamel treatment) for each adhesive. Tukey’s test at α = 0.05 was used as post-hoc test for μSBS and in situ DC data. The enamel-etching pattern was evaluated qualitatively. This study used 448 extracted maxillary and mandibular caries-free human molars. The teeth used were classified according to the Thylstrup and Fejerskov (TFI) index to diagnose dental fluorosis according to severity. Before selection of teeth, two examiners were calibrated as described by Ermis et al. This study used 224 teeth with a TFI score of 0 (without fluorosis) and 224 teeth with a TFI score of 4 from individuals living in the endemic fluorosis areas of Ecuador (Chimborazo City) with 2 ppm fluoride in drinking water. , Informed consent was obtained from the individuals under a protocol approved by the Ethics Committee Review Board (#3.183.007) before collecting the teeth. The teeth were disinfected in 0.5% chloramine, stored at 4°C in distilled water, and used within 6 months of extraction. The roots of all teeth were removed by sectioning at the cementoenamel junction. Following this, 128 teeth were used to evaluate the μSBS (n = 8 teeth per group), 128 teeth were used to evaluate in situ DC (n = 8 teeth per group) at the resin-enamel interfaces, and 192 teeth (n = 8 teeth per group) were used to evaluate the etching pattern. Each dental crown was then sectioned diagonally across the long axis of the tooth to produce four enamel specimens (buccal, lingual, and two proximal) with an area of approximately 5 mm 2 . The teeth were then randomly assigned to 16 experimental groups according to the combination of the independent variables: (1) enamel surface: sound enamel and fluorotic enamel; (2) adhesive: Clearfil Universal Bond (CUB) (Kuraray Noritake; Tokyo, Japan), Futurabond U (FBU) (VOCO; Cuxhaven, Germany), iBond Universal (IBU) (Heraeus Kulzer; Hanau, Germany), and Scotchbond Universal (SBU) (3M Oral Care; St Paul, MN, USA); (3) enamel treatment: 37% PA (Condac 37%, FGM; Joinville, SC, Brazil; PA etch-and-rinse) as the control and 17% EDTA (Biodinâmica; Ibiporã, PR, Brazil; EDTA etch-and-rinse). For enamel etching pattern, a control group with no treatment was added. Randomization of the teeth for all testing was performed for each substrate (sound enamel and fluorotic enamel). A person not involved in the research protocol performed this procedure using computer-generated numbers. The main outcome of the present study was enamel bond strength. The mean bond strengths of universal adhesives obtained with PA etch-and-rinse conditioning of the enamel was considered in the sample size calculation. According to the literature, the mean bond strength (± standard deviation) of several universal adhesives evaluated was 20.4 ± 3.0 MPa. In order to detect a difference of 8 MPa among the tested groups, using α = 0.05, a power of 80%, and a two-sided test, the estimated minimal sample size was 8 teeth per group. The same number of teeth per group (n = 8) were used for the other tests (in situ DC at the resin-enamel interfaces and etching pattern). All specimens from one tooth were embedded together in a polyvinyl chloride tube, 10 mm in height and 13 mm in diameter, using a chemically curing acrylic resin (Jet Clássico; São Paulo, SP, Brazil), leaving the enamel surface exposed at the top of the cylinder. The protocol suggested by Shimaoka et al was used to isolate the bonding area. Five to six perforations with an internal diameter of 0.8 mm were made in an acid-resistant, double-faced adhesive tape (Adelbras Ind e Com Adesivos; São Paulo, SP, Brazil) that was adapted to the enamel surface. This procedure was performed using a hygienic Ainsworth-style rubber-dam punch (Coltene Whaledent; Altstätten, Switzerland). The number of perforations on each enamel surface depended on the dimensions of the enamel specimens. The universal adhesives were applied to the enamel surface in accordance with the manufacturer’s instructions, as described in . A single operator performed all bonding procedures as follows: PA etch-and-rinse conditioning (control group): Before adhesive application, the enamel surface was etched with 37% PA gel for the time recommended by each manufacturer. The surface was then water rinsed with an air-water syringe for 15 s. The adhesive was applied, and the manual pressure exerted on the microbrush (Microbrush International; Grafton, WI, USA) during application was equivalent to 35 g . , EDTA etch-and-rinse conditioning: Before adhesive application, the enamel surface was actively etched with 17% EDTA applied on the enamel surface for 30 s. The surface was then rinsed with an air-water syringe for 15 s, followed by adhesive application as described for PA. After application of the adhesive, transparent polyethylene Tygon tubes (Tygon Medical Tubing Formulations 54-HL, Saint Gobain Performance Plastics; Akron, OH, USA), with the same internal diameter as the perforations and a height of 0.5 mm, were positioned on the perforations over the double-faced tape, ensuring that their lumen were congruent with the circular areas exposed by the perforations. Resin composite (Opallis, FGM) was carefully packed inside each tube, and a clear Mylar matrix strip was placed over the filled Tygon tube and pressed gently into place. The resin composite was light cured for 20 s using a light-emitting diode light-curing unit unit at 1200 mW/cm 2 (Radii-cal, SDI; Bayswater, Victoria, Australia). A radiometer (Demetron LED Radiometer, Kerr Sybron Dental Specialties; Middleton, WI, USA) was used to check the light intensity for every five specimens. These procedures were carried out using 10X magnifying loupes and with controlled temperature (23°C ± 2°C) and humidity (50% ± 5% relative humidity). After storing the specimens in distilled water for 24 h at 37°C, the Tygon tubes and the double-faced adhesive tape were carefully removed using a blade to expose the composite cylinders. Each specimen was examined under a stereomicroscope at 10X magnification. The bonded cylinder was discarded if there was any evidence of porosities or gaps at the interface. The specimens were attached to a shear-testing fixture (Odeme Biotechnology; Joaçaba, SC, Brazil) and positioned in a universal testing machine (Instron; Enfield, CT, USA). A thin wire (0.2 mm diameter) was looped around the base of each composite cylinder. The wire contacted the composite resin cylinder along half of its circumference. The setup of resin-enamel interface, wire loop, and center of the load cell was maintained in alignment to ensure the correct orientation of the shear forces. The crosshead speed was set at 1 mm/min until failure. The μSBS (MPa) was calculated by dividing the load at failure by the surface area (mm 2 ). After testing, the specimens were examined under an optical microscope (SZH-131, Olympus; Tokyo, Japan) at 100X magnification to define the location of bond failure. The type of failure was determined based on the percentage of substrate-free material: adhesive/mixed (A/M) failure at the resin/enamel interface or failure at the resin/enamel interface with partial cohesive failure of the neighboring substrates; cohesive (CE) failure exclusively within the enamel or failure exclusively within resin composite (CR); pre-test failures (PF). The etching pattern (n = 8 teeth per group) of the enamel surface was evaluated using an SEM (Vega 3 Tescan, Shimadzu; Tokyo, Japan). After teeth were prepared as previously described, the enamel surface for each type of enamel substrate (96 specimens of sound and 96 specimens of fluorotic enamel) was randomly assigned to be tested according to each group. For this purpose, in the PA and EDTA groups, enamel specimens with an area of approximately 5 mm 2 were previously etched according to the different experimental conditions , rinsed for 15 s, air dried, the adhesives were applied but not light cured. The enamel surfaces were immediately stored in acetone for 24 h to dissolve the monomer resins on the enamel surface. The specimens were then rinsed in deionized water for 5 min, immersed in a 96% alcohol bath for 5 min, followed by deionized water again for 5 min to dissolve and remove the SE primer and adhesive resins. Eight specimens of each substrate were used to evaluate the unetched enamel surfaces constituted the control group. All specimens were dried and dehydrated in a desiccator for 12 h, and the conditioned enamel surfaces were sputter-coated with gold/palladium in a vacuum evaporator (SCD 050, Balzers; Schaan, Liechtenstein). The entire surface of the treated enamel was examined using SEM (Vega 3 Tescan, Shimadzu). Photomicrographs of the representative surface areas were captured at 5000X magnification by a technician responsible for the SEM, who was blinded to all adhesive procedures. The in situ DC (n = 8 teeth per group) was evaluated as per the protocol outlined by Cardenas et al and Loguercio et al. Enamel specimens with areas of approximately 5 mm 2 were prepared as previously described. After that, the enamel specimens for each enamel substrate (96 specimens of sound and 96 specimens of fluorotic enamel) were randomly assigned for testing according to each group (12 enamel surfaces per group). After adhesive application, composite resin buildups were constructed on the bonded enamel using the same materials and protocols described for the μSBS test. After storage of the restored teeth in distilled water at 37°C for 24 h, the resin-enamel specimens were longitudinally sectioned across the bonded interface with a low-speed diamond saw (Isomet, Buehler) to obtain three resin-enamel slices. The resin-enamel slices were wet polished with 1500-, 2000-, and 2500-grit silicon carbide paper for 15 s each. They were then ultrasonically cleaned for 20 min in distilled water and stored in water for 24 h at 37°C. The micro-Raman microscope (XploRA ONE Raman microscope, Horiba Scientific; Piscataway, NJ, USA) was first calibrated for zero and then for coefficient values using a silicon sample. The samples were analyzed using a 638-nm diode laser with a 100X air objective. The Raman signal was acquired using 600 lines/mm grating centered between 500 and 2000 cm -1 , and the employed parameters were 100 mW, accumulation time 30 s, with 5 co-additions, spatial resolution 3 µm, and spectral resolution 5 cm -1 . Spectra were captured at the resin-enamel adhesive interface at three random sites for each specimen. Post-processing of the spectra was performed using LabSpec 6 Spectroscopy suite software. Additionally, the spectra of uncured adhesives were used as references. The ratio of the double-bond content of monomer to polymer in the adhesive was quantified by calculating the ratio derived from the aliphatic C=C (vinyl) absorption (1638 cm -1 ) to the aromatic C=C absorption (1608 cm -1 ) signals for both polymerized and unpolymerized samples (n = 8). The DC was calculated according to the following formula: DC = (1: [R-cured/R-uncured]) x 100 where “R” is the ratio of aliphatic and aromatic peak intensities at 1639 cm -1 and 1609 cm -1 in cured and uncured adhesives, respectively. In addition, the more intense peaks observed for all materials and the corresponding chemical bonding were recorded. All these procedures were performed by a technician responsible for the micro-Raman device, who was blinded to all adhesive procedures. The average μSBS of all resin-enamel specimens showing A/M failure mode from the same enamel specimens and tooth were obtained for statistical purposes. Specimens with cohesive and pre-test failures were not included in the data analysis. The same procedure was performed for the DC measurements. Therefore, the experimental unit of this study was the enamel specimen. The Kolmogorov-Smirnov test was employed to assess the data distribution for normality. Barlett’s test was performed to determine the validity of the assumption of equal variances. The μSBS data were analyzed using three-way ANOVA (enamel surface vs adhesive vs enamel treatment). The in situ DC data were analyzed using two-way ANOVA (enamel surface vs enamel treatment) for each adhesive. Tukey’s test at α = 0.05 was used as post-hoc test for μSBS and in situ DC data. The enamel-etching pattern was evaluated qualitatively. Microshear Bond Strength The majority of the specimens (96.8–100%) showed A/M failures . The triple cross-product interaction was not statistically significant (enamel surface vs adhesive vs enamel treatment; p = 0.47), nor was the two double cross-product interaction (enamel surface vs enamel treatment and adhesive vs enamel treatment; p = 0.32 and p = 0.37, respectively). However, the μSBS data for the double cross-product interaction enamel surface vs adhesive was statistically significant (p = 0.0001; ). Also, the main factor enamel treatment was not significant (p = 0.15; ). When sound and fluorotic enamel were compared, a higher mean μSBS was obtained in sound enamel for all adhesives and enamel treatments (p = 0.0002; ). Regarding adhesives, CUB and SBU showed statistically higher mean μSBS than did FBU and IBU in sound and fluorotic enamel (p = 0.0002; ). When CUB and SBU were compared, SBU showed higher μSBS in fluorotic enamel (p = 0.001; ). For pre-conditioning with EDTA, the mean μSBS were statistically similar to those obtained with the respective PA application in sound and fluorotic enamel (p = 0.15; ). Enamel-etching Pattern SEM images of the enamel surfaces under the different experimental conditions are shown in . Overall, when sound and fluorotic enamel were compared, there was more micro-irregularity and porosity over the entire fluorotic enamel surface. Independent of the enamel surface, PA and EDTA application completely removed the smear layer from both sound and fluorotic enamel surfaces, promoting the deepest and most pronounced etching pattern when compared with no etching . In Situ Degree of Conversion The DC values are shown in . The double cross-product interaction was not statistically significant (enamel surface vs enamel treatment; p = 0.32), as well as the main factor enamel treatment (p = 0.28; ). However, the main factor enamel surface was significant (p = 0.0001; ). A higher mean μSBS was obtained for sound enamel than for fluorotic enamel for all adhesives and enamel treatments (p = 0.0001; ). For all universal adhesives, the mean DC values were similar to those obtained with the respective PA and EDTA application in sound and fluorotic enamel (p = 0.28; ). The majority of the specimens (96.8–100%) showed A/M failures . The triple cross-product interaction was not statistically significant (enamel surface vs adhesive vs enamel treatment; p = 0.47), nor was the two double cross-product interaction (enamel surface vs enamel treatment and adhesive vs enamel treatment; p = 0.32 and p = 0.37, respectively). However, the μSBS data for the double cross-product interaction enamel surface vs adhesive was statistically significant (p = 0.0001; ). Also, the main factor enamel treatment was not significant (p = 0.15; ). When sound and fluorotic enamel were compared, a higher mean μSBS was obtained in sound enamel for all adhesives and enamel treatments (p = 0.0002; ). Regarding adhesives, CUB and SBU showed statistically higher mean μSBS than did FBU and IBU in sound and fluorotic enamel (p = 0.0002; ). When CUB and SBU were compared, SBU showed higher μSBS in fluorotic enamel (p = 0.001; ). For pre-conditioning with EDTA, the mean μSBS were statistically similar to those obtained with the respective PA application in sound and fluorotic enamel (p = 0.15; ). SEM images of the enamel surfaces under the different experimental conditions are shown in . Overall, when sound and fluorotic enamel were compared, there was more micro-irregularity and porosity over the entire fluorotic enamel surface. Independent of the enamel surface, PA and EDTA application completely removed the smear layer from both sound and fluorotic enamel surfaces, promoting the deepest and most pronounced etching pattern when compared with no etching . The DC values are shown in . The double cross-product interaction was not statistically significant (enamel surface vs enamel treatment; p = 0.32), as well as the main factor enamel treatment (p = 0.28; ). However, the main factor enamel surface was significant (p = 0.0001; ). A higher mean μSBS was obtained for sound enamel than for fluorotic enamel for all adhesives and enamel treatments (p = 0.0001; ). For all universal adhesives, the mean DC values were similar to those obtained with the respective PA and EDTA application in sound and fluorotic enamel (p = 0.28; ). The results of the present study showed that sound enamel resulted in higher mean bond strengths than did fluorotic enamel. It is known that fluorotic enamel is more acid-resistant due to the presence of fluorapatite. , Also, fluorotic enamel presents an external hypermineralized layer that is associated with a hypomineralized sub-surface, , which prevents adequate wetting of the enamel surface due to the low energy of the surface. Both characteristics adversely affect the bonding performance of the most recent adhesives, , , , , as well as universal adhesives to fluorotic enamel. , Clinical alternatives have been proposed to improve bonding to fluorotic enamel. For instance, Ermis et al. showed that if fluorotic enamel was ground, the superficial removal of the enamel layer exposes a sub-surface layer that is more reactive to bonding procedures, leading to better bond strength to fluorotic enamel. This has been highly recommended in cases of moderate or severe fluorosis. However, this technique removes sound tissue, which is contrary to the minimally invasive concept. On the other hand, mainly for self-etch adhesives, the application of phosphoric acid on fluorotic enamel is highly recommended. Mildly acidic self-etch adhesives did not sufficiently demineralize the fluorotic enamel surface, causing a less retentive pattern when compared to phosphoric enamel etching. , In the past, it has been recommended to etch fluorotic enamel for a longer period of time, , but it seems that 30 s of phosphoric-acid etching is sufficient to improve the surface roughness of moderately fluorotic teeth. However, future studies need to be done to evaluate the effect of different etching times on the bond strength to fluorotic enamel. As mentioned in the introduction section, as universal adhesives are essentially one-step self-etch adhesives that can be used in different adhesion strategies, phosphoric acid is also recommended to improve the bond strength to fluorotic enamel. , In the present study the use of pre-conditioning with EDTA was evaluated. The results showed that pre-conditioning with EDTA in both sound and fluorotic enamel yielded bond strengths similar to those produced with PA application, leading to acceptance of the first null hypothesis. EDTA is known as a potent chelating agent, with four carboxylic acid groups that promote the sequestration of metal ions to dental substrates and selectively dissolve hydroxyapatite. EDTA can also remove the surface smear layer, increase the intensity of the etching pattern, and consequently increase adhesive infiltration of the surface. , This increase in the enamel-etching pattern intensity is shown in . PA and EDTA were capable of creating a cleaner substrate with a more retentive etching pattern compared to non-etched substrate, leading to the acceptance of the second null hypothesis. These results corroborate the results of other authors, who reported an increase in the enamel-etching pattern when EDTA was applied for 30 s. Furthermore, these benefits could be related to the active application method. When EDTA was applied actively, the EDTA molecules were able to penetrate beyond the reach of the microbrush bristles, thus increasing the dissolution of the smear layer due to the fluid dynamics of the acid on the surface. On the other hand, pre-conditioning with EDTA did not influence the in situ DC of the adhesives; thus the third null hypothesis was accepted. It is known that when universal adhesives are applied actively, as in the present study, they improve the interaction of resin monomers with prismatic and interprismatic areas, independent of the type of universal adhesive used. Active application carryies fresh resin monomers to the deeper enamel layers. This finding was previously observed in both sound and fluorotic enamel when universal adhesives were used. In addition, active application may increase outward solvent diffusion, mainly for adhesives composed of solvents with low vapor pressures. This solvent evaporation may allow room for changes in polymer topology by reducing the intrinsic fraction of nanopores, enabling increased cross linking and improved mechanical properties of the polymer inside the enamel hybrid layer. Of the different universal adhesives compared, SBU showed the highest μSBS in fluorotic enamel. Additionally, SBU was the only adhesive used, and after pre-conditioning fluorotic enamel with EDTA, it showed efficacy similar to that on sound enamel. SBU contains a methacrylate-modified polyprenoic acid copolymer (VCP) that potentiates the chemical interaction of SBU with hydroxyapatite once it interacts with hydroxyapatite through an exchange of calcium and phosphate ions. , Thus, we hypothesized that even if the amount of hydroxyapatite is less in fluorotic enamel, the presence of VCP was sufficient to improve the chemical and micromechanical retention. In general, FBU and IBU showed a lower adhesive performance when compared to CUB and SBU under all experimental conditions. This could be attributed to the composition of the universal adhesives used in the present study. CUB and SBU contained a 10-methacryloyloxydecyl dihydrogen phosphate (MDP)-based adhesive, whereas the product information sheet of FBU showed that it did not contain 10-MDP. This acidic monomer is responsible for the chemical interaction with hydroxyapatite and forms a hydrolytically stable nanolayer with calcium, which increases the mechanical strength and protects against hydrolysis. IBU has a pH of 1.6, which is lower than that of the other universal adhesives evaluated in this study, and it contains 10-MDP. However, IBU is a 2-hydroxyethyl methacrylate (HEMA)-free adhesive. Although promising results have been reported for HEMA-free adhesives in terms of bond strength, they are more prone to phase separation at the interface. In addition, IBU contains acetone as the solvent. Therefore, active adhesive application could accelerate solvent evaporation and impair the efficacy of adhesive penetration at the resin-enamel interface. In the present study, the microshear bond strength test (µSBS) was used. This test is suitable for use with smaller bonding areas (around 1mm 2 ), which better concentrates the stress generated when compared to macro tests, as does the microtensile bond strength (µTBS); furthermore, both tests allow make it possible to evaluate multiple test specimens from each tooth. A significant advantage to the µSBS test over the microtensile bond strength test is that in the former, it was not necessary to trim the specimens before testing. According to Armstrong et al, “Trimming is very technique sensitive and it induces additional stress as reflected in the number of specimens that fail prior to testing, especially in weaker bonds or specimens with relatively brittle behavior.” Therefore, µSBS remain an especially useful test for a substrate like enamel, which is particularly sensitive to specimen preparation effects of µTBS testing. In the present study, active pre-conditioning with EDTA before application of universal adhesives showed similar efficacy to that of PA pre-conditioning of fluorotic enamel. Therefore, it could be an alternative to enamel etching without inducing accidental dentinal etching. However, it must be mentioned that this study provides only initial results. Hence, long-term in vitro studies and clinical studies should be conducted to elucidate the actual advantages of pre-conditioning fluorotic enamel with EDTA. Active pre-conditioning with EDTA could be considered an alternative to phosphoric acid, because the bond strength of universal adhesives to fluorotic enamel was similar for both conditioners, without compromising the other properties evaluated. |
Pharmacogenomics and Morphine | 574fc260-948b-4213-9f02-1c79ee395f13 | 8453761 | Pharmacology[mh] | Although clinical practice guidelines have been developed to standardize the treatment of pain, ≈10% to 30% of patients are not able to reach their pain management goals due to either inadequate analgesia or untoward side effects. There are many potential factors that can contribute to variable pain management outcomes, such as age, sex, or differences in pain perception and interindividual differences attributable to genetic variations, also known as polymorphisms. According to Angst et al, genetic effects are thought to be responsible for ≈12% to 60% of response variability in opioid treatment. Genetic polymorphisms may impact morphine pharmacokinetics (PK), which refers to the absorption, distribution, metabolism, and elimination of a drug from the body; or pharmacodynamics (PD), which refers to the effect that the drug has on the body. An example of a genetic polymorphism impacting the PK of morphine would be a mutation in a gene coding for an enzyme that metabolizes morphine that results in a reduction in the rate at which morphine is metabolized. As such, one would expect serum morphine levels to be higher in a person with this mutation when compared to a person without such a mutation, and this may increase the risk of untoward effects, such as respiratory depression. An example of a genetic polymorphism impacting the PD of morphine would be a mutation in the gene coding for the drug receptor target for morphine that results in reduced binding affinity. A person carrying this mutation may experience inadequate pain relief compared to a person carrying the normal receptor gene and may precipitate the need for a higher morphine dose or additional analgesics. Pharmacogenomics is the study of the impact that genetic polymorphisms have on drug response, and the use of clinical pharmacogenomics testing can help to elucidate genetic polymorphisms that play a role in the PK and PD for morphine.
Morphine encounters several proteins in the body, including uridine diphosphate glucuronosyltransferase family 2 member B7 (UGT2B7), organic cation transporter isoform 1 (OCT1), opioid receptor mu 1 (OPRM1), and P‐glycoprotein (P‐gp). We will discuss some of the more frequently studied genetic polymorphisms impacting these proteins and their associated functional characteristics.
UGT2B7 belongs to the uridine diphosphate glucuronosyltransferase group of phase II metabolic enzymes that are involved in the glucuronidation of compounds such as steroid hormones, bile acids, retinoids, and fatty acids. , UGT2B7 is predominantly expressed in the endoplasmic reticulum of hepatocytes and is also found in the gastrointestinal tract, kidney, pancreas, and brain. Figure shows that UGT2B7 converts morphine to M3G (90%) and morphine‐6‐glucuronide (M6G) (10%). Although M3G is the major metabolite, it does not confer any analgesic activity and cannot cross the blood‐brain barrier (BBB). , However, M3G is bioactive and is associated with neuroexcitatory effects, including allodynia, myoclonus, and seizures. M6G is an active metabolite and a potent analgesic that can cross the BBB and enhance the effects of morphine. There has been conflicting evidence in the literature regarding the functional characteristics of some UGT2B7 gene polymorphisms. Some of the most frequently studied UGT2B7 gene polymorphisms are UGT2B7 802T>C (rs7439366) and UGT2B7 –900G>A (rs7438135). The UGT2B7 802T>C polymorphism has been characterized in some studies as impacting interindividual variability in treatment outcomes. , For example, one study concluded that carriers of the UGT2B7 802T allele experienced a higher peak and extended analgesia compared to subjects homozygous for the UGT2B7 802C allele, indicating that the 802T allele may result in reduced glucuronidation activity. However, other studies do not demonstrate an association between the 802T allele and treatment outcome variability. , , Similar to the UGT2B7 –900G>A variant, there have been contradictory findings in the literature, as one study concluded that the 900A allele conferred greater activity over the wild‐type 900G allele, while another study did not find any significant impact on morphine PK due to this variant. In addition to UGT2B7 polymorphisms impacting PK, some studies have evaluated associations between UGT2B7 polymorphisms and disease risk or morphine adverse effects. Further research on UGT2B7 polymorphisms is needed to gain a better understanding of how to predict the functional capabilities of this essential morphine metabolic enzyme.
OCT1 is an influx transporter encoded by the solute carrier family 22 member 1 ( SLC22A1 ) gene. OCT1 is located in several tissues, but is abundantly expressed in the liver with much lower levels in other tissues, including intestine and skeletal muscle. Morphine is metabolized by UGT2B7 , which is predominantly located in the liver, and morphine is a high‐affinity substrate for OCT1, which is also predominantly located in the liver. Therefore, SLC22A1 gene polymorphisms that reduce the transporting capabilities of OCT1 would also theoretically reduce the metabolism of morphine, resulting in higher serum levels of morphine compared to wild‐type SLC22A1 . Many of the most frequently studied SLC22A1 gene polymorphisms confer a loss of function to the OCT1 transporter, including OCT1*2, OCT1*3, OCT1*4, OCT1*5 , and OCT1*6 . 23 According to one study, carriers of the loss‐of‐function OCT1 polymorphisms had significantly higher plasma concentrations compared to the noncarriers. Furthermore, compared to the carriers of 2 active OCT1 alleles, the area under the concentration‐time curve of morphine were 1.7‐fold higher in the carriers of no active OCT1 alleles and 1.5‐fold higher in the carriers of 1 active OCT1 allele. Among children, morphine clearance was significantly lower in homozygote carriers of loss‐of‐function OCT1 variants.
The OPRM1 gene encodes the MOR, which belongs to the G‐protein coupled receptor superfamily of transmembrane receptors. MOR is expressed throughout the brain, including the ventral tegmental area, nucleus accumbens, and the prefrontal cortex. MOR is the primary site of action for endogenous and exogenous opioid‐mediated pharmacologic responses and mediates the analgesia, tolerance, and reward effects of opioids. Additionally, due to MOR expression in the brain stem areas associated with respiration and on enteric neurons, morphine can also induce respiratory depression and inhibition of intestinal motility and intestinal secretions. Exploring polymorphisms in the OPRM1 gene would lend insight into how pharmacogenomics can impact morphine PD. One of the most frequently studied polymorphisms is the OPRM1 118 A>G variant (rs1799971), which has been shown to alter MOR signaling and/or expression in the human brain. The OPRM1 118A>G polymorphism is located in the +118 position in exon 1, which codes for the Asn40Asp substitution. There have been discordant findings in regard to the functional significance of the OPRM1 118A>G polymorphism in the scientific literature. Some studies have shown that OPRM1 118G/G homozygotes required a higher dose of morphine compared to patients with the wild‐type OPRM1 118A/A homozygotes. Campa et al examined the impact of OPRM1 polymorphisms on morphine pain relief in a cohort of 145 Italian patients and revealed that OPRM1 118A/A homozygotes were associated with a significantly higher decrease in pain compared to G/G homozygotes, and A/G heterozygotes showed no significant difference compared to G/G homozygotes. Furthermore, the study showed that patients sharing at least one OPRM1 118G allele were the poorest morphine responders and that OPRM1 118 A/A homozygotes were good responders to morphine. In another study of 207 patients using morphine for pain, seventy‐eight 118A/A homozygotes, seventeen 118A/G heterozygotes, and four 118G/G heterozygotes reported adequate pain control. The study concluded that 118GG homozygotes needed more morphine than 118A/G heterozygotes and 118A/A homozygotes. Finally, a study of 147 Taiwanese patients receiving morphine after a surgical procedure determined that 118G/G homozygotes consumed more morphine than 118A/A homozygotes during the first 48 hours postoperatively. Although the aforementioned studies along with other studies currently present in the literature have demonstrated statistically significant findings in regards to dosing differences based on OPRM1 gene polymorphisms, there are also studies that did not demonstrate differences in morphine dosing based on OPRM1 gene polymorphisms. , However, considering OPRM1 polymorphisms in regards to morphine treatment may be promising, as the existing data demonstrate that OPRM1 is moderately actionable. Further studies are needed with a larger sample size to reach a consensus regarding the functional characteristics of OPRM1 gene polymorphisms and their impact on morphine PD.
P‐gp is a member of the superfamily of adenosine triphosphate (ATP)‐binding cassette transporters and is an ATP‐dependent drug efflux pump for xenobiotic compounds with broad substrate specificity. P‐gp is encoded by the ATP‐binding cassette subfamily B member 1 ( ABCB1 ) gene and is endogenously expressed at the BBB and in the plasma membranes of cells in the small intestine, liver, and kidneys. As such, P‐gp can impact the PK of morphine, particularly regarding drug absorption from the intestines and first‐pass metabolism by the liver. P‐gp is a polymorphic protein with ≈1279 single‐nucleotide polymorphisms (SNPs) in the ABCB1 gene region, of which 62 SNPs have been identified in the coding region of ABCB1 as of April 30, 2009. The 3 most frequently studied ABCB1 SNPs in the coding region are rs1045642, rs1128503, and rs2032582. These 3 polymorphisms exhibit higher frequencies in White and Asian populations and lower frequencies in African populations. The rs1045642 variant corresponds to the ABCB1 C3435T polymorphism. In one study, it was shown that rs1045642 strongly and independently affects morphine responsiveness and that patients homozygous for the ABCB1 3435T allele and the OPRM1 118A allele were the best responders to morphine. However, another study showed that patients managed on morphine for pain associated with undergoing a cesarean section that were homozygous for the ABCB1 3435T allele trended toward a higher risk of developing persistent postoperative pain compared to the CT and CC genotypes. The rs1128503 variant corresponds to the ABCB1 C1236T polymorphism. A meta‐analysis exploring the impact of the rs1128503 variant on chemotherapy determined that patients with the CT and TT genotypes had a better response to chemotherapy than patients with wild‐type CC homozygotes. The results from the meta‐analysis may be potentially applicable to the impact of the rs1128503 variant on morphine PK. Furthermore, one study concluded that ABCB1 1236TT genotype had a significantly lower frequency of fatigue compared to the ABCB1 1236 CC homozygotes. The rs2032582 variant corresponds to the ABCB1 G2677T/A polymorphism. One study showed that the rs2032582 variant had a strong association with central side effects on morphine therapy. Another study showed that the ABCB1 2677TT homozygotes had a significantly lower frequency of fatigue while on morphine therapy compared to the wild‐type ABCB1 2677 GG homozygotes. Furthermore, there was a higher frequency of vomiting (grades 1‐3) in carriers of at least 1 ABCB1 2677G allele than in other patients. Despite the significant amount of literature available in regard to the 3 aforementioned SNPs, there has not been a consensus in regards to their phenotypic presentations. , ,
In addition to UGT2B7, OCT1, OPRM1 , and ABCB1 , there are other genes of interest cited in the literature that may impact morphine pharmacogenetics. The genes encoding for catechol‐O‐methyltransferase (COMT) and beta‐arrestin 2 (ARRB2) may be helpful in understanding morphine pharmacogenetics. The ARRB2 protein is a MOR‐interacting protein that is involved with MOR signal transduction and regulation. ARRB2 is expressed at high levels in the central nervous system and is thought to be involved with agonist‐mediated desensitization of G‐protein coupled receptors and cause specific dampening of cellular responses to stimuli, such as the opioid agonist activity of morphine on the MOR. There are 2 studies in the literature that explored the impact of ARRB2 on morphine PK, but there were no significant findings in either study. , COMT is an enzyme that catalyzes the breakdown of the catechol group on molecules, such as dopamine, norepinephrine, and epinephrine and has shown an association with pain sensitivity and analgesic response. The Val158Met substitution is the most studied polymorphism and is associated with a 3‐ to 4‐fold decrease in catalytic activity. , Therefore, the Val/Val genotype is associated with higher COMT activity than the Val/Met and Met/Met genotypes. Some studies have shown that patients expressing the Met/Met variant required less morphine to achieve analgesia, , , while another study showed that the Val/Met, but not the Met/Met genotype, was associated with reduced consumption of opioids for analgesia.
The genes UGT2B7, OCT1, OPRM1 , and ABCB1 show significant promise in predicting treatment responses for morphine therapy. The minimally effective analgesic concentration required for morphine analgesia varies from 6.3 to 53.6 ng/mL, suggesting a nearly 10‐fold difference in morphine sensitivity among individuals. , Determining morphine dosing via empirical methods can lead to delayed analgesia in some patients and potential overdose in others. Pharmacogenomics can help explain differences in morphine sensitivity that may have otherwise been misconstrued as medication nonadherence, unexplained adverse effects, or drug‐seeking behavior. For example, as previously evidenced in Campa et al, patients who were simultaneously ABCB1 T/T and OPRM1 A/A homozygotes were the best responders to morphine therapy and patients with at least one OPRM1 G allele were among the worst responders. The patients with at least 1 OPRM1 G allele may report to their clinicians that they are experiencing persistent pain and may request an increase in morphine dose or additional pain medicine. Without knowing their pharmacogenomic profile, the clinicians may mistakenly conclude that these patients are exhibiting drug‐seeking behavior, as they were dosed similarly to the other patients in the cohort. There are multiple barriers that challenge the clinical use of these genes in pharmacogenomic testing algorithms, and in a larger sense, the clinical implementation of pharmacogenomics testing with surrounding morphine therapy. First, in the case of all 4 of these genes, there is not a unanimous consensus regarding the phenotypic characterization for most of the alleles. This challenges the translation of real‐world evidence for these genes into clinical decision support tools for health care practitioners seeking to use pharmacogenomics at the bedside. Second, there are other genes of interest that require further interrogation to fully understand morphine pharmacogenomics, and there needs to be a greater understanding of the interplay between genetic polymorphisms at different genes. For example, as P‐gp is located on the liver and UGT2B7 is located inside the liver, there may be a unique impact on morphine therapy if a patient presents with an overactive P‐gp mutation and a reduced‐function UGT2B7 allele. Finally, there needs to be further interrogation of genetic targets of interest across different populations to understand differences in genotypic distribution and to identify novel polymorphisms. For example, a Brazilian cohort exhibited differences in the allelic frequency of ABCB1 3435T, where American Indians had an allelic frequency of 51.4% and people of African descent had an allelic frequency of 32.8%. Furthermore, the CYP2C19*3 allele was not present in this cohort, as CYP2C19*3 is more commonly found among Oceanian (14.64%) and East Asian (7.25%) populations. Addressing this barrier will help improve the representation of ethnically diverse populations in pharmacogenomic testing algorithms and improve their generalizability. Further research is needed to generate more real‐world evidence supporting the use of pharmacogenomics in morphine therapy and develop clinical decision‐making tools to translate research findings into tangible improvements in treatment outcomes.
The authors declare no conflicts of interest.
This project was supported (in part) by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number G12MD007597. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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An Integrated Platform for | 44dfb7e2-1573-46a1-ab17-3ba444f7e08f | 10668213 | Physiology[mh] | This paper presents an innovative and cost-effective behavioral platform designed to distinguish between different navigational elements, addressing the crucial need for better spatial cognition research paradigms. The platform’s flexibility allows for quick modifications without major software or hardware changes. Additionally, the freely available software, comprising “Maze” and “Stim Trigger” components, enables precise timestamping of neural events with behavior, while facilitating automatic reward delivery and brain stimulation control. Beyond spatial cognition assessment, the platform’s adaptability extends to nonspatial behavioral testing. The authors’ intention in openly sharing this software is to stimulate collaboration, spur future advancements, and extend its utility to a wider community of researchers. This platform represents a significant advancement in spatial cognition research and behavioral experimentation methods. Spatial cognition is a burgeoning research field in neuroscience that has implications in memory, aging, neurodevelopmental disorders, and progressive neurologic disorders. In the 1940s, Edward C. Tolman’s pioneering experiments revolutionized our comprehension of spatial learning and cognitive mapping. Through innovative research with rats, Tolman introduced the concept of cognitive maps, intricate mental representations enabling animals to navigate and comprehend their environments . Following his pioneering work, over the past 70 years landmark experiments like the “Morris water maze” developed by Morris, illuminated the role of spatial memory in rodents . Similarly, O’Keefe and Dostrovsky’s discovery of “place cells” in the hippocampus laying the foundation for understanding neural mechanisms underlying spatial navigation. Subsequently, researchers identified “head direction cells” and “grid cells” , further enriching our knowledge of spatial cognition. These foundational studies continue to shape current spatial cognition research, inspiring innovative approaches to investigating memory, learning, and cognitive mapping in both animals and humans. Today, advancements in virtual reality technology empower researchers to simulate intricate real-world environments, revolutionizing our understanding of spatial navigation . Moreover, technology advancement has allowed the implementation of complex experimental designs that help with dissecting the innerworkings of spatial navigation behavior and its neural basis . These innovative approaches have enabled investigations into how learning and memory, aging, and brain disease or disorders intersect with spatial cognition, fostering groundbreaking insights . Spatial memory is present in most animal species, and it is a key element in how individuals interact with their surroundings . The significance of spatial navigation across species can be observed in the wide variety of strategies that different species showcase, such as individual approaches, like those observed in rats and solitarily foraging ants, and group-based strategies like the large-scale migratory behaviors of sea turtles and lepidopterans . The use of animal models is common because they provide methodological benefits, such as the ability to use invasive electrophysiological recording or imaging devices in pertinent brain regions. The use of animal models in research requires the creation of innovative tools that enable scientists to investigate new concepts related to spatial navigation, learning and memory, anxiety-like behavior, decision-making, and other behavioral variables of interest. Researchers commonly employ mazes to assess spatial cognition, learning, and memory . These include the radial arm maze, T and Y -mazes, Morris water maze, and Barnes maze, which are among the most frequently used . The design of each maze and the task’s protocol dictate which aspects of spatial memory and cognition are evaluated. The Morris water maze and Barnes maze are examples of open mazes that offer multiple paths to navigate toward a designated objective, typically a shelter or escape platform, using the cues surrounding the testing area . The task-learning process for these mazes generally relies on negative reinforcers, in which the removal or avoidance of an aversive stimulus increases the likelihood of a desired behavior recurring. In the Morris water maze, the stress induced is greater than that induced by the Barnes maze, as measured by plasma corticosterone levels. . Alternatively, the radial arm maze, the T and Y- mazes, as well as versions such as the Cincinnati maze offer restricted route options . These mazes have led to significant advances in the field, for example, place cells were first observed in a restricted-route maze . Restricted route mazes are often used to study working memory and typically use positive reinforcers like food and water to motivate behavior . Albeit with some exceptions, the afore mentioned mazes focus on allocentric (map-like) processing of space. Allocentric processing relies on distal cues or “landmarks” to create a spatial reference frame . A remarkable exception is the study published by , showing that their “starmaze” could be used to develop allocentric, and sequential-egocentric tasks . Furthermore, studies on animal models, such as rodents navigating mazes, have shown that they rely more on local cues and directional signals to guide movements, which is consistent with stimulus-response learning rather than true egocentric navigation based on self-positioning within the environment . Thus, there is a need for experimental designs that further investigate the egocentric (e.g., body centered) frame as well as the interaction between both allocentric and egocentric frames of reference. We developed a new platform to fill a need for flexibility to advance spatial cognition research using novel experimental designs and apparatuses including those that go beyond allocentric spatial location processing. It is common practice to modify mazes and protocols, as seen in combinations like a radial arm maze submerged in a water tank . That is why we created a cost-efficient maze with a design based on a circular platform, similar to those used in the Barnes maze, which, when combined with custom MATLAB software, enables researchers to quickly develop customized experimental designs both within the field of spatial cognition research and beyond. Further, this new platform can be used to automate aspects of standerd existing mazes such as the Barnes, T and Y -mazes. Recording the activity of neurons in freely moving animals during task performance provides valuable insight into how different areas of the brain communicate with each other. The brain dynamics between areas such as the hippocampus, entorhinal cortex, subiculum, thalamus, retrosplenial, and parietal cortex are known to be critical for spatial cognition and other high-level cognitive processes like learning, memory, decision-making, and attention . To record neuronal activity simultaneously, researchers use recording arrays with tetrodes or multichannel silicon probes. Additionally, silicone probes offer the ability to record interactions within layered structures more easily, which is essential for understanding brain computations . Since the first publication using this software platform with tetrodes , we have developed and integrated the software to facilitate in vivo electrophysiological experiments using several recording platforms. The tasks that have employed it so far are focused on spatial cognition; however, the platform is flexible enough to allow for testing using many paradigms such as decision-making. To achieve our goal, we implemented two commonly used electrophysiology recording platforms, Neuralynx and Open Ephys, along with two real-time video tracking approaches. We chose these platforms because they offer complementary features. Neuralynx is widely used for its excellent analog signal processing capabilities (though newer systems are capable of analog and digital processing), while Open Ephys provides a cost-effective and open-source solution for digital signal processing. Accurate interpretation of the behavioral correlates of brain signals depends on precise synchronization of video and brain signals. Neuralynx includes the necessary video tracking features, while Open Ephys can be paired with other platforms such as Bonsai, an open-source software program for real-time video analysis and more. Furthermore, our platform has built in functionality for optogenetic experiments, which can modulate brain activity with high specificity using Transistor-Transistor-Logic binary signals, generated by turning a transistor on or off (TTL), signals to trigger laser pulses at specific user defined points in the maze. Our platform provides the hardware and software components necessary to flexibly and precisely measure brain signals during custom-designed tasks in freely moving animals if dictated by the experimental design or to conduct behavioral experiments without recording brain activity. Furthermore, the prospect exists for combining it with in vivo brain imaging techniques, such as the UCLA Miniscope, although this has not yet been realized. Hardware Platform The circular platform (T-60RT, Unfinished Furniture of Wilmington) is a 60-inch diameter Parawood tabletop, 3/4 inch thick. To seal the surface and improve paint adhesion we used KILZ water-based acrylic primer. The paint used was Chalky Finish Krylon “Misty Gray.” The color was selected to provide a neutral background to offer contrast with the rodents’ coat color, which in our case is white, brown, or black for video tracking purposes. However, other colors can be used to increase this contrast for other combinations of rodent strains or to mimic the color of the proximal or distal walls. The wall is made of low-density polyethylene and has a dual function: it holds the electronic components at a proper height for the animals to interact with them, and serves as a low boundary for the animals without obstructing the view of the surroundings, helping them use distal cues and avoid unintentionally crossing the edge of the maze. Different wall heights and other surface shapes can be used to assess the role of boundaries in the hippocampal processing of space, as observed in the activity of “boundary cells” . Our software and hardware platform can work with any maze shape or apparatus. Moreover, wall color and height can be manipulated to investigate the impact of its use as a proximal cue. For example, by matching the color of the floor, the effect of walls as a proximal cue can be further reduced. Furthermore, the walls can be removed if the platform is placed high enough to reduce the chances of an animal jumping off . LED cue lights We installed 32 evenly spaced CHANZON LED lights (3 V, 20 mA) on the maze wall using eBoot JST SM 2 Pin Plugs. In our configuration, each diode is connected to a 1.1-K resistor to reduce its brightness. Different resistors can be used to adjust the LEDs to the desired brightness. The wiring of electronic components, including the LEDs, uses XHF lever connectors for safety and easy modification. The LEDs are connected to a 48-channel USB-DIO-48 module through a Sysly(c) IDC50-B breakout board . Our Maze software (MATLAB) controls 48 TTL-compatible bits in the I/O module using the AIOUSB API library (ACCES I/O). The LED lights can be used as cues during experimental procedures and to automatically calibrate the maze location and zones of interest in the camera frame. Hardware systems Liquid reward To deliver liquid rewards to the animals, we incorporated eight solenoid-operated pinch valves (Cole-Parmer), which are linked to tubes containing the liquid. These valves facilitate the dispensing of water or nutritional drinks (such as Ensure) to animals undergoing water or food restriction, respectively. The tubes are connected to uniformly spaced spouts on the maze walls, with one spout positioned over every fourth LED. The use of fewer spouts would not necessitate any modifications to the maze software. These valves are controlled using a 16-channel Digital I/O USB Module (USB-IDO-16; ACCES I/O). The Maze software (MATLAB) uses the afore-mentioned AIOUSB API library to control the delivery of the liquid (ACCES I/O). Brain stimulation or Optogenetic stimulation Stimulation of the medial forebrain bundle is a strong reinforcer that is extensively used in animal models . Various laboratories have successfully used brain stimulation as a reinforcer in spatial cognition tasks in both mice and rats . Further, optogenetics is a powerful tool for modulating brain activity with temporal and spatial specificity . We provide two options for signal to trigger stimulation: unipolar or bipolar. We use a TTL signal designed to trigger a bipolar output by a constant current stimulus isolator (SYS-A365, World Precision Instruments). A data acquisition device (USB-1208FS-Plus, Measurement Computing) gates the TTL pulses used to control stimulation parameters via MATLAB using the MATLAB Data Acquisition Toolbox. The characteristics of the stimulation, such as frequency, duration and duty cycle can be determined in two separate software packages: “Stim Trigger” (for testing stimulation parameters alone in an operant chamber) and “Maze” (for delivering brain stimulation during experiments on the maze platform; MATLAB Runtime 9.2). For further details on selecting stimulation parameters for rodents, see . Duty cycle determines the percentage of each stimulus cycle that is set as positive however the number of stimuli depends on the duration and frequency. The unipolar TTL signal from the data acquisition device can be used as input for optogenetic laser control. The device can connect to the power supply for the laser via BNC (“Bayonet Neill–Concelman”) which is a quick connect/disconnect connector used for coaxial cables. The signal features can be determined in our software similarly to those for electrical stimulation. Electrophysiology data acquisition Headstages and probes We have used a variety of configurations for silicon probes. However, we will focus on the mice configuration using a single, H5 probe (Cambridge Neurotech). We attached the probe to an implantable nano-Drive. The probe was connected to a miniamplifier via an interposer board (Cambridge Neurotech). We used a custom-made cable (Neuralynx), containing SPI and MDR50 male connectors to connect the amplifier to a commutator (Saturn, Neuralynx) which helped to reduce torsion from the freely moving animal and safeguard the integrity of the components. We used a second custom-cable to connect the commutator to either the Open Ephys Acquisition Board or the Neuralynx Digital Lynx SX acquisition system. For tetrode recording, we used recording arrays built in-house that consisted of 18 or more independently drivable tetrodes for rats or 16 independently driveable tetrodes for mice . We have used a variety of electrode interface boards to interface with Neuralynx Digital Lynx SX: EIB-72-QC-Small for mice, and EIB-72-QC-Large, EIB-27-18TT, EIB-36-16TT, HS-72-QC-LED for rat recordings (Neuralynx). Acquisition systems The Open Ephys Acquisition Board and the Digital Lynx SX by Neuralynx are two popular systems for acquiring extracellular electrophysiology data. The Open Ephys board offers an interface between up to 512 channels of data and the computer via USB connection. As the project is open source, components and assembly instructions are freely available. Alternatively, pre-assembled components and remote training can be purchased . The Digital Lynx SX offers up to 512 channels with a modular configuration that can be customized to meet the needs and budget of experimenters. Additionally, it includes a Hardware Processing Platform for real-time closed loop data processing, and other advanced experiment designs using platforms such as MATLAB . Both systems offer a range of features and flexibility, making them popular choices for researchers conducting electrophysiology experiments. Software Our software is available in an OSF repository at: https://osf.io/svtzr/ . Maze In developing our maze software, we used the App Designer platform, a visual environment in MATLAB that enables the rapid creation of graphical user interfaces. This choice provides users with the ability to modify our code package in a relatively straightforward manner to better suit their needs. Some examples of the use of this software with further explanation of the functionalities used can be found in Results. The GUI includes the following functionalities . Control of electronic hardware Users can control all electronic hardware through the GUI. The control for the valves becomes available when users select Liquid reward . If users select Brain stimulation, the panel with the stimulation settings becomes visible and editable, along with a counter for manual (user-triggered) and animal-triggered stimulation. The settings that can be modified include duration, frequency, pulse profile, and delay after entry to the rewarded zone (this feature requires the animal to remain in the reward zone for the experimenter specified delay in order for the animal to obtain a stimulation). In the “Zone coordinates” panel , buttons corresponding to each zone number allow you to turn the LEDs on and off. When turned on they will become active when the zone is the next/active in the sequence. The LED can be set to blink (or not) and the blink rate can be specified. All changes to the LED status are recorded and timestamped in the acquisition system via TTL sent from the I/O board. Set zone characteristics The software is designed around spatial zones that are used to record maze events (e.g., when the animal crosses a particular region of the maze) or trigger rewards (e.g., when the animal reaches a specific location). The GUI allows users to set the characteristics of zones of interest . Users can adjust the number of zones to be tracked, and each time an animal enters or exits a zone, the zone number (1–32) is sent via TTL in binary format to the neural signal recording system via the USB-DIO-48 board where the event is precisely timestamped. The zone radius and hysteresis can also be adjusted. Zone hysteresis temporarily increases the zone radius when an animal enters a zone, reducing the likelihood of detecting slight head movements as false zone exits. When the hysteresis option is used, once the animal leaves the zone or the reward is delivered, the zone radius returns to its previous value. The “Zones coordinates” panel displays the numbers and camera pixel coordinates of up to 32 possible zones, as well as LED control buttons. To determine the location of each zone, users have two options: they can manually enter the xy pixel coordinates into the input boxes, or they can use the automatic calibration system . With the latter option, the system detects the location of each zone-associated LED using either Cheetah or Bonsai . The LEDs are detected sequentially as they light up from 1 to 32, and the system automatically places a zone at each detected location. The IDs for the zones of interest can be entered in the “Zones” panel . The “Zones” are indicated in green font to differentiate them from the inactive zones shown in black . Associating specific LEDs with specific zones allows the user to illuminate those LEDs as cues for the animal, either on every trial or only on user-defined trials. Additionally, cue lights can be positioned out of the view of the animal so that the experimenter can use them to ensure the maze software is tracking the animal’s sequential progress through the maze accurately, or the LEDs can be turned off and not used at all. Zone-triggered rewards The GUI offers zone-triggered reward functionality. The number of rewarded zones must align with the zone IDs entered under the “Rewarded Zones” panel , and these zones must also be included in the “Zones.” At any given time, only one zone can be set to be rewarded (i.e., until the animal reaches that zone, or the experimenter manually advances the animal to the next reward zone, the subsequent reward zone, if specified, remains inactive). Once the animal or a manual zone trigger occurs, the next zone in the “Rewarded Zone” panel becomes active. The currently rewarded zone is visually marked with a blue encirclement in the “Animal tracking” panel . Reward zones can be repeated and set to activate sequentially (if multiple reward zones are in use). Randomizing the selection order of these zones is also an option. Lists can contain a mix of rewarded and unrewarded zones, allowing some zones to track and timestamp the animal’s progress through key maze segments, while others can be timestamped and automatically paired with a reward if the zone’s reward criteria are met. Users can determine the type of reward bestowed on the animal on entry into one of the active rewarded zones (up to 32 zones can be active for an experiment) by using the “Reward Type” selection buttons. Real-time tracking of animal’s position The GUI displays real-time tracking of the animal’s position in relation to user-defined maze zones of interest . In the bottom right section of the GUI, the “Animal tracking” panel takes up most of the available space. The tracker displays the location of the animal as a red dot on the axes and provides numerical values for the “X” and “Y” coordinates. If a two-color (e.g., LED) tracking system is set up, and HD tracking is enabled in either Cheetah or Bonsai, the angle of the animal’s head is also displayed in the “Angle” text box . Otherwise, the heading is recorded/displayed as 0 degrees. The head direction is visualized as a blue tangent line that shows the orientation of the head. Animal ID and comment The right section of the GUI contains the Animal ID and Comment text boxes . The contents of these boxes are saved as a variable in the settings file when a session is ended or when the “Save Config File” button is pressed. This allows the complete configuration of all parameters to be loaded from the same file and stored as a record of the experiment details for that session. Settings file All the configuration variables are saved in settings files created and loaded in the program . This can be used to quickly store and load different experimental protocols to ensure consistency across days. The settings file includes the zone locations, reward variable, animal’s ID and notes from the loaded session. The settings files are stored in .mat format and contain all the settings as variables that can be conveniently accessed with MATLAB and read in with analysis code without the need to run the Maze software. Stim Trigger “Stim Trigger” provides a simplified GUI for controlling brain stimulation parameters and triggering methods, along with manual stimulation options and a counter to keep track of the number of delivered stimulations without the need of the full featured maze software . Its main purpose is to offer an easy-to-use platform for researchers to control brain stimulation and integrate it with other behavioral equipment or software. The software provides control over electrical or optogenetic brain stimulation, allowing for both manual triggering by the experimenter and automatic triggering by the animal. This stimulation is converted into a bipolar stimulus by the stimulus isolator. Alternatively, a unipolar TTL signal can be used to regulate a constant or pulsed laser output for optogenetics. The former method is used alongside a nose poke that operates with a +5-V TTL. Moreover, a Virtual Reality maze is integrated, using tablets and an Arduino, to deliver electrical brain stimulation rewards when the animal occupies a specific location in the virtual environment ( ; Arduino). Manually triggered stimulation can also be employed to shape behavior, such as training animals to approach the nose poke. The software empowers users to configure stimulation parameters through the GUI and utilizes the data acquisition device to trigger the stimulus isolator. As explained above, the duration and frequency determine the main characteristics of the unipolar signal and the duty cycle represents the ratio of time the stimulus is on compared with the time the stimulus is off. Bonsai Bonsai is a powerful open-source software designed for processing heterogeneous streams of data ( https://bonsai-rx.org ). It is particularly well-suited for real-time video analysis because of its advanced features and flexibility. In our case, we used LEDs mounted on the recording array to determine the animal’s location and then transferred the location via a UDP port to MATLAB . Additionally, Bonsai also allows for use of visual methods to determine the animal’s position that do not rely on LEDs, as long as the animal is distinguishable from the background. The animal’s location is extracted using various functions provided by Bonsai, such as Bonsai.Vision.Threshold, Bonsai.Vision.FindContours, Bonsai.Vision.BinaryRegionAnalysis, Bonsai.Vision.LargestBinaryRegion, and MemberSelector.Centroid. To standardize for different frame sizes the location of the animal is normalized using “Size” from the Video Camera frame. The information extracted by this pipeline is sent using Bonsai.Osc.SendMessage using the UDP port created via Bonsai.Osc.CreateUdpClient. The threshold settings must be changed to use Bonsai for automatic calibration using the LEDs in the platform. In the presented workflow, we create a .csv file to save the number of frames and timestamps. The location of the animal can also be saved in this file to have a log for the timestamped animal’s location. Data availability The presented code, except analysis code, is available in our data repository in OSF, link: https://osf.io/svtzr/ . The list of components to build the platform is available on Google Sheets, link: https://docs.google.com/spreadsheets/d/1GMOYG8HO3yyJB4AWzgjLCo-qlfUHs2DzC6-nCg6M2rA/edit?usp=sharing . Platform The circular platform (T-60RT, Unfinished Furniture of Wilmington) is a 60-inch diameter Parawood tabletop, 3/4 inch thick. To seal the surface and improve paint adhesion we used KILZ water-based acrylic primer. The paint used was Chalky Finish Krylon “Misty Gray.” The color was selected to provide a neutral background to offer contrast with the rodents’ coat color, which in our case is white, brown, or black for video tracking purposes. However, other colors can be used to increase this contrast for other combinations of rodent strains or to mimic the color of the proximal or distal walls. The wall is made of low-density polyethylene and has a dual function: it holds the electronic components at a proper height for the animals to interact with them, and serves as a low boundary for the animals without obstructing the view of the surroundings, helping them use distal cues and avoid unintentionally crossing the edge of the maze. Different wall heights and other surface shapes can be used to assess the role of boundaries in the hippocampal processing of space, as observed in the activity of “boundary cells” . Our software and hardware platform can work with any maze shape or apparatus. Moreover, wall color and height can be manipulated to investigate the impact of its use as a proximal cue. For example, by matching the color of the floor, the effect of walls as a proximal cue can be further reduced. Furthermore, the walls can be removed if the platform is placed high enough to reduce the chances of an animal jumping off . The circular platform (T-60RT, Unfinished Furniture of Wilmington) is a 60-inch diameter Parawood tabletop, 3/4 inch thick. To seal the surface and improve paint adhesion we used KILZ water-based acrylic primer. The paint used was Chalky Finish Krylon “Misty Gray.” The color was selected to provide a neutral background to offer contrast with the rodents’ coat color, which in our case is white, brown, or black for video tracking purposes. However, other colors can be used to increase this contrast for other combinations of rodent strains or to mimic the color of the proximal or distal walls. The wall is made of low-density polyethylene and has a dual function: it holds the electronic components at a proper height for the animals to interact with them, and serves as a low boundary for the animals without obstructing the view of the surroundings, helping them use distal cues and avoid unintentionally crossing the edge of the maze. Different wall heights and other surface shapes can be used to assess the role of boundaries in the hippocampal processing of space, as observed in the activity of “boundary cells” . Our software and hardware platform can work with any maze shape or apparatus. Moreover, wall color and height can be manipulated to investigate the impact of its use as a proximal cue. For example, by matching the color of the floor, the effect of walls as a proximal cue can be further reduced. Furthermore, the walls can be removed if the platform is placed high enough to reduce the chances of an animal jumping off . We installed 32 evenly spaced CHANZON LED lights (3 V, 20 mA) on the maze wall using eBoot JST SM 2 Pin Plugs. In our configuration, each diode is connected to a 1.1-K resistor to reduce its brightness. Different resistors can be used to adjust the LEDs to the desired brightness. The wiring of electronic components, including the LEDs, uses XHF lever connectors for safety and easy modification. The LEDs are connected to a 48-channel USB-DIO-48 module through a Sysly(c) IDC50-B breakout board . Our Maze software (MATLAB) controls 48 TTL-compatible bits in the I/O module using the AIOUSB API library (ACCES I/O). The LED lights can be used as cues during experimental procedures and to automatically calibrate the maze location and zones of interest in the camera frame. Liquid reward To deliver liquid rewards to the animals, we incorporated eight solenoid-operated pinch valves (Cole-Parmer), which are linked to tubes containing the liquid. These valves facilitate the dispensing of water or nutritional drinks (such as Ensure) to animals undergoing water or food restriction, respectively. The tubes are connected to uniformly spaced spouts on the maze walls, with one spout positioned over every fourth LED. The use of fewer spouts would not necessitate any modifications to the maze software. These valves are controlled using a 16-channel Digital I/O USB Module (USB-IDO-16; ACCES I/O). The Maze software (MATLAB) uses the afore-mentioned AIOUSB API library to control the delivery of the liquid (ACCES I/O). Brain stimulation or Optogenetic stimulation Stimulation of the medial forebrain bundle is a strong reinforcer that is extensively used in animal models . Various laboratories have successfully used brain stimulation as a reinforcer in spatial cognition tasks in both mice and rats . Further, optogenetics is a powerful tool for modulating brain activity with temporal and spatial specificity . We provide two options for signal to trigger stimulation: unipolar or bipolar. We use a TTL signal designed to trigger a bipolar output by a constant current stimulus isolator (SYS-A365, World Precision Instruments). A data acquisition device (USB-1208FS-Plus, Measurement Computing) gates the TTL pulses used to control stimulation parameters via MATLAB using the MATLAB Data Acquisition Toolbox. The characteristics of the stimulation, such as frequency, duration and duty cycle can be determined in two separate software packages: “Stim Trigger” (for testing stimulation parameters alone in an operant chamber) and “Maze” (for delivering brain stimulation during experiments on the maze platform; MATLAB Runtime 9.2). For further details on selecting stimulation parameters for rodents, see . Duty cycle determines the percentage of each stimulus cycle that is set as positive however the number of stimuli depends on the duration and frequency. The unipolar TTL signal from the data acquisition device can be used as input for optogenetic laser control. The device can connect to the power supply for the laser via BNC (“Bayonet Neill–Concelman”) which is a quick connect/disconnect connector used for coaxial cables. The signal features can be determined in our software similarly to those for electrical stimulation. To deliver liquid rewards to the animals, we incorporated eight solenoid-operated pinch valves (Cole-Parmer), which are linked to tubes containing the liquid. These valves facilitate the dispensing of water or nutritional drinks (such as Ensure) to animals undergoing water or food restriction, respectively. The tubes are connected to uniformly spaced spouts on the maze walls, with one spout positioned over every fourth LED. The use of fewer spouts would not necessitate any modifications to the maze software. These valves are controlled using a 16-channel Digital I/O USB Module (USB-IDO-16; ACCES I/O). The Maze software (MATLAB) uses the afore-mentioned AIOUSB API library to control the delivery of the liquid (ACCES I/O). Stimulation of the medial forebrain bundle is a strong reinforcer that is extensively used in animal models . Various laboratories have successfully used brain stimulation as a reinforcer in spatial cognition tasks in both mice and rats . Further, optogenetics is a powerful tool for modulating brain activity with temporal and spatial specificity . We provide two options for signal to trigger stimulation: unipolar or bipolar. We use a TTL signal designed to trigger a bipolar output by a constant current stimulus isolator (SYS-A365, World Precision Instruments). A data acquisition device (USB-1208FS-Plus, Measurement Computing) gates the TTL pulses used to control stimulation parameters via MATLAB using the MATLAB Data Acquisition Toolbox. The characteristics of the stimulation, such as frequency, duration and duty cycle can be determined in two separate software packages: “Stim Trigger” (for testing stimulation parameters alone in an operant chamber) and “Maze” (for delivering brain stimulation during experiments on the maze platform; MATLAB Runtime 9.2). For further details on selecting stimulation parameters for rodents, see . Duty cycle determines the percentage of each stimulus cycle that is set as positive however the number of stimuli depends on the duration and frequency. The unipolar TTL signal from the data acquisition device can be used as input for optogenetic laser control. The device can connect to the power supply for the laser via BNC (“Bayonet Neill–Concelman”) which is a quick connect/disconnect connector used for coaxial cables. The signal features can be determined in our software similarly to those for electrical stimulation. Headstages and probes We have used a variety of configurations for silicon probes. However, we will focus on the mice configuration using a single, H5 probe (Cambridge Neurotech). We attached the probe to an implantable nano-Drive. The probe was connected to a miniamplifier via an interposer board (Cambridge Neurotech). We used a custom-made cable (Neuralynx), containing SPI and MDR50 male connectors to connect the amplifier to a commutator (Saturn, Neuralynx) which helped to reduce torsion from the freely moving animal and safeguard the integrity of the components. We used a second custom-cable to connect the commutator to either the Open Ephys Acquisition Board or the Neuralynx Digital Lynx SX acquisition system. For tetrode recording, we used recording arrays built in-house that consisted of 18 or more independently drivable tetrodes for rats or 16 independently driveable tetrodes for mice . We have used a variety of electrode interface boards to interface with Neuralynx Digital Lynx SX: EIB-72-QC-Small for mice, and EIB-72-QC-Large, EIB-27-18TT, EIB-36-16TT, HS-72-QC-LED for rat recordings (Neuralynx). Acquisition systems The Open Ephys Acquisition Board and the Digital Lynx SX by Neuralynx are two popular systems for acquiring extracellular electrophysiology data. The Open Ephys board offers an interface between up to 512 channels of data and the computer via USB connection. As the project is open source, components and assembly instructions are freely available. Alternatively, pre-assembled components and remote training can be purchased . The Digital Lynx SX offers up to 512 channels with a modular configuration that can be customized to meet the needs and budget of experimenters. Additionally, it includes a Hardware Processing Platform for real-time closed loop data processing, and other advanced experiment designs using platforms such as MATLAB . Both systems offer a range of features and flexibility, making them popular choices for researchers conducting electrophysiology experiments. We have used a variety of configurations for silicon probes. However, we will focus on the mice configuration using a single, H5 probe (Cambridge Neurotech). We attached the probe to an implantable nano-Drive. The probe was connected to a miniamplifier via an interposer board (Cambridge Neurotech). We used a custom-made cable (Neuralynx), containing SPI and MDR50 male connectors to connect the amplifier to a commutator (Saturn, Neuralynx) which helped to reduce torsion from the freely moving animal and safeguard the integrity of the components. We used a second custom-cable to connect the commutator to either the Open Ephys Acquisition Board or the Neuralynx Digital Lynx SX acquisition system. For tetrode recording, we used recording arrays built in-house that consisted of 18 or more independently drivable tetrodes for rats or 16 independently driveable tetrodes for mice . We have used a variety of electrode interface boards to interface with Neuralynx Digital Lynx SX: EIB-72-QC-Small for mice, and EIB-72-QC-Large, EIB-27-18TT, EIB-36-16TT, HS-72-QC-LED for rat recordings (Neuralynx). The Open Ephys Acquisition Board and the Digital Lynx SX by Neuralynx are two popular systems for acquiring extracellular electrophysiology data. The Open Ephys board offers an interface between up to 512 channels of data and the computer via USB connection. As the project is open source, components and assembly instructions are freely available. Alternatively, pre-assembled components and remote training can be purchased . The Digital Lynx SX offers up to 512 channels with a modular configuration that can be customized to meet the needs and budget of experimenters. Additionally, it includes a Hardware Processing Platform for real-time closed loop data processing, and other advanced experiment designs using platforms such as MATLAB . Both systems offer a range of features and flexibility, making them popular choices for researchers conducting electrophysiology experiments. Our software is available in an OSF repository at: https://osf.io/svtzr/ . Maze In developing our maze software, we used the App Designer platform, a visual environment in MATLAB that enables the rapid creation of graphical user interfaces. This choice provides users with the ability to modify our code package in a relatively straightforward manner to better suit their needs. Some examples of the use of this software with further explanation of the functionalities used can be found in Results. The GUI includes the following functionalities . Control of electronic hardware Users can control all electronic hardware through the GUI. The control for the valves becomes available when users select Liquid reward . If users select Brain stimulation, the panel with the stimulation settings becomes visible and editable, along with a counter for manual (user-triggered) and animal-triggered stimulation. The settings that can be modified include duration, frequency, pulse profile, and delay after entry to the rewarded zone (this feature requires the animal to remain in the reward zone for the experimenter specified delay in order for the animal to obtain a stimulation). In the “Zone coordinates” panel , buttons corresponding to each zone number allow you to turn the LEDs on and off. When turned on they will become active when the zone is the next/active in the sequence. The LED can be set to blink (or not) and the blink rate can be specified. All changes to the LED status are recorded and timestamped in the acquisition system via TTL sent from the I/O board. Set zone characteristics The software is designed around spatial zones that are used to record maze events (e.g., when the animal crosses a particular region of the maze) or trigger rewards (e.g., when the animal reaches a specific location). The GUI allows users to set the characteristics of zones of interest . Users can adjust the number of zones to be tracked, and each time an animal enters or exits a zone, the zone number (1–32) is sent via TTL in binary format to the neural signal recording system via the USB-DIO-48 board where the event is precisely timestamped. The zone radius and hysteresis can also be adjusted. Zone hysteresis temporarily increases the zone radius when an animal enters a zone, reducing the likelihood of detecting slight head movements as false zone exits. When the hysteresis option is used, once the animal leaves the zone or the reward is delivered, the zone radius returns to its previous value. The “Zones coordinates” panel displays the numbers and camera pixel coordinates of up to 32 possible zones, as well as LED control buttons. To determine the location of each zone, users have two options: they can manually enter the xy pixel coordinates into the input boxes, or they can use the automatic calibration system . With the latter option, the system detects the location of each zone-associated LED using either Cheetah or Bonsai . The LEDs are detected sequentially as they light up from 1 to 32, and the system automatically places a zone at each detected location. The IDs for the zones of interest can be entered in the “Zones” panel . The “Zones” are indicated in green font to differentiate them from the inactive zones shown in black . Associating specific LEDs with specific zones allows the user to illuminate those LEDs as cues for the animal, either on every trial or only on user-defined trials. Additionally, cue lights can be positioned out of the view of the animal so that the experimenter can use them to ensure the maze software is tracking the animal’s sequential progress through the maze accurately, or the LEDs can be turned off and not used at all. Zone-triggered rewards The GUI offers zone-triggered reward functionality. The number of rewarded zones must align with the zone IDs entered under the “Rewarded Zones” panel , and these zones must also be included in the “Zones.” At any given time, only one zone can be set to be rewarded (i.e., until the animal reaches that zone, or the experimenter manually advances the animal to the next reward zone, the subsequent reward zone, if specified, remains inactive). Once the animal or a manual zone trigger occurs, the next zone in the “Rewarded Zone” panel becomes active. The currently rewarded zone is visually marked with a blue encirclement in the “Animal tracking” panel . Reward zones can be repeated and set to activate sequentially (if multiple reward zones are in use). Randomizing the selection order of these zones is also an option. Lists can contain a mix of rewarded and unrewarded zones, allowing some zones to track and timestamp the animal’s progress through key maze segments, while others can be timestamped and automatically paired with a reward if the zone’s reward criteria are met. Users can determine the type of reward bestowed on the animal on entry into one of the active rewarded zones (up to 32 zones can be active for an experiment) by using the “Reward Type” selection buttons. Real-time tracking of animal’s position The GUI displays real-time tracking of the animal’s position in relation to user-defined maze zones of interest . In the bottom right section of the GUI, the “Animal tracking” panel takes up most of the available space. The tracker displays the location of the animal as a red dot on the axes and provides numerical values for the “X” and “Y” coordinates. If a two-color (e.g., LED) tracking system is set up, and HD tracking is enabled in either Cheetah or Bonsai, the angle of the animal’s head is also displayed in the “Angle” text box . Otherwise, the heading is recorded/displayed as 0 degrees. The head direction is visualized as a blue tangent line that shows the orientation of the head. Animal ID and comment The right section of the GUI contains the Animal ID and Comment text boxes . The contents of these boxes are saved as a variable in the settings file when a session is ended or when the “Save Config File” button is pressed. This allows the complete configuration of all parameters to be loaded from the same file and stored as a record of the experiment details for that session. Settings file All the configuration variables are saved in settings files created and loaded in the program . This can be used to quickly store and load different experimental protocols to ensure consistency across days. The settings file includes the zone locations, reward variable, animal’s ID and notes from the loaded session. The settings files are stored in .mat format and contain all the settings as variables that can be conveniently accessed with MATLAB and read in with analysis code without the need to run the Maze software. In developing our maze software, we used the App Designer platform, a visual environment in MATLAB that enables the rapid creation of graphical user interfaces. This choice provides users with the ability to modify our code package in a relatively straightforward manner to better suit their needs. Some examples of the use of this software with further explanation of the functionalities used can be found in Results. The GUI includes the following functionalities . Control of electronic hardware Users can control all electronic hardware through the GUI. The control for the valves becomes available when users select Liquid reward . If users select Brain stimulation, the panel with the stimulation settings becomes visible and editable, along with a counter for manual (user-triggered) and animal-triggered stimulation. The settings that can be modified include duration, frequency, pulse profile, and delay after entry to the rewarded zone (this feature requires the animal to remain in the reward zone for the experimenter specified delay in order for the animal to obtain a stimulation). In the “Zone coordinates” panel , buttons corresponding to each zone number allow you to turn the LEDs on and off. When turned on they will become active when the zone is the next/active in the sequence. The LED can be set to blink (or not) and the blink rate can be specified. All changes to the LED status are recorded and timestamped in the acquisition system via TTL sent from the I/O board. Set zone characteristics The software is designed around spatial zones that are used to record maze events (e.g., when the animal crosses a particular region of the maze) or trigger rewards (e.g., when the animal reaches a specific location). The GUI allows users to set the characteristics of zones of interest . Users can adjust the number of zones to be tracked, and each time an animal enters or exits a zone, the zone number (1–32) is sent via TTL in binary format to the neural signal recording system via the USB-DIO-48 board where the event is precisely timestamped. The zone radius and hysteresis can also be adjusted. Zone hysteresis temporarily increases the zone radius when an animal enters a zone, reducing the likelihood of detecting slight head movements as false zone exits. When the hysteresis option is used, once the animal leaves the zone or the reward is delivered, the zone radius returns to its previous value. The “Zones coordinates” panel displays the numbers and camera pixel coordinates of up to 32 possible zones, as well as LED control buttons. To determine the location of each zone, users have two options: they can manually enter the xy pixel coordinates into the input boxes, or they can use the automatic calibration system . With the latter option, the system detects the location of each zone-associated LED using either Cheetah or Bonsai . The LEDs are detected sequentially as they light up from 1 to 32, and the system automatically places a zone at each detected location. The IDs for the zones of interest can be entered in the “Zones” panel . The “Zones” are indicated in green font to differentiate them from the inactive zones shown in black . Associating specific LEDs with specific zones allows the user to illuminate those LEDs as cues for the animal, either on every trial or only on user-defined trials. Additionally, cue lights can be positioned out of the view of the animal so that the experimenter can use them to ensure the maze software is tracking the animal’s sequential progress through the maze accurately, or the LEDs can be turned off and not used at all. Zone-triggered rewards The GUI offers zone-triggered reward functionality. The number of rewarded zones must align with the zone IDs entered under the “Rewarded Zones” panel , and these zones must also be included in the “Zones.” At any given time, only one zone can be set to be rewarded (i.e., until the animal reaches that zone, or the experimenter manually advances the animal to the next reward zone, the subsequent reward zone, if specified, remains inactive). Once the animal or a manual zone trigger occurs, the next zone in the “Rewarded Zone” panel becomes active. The currently rewarded zone is visually marked with a blue encirclement in the “Animal tracking” panel . Reward zones can be repeated and set to activate sequentially (if multiple reward zones are in use). Randomizing the selection order of these zones is also an option. Lists can contain a mix of rewarded and unrewarded zones, allowing some zones to track and timestamp the animal’s progress through key maze segments, while others can be timestamped and automatically paired with a reward if the zone’s reward criteria are met. Users can determine the type of reward bestowed on the animal on entry into one of the active rewarded zones (up to 32 zones can be active for an experiment) by using the “Reward Type” selection buttons. Real-time tracking of animal’s position The GUI displays real-time tracking of the animal’s position in relation to user-defined maze zones of interest . In the bottom right section of the GUI, the “Animal tracking” panel takes up most of the available space. The tracker displays the location of the animal as a red dot on the axes and provides numerical values for the “X” and “Y” coordinates. If a two-color (e.g., LED) tracking system is set up, and HD tracking is enabled in either Cheetah or Bonsai, the angle of the animal’s head is also displayed in the “Angle” text box . Otherwise, the heading is recorded/displayed as 0 degrees. The head direction is visualized as a blue tangent line that shows the orientation of the head. Animal ID and comment The right section of the GUI contains the Animal ID and Comment text boxes . The contents of these boxes are saved as a variable in the settings file when a session is ended or when the “Save Config File” button is pressed. This allows the complete configuration of all parameters to be loaded from the same file and stored as a record of the experiment details for that session. Settings file All the configuration variables are saved in settings files created and loaded in the program . This can be used to quickly store and load different experimental protocols to ensure consistency across days. The settings file includes the zone locations, reward variable, animal’s ID and notes from the loaded session. The settings files are stored in .mat format and contain all the settings as variables that can be conveniently accessed with MATLAB and read in with analysis code without the need to run the Maze software. Users can control all electronic hardware through the GUI. The control for the valves becomes available when users select Liquid reward . If users select Brain stimulation, the panel with the stimulation settings becomes visible and editable, along with a counter for manual (user-triggered) and animal-triggered stimulation. The settings that can be modified include duration, frequency, pulse profile, and delay after entry to the rewarded zone (this feature requires the animal to remain in the reward zone for the experimenter specified delay in order for the animal to obtain a stimulation). In the “Zone coordinates” panel , buttons corresponding to each zone number allow you to turn the LEDs on and off. When turned on they will become active when the zone is the next/active in the sequence. The LED can be set to blink (or not) and the blink rate can be specified. All changes to the LED status are recorded and timestamped in the acquisition system via TTL sent from the I/O board. The software is designed around spatial zones that are used to record maze events (e.g., when the animal crosses a particular region of the maze) or trigger rewards (e.g., when the animal reaches a specific location). The GUI allows users to set the characteristics of zones of interest . Users can adjust the number of zones to be tracked, and each time an animal enters or exits a zone, the zone number (1–32) is sent via TTL in binary format to the neural signal recording system via the USB-DIO-48 board where the event is precisely timestamped. The zone radius and hysteresis can also be adjusted. Zone hysteresis temporarily increases the zone radius when an animal enters a zone, reducing the likelihood of detecting slight head movements as false zone exits. When the hysteresis option is used, once the animal leaves the zone or the reward is delivered, the zone radius returns to its previous value. The “Zones coordinates” panel displays the numbers and camera pixel coordinates of up to 32 possible zones, as well as LED control buttons. To determine the location of each zone, users have two options: they can manually enter the xy pixel coordinates into the input boxes, or they can use the automatic calibration system . With the latter option, the system detects the location of each zone-associated LED using either Cheetah or Bonsai . The LEDs are detected sequentially as they light up from 1 to 32, and the system automatically places a zone at each detected location. The IDs for the zones of interest can be entered in the “Zones” panel . The “Zones” are indicated in green font to differentiate them from the inactive zones shown in black . Associating specific LEDs with specific zones allows the user to illuminate those LEDs as cues for the animal, either on every trial or only on user-defined trials. Additionally, cue lights can be positioned out of the view of the animal so that the experimenter can use them to ensure the maze software is tracking the animal’s sequential progress through the maze accurately, or the LEDs can be turned off and not used at all. The GUI offers zone-triggered reward functionality. The number of rewarded zones must align with the zone IDs entered under the “Rewarded Zones” panel , and these zones must also be included in the “Zones.” At any given time, only one zone can be set to be rewarded (i.e., until the animal reaches that zone, or the experimenter manually advances the animal to the next reward zone, the subsequent reward zone, if specified, remains inactive). Once the animal or a manual zone trigger occurs, the next zone in the “Rewarded Zone” panel becomes active. The currently rewarded zone is visually marked with a blue encirclement in the “Animal tracking” panel . Reward zones can be repeated and set to activate sequentially (if multiple reward zones are in use). Randomizing the selection order of these zones is also an option. Lists can contain a mix of rewarded and unrewarded zones, allowing some zones to track and timestamp the animal’s progress through key maze segments, while others can be timestamped and automatically paired with a reward if the zone’s reward criteria are met. Users can determine the type of reward bestowed on the animal on entry into one of the active rewarded zones (up to 32 zones can be active for an experiment) by using the “Reward Type” selection buttons. The GUI displays real-time tracking of the animal’s position in relation to user-defined maze zones of interest . In the bottom right section of the GUI, the “Animal tracking” panel takes up most of the available space. The tracker displays the location of the animal as a red dot on the axes and provides numerical values for the “X” and “Y” coordinates. If a two-color (e.g., LED) tracking system is set up, and HD tracking is enabled in either Cheetah or Bonsai, the angle of the animal’s head is also displayed in the “Angle” text box . Otherwise, the heading is recorded/displayed as 0 degrees. The head direction is visualized as a blue tangent line that shows the orientation of the head. The right section of the GUI contains the Animal ID and Comment text boxes . The contents of these boxes are saved as a variable in the settings file when a session is ended or when the “Save Config File” button is pressed. This allows the complete configuration of all parameters to be loaded from the same file and stored as a record of the experiment details for that session. All the configuration variables are saved in settings files created and loaded in the program . This can be used to quickly store and load different experimental protocols to ensure consistency across days. The settings file includes the zone locations, reward variable, animal’s ID and notes from the loaded session. The settings files are stored in .mat format and contain all the settings as variables that can be conveniently accessed with MATLAB and read in with analysis code without the need to run the Maze software. “Stim Trigger” provides a simplified GUI for controlling brain stimulation parameters and triggering methods, along with manual stimulation options and a counter to keep track of the number of delivered stimulations without the need of the full featured maze software . Its main purpose is to offer an easy-to-use platform for researchers to control brain stimulation and integrate it with other behavioral equipment or software. The software provides control over electrical or optogenetic brain stimulation, allowing for both manual triggering by the experimenter and automatic triggering by the animal. This stimulation is converted into a bipolar stimulus by the stimulus isolator. Alternatively, a unipolar TTL signal can be used to regulate a constant or pulsed laser output for optogenetics. The former method is used alongside a nose poke that operates with a +5-V TTL. Moreover, a Virtual Reality maze is integrated, using tablets and an Arduino, to deliver electrical brain stimulation rewards when the animal occupies a specific location in the virtual environment ( ; Arduino). Manually triggered stimulation can also be employed to shape behavior, such as training animals to approach the nose poke. The software empowers users to configure stimulation parameters through the GUI and utilizes the data acquisition device to trigger the stimulus isolator. As explained above, the duration and frequency determine the main characteristics of the unipolar signal and the duty cycle represents the ratio of time the stimulus is on compared with the time the stimulus is off. Bonsai is a powerful open-source software designed for processing heterogeneous streams of data ( https://bonsai-rx.org ). It is particularly well-suited for real-time video analysis because of its advanced features and flexibility. In our case, we used LEDs mounted on the recording array to determine the animal’s location and then transferred the location via a UDP port to MATLAB . Additionally, Bonsai also allows for use of visual methods to determine the animal’s position that do not rely on LEDs, as long as the animal is distinguishable from the background. The animal’s location is extracted using various functions provided by Bonsai, such as Bonsai.Vision.Threshold, Bonsai.Vision.FindContours, Bonsai.Vision.BinaryRegionAnalysis, Bonsai.Vision.LargestBinaryRegion, and MemberSelector.Centroid. To standardize for different frame sizes the location of the animal is normalized using “Size” from the Video Camera frame. The information extracted by this pipeline is sent using Bonsai.Osc.SendMessage using the UDP port created via Bonsai.Osc.CreateUdpClient. The threshold settings must be changed to use Bonsai for automatic calibration using the LEDs in the platform. In the presented workflow, we create a .csv file to save the number of frames and timestamps. The location of the animal can also be saved in this file to have a log for the timestamped animal’s location. The presented code, except analysis code, is available in our data repository in OSF, link: https://osf.io/svtzr/ . The list of components to build the platform is available on Google Sheets, link: https://docs.google.com/spreadsheets/d/1GMOYG8HO3yyJB4AWzgjLCo-qlfUHs2DzC6-nCg6M2rA/edit?usp=sharing . To demonstrate the potential of our platform we will describe a number of applications for these software packages across three laboratories and four institutions. The first will be of behavioral data collected from a “spatial reorientation” task that requires mice to use distal cues to get reoriented in space while running down a linear track . Furthermore, we would like to highlight additional publications that have used this platform. These include three publications employing a sequence task in rats , one publication using a task that requires rats to navigate toward a randomly selected cue light out of 32 possible options , and one using both . It is worth noting that all of these publications, involving both the sequence task and the random lights task, incorporated a pre-training phase training rats to shuttle between the ends of a linear track. Additionally, we present an instance where the “Stim Trigger” software was combined with a virtual maze to conduct experiments with mice . We also include an example with the object-place paired associate (OPPA) task . Finally, we describe its implementation on an unpublished task, the map-to-action transformation (MAT) task. First, we will elaborate on the application of this software platform for the spatial reorientation task, which was previously described, and has been used for both rats and mice . Briefly, the animal must travel back and forth over a linear track with an unmarked rewarded location. The starting point within the linear track is randomized, thus the distance to the rewarded location changes across trials. The animal is moved to a new starting location after each trial while in an enclosed start box where the animal receives a water reward for running to the end of the track and back into the start box. Before running the actual task, and after a week of recovery after medial forebrain bundle electrode implantation, mice were placed in a custom box with a nose poke port. They were trained to approach and poke their nose into port, which triggered a brain stimulation reinforcement. “Stim Trigger” controlled the characteristics of the brain stimulation like duration and frequency for each beam break. The other parameters like current and electrode wire combinations were configured on the stimulus isolator. Adjustments to these were made to achieve the highest response rate over a week. The optimal configuration was used as reinforcer for the entire length of the experiment. To run the task, the researchers used three zone markers. The configuration of the zones was the following: three tracked zones, one to start the trial (i.e., exit from the start box), one rewarded zone and one to mark the arrival at the end of the track. As the actual starting point varied in each trial by design, a manual zone skip feature was employed, triggered by a handheld device specifically designed for advancing presentation slides, to mark the beginning of each trial. The virtual location of the “Start zone” was set so the animal could not reach it, and the trial start was marked by pressing the “Next Cue” button using a handheld presentation clicker. Then, the “Rewarded Zone” became active and the animal could trigger the reward, which in this case was electrical stimulation of the medial forebrain bundle. For this application, the delay feature was used for the “Rewarded Zone” so that the animal must remain in the reward zone for a delay period to or obtained a brain stimulation reward. If the animal advances through the reward zone, or obtained a reward in the zone, then the next nonrewarded zone, called the “End Zone,” becomes active. After reaching the “End Zone,” the animal returns to the start box and consumes a water reward while the track is moved to the next randomly selected start location. Thus, at the end of the session the data for the start of the outward trajectory, entry into and exit from the reward zone, reward timestamp if any, and the time the rodent arrived at the end of the track can be extracted. A postprocessing script extracts the animal location from the video file and then calculates the velocity for each trial fixed with respect to the position relative to the reward zone. The velocity profile is visually displayed, enabling the user to identify and exclude trials with issues, such as instances of lost tracking that are too extensive to allow for accurate position estimation by the software. This exclusion process can be performed during visualization of the current session. This analysis code is available on request. The results showed that 3xTg-AD female mice performed significantly worse than non-Tg age-matched controls for the 1.5- and 2-s delays, but not for other delays . The six-month non-Tg female mice were able to identify the location of the reward zone and slowed down in preparation for stopping in the zone, whereas the six-month 3xTg-AD females did not. Overall, the study showed that six-month 3xTg-AD female mice were impaired at spatial reorientation compared with non-Tg mice. The virtual version of the task is identical except that the animal’s virtual location is restarted automatically to the next starting location from the end of the track . During the virtual task, the animal is placed on a tablet surface coated with mineral oil to facilitate smooth movement of its paws. The animal’s head is fixed to ensure that as it walks, the tablet detects the movement of its paws, thereby navigating the animal through the virtual environment, which is projected on the floor and three surrounding wall tablets. Tablet holders are 3D printed with a low-cost resin-based 3D printer and the design files for these tablet holders are available on request. The East, North and West tablets display the rest of the virtual room, which moves along with the animal locomotion. The virtual maze software was paired with “Stim Trigger” which controlled the delivery of brain stimulation as described above. Our next detailed example includes in vivo electrophysiological data. Rats were first trained on an alternation training task, where they learned to shuttle back and forth along a linear track created by walls that connect two opposite zones on the circular platform. Rats receive a brain stimulation that is delivered in at both ends of the linear track. Following the alternation training, rats underwent training on a “random lights task,” where sequences of up to 900 elements were drawn randomly with replacement from the 32 light/reward zones. Subsequently, rats were trained on the complex spatial sequence task, which involves rats learning to navigate to unmarked locations fixed in space in a specific sequence. Landmarks are distributed around the room for spatial orientation. We used a sequence (1-2-3- 4 -1-2-3- 5 -; ; ) that had a repeating path segment (1-2-3) followed by one of two distinct actions. Specifically, the rat learned in context 5 -1-2-3, to go to 4 for reward, while in context 4 -1-2-3 the rat must go to 5 . Movie 1. “Maze” software configuration for Sequence task. At the beginning of the video, a configuration file containing all the necessary settings for Sequence task is loaded. Then, the animal is connected, and electrophysiology recording and live location data are initiated. Subsequently the “Maze” program is initiated and the location of the animal is displayed in the bottom right corner of the software window. In the second part of the video, a rat completes the Sequence task by navigating between the rewarded zones. The path that the animal must travel from memory in order to obtain rewards at each zone is overlaid on the recording for easy visualization. 10.1523/ENEURO.0274-23.2023.video.1 Chromeless Video Player Thus, each action belongs to two spatial contexts, so navigation to zone 4 or 5 requires a map-to-action transformation. This emulates the common spatial memory problem one encounters when driving through an intersection and remembering the appropriate action given the current route and goals (e.g., turn left to a favorite restaurant vs right to home). Sets of three unguided (“memory”) runs through the complete 1-2-3- 4 -1-2-3- 5 sequence were interleaved with sets of three “cued” runs in which a light at each goal led the rat through the sequence . During memory runs, following an error, a light cue directs the rat to the next zone in the sequence. This complex spatial task, while likely engaging the hippocampus, hippocampal activity alone (e.g., splitter cells) is insufficient to predict the rat’s action . Note, because the sequence makes use of five zones selected from 32 evenly spaced zones distributed around the perimeter of the platform, alternate sequences which match the distance traveled for various elements of the sequence can be created or new sequences can be created by flipping and rotating the sequence to make a novel sequence (we have made use of both of these options in our experiments). The data presented here are the activity of two place cells recorded from the rat’s dorsal hippocampus while it navigated the 8-item sequence on circular platform. The cells have distinct firing patterns focused in a specific location on the platform . The animal can be trained by reinforcing their behavior with electrical medial forebrain bundle stimulation or food reward. Rats have been trained under both conditions on the three tasks described in this section. Additionally, this method allowed the researchers to detect the animal’s precise location during behavior, and record the neuronal activity with high temporal resolution, using the recording system. The next example of the use of our platform is with the object-place paired associate (OPPA) task. (previously described by ). In brief, rats are trained to travel to the end of a two-arm maze where they have to displace a specific object to obtain a reward out of two possible options. The animal must then navigate back to the center of the maze and go to the other arm. The goal of the current project is to analyze neural activity in the central platform, on each maze arm, and the choice platform where the objects are located. To do this, the Maze software collects accurate timestamps of the location of the animal, as well as entry in zones of interest. The maze software is set-up to detect movements in seven zones, one for each platform at the end of the arms, two for the maze arms, one for the central platform of the maze and two zones outside of the maze to timestamp the manual reward delivery . To obtain the location of the animal, Bonsai can send location data via UDP, as well as head direction (angle) to the maze software. Each zone entry is sent to the recording system as a TTL to obtain the precise timestamps of the maze events for post processing. The final example is the map-to-action transformation (MAT) task. Rats first learn to navigate to the reward location (R in , left) from a randomly selected set of seven start locations (S1–S7) using distal cues. The maze is surrounded by landmarks for orientation. Accurate navigation results in food or brain stimulation reward delivered at the reward location. After achieving allocentric condition criterion (over 80% correct trials for at least three out of four sessions), the transformation condition begins. In this condition, the rat is held at each start location in a translucent box for 10 s. This is done for Allocentric and Egocentric conditions to produce parallel datasets for each task. Next, an opaque box is placed over the rat while curtains are pulled obscuring distal cues ( , middle). The box is then removed, and the rat must now navigate to R while the distal cues are obscured. The hypothesis is that in this condition the animals must transform the allocentric location of R into an egocentric action sequence to reach the reward. After achieving the same criterion for the map-to-action transformation condition, the egocentric paradigm begins where the egocentric relationship between the start location and the rewarded location is maintained (e.g., 4 to 6). However, these locations are randomized for each trial while the distal cues are obscured by the curtains. There are two variations, right turn , right red and left turn, green. Each rat runs both the right turn and left turn variation separately, and the order is counterbalanced across rats. In this condition, the rat needs to develop a self-centered motor strategy to find the reward and cannot rely on any external cues which are unavailable (distal) or changed every trial (proximal). Spatial zones are positioned in “Maze” software in order to timestamp zone entry for each of the 8 arms as well as the center of the maze. Some animals are trained with food reward, while others with electrical stimulation of the medial forebrain bundle as the reinforcer. For the animals that receive medial forebrain bundle stimulation reinforcement, the delivery of the brain stimulation pulse train via TTL to the recording system is also timestamped. For all training phases, a nonrewarded zone is positioned in the center of the maze to timestamp entry into the center of the maze. In the case of the allocentric and transformation tasks, the rewarded location remains consistent throughout the session. Two rewarded zones are designated, one located within the correct zone and the other positioned outside of the maze. This ensures that on zone entry, the reward is delivered only once until the experimenter utilizes the “Next Cue” button to reactivate the rewarded zone on the maze. The zone that is positioned off the maze is also used to signal the end of an incorrect trial. Because of the continuously changing rewarded location for the egocentric task, the “Stim Trigger” software is used to deliver and timestamp the reinforcement delivery for correct trials. Furthermore, manually triggered TTLs can mark events that are not location-dependent, such as the animal placement into boxes. To do this, a wireless relay switch activated by a wireless radio frequency remote control can be used. This relay system is connected to the Neuralynx TTL acquisition board. Ten control rats have successfully completed all three paradigms of the task. Training for each phase takes a similar number of sessions, between 19 and 23. In spatial cognition research, it is essential to have the flexibility to quickly change the experimental setup without having to overhaul the software and hardware. To address this need, we present an inexpensive behavioral platform that can be paired with open-source or commercial software to create a variety of experimental setups. Our platform enables the generation of novel spatial navigation tasks, using positive reinforcement like brain stimulation, liquid, or food reward. We are presently using this platform in our laboratory to collect data using eight different mazes/experimental paradigms and there are countless more experiments that can be designed and run using this platform. Our software includes two highly flexible programs. The Maze program can use up to 32 user defined zones and deliver rewards automatically on zone entry or track progress through the zones. This program is highly synergistic with electrophysiology acquisition systems like Neuralynx and Open Ephys, as it timestamps zone entries and other behaviors using TTL signals triggered by the Maze program and delivered to Digital Lynx SX or Open Ephys Acquisition Board. The second program, “Stim Trigger,” can control brain stimulation using any type of equipment that can be paired with an Arduino board, such as a nose-poke and a virtual reality maze. Our platform distinguishes itself from other commercial and open-source software options for animal behavioral tracking by offering more than just tracking capabilities. For example, EthoVision is a commonly used video tracking software, capturing real-time movements and yielding detailed behavioral data. There are available extensions that carry a higher cost, such as EthoVisionXT, that incorporate a “Trial and hardware control” module with a USB-IO box. Noldus offers an extensive catalog for behavioral rodent studies; however, its modular software’s limitations arise when crucial modules are inaccessible, and its proprietary nature hampers cross-platform compatibility. Another example is ANY-maze, a versatile tool that supports varied animal movement tracking and behavior analyses, even within operant conditioning chambers. ANY-maze’s complete license includes updates and add-ons, and interface devices are available for hardware control. Although versatile, ANY-maze is not free and lacks intrinsic ability to synchronize with other extensively used software platforms like Python or MATLAB. Finally, our platform seamlessly integrates with Bonsai-RX and DeepLabCut, enhancing its capabilities even further. Bonsai-RX excels in real-time behavioral analysis and closed-loop experiments. It facilitates complex experimental designs through a user-friendly interface and pre-built components. Its adaptability stems from a modular structure that integrates hardware and software components, making it our choice for implementation. It allows researchers to perform real-time behavioral analysis and closed-loop experiments, while DeepLabCut’s deep learning algorithms enable accurate and automated tracking of key points on the subject’s body, allowing for precise analysis of movement and behavior. The synergy between this platform and these software solutions employing UDP connections facilitates the implementation of complex experimental setups, incorporating multiple data streams such as video tracking, electrophysiology, and optogenetics, offering researchers extensive possibilities for data analysis and visualization. We hope that the ingenuity of this approach goes beyond its impact on spatial cognition research. The adaptable behavioral platform introduced in this paper offers a wealth of possibilities for diverse nonspatial testing scenarios. By leveraging the “Maze” and “Stim Trigger” software components, researchers can seamlessly extend their investigations to many domains. For instance, in the realm of cognitive psychology, this platform could facilitate studies related to attention, memory, and decision-making. The capacity for precise time stamping of neural events coupled with automated reward delivery could also be harnessed to study reinforcement learning, habit formation, and associative learning processes. Moreover, within the field of behavioral neuroscience, the platform’s flexibility enables exploration of sensory perception or motor control. Researchers could use the brain stimulation control capability to investigate neural circuitry underlying other complex behaviors. In the context of pharmacological research, the platform might serve as a valuable tool for assessing drug effects on behavior, thereby aiding in the development of new treatments for a wide range of disorders. Classic self-stimulation paradigms can also be easily and inexpensively conducted using “Stim Trigger,” which opens many possibilities in the addiction field. The purpose of sharing these programs is 2-fold. First, to make the software available in its current state, and second, to solicit feedback from the broader community beyond our own groups, with the aim of enhancing and expanding our software package, including into fields beyond spatial cognition. We have focused on making our software compatible with open-source software and hardware like Bonsai and Open Ephys. A potential area for expansion is with another cutting-edge open-source technique, the UCLA Miniscope . It can be paired with our “Maze” software using the Miniscope V4-Data Acquisition System to synchronize Neuralynx or Bonsai (with a blinking LED for synchronization) video acquisition with the physiological data and timestamp location information. We seek to continue developing these tools and collaborating with other researchers to increase the possible applications of our work. Limitations Our software has limitations when it comes to compatibility with all experimental designs. For instance, the current version only allows for the delivery of rewards on entry to a zone or zones sequentially, but two rewarded zones cannot be available simultaneously, as we have not yet encountered a need for this functionality. While our software has been effectively used in both rats and mice, including several publications involving mice, it is important to note that the physical maze platform described in the methods section was primarily designed with larger rodents, such as rats, in mind. To address this, we propose the creation of scaled-down versions of the platform specifically tailored for smaller rodents. These scaled-down versions would function in a similar manner to the original platform, with the location and size of the zones adjusted proportionally based on the size of the camera frame. No modification of the software is needed to make use of a scaled down platform. We also plan to address compatibility issues. While the software and hardware are compatible with open-source software and hardware such as Bonsai and Open Ephys, we recognize that MATLAB is not freely available. Therefore, we aim to transition to other programming languages such as Python in the future. In the meantime, MATLAB can be used to compile the program (and we have made available a compiled version of the current program), so MATLAB is only needed when making edits to the program. While we acknowledge that a single platform may not be able to cover all experimental designs, the software’s flexible structure enables us and other users to create custom versions quickly. Our software has limitations when it comes to compatibility with all experimental designs. For instance, the current version only allows for the delivery of rewards on entry to a zone or zones sequentially, but two rewarded zones cannot be available simultaneously, as we have not yet encountered a need for this functionality. While our software has been effectively used in both rats and mice, including several publications involving mice, it is important to note that the physical maze platform described in the methods section was primarily designed with larger rodents, such as rats, in mind. To address this, we propose the creation of scaled-down versions of the platform specifically tailored for smaller rodents. These scaled-down versions would function in a similar manner to the original platform, with the location and size of the zones adjusted proportionally based on the size of the camera frame. No modification of the software is needed to make use of a scaled down platform. We also plan to address compatibility issues. While the software and hardware are compatible with open-source software and hardware such as Bonsai and Open Ephys, we recognize that MATLAB is not freely available. Therefore, we aim to transition to other programming languages such as Python in the future. In the meantime, MATLAB can be used to compile the program (and we have made available a compiled version of the current program), so MATLAB is only needed when making edits to the program. While we acknowledge that a single platform may not be able to cover all experimental designs, the software’s flexible structure enables us and other users to create custom versions quickly. |
Interdental papilla reconstruction: a systematic review | 27254358-1e4f-4a05-9925-abb6dd8c507f | 10794407 | Dental[mh] | The interdental papilla is an important anatomical part of the gingiva. It can reduce in height and can ultimately be lost due to a variety of causes which will be outlined in this introduction. This results in an open embrasure space commonly termed a ‘black triangle’. Black triangles can be highly unaesthetic and are a frequent cause of complaint by patients. An understanding of the available treatment options to manage this clinical issue is important for clinicians to ascertain. Anatomy of the interdental papilla The interdental papilla is the part of the gingiva that fills the embrasure space between the contact points of adjacent teeth. It is supported by the underlying alveolar bone and laterally by the borders of the teeth . It is comprised of masticatory mucosa and is composed of a dense connective tissue covered by oral epithelium . The shape of the interdental papilla is influenced by the contact points between adjacent teeth, the width of the interproximal tooth surfaces and the course of the cemento-enamel junction (CEJ). The interdental papilla is pyramidal in shape at the anterior teeth. In posterior regions, there are two papillae joined by a concave saddle region called a ‘col’ . The col can be either para-keratinised or non-keratinised . The papillary height decreases from the anterior to the posterior teeth due to the interproximal contact area being most coronal between the central incisors and becoming progressively more apical along the arch. In contrast, the width of the col increases from the anterior to the posterior regions. The presence of the interdental papilla contributes to the scalloped shape of the gingival margin. Animal and human studies In an experimental animal study investigating the anatomy of the interdental papilla, Kohl and Zander investigated the effects of removing the interdental papilla in rhesus monkeys. In a split mouth design, they removed all interdental soft tissue to bone in two rhesus monkeys and after 2 months gently cleaned and polished the sites. The monkeys were sacrificed and specimens were prepared to study the interdental tissues. They found that the morphology of the interdental papilla confirmed Cohen’s description and also concluded that the papilla and col reform to its original shape 8 weeks after the interdental tissues are removed. They also found that the col is non-keratinised and has a great deal of inflammation beneath it. To assess this in humans, Holmes conducted a human clinical study on 16 dental students. Specimens of excised interdental papillae were analysed. They found 30 out the 32 papillae had a concave shape in agreement with the findings of Cohen . They also found that 22 out of the 32 papillae did not regenerate back to their original height after 32–86 days with gaps present in the embrasure spaces which is in contrast to the animal study by Kohl and Zander . Role of the interdental papilla Historically, the function of the interdental papilla was thought to be only ‘deflection of food debris’. It was also theorised later that the interdental papilla could also have an important role as a barrier and defence to protect the underlying periodontal tissues . A ‘round cell infiltration’ was found in the interdental papillae examined in specimens excised from a group of dental students. The inflammatory infiltrate demonstrates a defence mechanism to the constant threat of bacterial invasion from dental plaque accumulation. The presence of the interdental papilla also plays an important role in aesthetics. A web-based study by Hochman et al. investigated the layperson’s aesthetic preference of the interdental papilla in a low smile line. The participants were 200 lay people with no job connection to the dental field. They were shown three different professional medical illustrations of the lips and teeth with a low smile line. The first figure showed the presence of the interdental papillae (Fig. ). The second figure showed an absence of interdental papillae and the presence of black triangles. The third figure showed an absence of interdental papilla with white restorations and long interproximal areas. The participants were shown the illustrations via an online survey tool and asked to select the preferred illustration. The results of the survey found that 98% of the participants preferred the presence of the interdental papilla compared to the black triangles. Ninety-two percent of participants preferred the restored long contact area compared with the black triangles and 70% preferred the natural presence of interdental papillae compared to the absent interdental papillae with white restorations and long contact points. This study demonstrates that even with a low smile line (which frequently is perceived by clinicians as being less challenging to treat), the absence of interdental papillae needs to be assessed in the smile analysis for restorative cases and that the clinical treatment of patients should include treatment options to manage missing interdental papilla. This was a simple but effective study demonstrating how a lay person can perceive the presence or absence of the interdental papilla even in a low smile line. However, limitations were that illustrations were used rather than actual clinical photographs which are much more realistic. Also, 80% of the participants were Caucasian, and a more diverse population could potentially have led to different results. Factors affecting the presence of the interdental papilla A clinical study by Tarnow et al. investigated the relationship between the distance from the most coronal point of the interdental bone crest to the apical edge of the interdental contact point and the associated presence or absence of the interdental papilla. The authors used a large sample size of 288 sites in 30 randomly selected patients. They found that as the distance (in millimetres) from the contact point to the bone crest increased, the presence of the papilla decreased. When the distance was 3–4 mm, an intact interdental papilla was present at 100% of sites. When the distance was 5 mm, an intact interdental papilla was present at 98% of sites. As the distance increased to 6 mm and above, there was partial or complete absence of the interdental papilla. For every millimetre increase, the chance of papilla presence reduced considerably. They concluded that the height of the interdental papilla is determined by the vertical height of the underlying bone. In a clinical study, Chow et al. studied 672 interproximal sites in 96 participants. Each interdental papilla was measured by a calibrated examiner and scored according to the classification and also scored as either ‘competent’ or ‘deficient’. The participants’ age, gender, ethnicity and history of orthodontic treatment were recorded also. They found that increasing age has an impact on the height of the papillae. They reported a 0.012-mm decrease in the height of the interdental papilla for every year in age. They also found that gingival thickness was related to the interdental papilla height. The presence of ‘competent’ papilla was associated with gingival thickness greater than 1.5 mm. Joshi et al. conducted a cross-sectional study assessing 150 interdental sites in 30 patients to assess factors associated with the extent of interdental papilla fill. They found that complete interdental papilla fill was significantly associated with tooth form or shape when the crown width-to-length ratio was greater than 0.88 and also when the bone crest to contact point distance of 5 mm or less. A higher gingival angle (measure of the gingival scallop) and an increased gingival thickness was significantly associated with competent papillae. Causes of loss of the interdental papilla The interdental papilla can be lost due to interproximal bone loss due to periodontitis. The treatment for periodontitis can also lead to formation of black triangles. Both non-surgical therapy and surgical therapy to treat periodontitis, especially pocket elimination or resective surgery, will lead to reduction of loss of the interdental papilla. Episodes of necrotising periodontal disease can also lead to the formation of black triangles. Iatrogenic damage such as over-contoured restorations and tissue damage from crown preparations can lead to the loss of interdental papilla. It can also be self-inflicted by the patient through traumatic brushing or overzealous use of interdental aids, pen chewing and piercings. Tooth-related factors that can cause loss of the interdental papilla are as follows: loss of the contact point, tooth malposition, abnormal tooth shape, triangular-shaped crowns, diastemas, divergent roots and over-eruption of a tooth. Orthodontic treatment can lead to loss of the interdental papilla. The prevalence of black triangle formation post-orthodontic treatment is reported to be 38% in adult patients . A systematic review by Rashid et al. aimed to assess the incidence of black triangles post-orthodontic therapy. Five studies were included and the incidence of black triangles following orthodontics was found to range from 38 to 58%. The authors reported that risk factors associated with the formation of black triangles were age, tooth-related factors, length of treatment and patient factors. Classification of the interdental papilla There can be varying degrees of loss of interdental papilla height and so a classification system for this is a useful tool for clinicians and to allow standardised care. Classifications provide a basis for diagnosis, prognosis and subsequent management. They are useful for research purposes to allow homogeneity of data and allow integration of data for purposes such as meta-analysis for systematic reviews. Nordland and Tarnow proposed a classification for the loss of interdental papillary height in 1998. It was based on three reference points: the contact point, buccal apical extent of the cemento-enamel junction (CEJ) and the interproximal CEJ. The classification is as follows: ‘Normal: the interdental papilla fills the embrasure space to the apical extent of the interdental contact point/area Class I: the tip of the interdental papilla lies between the interdental contact point and the most coronal extent of the CEJ Class II: the tip of the interdental papilla lies at/or apical to the interdental CEJ but coronal to the apical extent of the facial CEJ Class III: the tip of the interdental papilla lies level with or apical to the facial CEJ’ In 2004, Cardaropoli devised a newer classification of the interdental papilla height called the ‘Papilla presence index’ (PPI) with a scoring system from one to four. The classification is as follows: ‘Score 1: Papilla is completely present Score 2: Papilla is no longer completely present but the interdental CEJ is not visible Score 3: Papilla is no longer completely present and the interdental CEJ is visible Score 4: Papilla is no longer completely present. Both the buccal and interdental CEJ are visible’. Consequences of loss of interdental papilla The loss of the interdental papilla can cause the appearance of black triangles which can be aesthetically displeasing and lead to food impaction and phonetic problems. This can lead to a negative impact in the oral health–related quality of life and self-esteem for the patient . Introduction to study Due to its aesthetic impact, dentists often face a demand to try and manage or reconstruct the loss of interdental papilla. Treatment options for papilla reconstruction can be surgical, non-surgical or ortho-restorative in nature . However, the management of papilla reconstruction is currently unpredictable and limited with several challenges faced and there is no consensus in terms of guidelines or treatment recommendations . This systematic review on interdental papilla reconstruction aims to appraise the literature on the available treatment options to reconstruct the interdental papilla and evaluate how much evidence exists for the efficacy. The study aims to provide insight into the available treatment options and the strength of evidence for their use as a treatment option. It will allow clinicians to understand which options are available and to guide what further research is required to allow us to develop a protocol or guideline to manage loss of the interdental papilla. Aims and objectives The aim of this systematic review was to systematically assess the treatment options available for the reconstruction of the lost interdental papilla and to evaluate evidence for their efficacy.
The interdental papilla is the part of the gingiva that fills the embrasure space between the contact points of adjacent teeth. It is supported by the underlying alveolar bone and laterally by the borders of the teeth . It is comprised of masticatory mucosa and is composed of a dense connective tissue covered by oral epithelium . The shape of the interdental papilla is influenced by the contact points between adjacent teeth, the width of the interproximal tooth surfaces and the course of the cemento-enamel junction (CEJ). The interdental papilla is pyramidal in shape at the anterior teeth. In posterior regions, there are two papillae joined by a concave saddle region called a ‘col’ . The col can be either para-keratinised or non-keratinised . The papillary height decreases from the anterior to the posterior teeth due to the interproximal contact area being most coronal between the central incisors and becoming progressively more apical along the arch. In contrast, the width of the col increases from the anterior to the posterior regions. The presence of the interdental papilla contributes to the scalloped shape of the gingival margin.
In an experimental animal study investigating the anatomy of the interdental papilla, Kohl and Zander investigated the effects of removing the interdental papilla in rhesus monkeys. In a split mouth design, they removed all interdental soft tissue to bone in two rhesus monkeys and after 2 months gently cleaned and polished the sites. The monkeys were sacrificed and specimens were prepared to study the interdental tissues. They found that the morphology of the interdental papilla confirmed Cohen’s description and also concluded that the papilla and col reform to its original shape 8 weeks after the interdental tissues are removed. They also found that the col is non-keratinised and has a great deal of inflammation beneath it. To assess this in humans, Holmes conducted a human clinical study on 16 dental students. Specimens of excised interdental papillae were analysed. They found 30 out the 32 papillae had a concave shape in agreement with the findings of Cohen . They also found that 22 out of the 32 papillae did not regenerate back to their original height after 32–86 days with gaps present in the embrasure spaces which is in contrast to the animal study by Kohl and Zander .
Historically, the function of the interdental papilla was thought to be only ‘deflection of food debris’. It was also theorised later that the interdental papilla could also have an important role as a barrier and defence to protect the underlying periodontal tissues . A ‘round cell infiltration’ was found in the interdental papillae examined in specimens excised from a group of dental students. The inflammatory infiltrate demonstrates a defence mechanism to the constant threat of bacterial invasion from dental plaque accumulation. The presence of the interdental papilla also plays an important role in aesthetics. A web-based study by Hochman et al. investigated the layperson’s aesthetic preference of the interdental papilla in a low smile line. The participants were 200 lay people with no job connection to the dental field. They were shown three different professional medical illustrations of the lips and teeth with a low smile line. The first figure showed the presence of the interdental papillae (Fig. ). The second figure showed an absence of interdental papillae and the presence of black triangles. The third figure showed an absence of interdental papilla with white restorations and long interproximal areas. The participants were shown the illustrations via an online survey tool and asked to select the preferred illustration. The results of the survey found that 98% of the participants preferred the presence of the interdental papilla compared to the black triangles. Ninety-two percent of participants preferred the restored long contact area compared with the black triangles and 70% preferred the natural presence of interdental papillae compared to the absent interdental papillae with white restorations and long contact points. This study demonstrates that even with a low smile line (which frequently is perceived by clinicians as being less challenging to treat), the absence of interdental papillae needs to be assessed in the smile analysis for restorative cases and that the clinical treatment of patients should include treatment options to manage missing interdental papilla. This was a simple but effective study demonstrating how a lay person can perceive the presence or absence of the interdental papilla even in a low smile line. However, limitations were that illustrations were used rather than actual clinical photographs which are much more realistic. Also, 80% of the participants were Caucasian, and a more diverse population could potentially have led to different results.
A clinical study by Tarnow et al. investigated the relationship between the distance from the most coronal point of the interdental bone crest to the apical edge of the interdental contact point and the associated presence or absence of the interdental papilla. The authors used a large sample size of 288 sites in 30 randomly selected patients. They found that as the distance (in millimetres) from the contact point to the bone crest increased, the presence of the papilla decreased. When the distance was 3–4 mm, an intact interdental papilla was present at 100% of sites. When the distance was 5 mm, an intact interdental papilla was present at 98% of sites. As the distance increased to 6 mm and above, there was partial or complete absence of the interdental papilla. For every millimetre increase, the chance of papilla presence reduced considerably. They concluded that the height of the interdental papilla is determined by the vertical height of the underlying bone. In a clinical study, Chow et al. studied 672 interproximal sites in 96 participants. Each interdental papilla was measured by a calibrated examiner and scored according to the classification and also scored as either ‘competent’ or ‘deficient’. The participants’ age, gender, ethnicity and history of orthodontic treatment were recorded also. They found that increasing age has an impact on the height of the papillae. They reported a 0.012-mm decrease in the height of the interdental papilla for every year in age. They also found that gingival thickness was related to the interdental papilla height. The presence of ‘competent’ papilla was associated with gingival thickness greater than 1.5 mm. Joshi et al. conducted a cross-sectional study assessing 150 interdental sites in 30 patients to assess factors associated with the extent of interdental papilla fill. They found that complete interdental papilla fill was significantly associated with tooth form or shape when the crown width-to-length ratio was greater than 0.88 and also when the bone crest to contact point distance of 5 mm or less. A higher gingival angle (measure of the gingival scallop) and an increased gingival thickness was significantly associated with competent papillae.
The interdental papilla can be lost due to interproximal bone loss due to periodontitis. The treatment for periodontitis can also lead to formation of black triangles. Both non-surgical therapy and surgical therapy to treat periodontitis, especially pocket elimination or resective surgery, will lead to reduction of loss of the interdental papilla. Episodes of necrotising periodontal disease can also lead to the formation of black triangles. Iatrogenic damage such as over-contoured restorations and tissue damage from crown preparations can lead to the loss of interdental papilla. It can also be self-inflicted by the patient through traumatic brushing or overzealous use of interdental aids, pen chewing and piercings. Tooth-related factors that can cause loss of the interdental papilla are as follows: loss of the contact point, tooth malposition, abnormal tooth shape, triangular-shaped crowns, diastemas, divergent roots and over-eruption of a tooth. Orthodontic treatment can lead to loss of the interdental papilla. The prevalence of black triangle formation post-orthodontic treatment is reported to be 38% in adult patients . A systematic review by Rashid et al. aimed to assess the incidence of black triangles post-orthodontic therapy. Five studies were included and the incidence of black triangles following orthodontics was found to range from 38 to 58%. The authors reported that risk factors associated with the formation of black triangles were age, tooth-related factors, length of treatment and patient factors.
There can be varying degrees of loss of interdental papilla height and so a classification system for this is a useful tool for clinicians and to allow standardised care. Classifications provide a basis for diagnosis, prognosis and subsequent management. They are useful for research purposes to allow homogeneity of data and allow integration of data for purposes such as meta-analysis for systematic reviews. Nordland and Tarnow proposed a classification for the loss of interdental papillary height in 1998. It was based on three reference points: the contact point, buccal apical extent of the cemento-enamel junction (CEJ) and the interproximal CEJ. The classification is as follows: ‘Normal: the interdental papilla fills the embrasure space to the apical extent of the interdental contact point/area Class I: the tip of the interdental papilla lies between the interdental contact point and the most coronal extent of the CEJ Class II: the tip of the interdental papilla lies at/or apical to the interdental CEJ but coronal to the apical extent of the facial CEJ Class III: the tip of the interdental papilla lies level with or apical to the facial CEJ’ In 2004, Cardaropoli devised a newer classification of the interdental papilla height called the ‘Papilla presence index’ (PPI) with a scoring system from one to four. The classification is as follows: ‘Score 1: Papilla is completely present Score 2: Papilla is no longer completely present but the interdental CEJ is not visible Score 3: Papilla is no longer completely present and the interdental CEJ is visible Score 4: Papilla is no longer completely present. Both the buccal and interdental CEJ are visible’.
The loss of the interdental papilla can cause the appearance of black triangles which can be aesthetically displeasing and lead to food impaction and phonetic problems. This can lead to a negative impact in the oral health–related quality of life and self-esteem for the patient .
Due to its aesthetic impact, dentists often face a demand to try and manage or reconstruct the loss of interdental papilla. Treatment options for papilla reconstruction can be surgical, non-surgical or ortho-restorative in nature . However, the management of papilla reconstruction is currently unpredictable and limited with several challenges faced and there is no consensus in terms of guidelines or treatment recommendations . This systematic review on interdental papilla reconstruction aims to appraise the literature on the available treatment options to reconstruct the interdental papilla and evaluate how much evidence exists for the efficacy. The study aims to provide insight into the available treatment options and the strength of evidence for their use as a treatment option. It will allow clinicians to understand which options are available and to guide what further research is required to allow us to develop a protocol or guideline to manage loss of the interdental papilla.
The aim of this systematic review was to systematically assess the treatment options available for the reconstruction of the lost interdental papilla and to evaluate evidence for their efficacy.
A protocol was developed in adherence to the PRISMA-P checklist (Preferred Reporting Items for Systematic review and Meta-analysis Protocols) based on and the AMSTAR checklist (Assessing the Methodological Quality of Systematic Reviews) . This systematic review was registered with PROSPERO (registration number CRD42021281184). Focused question The main focused question of this review was as follows: ‘What are the available treatment options for reconstruction of the interdental papilla on natural teeth and how much evidence exists for their efficacy?’. Types of studies For this systematic review, any type of human study ranging from case reports to randomised controlled trials were included. Eligibility criteria The study selection criteria used in this systematic review were based on the PICOS method as follows: (P) The population was systemically healthy individuals with no age limit with loss of interdental papilla around natural teeth who underwent procedures aimed to reconstruct the interdental papilla. (I) Intervention: studies reporting on all forms of interventions aimed at reconstructing the interdental papilla were included. (C) Comparison: The control (if available) was a different type of intervention or no intervention. (O) Outcome variables: The following outcomes were evaluated: o Measurements of gingival level in the interdental papilla o Gingival recession o Probing pocket depth o Clinical attachment level o Bleeding on probing o Patient reported outcome measures relative to presence of the interdental papilla (S) Types of studies: any studies in humans (ranging from case reports, cohort studies to randomised controlled trials) The inclusion criteria were as follows: Studies reporting treatment aimed at reconstructing the interdental papilla around natural teeth in humans Follow up of at least 3 months post-treatment The following exclusion criteria were applied: Studies in animal models Reviews Studies focusing on dental implants Studies focusing on medically compromised patients Duplicate papers reporting data on the same sample and procedures as other publications Outcome variables The following outcomes were evaluated: Measurements of gingival level in the interdental papilla Recession Probing pocket depth Clinical attachment level Bleeding on probing Patient reported outcome measures relative to presence of the interdental papilla Risk of bias and methodological quality assessment To assess the quality of the included studies, the risk of bias was independently evaluated by two reviewers (MP and AG). The assessment tool used to assess the risk of bias varied depending on the type of study design. For randomised control trials, the Cochrane Collaborations Tool was used in which seven domains were assessed for each study and categorised into high, unclear or low risk. For case–control and cohort studies, the Newcastle Ottawa Tool was used. For case series, the Modified Delphi tool was used and for case studies the CARE checklist was utilised to assess the quality of the studies. The levels of bias were categorised as low risk, unclear risk or high risk of bias based on the parameters of the various tools used. An assessment across all key domains were summarised and carried out by two reviewers (MP and AG) and any discrepancies were resolved by discussion. Search strategy The search strategy involved searching the electronic databases Medline, Embase and the Cochrane Library Database. In addition to this, Open Grey search and manual search were also carried out with references of included papers and review articles also checked to determine any additional relevant papers. This included Journal of Clinical Periodontology, Journal of Periodontology, Journal of Dental Research and Journal of Periodontal Research. All papers up until October 2023 were included. There were no language restrictions applied on the initial search. The electronic search strategy used the following key words and MESH terms: dental papilla.mp. or exp Dental Papilla/ black triangle.mp. interdental papilla.mp. gingival recession.mp. or exp Gingival Recession/ treatment.mp. or exp Therapeutics/ management.mp. reconstruction.mp. regeneration.mp. or exp Regeneration/ repair.mp. The study selection was conducted independently by two reviewers (MP and AG) and was completed in two phases. Phase 1 involved the initial search involved screening relevant papers based on titles and abstracts that were potentially suitable and met the inclusion criteria. Any papers indicated as potentially suitable by at least one reviewer were included in the full text screening. In phase 2, the full texts of potentially suitable papers were screened again. Any papers that did not meet the inclusion criteria were excluded at this point. For any disagreements regarding the suitability of certain studies, reviewers tried to reach a consensus. In cases of continued disagreements, a third reviewer’s opinion (author RG) was sought for the final decision. After the full text screening, all suitable papers were added into a final database. A data extraction spreadsheet was used to record data from the eligible studies. In particular, the following data was recorded: Study design Number of participants Population demographics, e.g. age, gender, ethnicity Smoking status Diagnosis of participants Control group (yes/no, what intervention if any) Type of intervention Variables measured Papilla indices Follow-up time Drop-outs Outcomes of the intervention Setting Funding Conflict of interest Ethics approval/informed consent Research synthesis and method analysis Following the data extraction, the studies were analysed descriptively and similarities between the studies were determined and grouped together according to intervention type.
The main focused question of this review was as follows: ‘What are the available treatment options for reconstruction of the interdental papilla on natural teeth and how much evidence exists for their efficacy?’.
For this systematic review, any type of human study ranging from case reports to randomised controlled trials were included.
The study selection criteria used in this systematic review were based on the PICOS method as follows: (P) The population was systemically healthy individuals with no age limit with loss of interdental papilla around natural teeth who underwent procedures aimed to reconstruct the interdental papilla. (I) Intervention: studies reporting on all forms of interventions aimed at reconstructing the interdental papilla were included. (C) Comparison: The control (if available) was a different type of intervention or no intervention. (O) Outcome variables: The following outcomes were evaluated: o Measurements of gingival level in the interdental papilla o Gingival recession o Probing pocket depth o Clinical attachment level o Bleeding on probing o Patient reported outcome measures relative to presence of the interdental papilla (S) Types of studies: any studies in humans (ranging from case reports, cohort studies to randomised controlled trials) The inclusion criteria were as follows: Studies reporting treatment aimed at reconstructing the interdental papilla around natural teeth in humans Follow up of at least 3 months post-treatment The following exclusion criteria were applied: Studies in animal models Reviews Studies focusing on dental implants Studies focusing on medically compromised patients Duplicate papers reporting data on the same sample and procedures as other publications Outcome variables The following outcomes were evaluated: Measurements of gingival level in the interdental papilla Recession Probing pocket depth Clinical attachment level Bleeding on probing Patient reported outcome measures relative to presence of the interdental papilla
To assess the quality of the included studies, the risk of bias was independently evaluated by two reviewers (MP and AG). The assessment tool used to assess the risk of bias varied depending on the type of study design. For randomised control trials, the Cochrane Collaborations Tool was used in which seven domains were assessed for each study and categorised into high, unclear or low risk. For case–control and cohort studies, the Newcastle Ottawa Tool was used. For case series, the Modified Delphi tool was used and for case studies the CARE checklist was utilised to assess the quality of the studies. The levels of bias were categorised as low risk, unclear risk or high risk of bias based on the parameters of the various tools used. An assessment across all key domains were summarised and carried out by two reviewers (MP and AG) and any discrepancies were resolved by discussion.
The search strategy involved searching the electronic databases Medline, Embase and the Cochrane Library Database. In addition to this, Open Grey search and manual search were also carried out with references of included papers and review articles also checked to determine any additional relevant papers. This included Journal of Clinical Periodontology, Journal of Periodontology, Journal of Dental Research and Journal of Periodontal Research. All papers up until October 2023 were included. There were no language restrictions applied on the initial search. The electronic search strategy used the following key words and MESH terms: dental papilla.mp. or exp Dental Papilla/ black triangle.mp. interdental papilla.mp. gingival recession.mp. or exp Gingival Recession/ treatment.mp. or exp Therapeutics/ management.mp. reconstruction.mp. regeneration.mp. or exp Regeneration/ repair.mp. The study selection was conducted independently by two reviewers (MP and AG) and was completed in two phases. Phase 1 involved the initial search involved screening relevant papers based on titles and abstracts that were potentially suitable and met the inclusion criteria. Any papers indicated as potentially suitable by at least one reviewer were included in the full text screening. In phase 2, the full texts of potentially suitable papers were screened again. Any papers that did not meet the inclusion criteria were excluded at this point. For any disagreements regarding the suitability of certain studies, reviewers tried to reach a consensus. In cases of continued disagreements, a third reviewer’s opinion (author RG) was sought for the final decision. After the full text screening, all suitable papers were added into a final database. A data extraction spreadsheet was used to record data from the eligible studies. In particular, the following data was recorded: Study design Number of participants Population demographics, e.g. age, gender, ethnicity Smoking status Diagnosis of participants Control group (yes/no, what intervention if any) Type of intervention Variables measured Papilla indices Follow-up time Drop-outs Outcomes of the intervention Setting Funding Conflict of interest Ethics approval/informed consent
Following the data extraction, the studies were analysed descriptively and similarities between the studies were determined and grouped together according to intervention type.
Study selection The initial search yielded a total of 1956 citations including 2 papers selected through a manual search. After analysis of the titles and abstracts and after removal of duplicates, 64 papers remained eligible for full text analysis. The full texts were screened and 45 papers met the inclusion criteria. The kappa score was 0.89 for initial screening and 0.97 for final screening showing an excellent level of agreement. A table that only includes papers that were excluded during phase two/full text screening was added to supplementary section (Table ). The main reasons for exclusion were studies only presenting a description of a technique. One paper was a review. Study design and population Of the 44 papers included in the study, there were 7 randomised controlled trials [ , , , , ], 2 cohort studies , 19 case series [ – , , – , , ] and 17 case reports [ , – , – , – , , , ]. Fifteen papers reported on the use of hyaluronic acid [ – ], 6 papers reported on the use of platelet-rich fibrin (PRF) [ – ], 16 papers on the use of various grafting techniques [ , – , , , – , – ], 4 studies on orthodontics [ – ] and 4 studies on different modalities [ – ]. The study setting varied from various locations around the world from Asia, the Middle East, South America and Europe. Thirty-seven studies took place in university hospital settings whilst 2 studies took place in private practice settings and for 3 studies the setting was not clear. All studies were in single settings and there were no multicentre studies. The study population ranged from 1 to 143 patients and the number of defects reported ranged from 1 to 200. The follow-up times reported ranged from 3 months to 7 years. In one study , a smoker was included in one of the case reports whilst 28 studies excluded smokers and 14 studies did not report of smoking status of the participants. The outcome measures varied between studies but most commonly included black triangle height, width and surface area, percentage fill or reduction in black triangle area and change in papillary fill. Two studies by Lee et al. also reported the interdental papilla reconstruction rate. Three studies reported outcomes with change in PPI scores. One study reported on the ‘papilla esthetic score’ (PES) as an outcome. Four studies [ , , ] did not give numerical outcomes but reported the visual appearance of the papillae. Visual analog scores were reported for 4 studies [ , , ]. Tables , , , and report a description of studies with study outcomes divided according to modality of papilla reconstruction as follows: Hyaluronic acid (HA) (Table ) Fifteen of the included papers reported on the use of hyaluronic acid including 2 randomised controlled trials , 1 cohort study , 10 case series [ – ] and 2 case reports . All of the studies reported on the use of an injectable form of HA gel. Eight studies stated the manufacturers of the HA gel with two studies using Hyadent BG, 2 studies using Teosyal, 2 studies using Qi Sheng and one study using Genoss. One study reported on the use of ‘Restylane Lidocaine’ which is a ‘non-animal stabilised cross linked hyaluronic acid filler with a concentration of 20 ml/mg combined with 3% lidocaine’. The remaining studies did not state the specific brand or manufacturer of HA but termed it either as a commercially available HA or simply a hyaluronic acid gel or filler. The protocols varied for the methods in which the HA was used but broadly in most cases local anaesthetic was applied and the HA gel was injected usually 2–3 mm apically to the deficient papilla. This was repeated usually at 3 weekly intervals. Four studies repeated the intervention at 3 weeks and 6 weeks [ , , , ]. In one study, the injections were repeated at 3 weeks and at 3 months . For the two studies by Lee et al. (2006) , the HA application was repeated every 3 weeks up to five times until the papilla was mostly filled. Çankaya et al. repeated the HA injections every 3 weeks but the end-point of this was not made clear. Pitale et al. reported only 1 application of the HA injection. In the methodology reported by Singh et al. , the HA injection was repeated after the first application at the second and third weeks. The measurements made varied for each study but most commonly included black triangle height, width and surface area, percentage fill or reduction in black triangle area and change in papillary fill. Two studies by also reported the interdental papilla reconstruction rate. All studies reported an improvement in papillary fill at follow-ups ranging from 3 to 6 months with one study reporting outcomes up to 2 years. There were two randomised controlled trials within the HA group of studies. Abdelerouf et al. carried out an RCT on 10 patients with 36 papilla defects and compared the use of HA filler injection (Restylane lidocaine) with a saline injection in the control group. A series of three injections were given at 3 weekly intervals and the follow-up duration was 6 months. The results showed there was a statistically significant greater mean decrease in black triangle height for the test group at 3 months and a higher patient satisfaction VAS score at 6 months favouring the test (HA) group. However, there was no statistically significant difference at 6 months between groups. Ni et al. carried out a randomised controlled trial on 24 patients with 68 papilla defects which were randomised in a split-mouth design with the test sites receiving a series of 3 HA gel injections at 3 weekly intervals and the control sites receiving saline placebo injections. At the 12-month follow-up, they found that the height of the gingival papilla increased and the area of the black triangle reduced with the HA injections but it was not statistically significantly superior to the use of the saline injection. However, the HA-injected sites grew quicker than the saline group. Amongst other studies, Abdeloraouf et al. and Spano et al. reported on patient satisfaction using VAS scores and found scores of 45% and 62.5% in improvement of papilla perception respectively. One study (14) reported an overlay technique involving the creation of sub-periosteal tunnel from the alveolar mucosa to the affected papilla and injecting HA gel into the papilla and into the subperiosteal tunnel as a papillary augmentation technique. The mean papilla fill was 1.75 mm ± 0.5 at 6 months. 2. Platelet-rich fibrin (PRF) (Table ) Six of the included papers reported on the use of platelet-rich fibrin. These included 2 randomised controlled trials , 1 case series and 3 case reports . When combined with surgical interventions, the two randomised controlled trials within this group of studies demonstrated that PRF provides inferior results compared to the use of a connective tissue graft. However, the use of PRF was associated with less patient morbidity and greater patient satisfaction. Sharma et al. reported the results of a RCT comparing the use of the Han and Takei surgical papilla reconstruction technique in 20 defects. The control group received the Han and Takei surgical technique with a sub-epithelial connective tissue graft whilst the test group received the Han and Takei technique with PRF inserted into the pouch. At the 3-month follow-up, the mean reduction in CPTP (distance from contact point to alveolar crest) and the mean gain in papillary fill were statistically significant for group 1 compared to the PRF group 2, whilst the PRF group had less morbidity. Similarly, in a RCT by Singh et al. comparing surgical reconstruction of the interdental papilla in 40 sites with the use of PRF compared to with the use of a connective tissue graft, better results were yielded in the connective tissue graft control group. The increase in interdental papilla height was 3.10 mm (87.3%) and 3.45 mm (95.8%) and the complete papillary fill was 90% and 95% respectively. The patient satisfaction scores were higher in the PRF group. The 3 case reports and 1 case series showed favourable results with the use of PRF in combination with surgical reconstructive techniques at follow ups ranging from 3 to 6 months. 3. Soft tissue grafting (Table ) Fifteen of the included papers reported on the use surgical grafting procedures including 1 randomised controlled trial, 7 case series [ – , ] and 8 case reports [ , , – , , ]. The surgical procedures utilised included the Beagle’s technique, interproximal tunnelling, coronally advanced flap and the use of subepithelial connective tissue grafts and a free gingival graft. The Beagle’s surgical technique is described in a case report and involves creating a new papilla with partial thickness incisions palatal to the deficient papilla twice the length of the desired papilla. This is then reflected onto the labial aspect and sutured into position. The study describes a ‘much improved cosmetic situation’ which remained stable for 18 months but with a 4-mm false pocket. There are no numerical outcome measures stated to quantify the results. Chaulker et al. carried out an RCT comparing the effectiveness of the Beagle’s technique to the modified Beagle’s technique in 20 sites with class I or class II papillary recession defects in the maxillary area. The modified Beagle’s technique involves the incisions being carried out on the labial aspect rather than on the palatal side. The results at 6 months found that the modified Beagle’s technique led to increased filling of the papillary defect whilst conversely the Beagle technique led to more shrinkage of the papilla defect. This corresponds to 39.94% reduction in the area of the papillary defect in the Modified Beagle technique group and a 69.55% increase in the Beagle group. All other studies reported an improvement in papillary fill outcomes at follow-ups ranging from 4 months to 2 years with one paper reporting a 10-year outcome . 4. Orthodontic treatment (Table ) Four of the included papers reported on the use of orthodontics in the form of 1 cohort study, 1 case series and 2 case reports . Three studies reported an improvement in papillary fill at follow-ups ranging from 1 to 10 years. In a cohort study, Kandasmy et al. analysed casts of participants undergoing orthodontic treatment and compared them to casts of controls. They found that after 18 months, the height of the interdental papillae increased following palatal movement of labially placed or imbricated incisors and following the intrusion of one incisor relative to an adjacent incisor. In a study of 28 patients presenting with a diastema between the central incisors and associated loss of interdental papilla with one extruded central incisor, the combination of open flap debridement and orthodontic intrusion resulted in improved papilla presence index scores for 23 out of 28 patients at 1 year. A case report describing a multidisciplinary approach to managing interdental papilla loss between a maxillary right central and lateral incisor involved the use of surgical papilla reconstruction with a connective tissue graft and orthodontic movement. The results demonstrated 3-mm gain in papilla height and correction of the papilla architecture. A case report described the formation of a non-surgical papilla at the 1 year follow-up after periodontal treatment followed by orthodontic treatment using light force and simultaneous mesial stripping of the incisors. Other modalities Çankaya et al. reported on a RCT comparing surgical reconstruction of the interdental papilla with the use of concentrated growth factor compared to no surgical intervention. The concentrated growth factor was derived from centrifuged blood samples with the protocol described by Qiao et al. . The study reported for the test group a positive correlation with papillary thickness and the filling percentages and between the thrombocyte count and the 6- and 12-month filling percentages. McGuire et al. reported on a randomised controlled trial comparing cultured and expanded autologous fibroblast injections to a placebo and the results found no treatment effect at 4 months. However, the VAS score was superior for the test group. Other studies with reportedly favourable clinical outcomes describe the use of hemolasertherapy or the use of repeated curettage following acute necrotising ulcerative gingivitis . Due to the high heterogeneity of the studies owing to different study designs, protocols and outcome measures meta-analysis was not possible for any of the studies. The Cochrane risk of bias tool was used to assess the risk of bias of the randomised controlled trials. Seven domains were assessed for each of the papers and a traffic light system was used for each category as shown in Fig. . Four studies showed a high risk of bias whilst the remainder showed an unclear risk of bias and no papers were deemed to be low risk of bias. The Modified Delphi tool was used to assess risk of bias of case series. All papers included had at least one domain which put the paper into the overall category of high risk of bias. The Newcastle Ottawa scale was used to assess the risk of bias of cohort studies and this ranged from 8 stars to 9 stars . For the case reports, the risk of bias was assessed with the CARE checklist. A score out of 30 was made based on what was included in each case report from the checklist. Figure shows the totals for each paper. Only one paper scored 20 or above. Two papers had a low score of 12 out of 30 and the remainder were in between. This demonstrates that the quality of the case reports did not meet the highest standards based on the checklist.
The initial search yielded a total of 1956 citations including 2 papers selected through a manual search. After analysis of the titles and abstracts and after removal of duplicates, 64 papers remained eligible for full text analysis. The full texts were screened and 45 papers met the inclusion criteria. The kappa score was 0.89 for initial screening and 0.97 for final screening showing an excellent level of agreement. A table that only includes papers that were excluded during phase two/full text screening was added to supplementary section (Table ). The main reasons for exclusion were studies only presenting a description of a technique. One paper was a review.
Of the 44 papers included in the study, there were 7 randomised controlled trials [ , , , , ], 2 cohort studies , 19 case series [ – , , – , , ] and 17 case reports [ , – , – , – , , , ]. Fifteen papers reported on the use of hyaluronic acid [ – ], 6 papers reported on the use of platelet-rich fibrin (PRF) [ – ], 16 papers on the use of various grafting techniques [ , – , , , – , – ], 4 studies on orthodontics [ – ] and 4 studies on different modalities [ – ]. The study setting varied from various locations around the world from Asia, the Middle East, South America and Europe. Thirty-seven studies took place in university hospital settings whilst 2 studies took place in private practice settings and for 3 studies the setting was not clear. All studies were in single settings and there were no multicentre studies. The study population ranged from 1 to 143 patients and the number of defects reported ranged from 1 to 200. The follow-up times reported ranged from 3 months to 7 years. In one study , a smoker was included in one of the case reports whilst 28 studies excluded smokers and 14 studies did not report of smoking status of the participants. The outcome measures varied between studies but most commonly included black triangle height, width and surface area, percentage fill or reduction in black triangle area and change in papillary fill. Two studies by Lee et al. also reported the interdental papilla reconstruction rate. Three studies reported outcomes with change in PPI scores. One study reported on the ‘papilla esthetic score’ (PES) as an outcome. Four studies [ , , ] did not give numerical outcomes but reported the visual appearance of the papillae. Visual analog scores were reported for 4 studies [ , , ]. Tables , , , and report a description of studies with study outcomes divided according to modality of papilla reconstruction as follows: Hyaluronic acid (HA) (Table ) Fifteen of the included papers reported on the use of hyaluronic acid including 2 randomised controlled trials , 1 cohort study , 10 case series [ – ] and 2 case reports . All of the studies reported on the use of an injectable form of HA gel. Eight studies stated the manufacturers of the HA gel with two studies using Hyadent BG, 2 studies using Teosyal, 2 studies using Qi Sheng and one study using Genoss. One study reported on the use of ‘Restylane Lidocaine’ which is a ‘non-animal stabilised cross linked hyaluronic acid filler with a concentration of 20 ml/mg combined with 3% lidocaine’. The remaining studies did not state the specific brand or manufacturer of HA but termed it either as a commercially available HA or simply a hyaluronic acid gel or filler. The protocols varied for the methods in which the HA was used but broadly in most cases local anaesthetic was applied and the HA gel was injected usually 2–3 mm apically to the deficient papilla. This was repeated usually at 3 weekly intervals. Four studies repeated the intervention at 3 weeks and 6 weeks [ , , , ]. In one study, the injections were repeated at 3 weeks and at 3 months . For the two studies by Lee et al. (2006) , the HA application was repeated every 3 weeks up to five times until the papilla was mostly filled. Çankaya et al. repeated the HA injections every 3 weeks but the end-point of this was not made clear. Pitale et al. reported only 1 application of the HA injection. In the methodology reported by Singh et al. , the HA injection was repeated after the first application at the second and third weeks. The measurements made varied for each study but most commonly included black triangle height, width and surface area, percentage fill or reduction in black triangle area and change in papillary fill. Two studies by also reported the interdental papilla reconstruction rate. All studies reported an improvement in papillary fill at follow-ups ranging from 3 to 6 months with one study reporting outcomes up to 2 years. There were two randomised controlled trials within the HA group of studies. Abdelerouf et al. carried out an RCT on 10 patients with 36 papilla defects and compared the use of HA filler injection (Restylane lidocaine) with a saline injection in the control group. A series of three injections were given at 3 weekly intervals and the follow-up duration was 6 months. The results showed there was a statistically significant greater mean decrease in black triangle height for the test group at 3 months and a higher patient satisfaction VAS score at 6 months favouring the test (HA) group. However, there was no statistically significant difference at 6 months between groups. Ni et al. carried out a randomised controlled trial on 24 patients with 68 papilla defects which were randomised in a split-mouth design with the test sites receiving a series of 3 HA gel injections at 3 weekly intervals and the control sites receiving saline placebo injections. At the 12-month follow-up, they found that the height of the gingival papilla increased and the area of the black triangle reduced with the HA injections but it was not statistically significantly superior to the use of the saline injection. However, the HA-injected sites grew quicker than the saline group. Amongst other studies, Abdeloraouf et al. and Spano et al. reported on patient satisfaction using VAS scores and found scores of 45% and 62.5% in improvement of papilla perception respectively. One study (14) reported an overlay technique involving the creation of sub-periosteal tunnel from the alveolar mucosa to the affected papilla and injecting HA gel into the papilla and into the subperiosteal tunnel as a papillary augmentation technique. The mean papilla fill was 1.75 mm ± 0.5 at 6 months. 2. Platelet-rich fibrin (PRF) (Table ) Six of the included papers reported on the use of platelet-rich fibrin. These included 2 randomised controlled trials , 1 case series and 3 case reports . When combined with surgical interventions, the two randomised controlled trials within this group of studies demonstrated that PRF provides inferior results compared to the use of a connective tissue graft. However, the use of PRF was associated with less patient morbidity and greater patient satisfaction. Sharma et al. reported the results of a RCT comparing the use of the Han and Takei surgical papilla reconstruction technique in 20 defects. The control group received the Han and Takei surgical technique with a sub-epithelial connective tissue graft whilst the test group received the Han and Takei technique with PRF inserted into the pouch. At the 3-month follow-up, the mean reduction in CPTP (distance from contact point to alveolar crest) and the mean gain in papillary fill were statistically significant for group 1 compared to the PRF group 2, whilst the PRF group had less morbidity. Similarly, in a RCT by Singh et al. comparing surgical reconstruction of the interdental papilla in 40 sites with the use of PRF compared to with the use of a connective tissue graft, better results were yielded in the connective tissue graft control group. The increase in interdental papilla height was 3.10 mm (87.3%) and 3.45 mm (95.8%) and the complete papillary fill was 90% and 95% respectively. The patient satisfaction scores were higher in the PRF group. The 3 case reports and 1 case series showed favourable results with the use of PRF in combination with surgical reconstructive techniques at follow ups ranging from 3 to 6 months. 3. Soft tissue grafting (Table ) Fifteen of the included papers reported on the use surgical grafting procedures including 1 randomised controlled trial, 7 case series [ – , ] and 8 case reports [ , , – , , ]. The surgical procedures utilised included the Beagle’s technique, interproximal tunnelling, coronally advanced flap and the use of subepithelial connective tissue grafts and a free gingival graft. The Beagle’s surgical technique is described in a case report and involves creating a new papilla with partial thickness incisions palatal to the deficient papilla twice the length of the desired papilla. This is then reflected onto the labial aspect and sutured into position. The study describes a ‘much improved cosmetic situation’ which remained stable for 18 months but with a 4-mm false pocket. There are no numerical outcome measures stated to quantify the results. Chaulker et al. carried out an RCT comparing the effectiveness of the Beagle’s technique to the modified Beagle’s technique in 20 sites with class I or class II papillary recession defects in the maxillary area. The modified Beagle’s technique involves the incisions being carried out on the labial aspect rather than on the palatal side. The results at 6 months found that the modified Beagle’s technique led to increased filling of the papillary defect whilst conversely the Beagle technique led to more shrinkage of the papilla defect. This corresponds to 39.94% reduction in the area of the papillary defect in the Modified Beagle technique group and a 69.55% increase in the Beagle group. All other studies reported an improvement in papillary fill outcomes at follow-ups ranging from 4 months to 2 years with one paper reporting a 10-year outcome . 4. Orthodontic treatment (Table ) Four of the included papers reported on the use of orthodontics in the form of 1 cohort study, 1 case series and 2 case reports . Three studies reported an improvement in papillary fill at follow-ups ranging from 1 to 10 years. In a cohort study, Kandasmy et al. analysed casts of participants undergoing orthodontic treatment and compared them to casts of controls. They found that after 18 months, the height of the interdental papillae increased following palatal movement of labially placed or imbricated incisors and following the intrusion of one incisor relative to an adjacent incisor. In a study of 28 patients presenting with a diastema between the central incisors and associated loss of interdental papilla with one extruded central incisor, the combination of open flap debridement and orthodontic intrusion resulted in improved papilla presence index scores for 23 out of 28 patients at 1 year. A case report describing a multidisciplinary approach to managing interdental papilla loss between a maxillary right central and lateral incisor involved the use of surgical papilla reconstruction with a connective tissue graft and orthodontic movement. The results demonstrated 3-mm gain in papilla height and correction of the papilla architecture. A case report described the formation of a non-surgical papilla at the 1 year follow-up after periodontal treatment followed by orthodontic treatment using light force and simultaneous mesial stripping of the incisors.
Çankaya et al. reported on a RCT comparing surgical reconstruction of the interdental papilla with the use of concentrated growth factor compared to no surgical intervention. The concentrated growth factor was derived from centrifuged blood samples with the protocol described by Qiao et al. . The study reported for the test group a positive correlation with papillary thickness and the filling percentages and between the thrombocyte count and the 6- and 12-month filling percentages. McGuire et al. reported on a randomised controlled trial comparing cultured and expanded autologous fibroblast injections to a placebo and the results found no treatment effect at 4 months. However, the VAS score was superior for the test group. Other studies with reportedly favourable clinical outcomes describe the use of hemolasertherapy or the use of repeated curettage following acute necrotising ulcerative gingivitis . Due to the high heterogeneity of the studies owing to different study designs, protocols and outcome measures meta-analysis was not possible for any of the studies. The Cochrane risk of bias tool was used to assess the risk of bias of the randomised controlled trials. Seven domains were assessed for each of the papers and a traffic light system was used for each category as shown in Fig. . Four studies showed a high risk of bias whilst the remainder showed an unclear risk of bias and no papers were deemed to be low risk of bias. The Modified Delphi tool was used to assess risk of bias of case series. All papers included had at least one domain which put the paper into the overall category of high risk of bias. The Newcastle Ottawa scale was used to assess the risk of bias of cohort studies and this ranged from 8 stars to 9 stars . For the case reports, the risk of bias was assessed with the CARE checklist. A score out of 30 was made based on what was included in each case report from the checklist. Figure shows the totals for each paper. Only one paper scored 20 or above. Two papers had a low score of 12 out of 30 and the remainder were in between. This demonstrates that the quality of the case reports did not meet the highest standards based on the checklist.
The main objective of this systematic review was to appraise the literature for the available treatment options for reconstruction of the interdental papilla and to assess how much evidence exists for their efficacy. Formation of black triangles following non-surgical periodontal therapy and surgical periodontal therapy is an important sequalae of the treatment that clinicians must warn patients about. Loss of interdental papilla in anterior region can also be a frequent cause of dissatisfaction of patients. Cunliffe et al. reported findings of a patient survey based on perceptions of a series of clinical photographs. The participants ‘ranked black triangles as the third most disliked aesthetic problem after caries and visible crown margins’. Patient’s nowadays have higher aesthetic demands and reconstruction of the interdental papilla is therefore an important aim of periodontal treatment, on which many investigators in different countries have worked for several years but for which no consensus currently exists . Various treatment modalities have been employed for the reconstruction of the interdental papilla. Although most studies included here show improvement of ‘papillary fill’ outcomes at minimum 3 months, it is not possible to make conclusions regarding these techniques due to the lack of long-term data. The first clear difficulty related to RCTs investigating reconstruction of the interdental papilla is the measurement of the outcome, which ranges from subjective visual assessments to percentage papillary fill and change in black triangle dimensions. Amongst patient-reported outcomes (PROMs), the visual analog scale scores are used to assess patient and clinician perception in the change in the papillary defect. PROMs were only reported in four studies despite them being crucial as these treatments are intended to improve aesthetics and therefore should be used in all studies related to papillary reconstruction. The second important issue is related to the choice of the ‘control’ group due to the lack of evidence and consensus for a benefit of any treatment and the absence of a gold-standard treatment, limiting interpretation of results. Use of a connective tissue graft appears to lead to more favourable results compared with PRF when combined with the surgical Han and Takei technique (Singh et al., Sharma et al.), and the modified Beagle technique showed improvements compared with the original Beagle technique . The latter is described in a case report and involves creating a new papilla with partial thickness incisions palatal to the deficient papilla twice the length of the desired papilla. This is then reflected onto the labial aspect and sutured into position. The modified Beagle’s technique involves the incisions being carried out on the labial aspect rather than on the palatal side. Amongst non-surgical interventions, HA injections do not seem to lead to improvements beyond 3 months compared with saline injections . McGuire et al. reported a significant increase in papillary height in the test group with cell transplantation of cultured and expanded autologous fibroblast injections following a papilla priming procedure compared with the placebo control group at 2 months. However, at 3–4 months, there were no significant differences between the two groups. A visual analog scale was used by the participants and examiners and this was superior in the test group receiving the fibroblast injections. Based on the evidence provided by this systematic review, it seems that the most efficacious intervention for papilla reconstruction is the use of grafting with a sub-epithelial connective tissue graft, whilst non-surgical interventions, including the use of hyaluronic acid, seem to provide less clear benefits. The surgical techniques involving a connect tissue graft were described in several of the included papers [ , , , , , , – ]. They typically involved semi-lunar incisions, harvesting of a sub-epithelial connective tissue graft from the palate and insertion and coronal advancement of the papilla. Feuillet et al. described a tunnelling technique alongside placement of a connective tissue graft. Carnio et al. described a multidisciplinary case involving a periodontal-orthodontic-restorative approach involving a connective tissue graft. They all reported improvements in the interdental papillary fill. Nemcovsky et al. conducted a case series of 9 patients with 10 defects that underwent surgical papilla augmentation using an advanced papillary flap in combination with a free gingival graft. The results demonstrated an increase in the papilla index score for 8 out of the 10 procedures with a mean increase in PIS of 1.2 ± 0.92 units at 3 months. These conclusions seem to be in partial agreement with the recommendations proposed by Rasperini et al. in which the treatment on interdental papilla reconstruction was based on the presence of periodontal health or disease. In periodontal health, they advise soft tissue grafts, orthodontics or modification of the restoration. In the presence of periodontal intrabony defects, the surgical management of the defects even with papilla preservation flaps can result in some degree of recession in the interdental area . In the narrative review , various techniques are described which are designed to limit recession in the interdental area after periodontal regenerative surgery. This includes the use of enamel matrix derivatives with an envelope coronally advanced flap which is designed to limit supracrestal attachment collapse, increase the space for regeneration and reduce the loss of papilla. Rasperini et al. described the soft tissue wall technique for regenerative surgery on non-contained intrabony defects in which papilla preservation is used in conjunction with a trapezoidal coronally advanced flap. The authors reported at 12 months an improvement in interdental CAL gain of 7.1 ± 1 mm and a mean recession reduction of 1 ± 0.4 mm. The authors also mention some recent surgical techniques including the connective tissue graft wall, the entire papilla preservation technique , use of a connective tissue graft in combination with the single flap approach , the modified vestibular incision subperiosteal tunnel access and the non-incised papilla surgical approach . There was a high heterogeneity amongst the studies, mainly due to variations in the protocol, follow-up and outcome measures. Most of the studies included in this systematic review were judged to have either a moderate or high risk of bias. This reduces the quality of evidence and makes it more difficult to make recommendations based on their findings. To limit this, better designed studies need to be conducted. Ideally, these should be randomised controlled trials, with blinding where possible. All studies should be prospective studies rather than retrospective to limit bias also. Outcomes need to be reported more consistently for example with the same papilla indices. Patient-reported outcomes should always be included. Many of the procedures described in the case series and case reports should be further studied and backed up by randomised controlled trials to evaluate their efficacy with limited bias. Longer follow-ups are also needed. The studies need to have a clear inclusion and exclusion criteria especially regarding smoking status. Twelve papers [ , , , , , , , , ] did not report on the smoking status of the participants and this could have affected the outcome. A strength of the present systematic review is that a comprehensive search strategy was employed using three databases in addition to a manual and cross-reference search. There were no language restrictions and no lower limit of date of publication so all available literature could be systematically assessed. Due to the limited evidence base, we did not restrict this systematic review to RCTs, but tried to be very inclusive in terms of study design and patient numbers. The inclusion of cohort studies, case series and case reports allowed a wider range of studies and data to be incorporated into this systematic review but their lower levels of evidence has resulted in less high-quality data. The reported outcome variables were inconsistent amongst the studies with some papers [ , , , , ] reporting only a visual assessment of the outcome rather than numerical data, introducing a high level of bias. The evidence strength produced by this review is considerably more robust than what was reported in a systematic review by . They included 8 papers none of which were RCTs, and reported that all of the studies demonstrated ‘positive’ results. They set a limit for publications from 2010 onwards limiting evidence from studies previous to this date whilst this current systematic review did not have a limit to publication date.
Within the limitations of this systematic review, we can conclude that the loss of the interdental papilla remains an important clinical sequela with significant impact for patients suffering from periodontal disease. Amongst many different treatment modalities available for reconstruction of the interdental papilla, hyaluronic acid injections, PRF, surgical grafting and orthodontics seem to improve outcomes at a minimum 3 months. However, the use of grafting with sub-epithelial connective tissue graft seems to be associated with the most evidence for the longer-term reduction of ‘black triangles’. However, no robust direct comparisons between different techniques are available. Overall, there is insufficient evidence to make recommendations to clinicians and due to the high level of heterogeneity in the studies we cannot draw clear conclusions. Further research in this field should include good-quality RCTs of the most promising treatment modalities with at least a 12-month follow-up, using the appropriate controls and consistent papilla indices and PROMs as outcomes.
Below is the link to the electronic supplementary material. Supplementary file1 (DOCX 19 KB
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Health professionals’ and coroners’ views on less invasive perinatal and paediatric autopsy: a qualitative study | edf45306-38f0-4d2b-8356-0b259313c72a | 5965355 | Pathology[mh] | Autopsy (postmortem) examination remains the gold standard in the investigation of perinatal, infant and child deaths adding important clinical information in up to 76% of cases. Yet uptake rates have declined globally over recent years. In the UK, more than 50% of parents decline postmortem, a decision many bereaved parents later regret. As a result of advances in technology and concerns around declining uptake rates, less invasive methods of autopsy have been developed in recent years. Non-invasive autopsy (NIA) uses cross-sectional imaging techniques such as CT or MRI along with ancillary investigations such as microbiology and placental examination. This has the advantage of negating the need for body incisions, while maintaining high concordance with traditional autopsy in the perinatal, paediatric clinical and forensic settings. Minimally invasive autopsy (MIA) combines imaging with laparoscopic or image-guided tissue sampling. This approach requires only a small incision thereby reducing the overall cosmetic impact while providing tissue for analysis. Successful implementation of any new clinical pathway requires thorough evaluation to ensure acceptability among key stakeholders and examination of barriers to uptake, economic evaluation and an assessment of service and policy implications. To date, few studies have been conducted to assess attitudes of parents and health professionals towards less invasive versus standard autopsy. In a cross-sectional questionnaire to assess acceptability of MIA among healthcare professionals, Ben-Sasi et al reported that 40% thought it was more and 50% equally acceptable as full autopsy. As part of an National Institute for Health Research Health Technology Assessment feasibility study regarding acceptability of less invasive autopsy, we report the findings from qualitative interviews conducted with health professionals and HM Coroners to assess acceptability, predicted uptake and issues for service delivery.
This was a qualitative study using semistructured interviews and a purposive sampling approach. Recruitment Health professionals across the UK from a range of clinical backgrounds who would be involved in discussions with parents about autopsy examination or would conduct or interpret autopsy results were identified by the authors, purposively sampled and invited via email to participate in the study . A similar approach was used to recruit HM Coroners. The interviews were conducted by CL either face to face or by telephone between April 2016 and July 2017. Topic guide The semistructured discussion guide explored participants’ views towards NIA and MIA, perceived benefits, potential limitations or concerns, and implementation into clinical or coronial practice. At the start of the interview, participants were provided with a standardised overview of NIA and MIA . Analysis Data were analysed using thematic analysis supported by Nvivo V.10 (QSR International Pty) software. Data collection and analysis was performed concurrently. The first transcripts were coded independently by CL and MH, and a coding framework was agreed. Subsequent transcripts were coded by CL or MH, and a coding comparison run on Nvivo to ensure inter-rater reliability. Coding disagreements were discussed and resolved. CL coded the remainder of the transcripts according to the framework with subthemes added as appropriate. Final themes were reviewed and agreed by both authors. Data collection continued until saturation was reached.
Health professionals across the UK from a range of clinical backgrounds who would be involved in discussions with parents about autopsy examination or would conduct or interpret autopsy results were identified by the authors, purposively sampled and invited via email to participate in the study . A similar approach was used to recruit HM Coroners. The interviews were conducted by CL either face to face or by telephone between April 2016 and July 2017.
The semistructured discussion guide explored participants’ views towards NIA and MIA, perceived benefits, potential limitations or concerns, and implementation into clinical or coronial practice. At the start of the interview, participants were provided with a standardised overview of NIA and MIA .
Data were analysed using thematic analysis supported by Nvivo V.10 (QSR International Pty) software. Data collection and analysis was performed concurrently. The first transcripts were coded independently by CL and MH, and a coding framework was agreed. Subsequent transcripts were coded by CL or MH, and a coding comparison run on Nvivo to ensure inter-rater reliability. Coding disagreements were discussed and resolved. CL coded the remainder of the transcripts according to the framework with subthemes added as appropriate. Final themes were reviewed and agreed by both authors. Data collection continued until saturation was reached.
Sample characteristics Forty health professionals were contacted and 25 took part, from 11 different hospitals (63% recruitment rate) . Ten coroners were approached: one declined, five did not respond and four took part (40% recruitment rate). Nine health professionals were already offering NIA in clinical service and four coroners explained it was available in their jurisdictions at a cost, although none recalled using it for infant or childhood deaths. Six health professionals were offering MIA either as part of a study or a clinical service; no coroner was offering MIA for coronial cases. Four overarching themes were identified: (1) benefits, (2) concerns, (3) implementation issues and (4) predicted uptake. These are presented below with illustrate quotes in . Benefits of MIA and NIA are given in . Procedural benefits Participants acknowledged that there were certain circumstances where imaging would be particularly useful including congenital anatomical abnormalities such as ‘ brain malformations ’ , ‘ cardiac conditions ’ and ‘ skeletal dysplasias ’ and to confirm abnormal prenatal ultrasound findings. Several participants highlighted instances where NIA might provide greater diagnostic accuracy than full autopsy or ‘ show up things you were not expecting ’ such as a variety of abnormalities suggesting a syndrome. The main procedural benefit of MIA was imaging plus tissue sampling increasing the chances of a clinical finding. Five participants noted the potential benefits of showing MRI or CT images to aid explanation of findings when reporting autopsy results to parents. Seven interviewees speculated as to whether NIA would be quicker than full autopsy, others noted that often the ancillary investigations delay reporting. Finally, some participants speculated as to whether NIA and MIA would be more cost effective; however, there was an acknowledgement that this cost saving may be offset by increased uptake. One participant acknowledged that a ‘ hard economic analysis ’ was required. Psychological benefits These included health professionals and parents ‘ feeling more comfortable ’ discussing NIA and MIA than a full autopsy and NIA removing the need to open the head which was particularly distressing for parents. Some acknowledged parents might feel more comfortable consenting to imaging and laparoscopic approaches with which they were familiar. Regarding MIA, health professionals commented that a small incision alongside a biopsy was more palatable to parents than a large incision and organ removal. One interviewee commented that increasing choices helps parents feel they have more control. Faith groups Health professionals acknowledged that less invasive methods of autopsy, particularly NIA, would be preferable to members of the Muslim and Jewish community who traditionally decline autopsy as cutting of the body after death is prohibited, but acknowledged that a fast turnaround time would be required to return the body for burial. Two coroners commented that members of these communities had increasingly requested NIA despite having to cover the costs of the scan. One coroner commented on the positive effect NIA had with the faith community calling it a ‘ game changer ’ . No coroners had requests for NIA from families outside the Muslim and Jewish faiths although it was acknowledged that this was probably because it was not widely known about. Limitations of the technology One of the main concerns raised related to whether one could reach the same level of certainty with NIA and MIA as a traditional autopsy and the potential for missing a diagnosis or misdiagnosis. Participants also worried about parents consenting to NIA or MIA ‘inappropriately’. A great deal of importance was therefore placed on ensuring further validation and developing official guidance. More specifically, there were various circumstances where participants noted that NIA was unlikely to be suitable including ‘infections’, ‘complex cases where tissue from multiple sites is required’, ‘aneurysms’, ‘stillbirth where the baby dies abruptly’ and coronial cases where there was ‘negligent surgery’ or a ‘suspicious death’. Intensive care consultants discussed whether there would be value add of doing NIA on a child that had already been scanned, although one suggested that NIA might be useful for a neonate ‘with a constellation of congenital abnormalities’. Two participants commented on the importance of tissue for DNA analysis to provide recurrence risk although with MIA the main concern related to whether there was the potential for ‘ false negatives ’ . One participant commented that for complex cases, tissue may be required from multiple organs, thus requiring a ‘maximum minimally invasive approach’. Finally, one participant noted that we still need a ‘way of sampling the brain’ in a minimally invasive way. De-skilling the workforce Concerns around ‘ de-skilling ’ pathologists to conduct traditional autopsies and know when a full autopsy is required were raised, particularly in relation to NIA. Two anatomical pathology technologists (APTs) also raised concerns around loss of skills in conducting reconstructions and how their role would fit in with these new technologies. One APT commented that perhaps their role could change to take on some of the laparoscopic work or be trained in using scanning equipment. Skills and training Some of the most frequently cited issues around NIA and MIA related to the training that would be required of radiologists and pathologists to enable them to set up the service and conduct the procedures. For radiologists it was acknowledged that as well as having an interest in NIA, there would be a ‘learning curve because it is a completely different set of reporting’. A paediatric pathologist commented that some pathologists might be ‘put off… trying to use a tiny telescope ’. Moreover, the current lack of pathologists working in clinical practice was identified as a potential barrier. Others commented on the need to train staff both to have sufficient understanding of the techniques to be able to consent parents and ‘ to make sure the right type of post mortem is offered to the right type of patient’. One of the pathologists queried whether health professionals might be discouraged from consenting parents for a traditional autopsy because of the availability of NIA and MIA. Logistics Most participants acknowledged that successful implementation of NIA and MIA would require a multidisciplinary approach with pathologists and radiologists working together. Other key logistical challenges concerned having sufficient access to MRI and CT machines, particularly given that ‘everyone’s priority is for the live patients’ as well as having the computational infrastructure to transmit digital images to experts. Some participants raised concerns around whether you would ‘swamp the pathology department’ if there was an increase in uptake. Cost implications and equity of access A range of costs associated with implementation were identified, including training pathologists and radiologists as well as covering their time in clinic, the cost of the laparoscopic equipment required for MIA, the potential costs of dedicated pathology department MRI or CT machines to cope with the increase in uptake and the cost of offering an out-of-hours service. Concerns around equity of access and feasibility of offering NIA and MIA to all were frequently raised with concerns around less invasive autopsy becoming a ‘postcode lottery’. Three health professionals commented that a pragmatic solution would be to offer MIA and NIA through specialist centres although a midwife acknowledged that some parents may have concerns about their baby being moved to another hospital. In coronial cases, it was acknowledged that NIA is generally only requested by members of the Muslim and Jewish communities with one coroner noting that it should be advertised to everyone. Acceptance and governance Acceptance that NIA and MIA were reliable alternatives and the will to change current practice on the part of the paediatric pathology and radiology community were identified as key requirement for successful implementation, although it was also noted by a radiologist that ‘simply the fact that it’s novel and I would need some experience or training to do it…is not a reason not to do it’. The need for buy-in from hospital management to fund training and resources including an out-of-hours service to use scanning equipment was also discussed. Two coroners identified the need for guidance from the Royal College of Pathologists as to when MIA and NIA would be acceptable alternatives to a standard autopsy, with one commenting that current guidance requires ‘a thorough examination’. Two coroners highlighted the ‘political will’ that would be required for authorities to fund ‘a comprehensive out-of-hours service’, although one noted that this might be more likely if an economic evaluation showed NIA to be cost-effective. Likely uptake All participants felt that the availability of NIA and MIA would increase uptake of autopsy although this varied from a ‘much larger uptake’ (bereavement midwife) to ‘you might adjust the margins somewhat’ (consultant ICU). For health professionals already offering NIA or MIA, there had already been an increase in uptake. Participants acknowledged that some parents were still likely to have a preference for a traditional autopsy as it was likely to yield the most information. The vast majority advocated offering MIA and NIA using a tiered approach whereby parents' consent to the most invasive option they would accept but that if a diagnosis was made with a less invasive method, nothing further would be done.
Forty health professionals were contacted and 25 took part, from 11 different hospitals (63% recruitment rate) . Ten coroners were approached: one declined, five did not respond and four took part (40% recruitment rate). Nine health professionals were already offering NIA in clinical service and four coroners explained it was available in their jurisdictions at a cost, although none recalled using it for infant or childhood deaths. Six health professionals were offering MIA either as part of a study or a clinical service; no coroner was offering MIA for coronial cases. Four overarching themes were identified: (1) benefits, (2) concerns, (3) implementation issues and (4) predicted uptake. These are presented below with illustrate quotes in . Benefits of MIA and NIA are given in .
Participants acknowledged that there were certain circumstances where imaging would be particularly useful including congenital anatomical abnormalities such as ‘ brain malformations ’ , ‘ cardiac conditions ’ and ‘ skeletal dysplasias ’ and to confirm abnormal prenatal ultrasound findings. Several participants highlighted instances where NIA might provide greater diagnostic accuracy than full autopsy or ‘ show up things you were not expecting ’ such as a variety of abnormalities suggesting a syndrome. The main procedural benefit of MIA was imaging plus tissue sampling increasing the chances of a clinical finding. Five participants noted the potential benefits of showing MRI or CT images to aid explanation of findings when reporting autopsy results to parents. Seven interviewees speculated as to whether NIA would be quicker than full autopsy, others noted that often the ancillary investigations delay reporting. Finally, some participants speculated as to whether NIA and MIA would be more cost effective; however, there was an acknowledgement that this cost saving may be offset by increased uptake. One participant acknowledged that a ‘ hard economic analysis ’ was required. Psychological benefits These included health professionals and parents ‘ feeling more comfortable ’ discussing NIA and MIA than a full autopsy and NIA removing the need to open the head which was particularly distressing for parents. Some acknowledged parents might feel more comfortable consenting to imaging and laparoscopic approaches with which they were familiar. Regarding MIA, health professionals commented that a small incision alongside a biopsy was more palatable to parents than a large incision and organ removal. One interviewee commented that increasing choices helps parents feel they have more control. Faith groups Health professionals acknowledged that less invasive methods of autopsy, particularly NIA, would be preferable to members of the Muslim and Jewish community who traditionally decline autopsy as cutting of the body after death is prohibited, but acknowledged that a fast turnaround time would be required to return the body for burial. Two coroners commented that members of these communities had increasingly requested NIA despite having to cover the costs of the scan. One coroner commented on the positive effect NIA had with the faith community calling it a ‘ game changer ’ . No coroners had requests for NIA from families outside the Muslim and Jewish faiths although it was acknowledged that this was probably because it was not widely known about. Limitations of the technology One of the main concerns raised related to whether one could reach the same level of certainty with NIA and MIA as a traditional autopsy and the potential for missing a diagnosis or misdiagnosis. Participants also worried about parents consenting to NIA or MIA ‘inappropriately’. A great deal of importance was therefore placed on ensuring further validation and developing official guidance. More specifically, there were various circumstances where participants noted that NIA was unlikely to be suitable including ‘infections’, ‘complex cases where tissue from multiple sites is required’, ‘aneurysms’, ‘stillbirth where the baby dies abruptly’ and coronial cases where there was ‘negligent surgery’ or a ‘suspicious death’. Intensive care consultants discussed whether there would be value add of doing NIA on a child that had already been scanned, although one suggested that NIA might be useful for a neonate ‘with a constellation of congenital abnormalities’. Two participants commented on the importance of tissue for DNA analysis to provide recurrence risk although with MIA the main concern related to whether there was the potential for ‘ false negatives ’ . One participant commented that for complex cases, tissue may be required from multiple organs, thus requiring a ‘maximum minimally invasive approach’. Finally, one participant noted that we still need a ‘way of sampling the brain’ in a minimally invasive way. De-skilling the workforce Concerns around ‘ de-skilling ’ pathologists to conduct traditional autopsies and know when a full autopsy is required were raised, particularly in relation to NIA. Two anatomical pathology technologists (APTs) also raised concerns around loss of skills in conducting reconstructions and how their role would fit in with these new technologies. One APT commented that perhaps their role could change to take on some of the laparoscopic work or be trained in using scanning equipment. Skills and training Some of the most frequently cited issues around NIA and MIA related to the training that would be required of radiologists and pathologists to enable them to set up the service and conduct the procedures. For radiologists it was acknowledged that as well as having an interest in NIA, there would be a ‘learning curve because it is a completely different set of reporting’. A paediatric pathologist commented that some pathologists might be ‘put off… trying to use a tiny telescope ’. Moreover, the current lack of pathologists working in clinical practice was identified as a potential barrier. Others commented on the need to train staff both to have sufficient understanding of the techniques to be able to consent parents and ‘ to make sure the right type of post mortem is offered to the right type of patient’. One of the pathologists queried whether health professionals might be discouraged from consenting parents for a traditional autopsy because of the availability of NIA and MIA. Logistics Most participants acknowledged that successful implementation of NIA and MIA would require a multidisciplinary approach with pathologists and radiologists working together. Other key logistical challenges concerned having sufficient access to MRI and CT machines, particularly given that ‘everyone’s priority is for the live patients’ as well as having the computational infrastructure to transmit digital images to experts. Some participants raised concerns around whether you would ‘swamp the pathology department’ if there was an increase in uptake. Cost implications and equity of access A range of costs associated with implementation were identified, including training pathologists and radiologists as well as covering their time in clinic, the cost of the laparoscopic equipment required for MIA, the potential costs of dedicated pathology department MRI or CT machines to cope with the increase in uptake and the cost of offering an out-of-hours service. Concerns around equity of access and feasibility of offering NIA and MIA to all were frequently raised with concerns around less invasive autopsy becoming a ‘postcode lottery’. Three health professionals commented that a pragmatic solution would be to offer MIA and NIA through specialist centres although a midwife acknowledged that some parents may have concerns about their baby being moved to another hospital. In coronial cases, it was acknowledged that NIA is generally only requested by members of the Muslim and Jewish communities with one coroner noting that it should be advertised to everyone. Acceptance and governance Acceptance that NIA and MIA were reliable alternatives and the will to change current practice on the part of the paediatric pathology and radiology community were identified as key requirement for successful implementation, although it was also noted by a radiologist that ‘simply the fact that it’s novel and I would need some experience or training to do it…is not a reason not to do it’. The need for buy-in from hospital management to fund training and resources including an out-of-hours service to use scanning equipment was also discussed. Two coroners identified the need for guidance from the Royal College of Pathologists as to when MIA and NIA would be acceptable alternatives to a standard autopsy, with one commenting that current guidance requires ‘a thorough examination’. Two coroners highlighted the ‘political will’ that would be required for authorities to fund ‘a comprehensive out-of-hours service’, although one noted that this might be more likely if an economic evaluation showed NIA to be cost-effective.
These included health professionals and parents ‘ feeling more comfortable ’ discussing NIA and MIA than a full autopsy and NIA removing the need to open the head which was particularly distressing for parents. Some acknowledged parents might feel more comfortable consenting to imaging and laparoscopic approaches with which they were familiar. Regarding MIA, health professionals commented that a small incision alongside a biopsy was more palatable to parents than a large incision and organ removal. One interviewee commented that increasing choices helps parents feel they have more control.
Health professionals acknowledged that less invasive methods of autopsy, particularly NIA, would be preferable to members of the Muslim and Jewish community who traditionally decline autopsy as cutting of the body after death is prohibited, but acknowledged that a fast turnaround time would be required to return the body for burial. Two coroners commented that members of these communities had increasingly requested NIA despite having to cover the costs of the scan. One coroner commented on the positive effect NIA had with the faith community calling it a ‘ game changer ’ . No coroners had requests for NIA from families outside the Muslim and Jewish faiths although it was acknowledged that this was probably because it was not widely known about.
One of the main concerns raised related to whether one could reach the same level of certainty with NIA and MIA as a traditional autopsy and the potential for missing a diagnosis or misdiagnosis. Participants also worried about parents consenting to NIA or MIA ‘inappropriately’. A great deal of importance was therefore placed on ensuring further validation and developing official guidance. More specifically, there were various circumstances where participants noted that NIA was unlikely to be suitable including ‘infections’, ‘complex cases where tissue from multiple sites is required’, ‘aneurysms’, ‘stillbirth where the baby dies abruptly’ and coronial cases where there was ‘negligent surgery’ or a ‘suspicious death’. Intensive care consultants discussed whether there would be value add of doing NIA on a child that had already been scanned, although one suggested that NIA might be useful for a neonate ‘with a constellation of congenital abnormalities’. Two participants commented on the importance of tissue for DNA analysis to provide recurrence risk although with MIA the main concern related to whether there was the potential for ‘ false negatives ’ . One participant commented that for complex cases, tissue may be required from multiple organs, thus requiring a ‘maximum minimally invasive approach’. Finally, one participant noted that we still need a ‘way of sampling the brain’ in a minimally invasive way.
Concerns around ‘ de-skilling ’ pathologists to conduct traditional autopsies and know when a full autopsy is required were raised, particularly in relation to NIA. Two anatomical pathology technologists (APTs) also raised concerns around loss of skills in conducting reconstructions and how their role would fit in with these new technologies. One APT commented that perhaps their role could change to take on some of the laparoscopic work or be trained in using scanning equipment.
Some of the most frequently cited issues around NIA and MIA related to the training that would be required of radiologists and pathologists to enable them to set up the service and conduct the procedures. For radiologists it was acknowledged that as well as having an interest in NIA, there would be a ‘learning curve because it is a completely different set of reporting’. A paediatric pathologist commented that some pathologists might be ‘put off… trying to use a tiny telescope ’. Moreover, the current lack of pathologists working in clinical practice was identified as a potential barrier. Others commented on the need to train staff both to have sufficient understanding of the techniques to be able to consent parents and ‘ to make sure the right type of post mortem is offered to the right type of patient’. One of the pathologists queried whether health professionals might be discouraged from consenting parents for a traditional autopsy because of the availability of NIA and MIA.
Most participants acknowledged that successful implementation of NIA and MIA would require a multidisciplinary approach with pathologists and radiologists working together. Other key logistical challenges concerned having sufficient access to MRI and CT machines, particularly given that ‘everyone’s priority is for the live patients’ as well as having the computational infrastructure to transmit digital images to experts. Some participants raised concerns around whether you would ‘swamp the pathology department’ if there was an increase in uptake.
A range of costs associated with implementation were identified, including training pathologists and radiologists as well as covering their time in clinic, the cost of the laparoscopic equipment required for MIA, the potential costs of dedicated pathology department MRI or CT machines to cope with the increase in uptake and the cost of offering an out-of-hours service. Concerns around equity of access and feasibility of offering NIA and MIA to all were frequently raised with concerns around less invasive autopsy becoming a ‘postcode lottery’. Three health professionals commented that a pragmatic solution would be to offer MIA and NIA through specialist centres although a midwife acknowledged that some parents may have concerns about their baby being moved to another hospital. In coronial cases, it was acknowledged that NIA is generally only requested by members of the Muslim and Jewish communities with one coroner noting that it should be advertised to everyone.
Acceptance that NIA and MIA were reliable alternatives and the will to change current practice on the part of the paediatric pathology and radiology community were identified as key requirement for successful implementation, although it was also noted by a radiologist that ‘simply the fact that it’s novel and I would need some experience or training to do it…is not a reason not to do it’. The need for buy-in from hospital management to fund training and resources including an out-of-hours service to use scanning equipment was also discussed. Two coroners identified the need for guidance from the Royal College of Pathologists as to when MIA and NIA would be acceptable alternatives to a standard autopsy, with one commenting that current guidance requires ‘a thorough examination’. Two coroners highlighted the ‘political will’ that would be required for authorities to fund ‘a comprehensive out-of-hours service’, although one noted that this might be more likely if an economic evaluation showed NIA to be cost-effective.
All participants felt that the availability of NIA and MIA would increase uptake of autopsy although this varied from a ‘much larger uptake’ (bereavement midwife) to ‘you might adjust the margins somewhat’ (consultant ICU). For health professionals already offering NIA or MIA, there had already been an increase in uptake. Participants acknowledged that some parents were still likely to have a preference for a traditional autopsy as it was likely to yield the most information. The vast majority advocated offering MIA and NIA using a tiered approach whereby parents' consent to the most invasive option they would accept but that if a diagnosis was made with a less invasive method, nothing further would be done.
Participants in this study viewed less invasive autopsy as a positive development which was likely to increase uptake as parents would find it more acceptable, particularly those for whom current options are morally or religiously objectionable. Nevertheless, numerous challenges associated with implementation and concerns around the limitations of the technology were raised which will need to be addressed before widespread implementation into clinical practice. This study provides a unique, in-depth insight into the views of health professionals and coroners towards less invasive autopsy. Such insights are crucial given that paediatric and perinatal autopsy examination represent the largest group of consented autopsies. A number of practical challenges described in this study have previously been identified when considering autopsy imaging in adults. Recommendations from that work included standards of practice and training programmes for pathologist, radiologists and APTs (eg, APTs trained to operate scanners and undertake some minimally invasive procedures), imaging to be performed in any hospital equipped with scanning equipment with images then sent to a centre of expertise for reporting and conducting less invasive autopsy within already established centres of pathology addressing concerns around equity of access. Such strategies, while realistic, require capital investment and support from clinicians as well as hospital decision-makers, Royal Colleges and local authorities. A detailed costs and benefits economic analysis to determine the true cost of implementing the service is therefore required. Health professionals identified numerous situations where imaging could be as reliable as or even superior to full autopsy, comments that are supported by the current evidence on NIA. As much of the success of the procedure is highly dependent on the fetus/child being studied, the equipment used and the skills of the reporting team, further evaluation of MIA when offered as a clinical service will be important. Nevertheless, there were some circumstances where it was unclear whether imaging would useful. This highlights the importance of research to understand which circumstances are most suitable for which method of autopsy and development of formal guidance, both to ensure application in appropriate settings and to inform clinicians’ consultations with bereaved parents regarding the likely yield of imaging or other investigations so that informed decisions can be made. As part of this Health Technology Assessment feasibility study, information has been collected regarding the value (or not) of examination and histological sampling of specific organs by clinical indication to help guide parental decision-making. Further work is also required to determine reporting times for MIA, which may have the benefit of being quicker and improve on the current figure of 60% of autopsy reports meeting the NHS England recommended 42-day turnaround time. Lengthy reporting times have been identified as a critical issue for parents, many of whom feel they cannot move on until they receive a result. The need for approaches to reduce laboratory processing time and sample analysis has been identified as key to creating a viable clinical service. This may apply to NIA, but MIA will still require histological examination. Limitations Participants were self-selecting and there may be responder bias towards people who have strong views towards NIA and MIA. There was a low response rate for coroners (40%). This may be because it was not always possible to contact coroners directly. Finally, this research was only conducted with health professionals and coroners in the UK, opinions outside the UK may differ.
Participants were self-selecting and there may be responder bias towards people who have strong views towards NIA and MIA. There was a low response rate for coroners (40%). This may be because it was not always possible to contact coroners directly. Finally, this research was only conducted with health professionals and coroners in the UK, opinions outside the UK may differ.
Health professionals and coroners in this study viewed less invasive methods of autopsy as a positive development in perinatal and paediatric care which could potentially increase uptake. Nevertheless, the practical challenges associated with implementing these technologies will need to be addressed before they can be implemented into routine clinical practice. An economic analysis to determine the true costs and benefits of implementing the service is therefore required as is further research to assess acceptability and likely uptake with parents and religious groups.
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Maternal antenatal anxiety and electrophysiological functioning amongst a sub-set of preschoolers participating in the GUSTO cohort | acfaf86b-a3d6-48f8-beef-3204abd06462 | 7017524 | Physiology[mh] | Roughly 25% of women in their second trimester of pregnancy indicate some anxiety symptoms and roughly 15% of pregnant women meet clinical criteria . Yet, the number of indirectly affected individuals is likely greater-- antenatal maternal anxiety is related to a variety of offspring developmental outcomes. At age 18, offspring of mothers who had been anxious during pregnancy and were taking part in the ALSPAC cohort study had a 1.39 increased Odds Ratio of being diagnosed with anxiety . In earlier life, antenatal anxiety relates to parent and/or teacher reported preschool problematic behavior such as inattention or conduct problems, emotional symptoms, and/or comparatively poor cognitive development/inattention . In keeping with the recognition that child cognitive factors may moderate associations between risk and psychopathology (e.g., ), research examines the association between maternal anxiety and offspring lab-based cognitive functioning, including executive control. For example, antenatal anxiety associates with offspring school aged and adolescent working memory, cognitive inhibition, and executive functioning . Limited lab-based work with younger children reports similar associations: high antenatal maternal anxiety relates to reaction time variability, a potential marker of intelligence or attentional difficulties, amongst 5 year olds . Furthermore, antenatal maternal anxiety is found to predict offspring brain functioning, as measured by Event Related Potentials (ERP’s). ERP amplitudes indicate the degree of coordinated neuronal activity in response to stimuli presentation . ERP’s are not only a non-invasive way of examining brain functioning, but also reveal cognition as it unfolds. Such precision may be useful in tailoring offspring-directed prevention programs to fit individual cognitive-emotional difficulties. As reviewed by Pires et al. the N1, which occurs within the first 200 msec post-stimulus, may reflect inhibition at the sensory or exogenous level; the P2, which occurs following the N1 but still generally within 200 msec post-stimulus is commonly associated with early attention and perception of emotion ; and the later appearing N2 negative deflection, often occurring between 200 and 400 msec post-stimulus, is often linked to top-down inhibitory/executive control rather than response to stimulus discrepancy . Less work examines these components in preschoolers, though in conjunction with studies of slightly older young children, existing research suggests that these components are evoked in executive functioning tasks and may reflect somewhat similar, but not identical, processes. For example, when children between roughly 5 to 8 years of age took part in a cued-switch task, Elke & Wiebe observed stimulus-locked P2’s, though switch-related amplitude differences were only observed in children in the older age ranges . With regards to the negative deflections, within an examination of both adults’ and children’s ERP responses to conflict, N1 and N2 components were observed in both age groups, with the N1 and N2 more pronounced in the children . However, congruent versus incongruent stimuli only elicited marginal differences in the N1 in children, and neither group exhibited differences in the N2 by stimuli type . Somewhat similarly, results from a different Flanker study performed with children aged 4–8 suggests that the N2 can be observed regardless of age, and that its amplitude to incongruent stimuli relates to orienting abilities; however, that study also found that differences in N2 amplitudes across congruent and incongruent stimuli were only apparent, and only associated with executive control capabilities, amongst children 6 years and older . Still, other work examining performance during a switch-task in children roughly 3.0–4.5 years of age suggests a role for the N2 in executive control, as amplitudes are smaller amongst those who pass the switch than those who fail . Thus, there is still much to learn with regards to the nature of these components in preschool executive functioning research, and accordingly, their association with potential risk factors such as maternal anxiety. Amongst adolescents, ERP research has uncovered associations between maternal antenatal anxiety and adolescent offspring inhibitory processing and cognitive evaluation , but not stimulus driven inhibition . In contrast, in infancy, associations between maternal antenatal anxiety and earlier occurring, externally driven, aspects of cognitive functioning have been observed . Likewise, studies report associations with early-to-mid occurring components potentially reflecting attention and/or attentional biases . Still, to our knowledge no published work examines antenatal anxiety, or the closely related condition of antenatal depression, and ERPs during preschool, a period of rapid cognitive development when many executive functions beginning to come on-line. Maternal “antenatal anxiety”, per se? Despite research linking antenatal maternal mental health and stressful life experiences to offspring brain development, the precise biological mechanisms remains unclear. Possibilities include growth restriction in otherwise at-risk populations, direct and indirect (e.g., cytokine) influences upon cortisol transfer across the placenta, and moderation by genetic, ethnic, and postnatal environmental factors (e.g., see reviews by ). Many of such potential mechanisms are not specific to anxiety, and may also be expected to be influenced by comorbid conditions like depression. Still, some past work may suggest specificity. Anxiety predicted differences in neonatal brain micro-structure are not explained by perinatal depression . Pregnancy specific anxiety, but not state anxiety or depression, negatively impacts inhibitory control at school age. In addition, given the recognized stability between antenatal and postnatal maternal mental health, it remains possible that “antenatal” effects may, also be explained via postnatal mechanisms . Postnatal maternal mental health may affect offspring development via alterations in parenting practices, which are stress inducing to children and/or limit stimulation and support . Gender Offspring gender may moderate associations (e.g., ). Females (e.g., ) and males (e.g., ) have been reported to be more vulnerable to antenatal maternal mental health. Study aims We investigate antenatal maternal anxiety symptoms in relation to 3.5 year-old offspring neurophysiology within a novel ERP task. As this was the first ERP preschool study of its kind, we created a task that, similar to what children experience in the real-world, required the use of a number of processes potentially impacted by anxiety: the perception and exogenous perception of stimuli; attention/perception to emotional faces; endogenous control/inhibition; and memory. Nevertheless, this procedure still allowed us to examine the time course of information processing. We examined relations between antenatal maternal anxiety symptoms and three stimulus elicited ERP components likely akin to the aforementioned “N1”, “P2” and “N2”, and potentially respectively reflective of exogenous inhibition, early attention/emotional processing, and endogenous inhibition. However because latter components occur, de-facto, after prior components, rather than examining the absolute amplitude of the P2 and N2, instead the “P2_N1” (i.e., P2 minus N1) and “N2_P2” (i.e., N2 minus P2) complexes were examined to isolate unique neural activity at different points in time . We hypothesized a relation between antenatal anxiety and preschooler electrophysiology, but were uncertain whether it would be limited to an association with endogenous inhibition (e.g., the N2_P2), similar to when offspring are at much later stages of development , or a more broad array of components, more in keeping with infant research . We additionally explored specificity of timing (antenatal or postnatal) and insult (anxiety symptoms per se or also depression symptoms), as well as the potential moderating role of gender.
Despite research linking antenatal maternal mental health and stressful life experiences to offspring brain development, the precise biological mechanisms remains unclear. Possibilities include growth restriction in otherwise at-risk populations, direct and indirect (e.g., cytokine) influences upon cortisol transfer across the placenta, and moderation by genetic, ethnic, and postnatal environmental factors (e.g., see reviews by ). Many of such potential mechanisms are not specific to anxiety, and may also be expected to be influenced by comorbid conditions like depression. Still, some past work may suggest specificity. Anxiety predicted differences in neonatal brain micro-structure are not explained by perinatal depression . Pregnancy specific anxiety, but not state anxiety or depression, negatively impacts inhibitory control at school age. In addition, given the recognized stability between antenatal and postnatal maternal mental health, it remains possible that “antenatal” effects may, also be explained via postnatal mechanisms . Postnatal maternal mental health may affect offspring development via alterations in parenting practices, which are stress inducing to children and/or limit stimulation and support .
Offspring gender may moderate associations (e.g., ). Females (e.g., ) and males (e.g., ) have been reported to be more vulnerable to antenatal maternal mental health.
We investigate antenatal maternal anxiety symptoms in relation to 3.5 year-old offspring neurophysiology within a novel ERP task. As this was the first ERP preschool study of its kind, we created a task that, similar to what children experience in the real-world, required the use of a number of processes potentially impacted by anxiety: the perception and exogenous perception of stimuli; attention/perception to emotional faces; endogenous control/inhibition; and memory. Nevertheless, this procedure still allowed us to examine the time course of information processing. We examined relations between antenatal maternal anxiety symptoms and three stimulus elicited ERP components likely akin to the aforementioned “N1”, “P2” and “N2”, and potentially respectively reflective of exogenous inhibition, early attention/emotional processing, and endogenous inhibition. However because latter components occur, de-facto, after prior components, rather than examining the absolute amplitude of the P2 and N2, instead the “P2_N1” (i.e., P2 minus N1) and “N2_P2” (i.e., N2 minus P2) complexes were examined to isolate unique neural activity at different points in time . We hypothesized a relation between antenatal anxiety and preschooler electrophysiology, but were uncertain whether it would be limited to an association with endogenous inhibition (e.g., the N2_P2), similar to when offspring are at much later stages of development , or a more broad array of components, more in keeping with infant research . We additionally explored specificity of timing (antenatal or postnatal) and insult (anxiety symptoms per se or also depression symptoms), as well as the potential moderating role of gender.
Participants We focus on data from 71 mother-preschool (male offspring n = 42; female offspring n = 29) dyads, taking part in the larger prospective birth cohort study – Growing Up in Singapore Toward healthy Outcomes, which initially enrolled pregnant women attending one of two primary birthing hospitals in Singapore (“GUSTO”, ). Mothers were assessed from pregnancy and, with their children, a subsample were invited to the Neurodevelopment Research Center when the children were three-and-a-half years of age (see Fig. ). Eligibility for the current research was limited to those who were singletons at birth (e.g., no twins or triplets). Children were roughly 3.5 years old at the time of testing, with a mean age since delivery of 1257.91 days (SD = 28.36). All participants were Singaporean ethnic Chinese, ethnic Malay, or ethnic Indian. (See “ ” for additional study participant information.) Maternal demographics (e.g., education, household income, and age) were collected during the antenatal period. Income was assessed in bands, with a score of “4” indicating 4000–5999 SGD and a score of “3” indicating 2000 to 3999 SGD per month. As a point of reference, in 2013 the median Singaporean household income was $6257 SGD . Maternal education was assessed using an ordinal scale. For example, “2” = any secondary school (similar to “any high school”); “3” = GCE A Level or ITE/NTC (somewhat similar to an Associate’s degree); “4” = University degree. Maternal mental health Given our interest in the influence of pre- versus post- natal anxiety exposure, here, we focus on the State scale of the State-Trait Anxiety Inventory (STAI) form Y , In the larger GUSTO cohort, the Cronbach’s alphas for the State Scale at these time points were respectively 0.91 and 0.93. Depressive symptoms were assessed via the Edinburgh Postpartum Depression Scale (EPDS) . In the larger GUSTO cohort, the EPDS Chronbach alphas at these times were, respectively, 0.82 and 0.87. Mothers received questionnaires at 26 weeks antenatal and 24 month postnatal. ERP task design and administration The ERP recording occurred whilst children were asked to identify, via button press, happy versus angry “pirates.” Pirate stimuli consisted of Nimstim male faces with either happy or angry expressions on a purple or orange background, edited to be wearing a pirate hat. The NimStim database is highly used in developmental research, with Barnard-Brak and colleagues (Barnard-Brak 2017) reporting that over 800 studies of children have used this picture bank. Moreover, in their own research of 167 young children aged 30–83 months, Barnard-Brak et al. found good evidence of reliability and construct validity regardless of race, in a subsample of Nimstim pictures that Tottenham and colleagues reported as receiving a reliability rating of .80 or above. In the current research, chosen NimStim stimuli had received reliability ratings of at least 0.9 for angry expressions and 0.98 for happy expressions . The stimuli were rectangular in shape (length 16.8 cm and height 13.5 cm) and presented in the middle (6.8 cm from the top and bottom and 8.5 cm from the side bezels) of a 17 in., 4:3 dell monitor screen. In the Pre-Switch condition children were exposed to 50 trials with Pirate A appearing happy on a Color A background and Pirate B appearing angry on a Color B background. In the Post-Switch Blocks the pirates faces were “switched” for 66/78 trials. That is, children viewed the same stimuli, but for the majority of trials Pirate A now appeared angry on his same color background and Pirate B now appeared happy on his same color background, with the exception that in each post-switch block a small proportion of stimuli (12 trials) were identical to those used in the pre-condition trials. These 12 “pre” switch trials were intentionally included in the “post” switch block to maintain their pre-potent influence, prevent a complete association between the new color--expression pairings, and maintain the need for cognitive inhibition/selection during the latter post-switch stages. Both the pre- and post- switch portions of the task required attention to, and the perception of, emotional expressions. However, amongst children who formed associations between actors, emotional expressions, and backgrounds during the pre-switch phase, the post-switch phase was expected to require the inhibition of irrelevant exogenous information. Likewise during post-switch, amongst children who formed associations, the task was expected to require the management of conflict resulting from the difference in the current stimuli and the previously learned information (i.e., the expression-actor-color pairing). See Fig. a & b. The paradigm was manually forwarded by an experimenter to ensure that the child was looking at the screen before the stimulus appeared. Each stimulus was presented for a minimum of 1100 milliseconds and up to 10,000 milliseconds or until the child responded. Stimuli were separated by a 500 msec inter-stimulus interval. The experiment was conducted in a well-lit room and an experimenter was with the child in the room to provide instructions. The experimenter sat behind the child at the child’s 7 o’clock when the test trials began but did not help or guide the child in anyway during the test trials. Event related potential data collection and processing ERP was recorded using an EGI Dense Array EEG 300 system with a 0.1–100 Hz filter, initially referenced to the Vertex. A 128-channel geodesic hydrocel routine (sponge) net, without eye electrodes, was used during the experiment. Participants’ electroencephalogram (EEG) recordings were processed using Netstation 4.5.1 software (See Fig. ). Extraction windows were determined by reviewing both the grand average, as well as individual files so as to capture variation across individuals and across the 44 included frontal and central channels (see Additional file : Table S1 for a complete listing as well as Additional file : Figure S1). Extraction ranges for the N1, P2, and N2 were, respectively as follows: 62–206 msec, 197–341 msec, and 312–504 msec. These are similar to the timings identified in 4–8 year olds (e.g., initial negative deflection = 92–176; positive deflection = 250; N2 = 350, ; N2 = 300–500, ). Components were quantified by peak amplitudes. In keeping with studies of young children, we focused upon frontal and central channels (e.g., ). Included individual averages were comprised of an average of 37.92 pre-switch (76%; range: 20–49) and 45.23 post-switch (69%; range: 22–26) trials. Statistical analyses Task performance Differences in pre- and post- switch blocks behavioral performance (i.e., accuracy and reaction time) were examined. First, we compared behavioral data in the pre- and post- switch conditions. We expected that children who experienced cognitive conflict during the post-switch phase would exhibit less accuracy and slower reaction times during this latter condition . These analyses were conducted via a Repeated Measures ANCOVA, with gender and antenatal anxiety serving as covariates and pre-versus-post performance serving as the within subjects “Condition” variable. In addition we controlled for whether or not the children passed pre-switch (i.e., 75% or more accuracy). Children who did not pass pre-switch may have had difficulties perceiving emotions, but they may also simply not have understood the task’s instructions. Identical analyses compared the N1, P2_N1 and N2_P2 components during the pre-and post-switch conditions. Neither behavioral nor electrophysiological analyses included data from the 12 trials where pre-switch stimuli were presented in the post-switch blocks. Antenatal anxiety and post-condition ERP’s In cases where ANCOVA’s revealed significant differences between pre- and post- conditions, relations were further re-explored. In such cases, antenatal maternal anxiety was entered as a predictor variable in a regression where relevant ERP activity served as the outcome variable. These linear regressions adjusted for gender as well as possible confounders of pass-fail status and pre-condition. Given concerns about statistical power, no other potentially relevant covariates were included in our models. Such covariates were screened, and none (i.e., maternal age, household income, maternal education, ethnicity, child age at test) significantly correlated with both maternal mental health and child electrophysiology (see Additional file : Table S2). Next, to examine the potential moderating role of gender, we performed very similar analyses. The difference in this set of analyses was that rather than control for gender, we treated antenatal anxiety, gender, and their interaction as predictors. Subsequently, to address specificity, identical regressions were repeated examining depression, rather than anxiety, symptomatology. Then, to determine whether any of these observed findings would be better explained via associations with postnatal maternal mental health, we repeated the models containing antenatal maternal mental health symptoms, gender, pre-condition amplitude, and pre-switch passing status, additionally adjusting for postnatal maternal anxiety/depression symptoms. This adjustment was done in a separate step to guard against possible spurious associations arising from adjustment of mediator-colliders .
We focus on data from 71 mother-preschool (male offspring n = 42; female offspring n = 29) dyads, taking part in the larger prospective birth cohort study – Growing Up in Singapore Toward healthy Outcomes, which initially enrolled pregnant women attending one of two primary birthing hospitals in Singapore (“GUSTO”, ). Mothers were assessed from pregnancy and, with their children, a subsample were invited to the Neurodevelopment Research Center when the children were three-and-a-half years of age (see Fig. ). Eligibility for the current research was limited to those who were singletons at birth (e.g., no twins or triplets). Children were roughly 3.5 years old at the time of testing, with a mean age since delivery of 1257.91 days (SD = 28.36). All participants were Singaporean ethnic Chinese, ethnic Malay, or ethnic Indian. (See “ ” for additional study participant information.) Maternal demographics (e.g., education, household income, and age) were collected during the antenatal period. Income was assessed in bands, with a score of “4” indicating 4000–5999 SGD and a score of “3” indicating 2000 to 3999 SGD per month. As a point of reference, in 2013 the median Singaporean household income was $6257 SGD . Maternal education was assessed using an ordinal scale. For example, “2” = any secondary school (similar to “any high school”); “3” = GCE A Level or ITE/NTC (somewhat similar to an Associate’s degree); “4” = University degree.
Given our interest in the influence of pre- versus post- natal anxiety exposure, here, we focus on the State scale of the State-Trait Anxiety Inventory (STAI) form Y , In the larger GUSTO cohort, the Cronbach’s alphas for the State Scale at these time points were respectively 0.91 and 0.93. Depressive symptoms were assessed via the Edinburgh Postpartum Depression Scale (EPDS) . In the larger GUSTO cohort, the EPDS Chronbach alphas at these times were, respectively, 0.82 and 0.87. Mothers received questionnaires at 26 weeks antenatal and 24 month postnatal.
The ERP recording occurred whilst children were asked to identify, via button press, happy versus angry “pirates.” Pirate stimuli consisted of Nimstim male faces with either happy or angry expressions on a purple or orange background, edited to be wearing a pirate hat. The NimStim database is highly used in developmental research, with Barnard-Brak and colleagues (Barnard-Brak 2017) reporting that over 800 studies of children have used this picture bank. Moreover, in their own research of 167 young children aged 30–83 months, Barnard-Brak et al. found good evidence of reliability and construct validity regardless of race, in a subsample of Nimstim pictures that Tottenham and colleagues reported as receiving a reliability rating of .80 or above. In the current research, chosen NimStim stimuli had received reliability ratings of at least 0.9 for angry expressions and 0.98 for happy expressions . The stimuli were rectangular in shape (length 16.8 cm and height 13.5 cm) and presented in the middle (6.8 cm from the top and bottom and 8.5 cm from the side bezels) of a 17 in., 4:3 dell monitor screen. In the Pre-Switch condition children were exposed to 50 trials with Pirate A appearing happy on a Color A background and Pirate B appearing angry on a Color B background. In the Post-Switch Blocks the pirates faces were “switched” for 66/78 trials. That is, children viewed the same stimuli, but for the majority of trials Pirate A now appeared angry on his same color background and Pirate B now appeared happy on his same color background, with the exception that in each post-switch block a small proportion of stimuli (12 trials) were identical to those used in the pre-condition trials. These 12 “pre” switch trials were intentionally included in the “post” switch block to maintain their pre-potent influence, prevent a complete association between the new color--expression pairings, and maintain the need for cognitive inhibition/selection during the latter post-switch stages. Both the pre- and post- switch portions of the task required attention to, and the perception of, emotional expressions. However, amongst children who formed associations between actors, emotional expressions, and backgrounds during the pre-switch phase, the post-switch phase was expected to require the inhibition of irrelevant exogenous information. Likewise during post-switch, amongst children who formed associations, the task was expected to require the management of conflict resulting from the difference in the current stimuli and the previously learned information (i.e., the expression-actor-color pairing). See Fig. a & b. The paradigm was manually forwarded by an experimenter to ensure that the child was looking at the screen before the stimulus appeared. Each stimulus was presented for a minimum of 1100 milliseconds and up to 10,000 milliseconds or until the child responded. Stimuli were separated by a 500 msec inter-stimulus interval. The experiment was conducted in a well-lit room and an experimenter was with the child in the room to provide instructions. The experimenter sat behind the child at the child’s 7 o’clock when the test trials began but did not help or guide the child in anyway during the test trials.
ERP was recorded using an EGI Dense Array EEG 300 system with a 0.1–100 Hz filter, initially referenced to the Vertex. A 128-channel geodesic hydrocel routine (sponge) net, without eye electrodes, was used during the experiment. Participants’ electroencephalogram (EEG) recordings were processed using Netstation 4.5.1 software (See Fig. ). Extraction windows were determined by reviewing both the grand average, as well as individual files so as to capture variation across individuals and across the 44 included frontal and central channels (see Additional file : Table S1 for a complete listing as well as Additional file : Figure S1). Extraction ranges for the N1, P2, and N2 were, respectively as follows: 62–206 msec, 197–341 msec, and 312–504 msec. These are similar to the timings identified in 4–8 year olds (e.g., initial negative deflection = 92–176; positive deflection = 250; N2 = 350, ; N2 = 300–500, ). Components were quantified by peak amplitudes. In keeping with studies of young children, we focused upon frontal and central channels (e.g., ). Included individual averages were comprised of an average of 37.92 pre-switch (76%; range: 20–49) and 45.23 post-switch (69%; range: 22–26) trials.
Task performance Differences in pre- and post- switch blocks behavioral performance (i.e., accuracy and reaction time) were examined. First, we compared behavioral data in the pre- and post- switch conditions. We expected that children who experienced cognitive conflict during the post-switch phase would exhibit less accuracy and slower reaction times during this latter condition . These analyses were conducted via a Repeated Measures ANCOVA, with gender and antenatal anxiety serving as covariates and pre-versus-post performance serving as the within subjects “Condition” variable. In addition we controlled for whether or not the children passed pre-switch (i.e., 75% or more accuracy). Children who did not pass pre-switch may have had difficulties perceiving emotions, but they may also simply not have understood the task’s instructions. Identical analyses compared the N1, P2_N1 and N2_P2 components during the pre-and post-switch conditions. Neither behavioral nor electrophysiological analyses included data from the 12 trials where pre-switch stimuli were presented in the post-switch blocks. Antenatal anxiety and post-condition ERP’s In cases where ANCOVA’s revealed significant differences between pre- and post- conditions, relations were further re-explored. In such cases, antenatal maternal anxiety was entered as a predictor variable in a regression where relevant ERP activity served as the outcome variable. These linear regressions adjusted for gender as well as possible confounders of pass-fail status and pre-condition. Given concerns about statistical power, no other potentially relevant covariates were included in our models. Such covariates were screened, and none (i.e., maternal age, household income, maternal education, ethnicity, child age at test) significantly correlated with both maternal mental health and child electrophysiology (see Additional file : Table S2). Next, to examine the potential moderating role of gender, we performed very similar analyses. The difference in this set of analyses was that rather than control for gender, we treated antenatal anxiety, gender, and their interaction as predictors. Subsequently, to address specificity, identical regressions were repeated examining depression, rather than anxiety, symptomatology. Then, to determine whether any of these observed findings would be better explained via associations with postnatal maternal mental health, we repeated the models containing antenatal maternal mental health symptoms, gender, pre-condition amplitude, and pre-switch passing status, additionally adjusting for postnatal maternal anxiety/depression symptoms. This adjustment was done in a separate step to guard against possible spurious associations arising from adjustment of mediator-colliders .
Differences in pre- and post- switch blocks behavioral performance (i.e., accuracy and reaction time) were examined. First, we compared behavioral data in the pre- and post- switch conditions. We expected that children who experienced cognitive conflict during the post-switch phase would exhibit less accuracy and slower reaction times during this latter condition . These analyses were conducted via a Repeated Measures ANCOVA, with gender and antenatal anxiety serving as covariates and pre-versus-post performance serving as the within subjects “Condition” variable. In addition we controlled for whether or not the children passed pre-switch (i.e., 75% or more accuracy). Children who did not pass pre-switch may have had difficulties perceiving emotions, but they may also simply not have understood the task’s instructions. Identical analyses compared the N1, P2_N1 and N2_P2 components during the pre-and post-switch conditions. Neither behavioral nor electrophysiological analyses included data from the 12 trials where pre-switch stimuli were presented in the post-switch blocks.
In cases where ANCOVA’s revealed significant differences between pre- and post- conditions, relations were further re-explored. In such cases, antenatal maternal anxiety was entered as a predictor variable in a regression where relevant ERP activity served as the outcome variable. These linear regressions adjusted for gender as well as possible confounders of pass-fail status and pre-condition. Given concerns about statistical power, no other potentially relevant covariates were included in our models. Such covariates were screened, and none (i.e., maternal age, household income, maternal education, ethnicity, child age at test) significantly correlated with both maternal mental health and child electrophysiology (see Additional file : Table S2). Next, to examine the potential moderating role of gender, we performed very similar analyses. The difference in this set of analyses was that rather than control for gender, we treated antenatal anxiety, gender, and their interaction as predictors. Subsequently, to address specificity, identical regressions were repeated examining depression, rather than anxiety, symptomatology. Then, to determine whether any of these observed findings would be better explained via associations with postnatal maternal mental health, we repeated the models containing antenatal maternal mental health symptoms, gender, pre-condition amplitude, and pre-switch passing status, additionally adjusting for postnatal maternal anxiety/depression symptoms. This adjustment was done in a separate step to guard against possible spurious associations arising from adjustment of mediator-colliders .
Task statistics Descriptive statistics and comparisons of included versus excluded dyads Amongst the 479 singleton-born preschoolers who attended the laboratory visit, those providing artefact free data (hereafter “ERP+”) were from families with slightly greater household income than were those who did not (hereafter “ERP-,”), t(446) = 2.53, p = .012. There were no significant differences between the ERP+ and ERP- groups with regards to maternal education. In addition, the ERP+ children were very slightly but significantly older (i.e., mean difference in age of ~ 8 days), t (477) = 2.24, p = 0.025. There were no differences in maternal age, ethnicity, or child gender. ERP+ preschoolers had mothers who indicated lower levels of antenatal mental health symptoms than those who did not, t (457) Anxiety = − 2.81, p = 0.005; t (465) Depression = − 1.98, p = 0.048. No significant differences were observed with regards to postnatal maternal mental health. The ERP+ ( n = 71) group also did not differ from a subset of the ERP- group ( n = 33) comprised of children who met task behavioral expectations, but were excluded due to excessive artefacts, with regards to post-switch accuracy, post switch correct reaction time and pre-switch accuracy, though the correct reaction times of the ERP+ group were marginally faster than those of the ERP-group (ERP+: M = 1786.49 msec, SD = 722.35 msec; ERP-: 2109.21 msec, SD = 942.29 msec, t(102) = − 1.92, p = 0.06). Additional statistics, as well as means/frequencies for the ERP+ and ERP- groups can be found in Table . Pre- vs post- condition behavioral data in the included sample As reported in Additional file : Table S3, accounting for antenatal anxiety, gender, and whether or not the child passed pre-switch, no significant differences were observed with either accuracy or correct reaction times across pre and post conditions, nor were any interactions between gender/antenatal anxiety/failure of pre-switch and pre-post performance observed. Pre- vs post- condition electrophysiological data (see Table ) When considering whether or not children passed pre-switch, as well as anxiety and gender, significant differences were observed between the N1 amplitude in the pre and post condition (F (1, 64) = 7.74, p < 0.01), as well as for the P2_N1 amplitude in the pre and post condition (F (1, 64) = 6.27, p < 0.05), but no significant differences were observed for N2_P2 amplitude. In addition, both the N1 amplitude pre-post difference (F (1, 64) = 5.62, p < .05) and the P2_N1 amplitude pre-post difference (F (1, 64) = 6.24, p < .05)) were significantly moderated by anxiety. The P2_N1 amplitude pre-post difference was also significantly moderated by gender, F (1, 64) = 5.58, p < 0.05). Antenatal anxiety and post condition ERP’s (see Table and Figs. , , ) As noted, the N1 and P2_N1 amplitudes significantly differed between pre-and post- conditions. Therefore, we further explored anxiety’s relation to the N1 post condition and the P2_N1 post condition in a series of regression analyses, reported in Table (See Additional file : Table S4, for correlations between mental health and the N1-PRE, P2_N1-PRE, N1-POST, and separately P2_N1-POST). Both maternal anxiety and maternal depression significantly associated with “smaller” (less negative) N1-POST amplitudes, (Anxiety: B = 0.38, p < .001; Depression: B = 0.35, p < .001). These relations were marginally (in the case of anxiety) and significantly (in the case of depression) moderated by gender (Anxiety*Gender: B = 0.20, p < . 10; Depression*Gender: B = 0.21, p < .05). Both antenatal anxiety and depressive symptoms remained significant predictors of N1-POST when postnatal maternal mental health was considered (Anxiety: B = 0.48, p < .001; Depression: B = 0.42, p < .001). In addition, both maternal anxiety and maternal depression significantly associated with smaller (less positive) P2_N1-POST amplitudes (Anxiety: B = − 0.34, p < .001; Depression: B = − 0.27, p < .05. Though gender was also significantly associated it did not moderate relations with P2_N1-POST amplitudes. Both antenatal anxiety and depressive symptoms remained significant predictors of P2_N1-POST when postnatal maternal mental health was considered (Anxiety: B = 0.45, p < .001; Depression: B = 0.40, p < .01). Because one case was an outlier from the regression mean in all our analyses, we repeated the regressions after removing that case. Regardless of whether we included maternal postnatal anxiety into the models, or concurrently examined maternal anxiety x gender, the main effect of maternal antenatal anxiety remained significantly predictive of the N1 and P2_N1, with p values ranging from p < 0.001 to p = 0.004. Likewise, regardless of whether we included maternal postnatal depression in our models, or included the interactive effect of depression x gender, the main effect of maternal antenatal depression remained a significant (i.e., in four models p’s ranged from 0.007 to 0.016) or marginal (i.e., in two models p was <.10) predictor of the N1 and P2_N1. In contrast, after removing the one outlying case, the interactive effects of maternal mental health and gender upon the N1 became non-significant (antenatal anxiety x gender: p = 0.53; antenatal depression x gender: p = 0.44), and remained non-significant with regards to the P2_N1.
Descriptive statistics and comparisons of included versus excluded dyads Amongst the 479 singleton-born preschoolers who attended the laboratory visit, those providing artefact free data (hereafter “ERP+”) were from families with slightly greater household income than were those who did not (hereafter “ERP-,”), t(446) = 2.53, p = .012. There were no significant differences between the ERP+ and ERP- groups with regards to maternal education. In addition, the ERP+ children were very slightly but significantly older (i.e., mean difference in age of ~ 8 days), t (477) = 2.24, p = 0.025. There were no differences in maternal age, ethnicity, or child gender. ERP+ preschoolers had mothers who indicated lower levels of antenatal mental health symptoms than those who did not, t (457) Anxiety = − 2.81, p = 0.005; t (465) Depression = − 1.98, p = 0.048. No significant differences were observed with regards to postnatal maternal mental health. The ERP+ ( n = 71) group also did not differ from a subset of the ERP- group ( n = 33) comprised of children who met task behavioral expectations, but were excluded due to excessive artefacts, with regards to post-switch accuracy, post switch correct reaction time and pre-switch accuracy, though the correct reaction times of the ERP+ group were marginally faster than those of the ERP-group (ERP+: M = 1786.49 msec, SD = 722.35 msec; ERP-: 2109.21 msec, SD = 942.29 msec, t(102) = − 1.92, p = 0.06). Additional statistics, as well as means/frequencies for the ERP+ and ERP- groups can be found in Table . Pre- vs post- condition behavioral data in the included sample As reported in Additional file : Table S3, accounting for antenatal anxiety, gender, and whether or not the child passed pre-switch, no significant differences were observed with either accuracy or correct reaction times across pre and post conditions, nor were any interactions between gender/antenatal anxiety/failure of pre-switch and pre-post performance observed. Pre- vs post- condition electrophysiological data (see Table ) When considering whether or not children passed pre-switch, as well as anxiety and gender, significant differences were observed between the N1 amplitude in the pre and post condition (F (1, 64) = 7.74, p < 0.01), as well as for the P2_N1 amplitude in the pre and post condition (F (1, 64) = 6.27, p < 0.05), but no significant differences were observed for N2_P2 amplitude. In addition, both the N1 amplitude pre-post difference (F (1, 64) = 5.62, p < .05) and the P2_N1 amplitude pre-post difference (F (1, 64) = 6.24, p < .05)) were significantly moderated by anxiety. The P2_N1 amplitude pre-post difference was also significantly moderated by gender, F (1, 64) = 5.58, p < 0.05).
Amongst the 479 singleton-born preschoolers who attended the laboratory visit, those providing artefact free data (hereafter “ERP+”) were from families with slightly greater household income than were those who did not (hereafter “ERP-,”), t(446) = 2.53, p = .012. There were no significant differences between the ERP+ and ERP- groups with regards to maternal education. In addition, the ERP+ children were very slightly but significantly older (i.e., mean difference in age of ~ 8 days), t (477) = 2.24, p = 0.025. There were no differences in maternal age, ethnicity, or child gender. ERP+ preschoolers had mothers who indicated lower levels of antenatal mental health symptoms than those who did not, t (457) Anxiety = − 2.81, p = 0.005; t (465) Depression = − 1.98, p = 0.048. No significant differences were observed with regards to postnatal maternal mental health. The ERP+ ( n = 71) group also did not differ from a subset of the ERP- group ( n = 33) comprised of children who met task behavioral expectations, but were excluded due to excessive artefacts, with regards to post-switch accuracy, post switch correct reaction time and pre-switch accuracy, though the correct reaction times of the ERP+ group were marginally faster than those of the ERP-group (ERP+: M = 1786.49 msec, SD = 722.35 msec; ERP-: 2109.21 msec, SD = 942.29 msec, t(102) = − 1.92, p = 0.06). Additional statistics, as well as means/frequencies for the ERP+ and ERP- groups can be found in Table .
As reported in Additional file : Table S3, accounting for antenatal anxiety, gender, and whether or not the child passed pre-switch, no significant differences were observed with either accuracy or correct reaction times across pre and post conditions, nor were any interactions between gender/antenatal anxiety/failure of pre-switch and pre-post performance observed.
) When considering whether or not children passed pre-switch, as well as anxiety and gender, significant differences were observed between the N1 amplitude in the pre and post condition (F (1, 64) = 7.74, p < 0.01), as well as for the P2_N1 amplitude in the pre and post condition (F (1, 64) = 6.27, p < 0.05), but no significant differences were observed for N2_P2 amplitude. In addition, both the N1 amplitude pre-post difference (F (1, 64) = 5.62, p < .05) and the P2_N1 amplitude pre-post difference (F (1, 64) = 6.24, p < .05)) were significantly moderated by anxiety. The P2_N1 amplitude pre-post difference was also significantly moderated by gender, F (1, 64) = 5.58, p < 0.05).
and Figs. , , ) As noted, the N1 and P2_N1 amplitudes significantly differed between pre-and post- conditions. Therefore, we further explored anxiety’s relation to the N1 post condition and the P2_N1 post condition in a series of regression analyses, reported in Table (See Additional file : Table S4, for correlations between mental health and the N1-PRE, P2_N1-PRE, N1-POST, and separately P2_N1-POST). Both maternal anxiety and maternal depression significantly associated with “smaller” (less negative) N1-POST amplitudes, (Anxiety: B = 0.38, p < .001; Depression: B = 0.35, p < .001). These relations were marginally (in the case of anxiety) and significantly (in the case of depression) moderated by gender (Anxiety*Gender: B = 0.20, p < . 10; Depression*Gender: B = 0.21, p < .05). Both antenatal anxiety and depressive symptoms remained significant predictors of N1-POST when postnatal maternal mental health was considered (Anxiety: B = 0.48, p < .001; Depression: B = 0.42, p < .001). In addition, both maternal anxiety and maternal depression significantly associated with smaller (less positive) P2_N1-POST amplitudes (Anxiety: B = − 0.34, p < .001; Depression: B = − 0.27, p < .05. Though gender was also significantly associated it did not moderate relations with P2_N1-POST amplitudes. Both antenatal anxiety and depressive symptoms remained significant predictors of P2_N1-POST when postnatal maternal mental health was considered (Anxiety: B = 0.45, p < .001; Depression: B = 0.40, p < .01). Because one case was an outlier from the regression mean in all our analyses, we repeated the regressions after removing that case. Regardless of whether we included maternal postnatal anxiety into the models, or concurrently examined maternal anxiety x gender, the main effect of maternal antenatal anxiety remained significantly predictive of the N1 and P2_N1, with p values ranging from p < 0.001 to p = 0.004. Likewise, regardless of whether we included maternal postnatal depression in our models, or included the interactive effect of depression x gender, the main effect of maternal antenatal depression remained a significant (i.e., in four models p’s ranged from 0.007 to 0.016) or marginal (i.e., in two models p was <.10) predictor of the N1 and P2_N1. In contrast, after removing the one outlying case, the interactive effects of maternal mental health and gender upon the N1 became non-significant (antenatal anxiety x gender: p = 0.53; antenatal depression x gender: p = 0.44), and remained non-significant with regards to the P2_N1.
Despite maternal anxiety’s prevalence and its import to child outcomes, to our knowledge, this is the first investigation of maternal antenatal anxiety symptomatology and performance during a preschool electrophysiology task designed to tap executive functioning, as well as attention, emotion perception, and memory formation. We observed significant associations between antenatal maternal anxiety symptoms and preschoolers’ neurophysiology, which remained after adjusting for postnatal influences. This echoes findings from a large-scale examination of maternal antenatal and postnatal anxiety and other aspects of cognitive functioning . Likewise, we observed similar associations between antenatal maternal depression symptoms and preschool functioning, despite relatively low average scores for maternal antenatal depression in the current sample. Notable associations occurred between maternal mental health and both the N1-POST and N1_P2-POST amplitudes. Higher levels of antenatal anxiety, and depression, predicted less N1-POST activity, or less downward fluctuation in this negative-going early component, often associated with sensory discrimination and exogenous inhibition. Past research suggests exogenous inhibition may not be affected in older offspring of mothers with antenatal anxiety , though work with infants finds antenatal anxiety predictive of alterations in relatively early stages of information processing including those indicative of attention . In accordance with these findings from infants, here in our sample of preschoolers, we additional observed higher antenatal maternal anxiety and depression associated with smaller P2 amplitudes, perhaps indicating differential attention to the emotional faces. For example, social anxiety in children has previously been found associated with lower P2 amplitudes from frontal channels in response to pictures of angry and neutral NimStim faces . Still, and of note, in the current research, significant correlations were only observed between the maternal mental health variable and post, but not pre, switch components. Were observed differences entirely due to variation in emotional salience and/or perception, relations should have been observed with both pre- and post-switch blocks. Alternatively, then, our findings might also suggest that those exposed to higher levels of antenatal maternal mental health symptoms found the task to be easier , requiring less attentional capacity. Why might this be the case? One post-hoc explanation is that preschoolers born to mothers who experienced higher levels of maternal mental health symptomatology may have approached the task differently, and thus had less need for attentional processing as well as exogenous inhibition during the post-switch phase. Although work in other fields suggests that elements of anticipatory control may be observed beginning in infancy , ERP research suggests that young children may not exhibit attentional anticipatory control unless required to do so, instead relying on reactive control. The P2 may index attention to salient information as well as proactive interference, arising from a prior stimulus-associated response—with its magnitude influenced by the extent of the prior association. If children formed a strong association between the context (i.e., actor identity and background color), expression, and left-versus-right button press response, then following the switch, the prior context-response association may have been considered more salient and/or created proactive interference for children as they assessed the stimuli. If, children born to mothers higher on anxiety did not (or did not fully) form such associations, then the significance of the stimuli as well as any proactive interference would be expected to decline, and their P2s might have been smaller in magnitude than those born to mothers lower on anxiety. Likewise, more negative N1’s are typically associated with greater difficulty . If preschoolers (born to mothers low on antenatal anxiety) were better at forming associations between the colors-faces-and-actors during the pre-switch condition, they would have, de facto, have had more need for exogenous inhibition during the post-switch, and so more pronounced N1-POSTs. Indeed, within GUSTO, antenatal anxiety associates with infant hippocampal development and worsened memory for associations between pairs . Alternatively, it is also possible that the children who were high on antenatal anxiety were simply less distracted by extraneous details, focusing more on the emotions, and so showing less conflict or attention. However, this does not seem likely as significant simple correlations between maternal mental health and pre-switch N1 and P2_N1 components were not observed. As such it also seems unlikely that the current findings simply reflect a lack of overall task engagement. Despite its novelty, the current work had a number of limitations. Given the paucity of similar preschool research, and because we expected our final sample would be limited in size, we created a task that we hoped would tap cognitive flexibility/inhibition but that also was achievable by children of this age and incorporated multiple processes likely impacted by anxiety. This approach increased feasibility and ecological validity and allowed us the greatest chance of avoiding Type II errors. However, it limits our understanding of the exact cognitive mechanism behind the observed association. In addition, it also limits the extent to which we can compare our findings with those observed in older offspring of mothers high on antenatal anxiety. Work with older offspring suggests relations with endogenous forms of cognitive inhibition (i.e., the N2). Here we did not observe such effects. This may not be surprising as work examining the N2 in 4–8 year olds suggests that the N2 effect may only be observed in children older than 6 years of age . Furthermore, our pattern of findings suggests that for some children, this task may not even have measured executive control. Likewise, though we suspect that our between group N1 and P2 differences may have been influenced by differences in the formation of associations between expressions, actors, colors, and responses, we do not have enough post-switch trials to further test this explanation. To better assess this idea, future work should determine whether, as would be expected , N1 and P2 amplitudes decrease across repeat post-switch trials as children update associative memory with the post-switch color-actor-expression associations. Likewise it should examine whether N1 amplitudes become less pronounced as extraneous aspects of the stimuli become less salient. Second, the large amount of data loss cannot be ignored, and may have been further minimized by the use of more technologically advanced ERP processing pipelines including newly freely available platforms such as HAPPE . Yet, our sample of 71 three-and-a-half year olds is as large or larger than other similar preschool ERP investigations of executive functioning (e.g., n = 50 ; n = 27 ). Moreover, the most similar research, which has been conducted with not only 3 year olds but also older preschoolers who may be more compliant, also exhibits somewhat high levels of data loss (e.g. 30% lost in three-to-four-and-a-half year olds, ; 45% lost in 3-to-5 year old control subjects, ; 25% lost in four-to-six-year-olds, ). In the current research, amongst children who took part in the task and fulfilled behavioral criteria, about 25% were excluded due to excessive artefacts. The majority of data were “lost” due to the parent’s or preschooler’s refusal to take part in the task ( n = 174) or because the preschooler did not meet behavioral expectations during the task ( n = 182). It is difficult to know whether similar refusal rates occur in other developmental ERP research: unlike what occurs in many projects, here, participants did not come to the laboratory specifically to take part in an ERP experiment, but rather to participate in a general cognitive-emotional follow up session for 3 year olds participating in a cohort study. That is, the sample was not pre-selected for ERP interest, nor was performing ERP the only goal of the visit. Indeed, this may have resulted in a more representative sample than what is typically observed- with demographics indicating that the ERP+ and ERP- groups were similar with regards to maternal education. Furthermore, although the groups did show differences with regards to household income, even the “wealthier” ERP+ group had mean incomes and educational levels that were in keeping with those observed in Singapore as a whole. This is in contrast to other ERP samples with levels of maternal education that exceed the population median. Nevertheless, although mean antenatal mental health scores amongst both ERP+ and ERP- mothers were below STAI and EPDS clinical screening “cutoffs” , ERP- mothers reported significantly higher scores. Future research may wish to specifically target children whose mothers screened high for antenatal maternal mental health problems to determine whether the current results differ in populations at greater risk. The inclusion of a broader participant pool may also allow for a better understanding of the moderating role of gender at this developmental stage. Work with older children and adolescents reports larger effects in male than female offspring. Whilst our initial findings suggested that maternal mental health differentially impacted female and male preschool offspring electrophysiology, after removing an outlier, the maternal mental health by gender interactions did not remain significant. Larger more inclusive studies will be able to better determine whether our initial findings concerning an interactive role of gender were spurious.
We observed antenatal maternal anxiety and depression symptoms related to neurophysiology. These effects were not attenuated by postnatal maternal mental health. This electrophysiological study, then, echoes research examining antenatal mental health and neonatal brain development , and underscores the importance of interventions to improve maternal psychological well-being prior to or during the antenatal period. Moreover, our findings suggest the potential need for early life cognitive-emotional intervention-prevention programs targeted to offspring of mothers who experienced depression and anxiety symptoms during pregnancy. Such programs might focus on associative memory, exogenous sensory inhibition, attention, and/or emotional processing difficulties.
Additional file 1: Table S1. List of Included Electrodes by Hemisphere and Region. Table S2. Relations between Covariates, Antenatal Maternal Mental Health, and Preschool Electrophysiology. Table S3. Task Behavioral Performance. Table S4. Correlations between Maternal Mental Health and ERP Variables. Figure S1. Topography in the 71 ERP+ sample.
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The proteomic landscape of trophoblasts unravels calcium-dependent syncytialization processes and beta-chorionic gonadotropin (ß-hCG) production | a4591906-dabb-4aa5-b857-0410dc796020 | 11877844 | Biochemistry[mh] | The human placenta is a highly specialized organ necessary for the normal growth and development of the fetus. Therefore, the proper differentiation and fusion of villous cytotrophoblasts into multinucleated syncytiotrophoblasts (STB) plays a crucial role in implantation, feto-maternal nutrient exchange, and the production of pregnancy hormones as human chorionic gonadotropin (hCG), progesterone and estrogen . However, an insufficient syncytialization process is associated with various pregnancy disorders as pre-eclampsia (PE), intrauterine growth restriction (IUGR) or spontaneous abortion . The involvement of several proteins in syncytialization has been investigated in various studies. For example, syncytin-1 , syncytin-2 , E-cadherin or the formation of hCG are common syncytialization markers of trophoblasts. The syncytialization process is mediated by several signaling pathways including cAMP-PKA, MAPK11/14, ERK /2, Wnt/beta-catenin and p38MAPK . Activation of the cAMP-PKA pathway leads to the formation of the transcription factor Glial Cell Missing 1 (GCM1), which initiates the expression of Syncytin-1 (ERVW-1), which is essential for cell fusion . In addition, an increase in cyclic adenosine monophosphate (cAMP) promotes the expression of marker proteins such as hCG β-subunit, placental protein 13, human placental lactogen and placental alkaline phosphatase . Primary trophoblasts survive for a few days in culture, therefore in vitro cell culture models for human trophoblasts, such as BeWo or JEG-3 cells, have been used for many years . BeWo cells originate from a chorionic carcinoma of the fetal placenta derived from a male fetus and have similar properties to primary trophoblasts. BeWo cells grow adherently, are epithelial-like and syncytialization is inducible by forskolin (FSK). Like the primary trophoblasts of the human placenta, BeWo cells also produce and secrete hormones, including the peptide hormones human chorionic gonadotropin (hCG = pregnancy hormone) and chorionic somatomammotropin (placental lactogen) as well as various steroid hormones such as progesterone and estradiol. In contrast, JEG-3 cells do not syncytialize after FSK stimulation . BeWo cells are therefore a suitable model system to investigate trophoblast syncytialization and hormone production and secretion. The active transport of minerals from the maternal to the fetal side of the placenta is achieved by the syncytiotrophoblast layer . Some ion channels of the transient receptor potential (TRP) family appear to play an essential role in this process. Among others TRPV6, TRPV2 and TRPM7 transcripts are detectable in human syncytiotrophoblasts and mouse placenta . An insufficient supply of calcium to the fetus during pregnancy manifests itself as skeletal dysplasia accompanied with reduced growth of the embryo. This phenotype was observed in TRPV6 knockout ( Trpv6 −/− ) mice as well as in Trpv6 mt/mt mice which have a single point mutation within the pore of the channel. Compared to wild-type trophoblasts, Trpv6 mt/mt trophoblasts have a lower calcium content, different morphology and altered protein profiles, e.g. proteins that are necessary for the formation of the extracellular matrix are deregulated . Additionally primary trophoblasts from wildtype mice cultured in the presence of low calcium show a phenotype similar to Trpv6 −/− mice . This suggests that the role of calcium should also be further investigated in human trophoblasts and syncytiotrophoblasts. Human BeWo cells also express TRPV2 and TRPV6 and their morphology also depend on the extracellular calcium concentration . The morphology and physiology of mouse and human placenta differ in many aspects, e.g. there appears to be no orthologue of the human pregnancy hormone β-hCG in mice. Therefore, we decided to analyze the calcium dependence of protein profiles in BeWo cells, which have many of the characteristics of human placental trophoblasts and therefore represent cytotrophoblast- and, after FSK induced cell fusion, syncytiotrophoblast-like phenotypes.
BeWo cell culture Human BeWo cells (Ubigene, Montrouge, France) were cultured in F-12 Nut Mix medium (ThermoFisher, Karlsruhe, Germany) containing 2mM Glutamax, 20% fetal bovine serum (Corning, Tewksbury, MA, USA) and 1% penicillin/streptomycin solution (Sigma-Aldrich-Merck, Darmstadt, Germany) in 75cm 2 culture flasks in presence of 5% CO 2 at 37 °C. The medium was changed every two days and at 90% confluence the cells were washed with PBS buffer (136mM NaCl, 2.7mM KCl, 1.47mM KH 2 PO, 8mM Na 2 HPO 4 × 2H 2 O) before trypsin incubation (21.5µM Trypsin, 684µM EDTA in PBS). Immunostaining of BeWo cells The BeWo cells were grown in a 24 well plate with poly-L-lysine coated glass coverslips (diameter 12 mm) until 70% confluence. To induce syncytialization, 2mL cell culture medium was supplemented with 0.45% DMSO (Sigma-Aldrich-Merck, Darmstadt, Germany) or 30µM FSK/0.45% DMSO (Sigma-Aldrich, Darmstadt, Germany) and incubated for 48 h. The medium was removed, and the cells were washed with 300 µl PBS and fixed with methanol (-20 °C) for 20 min. Cells were washed with PBS, 300 µl of freshly prepared blocking buffer [0.1% Triton X (Carl Roth, Karlsruhe, Germany), 1% normal donkey serum (Sigma-Aldrich-Merck, Darmstadt, Germany) and 3% BSA (Carl Roth, Karlsruhe, Germany) in PBS was applied and the cells were incubated for 1 h at room temperature on the shaking plate. After removing the blocking buffer, the cells were washed 3 times with PBS for three minutes and were incubated over night at 4 °C with 250 µl of the zona occludens protein (ZO-1) specific primary antibody from rabbit (1:1000 in blocking buffer, Invitrogen, Schwerte, Germany). The next day, the primary antibody was removed, the cells were washed 3 times with PBS and incubated for 1 h at RT, protected from light, with 300 µl of the secondary antibody Alexa Fluor 488 anti-rabbit antibody (Invitrogen, Schwerte, Germany, 1:1000 in blocking buffer). After removal of the antibody and a washing step, the cell nuclei were stained using DAPI (2 µg/ml in PBS, Sigma-Aldrich-Merck, Darmstadt, Germany), the cells were washed, and the coverslips were attached to slides using mounting agent (Immu-Mount ™ , Thermo Scientific). Images of the stained BeWo cells were taken with an Imager 2 microscope (Zeiss) obtaining a Axiocam MRm (Zeiss). The fusion index was analyzed (Axio Vision 4.8) by calculating the cell fusion normalized to the cell number using the formula ((NNS-S)/T) x 100% (NNS = number of nuclei in syncytia, S = number of syncytia, T = total number of nuclei; 0.94mM Ca 2+ DMSO N = 6, n = 508; 0.94mM Ca 2+ FSK N = 6, n = 348; 0.35mM Ca 2+ DMSO N = 6, n = 367; 0.35mM Ca 2+ FSK N = 6, n = 256). Determination of β-hCG, estrogen and progesterone in BeWo cell culture supernatant To determine hormone production before/after FSK incubation, small cell culture flasks (Falkon, 25cm 2 ) were cultured until cells reached 70% confluence. BeWo cells were incubated either with medium containing 0.45% DMSO or 30µM FSK/0.45% DMSO for 48 h, medium was removed and stored at -20 °C until the β-hCG, progesterone and estradiol concentration was determined in the central laboratory of the Universitätsklinikum des Saarlandes, Germany via electrochemiluminescence immunoassay (ECLIA). BeWo cells cultured with low calcium medium For each experiment, cells were grown in four small cell culture flasks (Falkon, 25cm 2 ) until confluence reached 70%. The medium was replaced either by the cell culture medium containing 0.94mM Ca 2+ (Ca 2+ norm/N), which corresponds to the general Ca 2+ concentration used for the cultivation of BeWo cells, or reduced 0.35mM Ca 2+ (Ca 2+ low/L) with 30 μm FSK/0.45% DMSO (FSK) or with 0.45% DMSO (ctrl). The amount of EDTA was calculated with the Webmaxcstandard7/3/2009 software (0.6 mM EDTA) and calcium concentrations were validated using a Dri-Chem NX500i 546 System (FujiFilm, Japan) measurement. Cells were incubated for 48 h, and the cell culture supernatant was removed, and hormone concentration (β-hCG, progesterone and estradiol) was determined. The cells were harvested with a cell scraper (Corning, Tewksbury, MA, USA), centrifuged, washed with PBS, centrifuged again and the cell pellet was stored at -80 °C. Preparation of BeWo cell lysates for western blot proteome analysis BeWo cell lysates were prepared from the frozen cell pellets. Pellets were resuspended with 2 ml RIPA lysis buffer (150mM NaCl, 50mM Tris HCl pH 8, 5mM EDTA, 1% Nonidet P40, 0.1% SDS, 0.5% Na-deoxycholate + protease inhibitors cocktail (Roche, Mannheim, Germany) and the cells were lysed using ultrasound sonification (Bandelin, Berlin, Germany). Cell suspension was sheared 10 times (24G gauge needle) and incubated for 30 min at 4 °C on a shaker. After incubation, the suspension was centrifuged using an ultracentrifuge (Beckmann Coulter Optima ™ MAX-E ultracentrifuge) at 100.000xg at 6 °C for 1 h. The supernatant containing the solubilized proteins was collected and was used for further experiments. Protein concentration determination and precipitation with trichloroacetic acid (TCA) The protein amount was determined using the Pierce ™ BCA Protein Assay Kit (ThermoFisher, Waltham, MA, USA). Due to the low sample concentrations, for MS analysis 200 µg protein in the lysate was mixed with the same volume of 40% TCA stock solution (4 °C), incubated on ice for 20 min, centrifuged at 2 °C for 10 min at 14,000 rpm and the supernatant was discarded. The pellet was washed twice with two volumes of acetone, mixed, centrifuged and the supernatant was discarded. The pellet was dried at room temperature in an open tube and reconstituted in 30 µl 2x denaturing buffer (SDS 8% (w/v) TRIS pH 6.8 120mM, bromophenol blue 0.01% (w/v), glycine 20% (v/v), β-mercaptoethanol 10% (v/v)). Western blot 30 µg of protein lysates (1:1 diluted with 2x denaturing buffer) were denatured at 60 °C for 20 min and separated in a 4–12% SDS-polyacrylamide Bolt Bis-Tris gradient gel (Invitrogen, Schwerte, Germany) using MOPS running buffer (50 mM MOPS, 50 mM Tris, 0.1% SDS, 1 mM EDTA, pH 7.7). After separation, the proteins were transferred to nitrocellulose membrane (Trans-Blot Turbo Transfer System, Bio-Rad Laboratories, Feldkirchen, Germany), blocked and incubated with antibodies as described before . Aromatase antibody from mouse (1:100, sc-374176, Santa Cruz Biotechnology, USA) or HSD11B2 antibody from rabbit (1:200, sc-20176, Santa Cruz Biotechnology, USA) was incubated overnight at 4 °C and the secondary anti-mouse HRP antibody (1:10 000, NA9310V, GE Healthcare UK Limited, Amersham) or anti-rabbit HRP antibody (1: 30 000, NA9340V, Cytiva, Buckinghamshire, UK) for 1 h at room temperature. Calnexin antibody (1:1000, SPA865, Enzo Life Sciences, Lörrach, Germany) incubation was used as loading control. The densitometric analysis was performed with the AIDA Image Analysis Software. Preparation of BeWo cell lysates for proteome analysis 200 µg of the concentrated BeWo cell lysates were loaded on a 4–12% gradient gel (Bolt, ThermoFisher, Karlsruhe, Germany) and separated by gel electrophoresis using electrophoresis buffer. The proteins were fixed on the gel with a 40% ethanol- and 10% acetic acid solution, the gel was washed with demineralized water and the proteins were visualized with a colloidal Coomassie staining solution (0.12% (w/v) Coomassie G250, 10% (w/v) ammonium sulphate, 10% (v/v) phosphoric acid, 20% (v/v) methanol in H 2 0). Eight bands per sample were cut and alternately washed with wash solution A (50 mM NH 4 HCO 3 ) and B (50 mM NH 4 HCO 3 and 50% (v/v) acetonitrile). Disulfide bridges were reduced with 10mM dithiothreitol (in wash solution A) for 30 min at 56 °C, the free thiol groups were carbamidomethylated with 5 mM iodoacteamide (in wash solution A) incubation in the dark, and the gel bands were washed alternately with wash solutions A and B again. After drying the bands in a vacuum centrifuge, they were incubated overnight with 15 µl porcine trypsin (10 ng/µl, Promega) at 37 °C. Tryptic peptides were extracted twice after incubation with an extraction buffer (2.5% formic acid, 50% acetonitrile) in an ultrasonic bath. Combined extracts were dried in a vacuum centrifuge and resuspended in 19 µl 0.1% (v/v) formic acid. Proteome analysis with Nano-LC-HR-MS/MS Label free proteome analysis was done four times (two biological and technical replicates) for each of the four different cell culture conditions: (1) Ca 2+ norm (N) DMSO (ctrl), (2) Ca 2+ norm (N) FSK, (3) Ca 2+ low (L) DMSO (ctrl) and (4) Ca 2+ low (L) FSK, respectively. In total 144 fractions were analyzed by LC-ESI-HRMS/MS as described at Diener et al. 2023 with minor modifications. Tryptic peptides were analyzed by data-dependent nano-LC-ESI-HR-MS/MS analysis using the instrumentation setup: Ultimate 3000 RSLC nano system, Ultimate3000 RS autosampler, Nanospray Flex Ion source coupled to a Thermo Scientific Orbitrap Eclipse Tribrid mass spectrometer (Thermo Scientific, Germany). Peptides were separated with a gradient generated with buffer A (water and 0.1% formic acid) and buffer B (90% acetonitrile and 0.1% formic acid) at a flow rate of 300 nl/min: 0–5 min 4% B, 5–80 min to 31% B, 80–95 min to 50% B, 95–100 min to 90% B, 100–105 min hold 90% B, 105–106 min to 4% B and 106–120 min to 4% B. Peptides were trapped on a C18 trap column (75 μm × 2 cm, Acclaim PepMap100C18, 3 μm) and separated on a reverse phase column (nano viper DNV Pep Map ™ Neo capillary column, C18; 2 μm; 75 μm × 50 cm). The chromatography effluent was sprayed into the mass spectrometer using a nano ESI emitter (stainless steel, Thermo Scientific, ionization energy: 2.4 keV). MS1 peptide spectra were acquired using the Orbitrap analyzer ( R = 120k, RF lens = 30%, m/z = 375–1500, MaxIT: auto, profile data, intensity threshold of 10 4 ). Dynamic exclusion of the 10 most abundant peptides was performed for 60 s. MS2 spectra were collected in the linear ion trap (isolation mode: quadrupole, isolation window: 1.2, activation: HCD, HCD collision energy: 30%, scan rate: fast, data type: centroid). Raw LC-MS data analysis Raw file analysis was performed with Proteome Discoverer 3.0 (Thermo Fisher Scientific) using the Sequest HT algorithm to search against reviewed UniProt Homo sapiens database (20 354 sequences, Version November 2023). The raw files of the individual bands belonging to a sample were combined as fractions of the sample. The database search parameters were used as follows: trypsin as full proteolytic enzyme, peptides with up to two missed cleavage sites, precursor mass tolerance of 10ppm for finding peptide candidates, fragment mass tolerance of 0.6 Da for matching fragment peaks, a minimum peptide length of 6 and a maximum length of 144 with max number of peptides reported of 10, Cystein carbamidomethylation as static and oxidation (M) and N-acetylation as dynamic modification. The Peptide Spectrum Matches (PSM) validation with “Percolator” occurred using “Target/Decoy strategy” whereby validation based on q-value and false discovery rate (FDR) cutoff filter was set to 0.01. As part of label free quantification (LFQ) “Minora Feature Detector” was used to detect chromatographic peaks in MS1 data and charting them to peptide spectral matches. Just high confident PSM were used for component verification. Another part of quantification is to map features from different raw files by retention time alignment using “Feature mapper” node with a maximum retention time shift of 10 and a max mass tolerance of 10ppm allowed. Modifications with a lower site-probability threshold than 75/100 were not shown for peptides (“PSM Grouper”). The “Precursor Ion Quantifier” was main component of LFQ whereby precursor abundances based on intensity. Each protein group contained at least two peptides and in one of four comparisons at least 2 unique peptides were included for quantification. All peptides were used that were not shared between different proteins or protein groups and shared peptides were assigned to protein that had more identifications but not for the other proteins they were contained in. To correct for experimental bias the program used the total peptide amount for normalization. Protein abundances were calculated by summing sample abundances of the connected peptide groups. Proteome discoverer software used pairwise ratio method for fold change analysis and identification of differences. The abundance ratios were calculated as median of all possible pairwise ratios calculated between replicates of all connected peptides with a maximum fold change of 100. No missing value imputation was done. PD3.0 software used t-test based on distribution of “background” proteins for p -value calculation to complete statistical testing and visualized the results by generating volcano plot. The x-axis of the volcano blots displays the log2 fold change value and y-axis the log 10 p -value ( p -value significance setting 0.05; -log10 (0.05) = 1,3). Bioinformatic analysis Proteins, that were identified as significantly dysregulated were further analyzed by GO term enrichment analysis (for biological processes) with the free software ShinyGO 0.80 with 0.05 FDR cutoff ( http://bioinformatics.sdstate.edu/go/ ) (Xejin G, Jianil Q, Spors E et al. South Dakota State University (SDSU)) and GOrilla (BMC Bioinformatics 2009, 10:48) (Eran Eden, Doron Lipson, Sivan Yogev, Zohar Yakhini). To illustrate biological variances between samples, heat maps were created with the program Morpheus ( http://software.broadinstitute.org/morpheus ) using normalized abundance values of each protein. Statistical analysis and figures The statistical analysis of hormone levels, fusion index and densitometric analysis of western blot was performed with GraphPad Prism 8.0.2. When comparing two groups, the unpaired t-test was used. Multiple conditions were compared with a One-way ANOVA test corrected for multiple comparisons using Bonferroni test. A significance level of p < 0.05 was selected for both tests. Graphical Figures were created with BioRender.com and CorelDraw X7 Version 17.0.0.491.
Human BeWo cells (Ubigene, Montrouge, France) were cultured in F-12 Nut Mix medium (ThermoFisher, Karlsruhe, Germany) containing 2mM Glutamax, 20% fetal bovine serum (Corning, Tewksbury, MA, USA) and 1% penicillin/streptomycin solution (Sigma-Aldrich-Merck, Darmstadt, Germany) in 75cm 2 culture flasks in presence of 5% CO 2 at 37 °C. The medium was changed every two days and at 90% confluence the cells were washed with PBS buffer (136mM NaCl, 2.7mM KCl, 1.47mM KH 2 PO, 8mM Na 2 HPO 4 × 2H 2 O) before trypsin incubation (21.5µM Trypsin, 684µM EDTA in PBS).
The BeWo cells were grown in a 24 well plate with poly-L-lysine coated glass coverslips (diameter 12 mm) until 70% confluence. To induce syncytialization, 2mL cell culture medium was supplemented with 0.45% DMSO (Sigma-Aldrich-Merck, Darmstadt, Germany) or 30µM FSK/0.45% DMSO (Sigma-Aldrich, Darmstadt, Germany) and incubated for 48 h. The medium was removed, and the cells were washed with 300 µl PBS and fixed with methanol (-20 °C) for 20 min. Cells were washed with PBS, 300 µl of freshly prepared blocking buffer [0.1% Triton X (Carl Roth, Karlsruhe, Germany), 1% normal donkey serum (Sigma-Aldrich-Merck, Darmstadt, Germany) and 3% BSA (Carl Roth, Karlsruhe, Germany) in PBS was applied and the cells were incubated for 1 h at room temperature on the shaking plate. After removing the blocking buffer, the cells were washed 3 times with PBS for three minutes and were incubated over night at 4 °C with 250 µl of the zona occludens protein (ZO-1) specific primary antibody from rabbit (1:1000 in blocking buffer, Invitrogen, Schwerte, Germany). The next day, the primary antibody was removed, the cells were washed 3 times with PBS and incubated for 1 h at RT, protected from light, with 300 µl of the secondary antibody Alexa Fluor 488 anti-rabbit antibody (Invitrogen, Schwerte, Germany, 1:1000 in blocking buffer). After removal of the antibody and a washing step, the cell nuclei were stained using DAPI (2 µg/ml in PBS, Sigma-Aldrich-Merck, Darmstadt, Germany), the cells were washed, and the coverslips were attached to slides using mounting agent (Immu-Mount ™ , Thermo Scientific). Images of the stained BeWo cells were taken with an Imager 2 microscope (Zeiss) obtaining a Axiocam MRm (Zeiss). The fusion index was analyzed (Axio Vision 4.8) by calculating the cell fusion normalized to the cell number using the formula ((NNS-S)/T) x 100% (NNS = number of nuclei in syncytia, S = number of syncytia, T = total number of nuclei; 0.94mM Ca 2+ DMSO N = 6, n = 508; 0.94mM Ca 2+ FSK N = 6, n = 348; 0.35mM Ca 2+ DMSO N = 6, n = 367; 0.35mM Ca 2+ FSK N = 6, n = 256).
To determine hormone production before/after FSK incubation, small cell culture flasks (Falkon, 25cm 2 ) were cultured until cells reached 70% confluence. BeWo cells were incubated either with medium containing 0.45% DMSO or 30µM FSK/0.45% DMSO for 48 h, medium was removed and stored at -20 °C until the β-hCG, progesterone and estradiol concentration was determined in the central laboratory of the Universitätsklinikum des Saarlandes, Germany via electrochemiluminescence immunoassay (ECLIA).
For each experiment, cells were grown in four small cell culture flasks (Falkon, 25cm 2 ) until confluence reached 70%. The medium was replaced either by the cell culture medium containing 0.94mM Ca 2+ (Ca 2+ norm/N), which corresponds to the general Ca 2+ concentration used for the cultivation of BeWo cells, or reduced 0.35mM Ca 2+ (Ca 2+ low/L) with 30 μm FSK/0.45% DMSO (FSK) or with 0.45% DMSO (ctrl). The amount of EDTA was calculated with the Webmaxcstandard7/3/2009 software (0.6 mM EDTA) and calcium concentrations were validated using a Dri-Chem NX500i 546 System (FujiFilm, Japan) measurement. Cells were incubated for 48 h, and the cell culture supernatant was removed, and hormone concentration (β-hCG, progesterone and estradiol) was determined. The cells were harvested with a cell scraper (Corning, Tewksbury, MA, USA), centrifuged, washed with PBS, centrifuged again and the cell pellet was stored at -80 °C.
BeWo cell lysates were prepared from the frozen cell pellets. Pellets were resuspended with 2 ml RIPA lysis buffer (150mM NaCl, 50mM Tris HCl pH 8, 5mM EDTA, 1% Nonidet P40, 0.1% SDS, 0.5% Na-deoxycholate + protease inhibitors cocktail (Roche, Mannheim, Germany) and the cells were lysed using ultrasound sonification (Bandelin, Berlin, Germany). Cell suspension was sheared 10 times (24G gauge needle) and incubated for 30 min at 4 °C on a shaker. After incubation, the suspension was centrifuged using an ultracentrifuge (Beckmann Coulter Optima ™ MAX-E ultracentrifuge) at 100.000xg at 6 °C for 1 h. The supernatant containing the solubilized proteins was collected and was used for further experiments.
The protein amount was determined using the Pierce ™ BCA Protein Assay Kit (ThermoFisher, Waltham, MA, USA). Due to the low sample concentrations, for MS analysis 200 µg protein in the lysate was mixed with the same volume of 40% TCA stock solution (4 °C), incubated on ice for 20 min, centrifuged at 2 °C for 10 min at 14,000 rpm and the supernatant was discarded. The pellet was washed twice with two volumes of acetone, mixed, centrifuged and the supernatant was discarded. The pellet was dried at room temperature in an open tube and reconstituted in 30 µl 2x denaturing buffer (SDS 8% (w/v) TRIS pH 6.8 120mM, bromophenol blue 0.01% (w/v), glycine 20% (v/v), β-mercaptoethanol 10% (v/v)).
30 µg of protein lysates (1:1 diluted with 2x denaturing buffer) were denatured at 60 °C for 20 min and separated in a 4–12% SDS-polyacrylamide Bolt Bis-Tris gradient gel (Invitrogen, Schwerte, Germany) using MOPS running buffer (50 mM MOPS, 50 mM Tris, 0.1% SDS, 1 mM EDTA, pH 7.7). After separation, the proteins were transferred to nitrocellulose membrane (Trans-Blot Turbo Transfer System, Bio-Rad Laboratories, Feldkirchen, Germany), blocked and incubated with antibodies as described before . Aromatase antibody from mouse (1:100, sc-374176, Santa Cruz Biotechnology, USA) or HSD11B2 antibody from rabbit (1:200, sc-20176, Santa Cruz Biotechnology, USA) was incubated overnight at 4 °C and the secondary anti-mouse HRP antibody (1:10 000, NA9310V, GE Healthcare UK Limited, Amersham) or anti-rabbit HRP antibody (1: 30 000, NA9340V, Cytiva, Buckinghamshire, UK) for 1 h at room temperature. Calnexin antibody (1:1000, SPA865, Enzo Life Sciences, Lörrach, Germany) incubation was used as loading control. The densitometric analysis was performed with the AIDA Image Analysis Software.
200 µg of the concentrated BeWo cell lysates were loaded on a 4–12% gradient gel (Bolt, ThermoFisher, Karlsruhe, Germany) and separated by gel electrophoresis using electrophoresis buffer. The proteins were fixed on the gel with a 40% ethanol- and 10% acetic acid solution, the gel was washed with demineralized water and the proteins were visualized with a colloidal Coomassie staining solution (0.12% (w/v) Coomassie G250, 10% (w/v) ammonium sulphate, 10% (v/v) phosphoric acid, 20% (v/v) methanol in H 2 0). Eight bands per sample were cut and alternately washed with wash solution A (50 mM NH 4 HCO 3 ) and B (50 mM NH 4 HCO 3 and 50% (v/v) acetonitrile). Disulfide bridges were reduced with 10mM dithiothreitol (in wash solution A) for 30 min at 56 °C, the free thiol groups were carbamidomethylated with 5 mM iodoacteamide (in wash solution A) incubation in the dark, and the gel bands were washed alternately with wash solutions A and B again. After drying the bands in a vacuum centrifuge, they were incubated overnight with 15 µl porcine trypsin (10 ng/µl, Promega) at 37 °C. Tryptic peptides were extracted twice after incubation with an extraction buffer (2.5% formic acid, 50% acetonitrile) in an ultrasonic bath. Combined extracts were dried in a vacuum centrifuge and resuspended in 19 µl 0.1% (v/v) formic acid.
Label free proteome analysis was done four times (two biological and technical replicates) for each of the four different cell culture conditions: (1) Ca 2+ norm (N) DMSO (ctrl), (2) Ca 2+ norm (N) FSK, (3) Ca 2+ low (L) DMSO (ctrl) and (4) Ca 2+ low (L) FSK, respectively. In total 144 fractions were analyzed by LC-ESI-HRMS/MS as described at Diener et al. 2023 with minor modifications. Tryptic peptides were analyzed by data-dependent nano-LC-ESI-HR-MS/MS analysis using the instrumentation setup: Ultimate 3000 RSLC nano system, Ultimate3000 RS autosampler, Nanospray Flex Ion source coupled to a Thermo Scientific Orbitrap Eclipse Tribrid mass spectrometer (Thermo Scientific, Germany). Peptides were separated with a gradient generated with buffer A (water and 0.1% formic acid) and buffer B (90% acetonitrile and 0.1% formic acid) at a flow rate of 300 nl/min: 0–5 min 4% B, 5–80 min to 31% B, 80–95 min to 50% B, 95–100 min to 90% B, 100–105 min hold 90% B, 105–106 min to 4% B and 106–120 min to 4% B. Peptides were trapped on a C18 trap column (75 μm × 2 cm, Acclaim PepMap100C18, 3 μm) and separated on a reverse phase column (nano viper DNV Pep Map ™ Neo capillary column, C18; 2 μm; 75 μm × 50 cm). The chromatography effluent was sprayed into the mass spectrometer using a nano ESI emitter (stainless steel, Thermo Scientific, ionization energy: 2.4 keV). MS1 peptide spectra were acquired using the Orbitrap analyzer ( R = 120k, RF lens = 30%, m/z = 375–1500, MaxIT: auto, profile data, intensity threshold of 10 4 ). Dynamic exclusion of the 10 most abundant peptides was performed for 60 s. MS2 spectra were collected in the linear ion trap (isolation mode: quadrupole, isolation window: 1.2, activation: HCD, HCD collision energy: 30%, scan rate: fast, data type: centroid).
Raw file analysis was performed with Proteome Discoverer 3.0 (Thermo Fisher Scientific) using the Sequest HT algorithm to search against reviewed UniProt Homo sapiens database (20 354 sequences, Version November 2023). The raw files of the individual bands belonging to a sample were combined as fractions of the sample. The database search parameters were used as follows: trypsin as full proteolytic enzyme, peptides with up to two missed cleavage sites, precursor mass tolerance of 10ppm for finding peptide candidates, fragment mass tolerance of 0.6 Da for matching fragment peaks, a minimum peptide length of 6 and a maximum length of 144 with max number of peptides reported of 10, Cystein carbamidomethylation as static and oxidation (M) and N-acetylation as dynamic modification. The Peptide Spectrum Matches (PSM) validation with “Percolator” occurred using “Target/Decoy strategy” whereby validation based on q-value and false discovery rate (FDR) cutoff filter was set to 0.01. As part of label free quantification (LFQ) “Minora Feature Detector” was used to detect chromatographic peaks in MS1 data and charting them to peptide spectral matches. Just high confident PSM were used for component verification. Another part of quantification is to map features from different raw files by retention time alignment using “Feature mapper” node with a maximum retention time shift of 10 and a max mass tolerance of 10ppm allowed. Modifications with a lower site-probability threshold than 75/100 were not shown for peptides (“PSM Grouper”). The “Precursor Ion Quantifier” was main component of LFQ whereby precursor abundances based on intensity. Each protein group contained at least two peptides and in one of four comparisons at least 2 unique peptides were included for quantification. All peptides were used that were not shared between different proteins or protein groups and shared peptides were assigned to protein that had more identifications but not for the other proteins they were contained in. To correct for experimental bias the program used the total peptide amount for normalization. Protein abundances were calculated by summing sample abundances of the connected peptide groups. Proteome discoverer software used pairwise ratio method for fold change analysis and identification of differences. The abundance ratios were calculated as median of all possible pairwise ratios calculated between replicates of all connected peptides with a maximum fold change of 100. No missing value imputation was done. PD3.0 software used t-test based on distribution of “background” proteins for p -value calculation to complete statistical testing and visualized the results by generating volcano plot. The x-axis of the volcano blots displays the log2 fold change value and y-axis the log 10 p -value ( p -value significance setting 0.05; -log10 (0.05) = 1,3).
Proteins, that were identified as significantly dysregulated were further analyzed by GO term enrichment analysis (for biological processes) with the free software ShinyGO 0.80 with 0.05 FDR cutoff ( http://bioinformatics.sdstate.edu/go/ ) (Xejin G, Jianil Q, Spors E et al. South Dakota State University (SDSU)) and GOrilla (BMC Bioinformatics 2009, 10:48) (Eran Eden, Doron Lipson, Sivan Yogev, Zohar Yakhini). To illustrate biological variances between samples, heat maps were created with the program Morpheus ( http://software.broadinstitute.org/morpheus ) using normalized abundance values of each protein.
The statistical analysis of hormone levels, fusion index and densitometric analysis of western blot was performed with GraphPad Prism 8.0.2. When comparing two groups, the unpaired t-test was used. Multiple conditions were compared with a One-way ANOVA test corrected for multiple comparisons using Bonferroni test. A significance level of p < 0.05 was selected for both tests. Graphical Figures were created with BioRender.com and CorelDraw X7 Version 17.0.0.491.
In cell culture, FSK treatment was used to stimulate adenylate cyclase and thus increases the intracellular cAMP concentration. cAMP can in turn activate the cAMP-dependent protein kinase A (PKA) and cAMP response element binding protein (CREB) and subsequently controls cellular mechanisms such as gene transcription. In BeWo cells, PKA activation ultimately leads to the fusion of the trophoblast-like cells . Therefore, BeWo cells cultured with DMSO (negative control) represent cytotrophoblast-like cells and treatment with FSK induces differentiation in syncytiotrophoblast-like cells (STB-like cell). To validate possible changes in cell morphology as well as tight and adherend junctions of the trophoblast-like cells, the localization of the tight junctional protein zona occludens-1 (ZO-1) in the presence or absence of FSK was investigated by immunofluorescence (Suppl. Figure ). The size of the BeWo epithelial cells and their cell nuclei increased after FSK treatment (Suppl. Figure A). In contrast, the length of continuous ZO-1 staining between adjacent cells decreased, indicating the disruption of tight junctions resulting in the presence of multinucleated fused cells. Moreover, after FSK treatment BeWo cells show a high fusion index ((NNS-S)/T) x 100%, NNS = number of nuclei in syncytia, S = number of syncytia, T = total number of nuclei) (Suppl. Figure B). The β-hCG concentration also increased significantly after FSK (Suppl. Figure C), whereby the stimulated BeWo cells in the cell culture secreted an average of 953 mIU/ml hCG. Syncytialization of cytotrophoblast-like cells depends on the extracellular calcium concentration As shown in previous experiments, mouse trophoblasts and BeWo cell morphology and function depends on the presence of intra-and extracellular calcium . BeWo cells cultured in the presence of different calcium concentrations (Suppl. Figure ) show an altered morphology at 0.35mM Ca 2+ but are still able to grow. Therefore, we decided to compare the normal Ca 2+ concentration in the medium of 0.94 mM, with the 0.35 mM concentration, which was chosen as the low-calcium condition. First, the influence of the reduced extracellular calcium concentration on cell fusion was visualized by immunostaining with the ZO-1 antibody. Therefore, the calcium concentration was reduced from 0.94 mM (in the following named as Ca 2+ normal and labelled in figures as Ca 2+ N) to 0.35mM (in the following named as Ca 2+ low and labelled in figures as Ca 2+ L) in the medium, BeWo cells were treated with FSK or DMSO (Fig. A) and the fusion index was determined. In the presence of FSK the fusion index was significantly higher under both low and normal calcium concentrations. The fusion index was significantly higher in the presence of FSK and normal calcium compared to cells cultured in low calcium medium and FSK (Fig. B), whereas the fusion index of cells cultured with DMSO was not significantly different. The experiment shows that the fusion of the trophoblasts also depends on the extracellular calcium concentration. β-hCG, estradiol and progesterone secretion is differentially stimulated by calcium The pregnancy hormone and syncytialization marker β-hCG is involved in different processes in syncytiotrophoblasts . It is secreted autocrine and controls cytotrophoblast cell fusion and steroid hormone synthesis . We next tested if calcium has an impact on hCG secretion (Fig. A). As expected, the β-hCG secretion increased after BeWo cell incubation with FSK in the presence of normal and reduced calcium exposure about 3.6 and 3.4 times, respectively (Suppl. Figure C, Fig. A). However, the basal β-hCG secretion is lower in cells in the presence of low calcium (Suppl. Figure C) as well as after induction of syncytialization with FSK (Fig. A, Suppl. Figure B). After syncytialization of BeWo cells under low calcium conditions, only 1/3 of the regular hCG level achieved under normal calcium conditions after FSK treatment could be measured in the supernatant. This difference was also observed without FSK treatment (Suppl. Figure C, Fig. A). These results show that the β-hCG secretion of cytotrophoblast-like and the β-hCG secretion of STB-like cells are calcium dependent. The concentrations of progesterone (mean value: 56.6 ng/m) and estradiol (mean value: 901.8 pg/ml) also significantly increase after FSK treatment (Fig. B and C, Suppl. Figure D and G) in the presence of 0.94 mM calcium. However, compared with β-hCG, the secretion of estradiol and progesterone is not calcium dependent (Fig. B and C, Suppl. Figure F, I). Proteome analysis of cytotrophoblast- and syncytiotrophoblast-like phenotypes To monitor potential changes of protein expression during syncytialization we first analyzed multiple sets of proteome experiments using BeWo cells that were not stimulated (ctrl) or stimulated by FSK (48 h) to induce syncytialization. In both experiments, cells were cultured with 0.94 mM calcium (Ca 2+ N). After incubation in the presence/absence of FSK, cell lysates were prepared, same protein amounts were separated on a denaturing gel, fractionated and tryptic digested. Tryptic peptides were extracted and analyzed by nano-LC-HR-MS/MS analysis. The different fractions belonging to one sample were combined and a qualitative and semi quantitative calculation with a label free quantification method based on precursor ion intensity (abundance value) was performed. In BeWo trophoblast-like cells a total of 7260 proteins was identified before and after inducing syncytialization (Ca 2+ N ctrl, N = 4 vs. Ca 2+ N FSK, N = 4) (Fig. E, Suppl. Table ). After cell treatment with FSK, 326 proteins were upregulated or exclusively expressed ( green spots Fig. E and F, Suppl. Table ), indicating that the expression of these proteins is induced during cytotrophoblast cell fusion and is characteristic for STB cellular maintenance. This group of proteins includes well-known markers for placental epithelial cells such as nectin-4 , cytokeratin-17 and syndecan-1 , transcription factors (e.g. zinc finger proteins, GCM1), mitochondrial enzymes, candidates involved in protein kinase signaling or fatty acid and lipid biosynthesis. However, transporters and the transient receptor potential subfamily V member 2 (TRPV2) (Fig. A and D, Suppl. Figure ), a calcium permeable ion channel which was previously mentioned at the transcriptome level as part of murine placenta development, were also upregulated after FSK cell treatment. Gene Ontology (GO) term analysis of the proteins upregulated after FSK stimulation reveals GO term enrichment for biological processes like ISG15-conjugation which was already mentioned in connection with pre-eclampsia , tissue growth, hormone secretion or ATP- synthesis (Fig. B right ). On the other hand, 165 proteins occurred to be downregulated after syncytialization (Fig. E, red spots Fig. F, Suppl. Table ). Most of them are related to detoxification, stress response or processes involved in Cu/Zn ion homeostasis (Fig. B left). Of the 491 deregulated proteins we detected in this study, 40 proteins (Fig. D, blue spots in Fig. F) have an affiliation to syncytialization processes, steroid and glycoprotein hormone metabolism, or lipid synthesis (Fig. C) or are listed as “tissue enriched (placenta)” in UniProt (Fig. D). Calcium dependence of the protein expression during syncytialization and hormone synthesis Since we found that the changes in protein expression data matched with previously identified proteins with known syncytiotrophoblast function, and changes in calcium homeostasis seems to be related to some pregnancy associated pathologies, e.g. pre-eclampsia (PE), we checked whether and how protein expression profiles in cytotrophoblasts- and STB-like cells change in relation to a reduction of the extracellular calcium. For characterization of calcium dependence, the expression profiles of the following BeWo cell lysates were compared: (Ca 2+ N ctrl) vs. (Ca 2+ low ctrl) to determine calcium-dependent processes in cytotrophoblast-like cells, or (Ca 2+ N FSK) vs. (Ca 2+ low FSK) to determine calcium-dependent processes in STB-like cells, or (Ca 2+ L ctrl) vs. (Ca 2+ low FSK) to determine calcium-independent processes during syncytialization, whereby it is checked whether these proteins are also upregulated under regular calcium after syncytialization. (Fig. , Suppl. Figures , , Suppl. Tables , , ). Regarding the process of differentiation from BeWo cytotrophoblast- to STB-like cells (ctrl vs. FSK), calcium-independent syncytialization markers were identified that were significantly upregulated under both, reduced and normal calcium conditions after FSK stimulation (Ca 2+ N ctrl vs. Ca 2+ N FSK and in Ca 2+ L ctrl vs. Ca 2+ L FSK) (Fig. , Suppl. Figure , Suppl. Tables , , ). This group includes the steroid hormone synthesis enzymes aromatase (CYP19A1) ) and the cholesterol-side chain cleavage enzyme (CYP11A1), the angiogenesis-stimulating placental growth factor (PGF), the junction protein cadherin-5 (CDH5) and dysferlin (DYSF) (Suppl. Figure ), which has already been linked to cytotrophoblast fusion in model systems . Moreover, the PKA regulator A-kinase anchor protein 12 (AKAP12), pleckstrin homology-like domain family A member 3 (PHLDA3), the transcriptional regulator RING1 and YY1-binding protein (RYBP), which has also been mentioned in connection with preeclampsia and microtubule-associated serine/threonine protein kinase 4 (MAST4) were upregulated in both calcium conditions (Suppl. Tables , , , Suppl. Figure ). Further syncytialization markers such as syncytin-1 GCM1, the steroid hormone synthesis enzyme 17-beta-hydroxysteroid dehydrogenase type 1 (HSD17B1) and the known preeclampsia marker inhibin alpha chain (INHA) as well as the calcium channel TRPV2 , the cadherin binding protein Cordon bleu protein like 1 (COBLL1) and Pleckstrin homology-like domain family B member 2 (PHLDB2) could not be clearly classified with regard to their calcium dependence (Suppl. Figure ). They were only quantified as higher expressed by mass spectrometry under normal calcium (Ca 2+ N ctrl vs. Ca 2+ N FSK) conditions after FSK incubation (Suppl. Table ) but there were no differences in experiments with calcium as variable factor (Suppl. Tables , , ). In contrast to the previously mentioned proteins, however, numerous proteins were also formed in a calcium-dependent manner, for example determined by comparing the STB-like cell lysate either cultured with 0.94mM or 0.35mM calcium: 459 proteins were more abundant in FSK stimulated cells that were cultured under normal calcium (Fig. D, Suppl. Table ) and 182 proteins were more abundant under low calcium. After syncytialization under normal calcium, proteins that are part of cellular respiration were mainly increased in expression (Fig. B, left ), while pathway analysis (with ShinyGo) of upregulated proteins after syncytialization under low calcium generally revealed proteins that are part of biological processes such as fiber and organ development, intermediate filament associated processes and homeostatic processes (Fig. B, right ). Regarding the general functions (identified with GOrilla) of proteins that were significantly higher expressed after syncytialization under normal calcium Ca 2+ N FSK, it is noticeable that 40 proteins with transcriptional regulatory activity (mainly zinc finger proteins, (Fig. A, Suppl. Table ) and 21 proteins that are important for the structural constituent of ribosomes were identified. This observation is consistent with the functions of syncytiotrophoblasts, which are the main source of steroid and glycopeptide hormones in the placenta and are therefore considered to be a trigger of numerous pregnancy-preserving processes, most of which are driven by transcriptional induction . In contrast, under reduced calcium (Ca 2+ L FSK), proteins with zinc ion transmembrane transporter activity (SLC39A7, SLC39A9, SLC39A10), with sodium transmembrane transporter activity (SLC20A2, SLC38A2, SLC4A7, SLC23A2, SLC38A1) and with Ca 2+ sensor activity (STIM2) were mainly upregulated, possibly for compensatory reasons. Considering and comparing all cell culture conditions (Suppl. Tables – ) 22 of the 40 proteins (selected via UniProt for their known syncytiotrophoblast function/placental expression ( from Fig. D, blue spots in Figs. E and E) were significantly deregulated in a calcium dependent manner. Table 5 ( supplement ) shows an overview of these 40 proteins (also seen in Figs. and ) and their expression levels in relation to the culture conditions. 13 proteins were significantly more expressed under regular calcium conditions in FSK stimulated BeWo cells (Suppl. Table ). Of these proteins, some were detected as exclusively upregulated after FSK stimulation in the presence of regular calcium (NDUFAB1, S100P, SEC61G, NMES1, ATP5MG, DAD1, COX7) and some were also upregulated under reduced calcium. Interestingly their expression upregulation was higher (HSD11B2, SDC1, UBE2D2, ERVFDR-1) under regular calcium. The expression of enzymes for the synthesis of steroid hormones and the secretion of steroid hormones are increased during syncytialization Enzymes of steroid hormone synthesis were identified in the BeWo cell proteome (thickly marked in Fig. A) and, in addition, proteins that are upregulated in the presence of FSK were represented by bar charts (Fig. B-D). Aromatase, is the key enzyme for the synthesis of estradiol in trophoblasts. It is a cytochrome P450 monooxygenase that catalyzes the conversion of C19 androgens, androst-4-ene-3,17-dione (androstenedione) and testosterone to the C18 estrogens, estrone and estradiol, (Fig. A) and was detected during mass spectrometry and western blot (Fig. B). Since the secretion of estradiol in the BeWo cells is increased during syncytialization but does not appear to be calcium-dependent (Fig. C), we also monitored the aromatase expression by western blot in BeWo cell lysates ( ≙ four culture conditions). Densiometric analysis of the stain intensity of the aromatase revealed that BeWo cells treated with FSK produced significantly more aromatase under both reduced and normal calcium conditions (Fig. B, top ) and there is no significant relation to the calcium reduction, which was confirmed by mass spectrometric quantitative analysis (Fig. B, bar charts below , Suppl. Tables , , ). Therefore, synthesis of aromatase shows no calcium dependency which is in line with the measured estradiol concentrations (Fig. C). However, aromatase expression itself also appears to be a syncytial marker. 17-beta-hydroxysteroid dehydrogenase type 1 (HSD17B1) also catalyzes the synthesis of estradiol from estrone (Fig. A). The expression of HSD17B1 was only significantly increased after FSK stimulation under normal calcium conditions (Fig. D, top , Suppl. Table , Suppl. Figure ) (fusion marker) and shows the same tendency in the presence of reduced calcium. However, the HSD17B1-expression level of unstimulated (ctrl) and stimulated (FSK) cells was similar in the presence of low and high calcium. All these observations trend to favour calcium-independent estradiol synthesis in human STB. Progesterone (P4) secretion revealed to be calcium independent (Fig. B). Cholesterol serves as the precursor for steroid hormone synthesis and is transported through the plasma membrane via lipoproteins (Fig. A). The catalysis of cholesterol to progesterone takes place in the inner mitochondrial membrane. Several relevant actors are involved in this process: adrenodoxin reductase (AdxR), which transfers electrons from reduced NADP to the electron transfer protein adrenodoxin (FDX1), which provides the electrons for the catalysis reaction of cholesterol to pregnenolone by cholesterol-side chain cleavage enzyme P450 (CYP11A1). The resulting pregnenolone (P5) is converted to progesterone (P4) by 3 beta-hydroxysteroid dehydrogenase/Delta 5–>4-isomerase type 1 (HSD3B1) and cofactor NAD+ . Except for adrenodoxin reductase, all proteins involved in the synthesis of progesterone were identified by proteome analysis. Here HSD3B1 expression showed no significant differences after either FSK stimulation or calcium reduction (Suppl. Tables – ), while CYP11A1 expression was found to be increased after FSK treatment, but showed no calcium dependence (Fig. D bottom , Suppl. Tables , , , Suppl. Figure ). FDX1 is also a protein whose expression is induced by adenylyl cyclase activation during syncytialization. Regarding the FDX1 expression of FSK treated cells cultured under different calcium conditions the levels were comparable (Suppl. Table ), but expression in unstimulated cells (ctrl) was significantly reduced when cells were cultured with low calcium (Fig. C, top , Suppl. Table , Suppl. Figure ). Therefore, the expression of FDX1 may be impaired with reduced calcium in cytotrophoblasts. The expression of aldo-keto reductase family 1 member C3 (AKR1C3) also did not differ significantly after either FSK stimulation or calcium reduction (Suppl. Tables – , Suppl. Figure ). Contrary to that, the expression of 11-beta-hydroxysteroid dehydrogenase type 2 (HSD11B2), an enzyme involved in cortisol metabolism, showed calcium dependency in differentiated cells cultured in the presence of FSK (Fig. C bottom , 5E, Suppl. Table , Suppl. Figure ), as determined by MS-analysis as well as visualized by Western blot.
As shown in previous experiments, mouse trophoblasts and BeWo cell morphology and function depends on the presence of intra-and extracellular calcium . BeWo cells cultured in the presence of different calcium concentrations (Suppl. Figure ) show an altered morphology at 0.35mM Ca 2+ but are still able to grow. Therefore, we decided to compare the normal Ca 2+ concentration in the medium of 0.94 mM, with the 0.35 mM concentration, which was chosen as the low-calcium condition. First, the influence of the reduced extracellular calcium concentration on cell fusion was visualized by immunostaining with the ZO-1 antibody. Therefore, the calcium concentration was reduced from 0.94 mM (in the following named as Ca 2+ normal and labelled in figures as Ca 2+ N) to 0.35mM (in the following named as Ca 2+ low and labelled in figures as Ca 2+ L) in the medium, BeWo cells were treated with FSK or DMSO (Fig. A) and the fusion index was determined. In the presence of FSK the fusion index was significantly higher under both low and normal calcium concentrations. The fusion index was significantly higher in the presence of FSK and normal calcium compared to cells cultured in low calcium medium and FSK (Fig. B), whereas the fusion index of cells cultured with DMSO was not significantly different. The experiment shows that the fusion of the trophoblasts also depends on the extracellular calcium concentration.
The pregnancy hormone and syncytialization marker β-hCG is involved in different processes in syncytiotrophoblasts . It is secreted autocrine and controls cytotrophoblast cell fusion and steroid hormone synthesis . We next tested if calcium has an impact on hCG secretion (Fig. A). As expected, the β-hCG secretion increased after BeWo cell incubation with FSK in the presence of normal and reduced calcium exposure about 3.6 and 3.4 times, respectively (Suppl. Figure C, Fig. A). However, the basal β-hCG secretion is lower in cells in the presence of low calcium (Suppl. Figure C) as well as after induction of syncytialization with FSK (Fig. A, Suppl. Figure B). After syncytialization of BeWo cells under low calcium conditions, only 1/3 of the regular hCG level achieved under normal calcium conditions after FSK treatment could be measured in the supernatant. This difference was also observed without FSK treatment (Suppl. Figure C, Fig. A). These results show that the β-hCG secretion of cytotrophoblast-like and the β-hCG secretion of STB-like cells are calcium dependent. The concentrations of progesterone (mean value: 56.6 ng/m) and estradiol (mean value: 901.8 pg/ml) also significantly increase after FSK treatment (Fig. B and C, Suppl. Figure D and G) in the presence of 0.94 mM calcium. However, compared with β-hCG, the secretion of estradiol and progesterone is not calcium dependent (Fig. B and C, Suppl. Figure F, I).
To monitor potential changes of protein expression during syncytialization we first analyzed multiple sets of proteome experiments using BeWo cells that were not stimulated (ctrl) or stimulated by FSK (48 h) to induce syncytialization. In both experiments, cells were cultured with 0.94 mM calcium (Ca 2+ N). After incubation in the presence/absence of FSK, cell lysates were prepared, same protein amounts were separated on a denaturing gel, fractionated and tryptic digested. Tryptic peptides were extracted and analyzed by nano-LC-HR-MS/MS analysis. The different fractions belonging to one sample were combined and a qualitative and semi quantitative calculation with a label free quantification method based on precursor ion intensity (abundance value) was performed. In BeWo trophoblast-like cells a total of 7260 proteins was identified before and after inducing syncytialization (Ca 2+ N ctrl, N = 4 vs. Ca 2+ N FSK, N = 4) (Fig. E, Suppl. Table ). After cell treatment with FSK, 326 proteins were upregulated or exclusively expressed ( green spots Fig. E and F, Suppl. Table ), indicating that the expression of these proteins is induced during cytotrophoblast cell fusion and is characteristic for STB cellular maintenance. This group of proteins includes well-known markers for placental epithelial cells such as nectin-4 , cytokeratin-17 and syndecan-1 , transcription factors (e.g. zinc finger proteins, GCM1), mitochondrial enzymes, candidates involved in protein kinase signaling or fatty acid and lipid biosynthesis. However, transporters and the transient receptor potential subfamily V member 2 (TRPV2) (Fig. A and D, Suppl. Figure ), a calcium permeable ion channel which was previously mentioned at the transcriptome level as part of murine placenta development, were also upregulated after FSK cell treatment. Gene Ontology (GO) term analysis of the proteins upregulated after FSK stimulation reveals GO term enrichment for biological processes like ISG15-conjugation which was already mentioned in connection with pre-eclampsia , tissue growth, hormone secretion or ATP- synthesis (Fig. B right ). On the other hand, 165 proteins occurred to be downregulated after syncytialization (Fig. E, red spots Fig. F, Suppl. Table ). Most of them are related to detoxification, stress response or processes involved in Cu/Zn ion homeostasis (Fig. B left). Of the 491 deregulated proteins we detected in this study, 40 proteins (Fig. D, blue spots in Fig. F) have an affiliation to syncytialization processes, steroid and glycoprotein hormone metabolism, or lipid synthesis (Fig. C) or are listed as “tissue enriched (placenta)” in UniProt (Fig. D).
Since we found that the changes in protein expression data matched with previously identified proteins with known syncytiotrophoblast function, and changes in calcium homeostasis seems to be related to some pregnancy associated pathologies, e.g. pre-eclampsia (PE), we checked whether and how protein expression profiles in cytotrophoblasts- and STB-like cells change in relation to a reduction of the extracellular calcium. For characterization of calcium dependence, the expression profiles of the following BeWo cell lysates were compared: (Ca 2+ N ctrl) vs. (Ca 2+ low ctrl) to determine calcium-dependent processes in cytotrophoblast-like cells, or (Ca 2+ N FSK) vs. (Ca 2+ low FSK) to determine calcium-dependent processes in STB-like cells, or (Ca 2+ L ctrl) vs. (Ca 2+ low FSK) to determine calcium-independent processes during syncytialization, whereby it is checked whether these proteins are also upregulated under regular calcium after syncytialization. (Fig. , Suppl. Figures , , Suppl. Tables , , ). Regarding the process of differentiation from BeWo cytotrophoblast- to STB-like cells (ctrl vs. FSK), calcium-independent syncytialization markers were identified that were significantly upregulated under both, reduced and normal calcium conditions after FSK stimulation (Ca 2+ N ctrl vs. Ca 2+ N FSK and in Ca 2+ L ctrl vs. Ca 2+ L FSK) (Fig. , Suppl. Figure , Suppl. Tables , , ). This group includes the steroid hormone synthesis enzymes aromatase (CYP19A1) ) and the cholesterol-side chain cleavage enzyme (CYP11A1), the angiogenesis-stimulating placental growth factor (PGF), the junction protein cadherin-5 (CDH5) and dysferlin (DYSF) (Suppl. Figure ), which has already been linked to cytotrophoblast fusion in model systems . Moreover, the PKA regulator A-kinase anchor protein 12 (AKAP12), pleckstrin homology-like domain family A member 3 (PHLDA3), the transcriptional regulator RING1 and YY1-binding protein (RYBP), which has also been mentioned in connection with preeclampsia and microtubule-associated serine/threonine protein kinase 4 (MAST4) were upregulated in both calcium conditions (Suppl. Tables , , , Suppl. Figure ). Further syncytialization markers such as syncytin-1 GCM1, the steroid hormone synthesis enzyme 17-beta-hydroxysteroid dehydrogenase type 1 (HSD17B1) and the known preeclampsia marker inhibin alpha chain (INHA) as well as the calcium channel TRPV2 , the cadherin binding protein Cordon bleu protein like 1 (COBLL1) and Pleckstrin homology-like domain family B member 2 (PHLDB2) could not be clearly classified with regard to their calcium dependence (Suppl. Figure ). They were only quantified as higher expressed by mass spectrometry under normal calcium (Ca 2+ N ctrl vs. Ca 2+ N FSK) conditions after FSK incubation (Suppl. Table ) but there were no differences in experiments with calcium as variable factor (Suppl. Tables , , ). In contrast to the previously mentioned proteins, however, numerous proteins were also formed in a calcium-dependent manner, for example determined by comparing the STB-like cell lysate either cultured with 0.94mM or 0.35mM calcium: 459 proteins were more abundant in FSK stimulated cells that were cultured under normal calcium (Fig. D, Suppl. Table ) and 182 proteins were more abundant under low calcium. After syncytialization under normal calcium, proteins that are part of cellular respiration were mainly increased in expression (Fig. B, left ), while pathway analysis (with ShinyGo) of upregulated proteins after syncytialization under low calcium generally revealed proteins that are part of biological processes such as fiber and organ development, intermediate filament associated processes and homeostatic processes (Fig. B, right ). Regarding the general functions (identified with GOrilla) of proteins that were significantly higher expressed after syncytialization under normal calcium Ca 2+ N FSK, it is noticeable that 40 proteins with transcriptional regulatory activity (mainly zinc finger proteins, (Fig. A, Suppl. Table ) and 21 proteins that are important for the structural constituent of ribosomes were identified. This observation is consistent with the functions of syncytiotrophoblasts, which are the main source of steroid and glycopeptide hormones in the placenta and are therefore considered to be a trigger of numerous pregnancy-preserving processes, most of which are driven by transcriptional induction . In contrast, under reduced calcium (Ca 2+ L FSK), proteins with zinc ion transmembrane transporter activity (SLC39A7, SLC39A9, SLC39A10), with sodium transmembrane transporter activity (SLC20A2, SLC38A2, SLC4A7, SLC23A2, SLC38A1) and with Ca 2+ sensor activity (STIM2) were mainly upregulated, possibly for compensatory reasons. Considering and comparing all cell culture conditions (Suppl. Tables – ) 22 of the 40 proteins (selected via UniProt for their known syncytiotrophoblast function/placental expression ( from Fig. D, blue spots in Figs. E and E) were significantly deregulated in a calcium dependent manner. Table 5 ( supplement ) shows an overview of these 40 proteins (also seen in Figs. and ) and their expression levels in relation to the culture conditions. 13 proteins were significantly more expressed under regular calcium conditions in FSK stimulated BeWo cells (Suppl. Table ). Of these proteins, some were detected as exclusively upregulated after FSK stimulation in the presence of regular calcium (NDUFAB1, S100P, SEC61G, NMES1, ATP5MG, DAD1, COX7) and some were also upregulated under reduced calcium. Interestingly their expression upregulation was higher (HSD11B2, SDC1, UBE2D2, ERVFDR-1) under regular calcium.
Enzymes of steroid hormone synthesis were identified in the BeWo cell proteome (thickly marked in Fig. A) and, in addition, proteins that are upregulated in the presence of FSK were represented by bar charts (Fig. B-D). Aromatase, is the key enzyme for the synthesis of estradiol in trophoblasts. It is a cytochrome P450 monooxygenase that catalyzes the conversion of C19 androgens, androst-4-ene-3,17-dione (androstenedione) and testosterone to the C18 estrogens, estrone and estradiol, (Fig. A) and was detected during mass spectrometry and western blot (Fig. B). Since the secretion of estradiol in the BeWo cells is increased during syncytialization but does not appear to be calcium-dependent (Fig. C), we also monitored the aromatase expression by western blot in BeWo cell lysates ( ≙ four culture conditions). Densiometric analysis of the stain intensity of the aromatase revealed that BeWo cells treated with FSK produced significantly more aromatase under both reduced and normal calcium conditions (Fig. B, top ) and there is no significant relation to the calcium reduction, which was confirmed by mass spectrometric quantitative analysis (Fig. B, bar charts below , Suppl. Tables , , ). Therefore, synthesis of aromatase shows no calcium dependency which is in line with the measured estradiol concentrations (Fig. C). However, aromatase expression itself also appears to be a syncytial marker. 17-beta-hydroxysteroid dehydrogenase type 1 (HSD17B1) also catalyzes the synthesis of estradiol from estrone (Fig. A). The expression of HSD17B1 was only significantly increased after FSK stimulation under normal calcium conditions (Fig. D, top , Suppl. Table , Suppl. Figure ) (fusion marker) and shows the same tendency in the presence of reduced calcium. However, the HSD17B1-expression level of unstimulated (ctrl) and stimulated (FSK) cells was similar in the presence of low and high calcium. All these observations trend to favour calcium-independent estradiol synthesis in human STB. Progesterone (P4) secretion revealed to be calcium independent (Fig. B). Cholesterol serves as the precursor for steroid hormone synthesis and is transported through the plasma membrane via lipoproteins (Fig. A). The catalysis of cholesterol to progesterone takes place in the inner mitochondrial membrane. Several relevant actors are involved in this process: adrenodoxin reductase (AdxR), which transfers electrons from reduced NADP to the electron transfer protein adrenodoxin (FDX1), which provides the electrons for the catalysis reaction of cholesterol to pregnenolone by cholesterol-side chain cleavage enzyme P450 (CYP11A1). The resulting pregnenolone (P5) is converted to progesterone (P4) by 3 beta-hydroxysteroid dehydrogenase/Delta 5–>4-isomerase type 1 (HSD3B1) and cofactor NAD+ . Except for adrenodoxin reductase, all proteins involved in the synthesis of progesterone were identified by proteome analysis. Here HSD3B1 expression showed no significant differences after either FSK stimulation or calcium reduction (Suppl. Tables – ), while CYP11A1 expression was found to be increased after FSK treatment, but showed no calcium dependence (Fig. D bottom , Suppl. Tables , , , Suppl. Figure ). FDX1 is also a protein whose expression is induced by adenylyl cyclase activation during syncytialization. Regarding the FDX1 expression of FSK treated cells cultured under different calcium conditions the levels were comparable (Suppl. Table ), but expression in unstimulated cells (ctrl) was significantly reduced when cells were cultured with low calcium (Fig. C, top , Suppl. Table , Suppl. Figure ). Therefore, the expression of FDX1 may be impaired with reduced calcium in cytotrophoblasts. The expression of aldo-keto reductase family 1 member C3 (AKR1C3) also did not differ significantly after either FSK stimulation or calcium reduction (Suppl. Tables – , Suppl. Figure ). Contrary to that, the expression of 11-beta-hydroxysteroid dehydrogenase type 2 (HSD11B2), an enzyme involved in cortisol metabolism, showed calcium dependency in differentiated cells cultured in the presence of FSK (Fig. C bottom , 5E, Suppl. Table , Suppl. Figure ), as determined by MS-analysis as well as visualized by Western blot.
Pregnancy associated pathologies like PE, IUGR or miscarriages may result from insufficient syncytialization of cytotrophoblast cells, defective synthesis of glucopeptide- or steroid hormones or inadequate feto-maternal exchange of nutrients like calcium . The β-hCG level in the maternal blood increases exponentially by more than a hundredfold from the seventh day of conception (5-50mIU/mL) to the third week of pregnancy (18-7340mIU/mL) . The syncytialization process of cytotrophoblasts is also accompanied by the production of β-hCG. Syncytiotrophoblasts are the main source of the pregnancy hormone and induce trophoblast invasion , syncytialization and synthesis of steroid hormones . Compared to previous BeWo proteome studies , we were able to identify more than 7000 proteins and compare their expression profiles for the first time. The differences between the studies are due to different experimental parameters as well as different mass spectrometers. Interestingly, two studies found many proteins that we also identified and concluded that there is a high similarity between the proteomes of BeWo cells and those of placental tissue and villous trophoblasts . Our proteome analysis of cytotrophoblast- and STB-like cells showed, that the expression of many proteins, which are involved in syncytialization, depend on the presence of FSK in BeWo cells and some also on the extracellular calcium concentration, even if oxygen level and calcium concentrations were not fully equivalent to physiological conditions present in the placenta. Hereafter, we recapped the cellular processes taking place in STB and tried to categorize them regarding the relevance of calcium in cytotrophoblast- and STB-like BeWo cells. β-hCG synthesis depends on cAMP mediated activation of kinases such as p38 and PKA and associated transcription factors. In addition, calcium activates PKC, which can also induce hCG synthesis . The signaling of these protein kinases is regulated by anchor proteins (AKAPs) . By comparing the different proteome datasets, we identified AKAP12 as a new syncytiotrophoblast fusion marker induced by adenylyl cyclase activation via FSK that was upregulated in a calcium-independent manner after syncytialization (Suppl. Tables , , , Suppl. Table 5, Suppl. Figure ). The activated transcription factor ATF-1 was reported to be a relevant factor for embryo-maternal crosstalk . We found that the expression of ATF1 in FSK treated cells depends on the extracellular calcium concentration (Suppl. Table , Suppl. Table 5, Suppl. Figure ). The two subunits of hCG, the shared α-subunit (CGA) of the glycoproteins LH, FSH, TSH and hCG and the placenta-specific beta-subunit, were both also significantly higher expressed in the presence of FSK and showed calcium dependence (Figs. and , Suppl. Table , Suppl. Table , Suppl. Table 5, Suppl. Figure ). The influence of calcium on hormone synthesis was also investigated in Leydig cells, where calcium induces testosterone synthesis via the protein kinase C signaling pathway and in BeWo cells, where calcium promotes the secretion of β-hCG into the medium . The fact that our study now revealed that several proteins involved in hCG synthesis are expressed in a calcium-dependent manner, as well as calcium-dependent hCG secretion (Fig. ), at both cytotrophoblast- and STB-like cell level, confirms that calcium is not only important for fetal mineral supply, but also for the synthesis of the hCG hormone at the feto-maternal barrier. β-hCG is in turn secreted autocrinally by the STB and acts via the G s protein-coupled lutropin-choriogonadotropic hormone receptor, which can induce numerous signaling cascades via AC-cAMP-PKA activation or by direct activation via the beta/gamma subunit (Pl3K-AKT-mTor signaling pathway ,. This induces the transcription of various hCG-mediated proteins that are important for trophoblast function summarized in Fig. , including enzymes necessary for steroid hormone synthesis. Steroid hormone synthesis induced by FSK treatment has already been investigated in various cell lines and tissues, whereby the forskolin induced increase of progesterone and estradiol was already observed and was confirmed in our study (Fig. B, C) but no calcium dependence was observed in contrast to previous EGTA studies in placental cells . Most of the studies focused on the influence of forskolin on steroid hormone synthesis in H29R cells, an endocrine cell line derived from human adrenocortical carcinoma. Here, FSK increased the expression of aromatase (CYP19A1), CYP17, CYP11A1 and CYP11B1 determined by RT-PCR and corresponding products of steroid hormone syntheses such as estradiol and cortisol were also measured in a higher extent . In addition, the incubation of MA-10 Leydig cells with FSK led to an increase of intracellular calcium, which was associated with higher levels of the steroid hormone progesterone . Moreover, a calcium dependence at early steps of steroidogenesis has also been demonstrated by numerous independent observations in bovine glomerulosa cells . However, regarding the influence of calcium on steroid hormone synthesis in BeWo cells, the proteome study and western blots (Figs. F and B-E, Suppl. Tables – , Suppl. Figure ) demonstrate that the expression of aromatase (CYP19A1), CYP11A1 and HSD17B1 is not calcium dependent, whereas the expression of FDX and HSD11B2 is. HSD11B2 is an enzyme of cortisol metabolism that converts bioactive cortisol into inactive cortisone and represents the feto-maternal glucocorticoid barrier and was determined for the first time in our study to be expressed in a calcium-dependent manner in STB-like cells. It has already been mentioned to be upregulated by hCG during syncytialization to protect the fetus from excessive amounts of maternal glucocorticoids, as these are associated with pregnancy pathologies such as IUGR or the development of chronic diseases later in life . The increase of cortisol may cause delayed fetal growth as consequence of bone resorption and mineral loss as it is the case in Cushing-syndrom patients . In addition, we identified several proteins which were mentioned to be important in syncytiotrophoblast function (Fig. , gene names in bold). For example, syncytin-1 and the syncytin/PGF-activator GCM1 are upregulated after FSK treatment which is in line with former reports (Suppl. Table , Suppl. Figure ). Also, INHA and the cation channel TRPV2, which has been reported to be involved in the regulation of the placentation process in mice are upregulated in FSK treated cells (Suppl. Table , Suppl. Figure ). However, other TRP channel proteins, like TRPV6, showed low expression and were only detectable after enrichment by immunoprecipitation from the BeWo lysates . The angiogenesis activator PGF and cell adhesion and syncytial marker protein CDH5 were upregulated under both normal and reduced calcium after syncytialization and represent calcium-independent markers of cell differentiation (Suppl. Tables , , Suppl. Figure ). In contrast, the receptor of the syncytin-1 protein SLC1A5 (Suppl. Tables , , Suppl. Figure ) and the fusion protein syncytin-2 (ERVFRD-1) were found to be calcium-dependent. One of the functions of the p38 protein kinase is the induction of syncytin-2 synthesis , which triggers cell-cell fusion via its receptor MFSD2A . The induction of syncytin-2 expression during syncytialization was also shown by our analysis. (Fig. D, F) and, additionally a calcium dependence of the achievable expression level after FSK induced syncytialization was determined (Fig. E, F, Suppl. Table ). The higher expression after adenylyl cyclase activation (FSK) and calcium dependence was also observed for the ubiquitin conjugated enzyme E2 D2 (UBE2D2) (Suppl. Tables , , , Suppl. Figure ) which, in addition to its ubiquitous functions as a ligase in various cells, was mentioned in the context of GCM1 stability. It is involved in degradation and ubiquitination of GCM1, and its knockdown led to a prolonged GCM1 half-life in vivo . Increased expression after syncytialization with calcium dependence of the expression level was also observed for syndecan-1 (SDC1) (Fig. E, F, Suppl. Tables , , , Suppl. Figure ). Dysregulations in the expression of proteoglycans such as SDC1 have been associated with fetal growth restriction and PE based on transcriptome data and also serve as a prognostic marker for unfavorable pregnancy outcomes. The protein S100P, is one of the proteins that is exclusively expressed after FSK in the presence of normal calcium (Fig. E, F, Suppl. Table , Suppl. Figure ), and is one of the factors that play an essential role in the regulation of trophoblast syncytialization . In JAR cells, another choriocarcinoma cell line, the upregulation of S100P correlated with the cell proliferation. Moreover, loss of S100P impaired ß-hCG secretion in the human cytotrophoblast stem cell model , and the expression of S100P was significantly reduced in placentas of patients with spontaneous abortions . Next the potential compensatory upregulation of cyclic AMP-dependent transcription factor (ATF-3) expression during cell differentiation under reduced calcium (Suppl. Table ) also implies that calcium participates in ATF-3 synthesis (Suppl. Figure ). ATF-3 expression promotes trophoblast proliferation and has been reported to reduce inflammation in human fetal membranes . ATF-3 deficiency is associated with recurrent implantation failure and is part of PE pathology . Moreover, the Transforming growth factor beta receptor type 3 (TGFBR3), which has been described as an Inhibin-coreceptor, is involved in the regulation of the FSH level in gonadotropic cells and affecting female fertility , showed a high calcium dependency (Fig. E, F; Suppl. Tables – , Suppl. Figure ). Calcium had an expression-suppressing effect with and without FSK treatment. Finally, the adiponectin receptor protein 1 (ADIPOR1) was also classified as a calcium-dependent syncytial marker that is expressed significantly more under reduced calcium in both, undifferentiated and FSK stimulated BeWo cells (Fig. D, F; Suppl. Figures and ; Fig. E, F, Suppl. Tables , ). This receptor, together with its ligand adiponectin, has also already been associated with the formation of the placental syncytium . In earlier studies, the influence of calcium during syncytialization was investigated using GFP and dsRed-BeWo cell lines, for example, whereby syncytialization was quantified using fluorescence-activated cell sorting . Here, an increase in intracellular calcium levels or nifedipine treatment reduced the extent of cell fusion. In our study, we decided to quantify snycytialization using ZO-1 staining, hormone assays and additionally by identifying numerous fusion markers using high-resolution mass spectrometry, and to reduce calcium concentration extracellularly. Considering the results of ZO-1 visualization and the calcium-dependent increase of the fusion index (Fig. ) as well as the identification of various calcium-dependently expressed fusion markers we come to the conclusion that in addition to β-hCG synthesis and secretion, the syncytialization of trophoblasts seems to be also calcium- dependent.
Taken together, in addition to confirming known syncytialization markers at the proteome level, numerous new proteins were identified for the first time in this study. Their expression is induced as part of the syncytial process. These include proteins involved in β-hCG and steroid hormone synthesis, suggesting that syncytialization and enzymes involved in steroid hormone synthesis are tightly linked. The expression of some of these proteins show a calcium dependency. In STB-like cells, cation channels are expressed in a compensatory manner if calcium is reduced, whereas under regular calcium conditions, transcription factors and components of the translation process are upregulated to a greater extent. Calcium therefore acts as a regulator of hormone expression and secretion. It is already known that an adequate calcium supply is important for the development of the growing fetus on many levels. However, this study provides deeper insights into trophoblast functions and shows that β-hCG expression, secretion and the syncytialization in general are calcium-dependent in trophoblast-like cells.
Below is the link to the electronic supplementary material. Supplementary Material 1: Supplement Table 1 : Proteome Discoverer 3.0 result export of BeWo cell lysates +/- FSK (4 replicates) cultured with normal calcium (0.94 mM). Overview of all identified proteins and of dysregulated proteins with corresponding experimental q-value, program specific peptide score, protein coverage, peptide count, peptide spectrum matches, unique peptides, amino acid count, molecular weight, sequence score, abundance ratios, (adjusted) abundance ratio p-values, abundance ratios variability, grouped abundances, sample specific abundances, normalized abundances, normalized abundances, samples in which the protein was found, protein groups. Supplementary Material 2: Supplement Table 2 : Proteome Discoverer 3.0 result export of BeWo cell lysates +/- FSK (4 replicates) cultured with low calcium (0.35 mM). Supplementary Material 3: Supplement Table 3 : Proteome Discoverer 3.0 result export of BeWo cell lysates (4 replicates) cultured with DMSO and either with low (0.35 mM) or high (0.94 mM) calcium. Supplementary Material 4: Supplement Table 4 : Proteome Discoverer 3.0 result export of BeWo cell lysates (4 replicates) cultured with FSK and either with low (0.35 mM) or high (0.94 mM) calcium. Supplementary Material 5: Supplement Table 5 : Overview of dysregulated proteins in four analyzes. To create the table, each selected protein was marked in all four analyzes of Proteome Discoverer 3.0, in which two conditions were compared with each other, and the corresponding protein p -value of the abundance ratio, which was calculated using the unpaired t test from Proteome Discoverer 3.0, was selected. If there was a significant difference in one of the four analyzes ( p -value of the protein in one analysis < 0.05), this is shown in the table with an arrow. In analysis 1, protein expression in cytotrophoblast-like cells (T) was compared to expression in STB-like cells (STB) cultured under normal calcium, to determine syncytialization markers in general. In analysis 2, protein expression in T cultured under normal calcium conditions was compared to expression in T cultured under low calcium conditions to determine calcium-dependently expressed proteins in cytotrophoblast-like cells. In analysis 3, protein expression in STB cultured under normal calcium was compared to expression in STB cultured under low calcium to determine calcium-dependently expressed proteins in syncytiotrophoblast-like cells. In analysis 4, protein expression in cytotrophoblast-like cells (T) was compared with expression in STB-like cells (STB) cultured under low calcium, representing the syncytialization process occurring under low calcium, to determine whether the syncytialization markers identified in analysis 1 were also upregulated after incubation with low calcium. In the table, the red arrow pointing upwards indicates upregulation of the protein in the comparison condition (second condition) and the blue arrow pointing downwards indicates downregulation in the comparison condition. The red-colored proteins showed calcium dependence at STB level, the orange-colored proteins at cytotrophoblast level and the black-colored proteins showed no differences in analysis 2 and 3, indicating a rather calcium-independent expression. Supplementary Material 6: Supplement Fig. 1 : Confirmation of FSK induced syncytialization of BeWo cells. (A) Immunofluorescence staining of tight junctions zona occludens protein 1 (ZO-1) (green) to visualize BeWo cell outlines and DAPI (blue) to stain the nuclei. Cells were treated with 30 µM FSK for 48h to induce fusion into syncytiotrophoblast-like phenotypes (STB). Cell treatment with DMSO was used as a negative control (ctrl) (≙ cytotrophoblast cells) (B) Determination of trophoblastic fusion index as ((NNS-S)/T) x 100% (NNS = number of nuclei in syncytia, S = number of syncytia, T = total number of nuclei) to analyze the level of multinucleated cells before and after FSK treatment. Analysis with unpaired t-test, N = 6 (C) Measurement of β-hCG hormone level from cell culture supernatant after 48h incubation with either DMSO or FSK as a marker for syncytialization. The determined hormone concentration was initially related to 1µg protein and afterwards normalized to reference concentration (ctrl) (factor = 1) within the experiment. Analysis with unpaired t-test, N = 6. Supplementary Material 7: Supplement Fig. 2 : Influence of the calcium concentration in the cell culture medium (extracellular calcium) on the morphology and confluence of BeWo cells, stained with Haema-Quick Stain Set, after 48h incubation time. Scale bar corresponds to 100µM. Supplementary Material 8: Supplement Fig. 3 : Influence of calcium on steroid hormone secretion of BeWo cells in cell culture supernatant. Cells were stimulated with 30µM FSK. DMSO was used as negative control. The determined hormone concentration was initially related to 1µg protein and afterwards normalized to reference concentration (factor = 1) within the experiment. Ca 2+ L (low) = 0.35 mM, Ca 2+ N (normal) = 0.94mM ( A-C) β-hCG secretion in different treated cells. Analyzed with unpaired t-test, N = 6 ( D-F ) Progesterone secretion in different treated cells. Analyzed with unpaired t-test, N = 6 ( G-I ) Estradiol secretion in different treated cells. Analyzed with unpaired t-test, N = 6. Comparison of hormone secretion of BeWo cells treated with low calcium levels and either FSK or DMSO (A, E, H), of BeWo cells treated with FSK and either 0.94mM or 0.35mM calcium (B), of of BeWo cells treated with DMSO and either 0.94mM or 0.35mM calcium (C, F, I) or of BeWo cells treated with 0.94mM calcium and either FSK or DMSO (D, G). Supplementary Material 9: Supplement Fig. 4 : Proteome analysis before syncytialization under normal and under low calcium conditions. (A) Identification and quantification profile of proteome analysis. (B) Volcano plot of quantified proteins in proteome analysis of cytotrophoblast-like cells, N = 4, unpaired t-test. (C) Heatmap of quantified proteins. Lower right side: Heat map of all quantified proteins in proteome analysis of RIPA lysates from unstimulated cytotrophoblast under normal and under low calcium conditions ( p < 0.05 and p > 0.05). Upper right side: Heat map of all dysregulated proteins. Lower left side: Heat map of selected proteins due to placental expression and due to classification as part of syncytialization from proteome analysis of stimulated and unstimulated trophoblast-like cells under normal calcium conditions (Fig. 3). Supplementary Material 10: Supplement Fig. 5 : Proteome analysis of undifferentiated and syncytializated trophoblasts under low calcium conditions. (A) Identification and quantification profile of proteome analysis. (B) Volcano plot of quantified proteins in proteome analysis of unstimulated and stimulated trophoblasts, N = 4, unpaired t-test. (C) Heatmap of quantified proteins under low calcium conditions. Lower right side: Heat map of all quantified proteins in proteome analysis ( p < 0.05 and p > 0.05). Upper right side: Heat map of all dysregulated proteins. Lower left side: Heat map of selected proteins due to placental expression and due to classification as part of syncytialization from proteome analysis of stimulated and unstimulated trophoblasts under normal calcium conditions (Fig. 3). Supplementary Material 11: Supplement Fig. 6 : Comparison of the expression of ADIPOR1, AKAP12, AKR1C3, ALPG, ALPP, APOA4, ATF1, ATF3, ATP5MG, CHD5, CGA, CGB, COBLL1, COX7C, CYP11A1, CYP19A1, DAD1, DYSF, ERVFRD-1, ERVW-1, ESRRA, FADS2, FDX1, GCM1, HSD3B1, HSD11B2, HSD17B1, INHA, MAST4, NDUFAB1, NMES1,PGF, PHLDA3, PHLDB2, RYBP, S100P, SDC1, SEC61G, SELENOI, SLC1A5, TGFBR3, TJP1, TRPV2 and UBE2D2 in lysates of different cultured cells, visualized by bar charts (unpaired t-test).
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Implementing an initiative promote evidence-informed practice: part 2—healthcare professionals’ perspectives of the evidence rounds programme | c66b5f9a-03ca-450a-80bb-d6c8e21e7654 | 6402168 | Pediatrics[mh] | Evidence-informed decision making is fundamental to the provision of healthcare and central to this is the translation of research evidence into clinical practice. The use of the term “evidence-informed” highlights the need to acknowledge and address contextual influences and consider how the best available evidence can be used in specific circumstances . There is a need to improve translation of research evidence into practice . The ever-growing volume of research publications , the complex nature of research , gaps in skills such as knowledge of how to interpret statistical information, publication bias and nonlinear, non-rational processes in decision making are just some of the potential barriers to translating evidence into practice. Research is growing in fields that attempt to tackle and narrow the gap between knowledge and action such as knowledge translation (KT), dissemination and implementation science, knowledge mobilisation and knowledge brokering. KT strategies can employ single or multiple components such as professional educational meetings eg. journal clubs, educational materials, educational outreach visits, knowledge brokers, audit and feedback etc. A limitation of the traditional educational model of journal club is that its primary focus is on the critical appraisal of a single source . A Cochrane systematic review of 81 trials involving nearly 11,000 healthcare professionals found that standalone continuing education meetings and those with additional components can lead to small improvements in patient care and clinical practice with the exception of very complex behaviours . In a systematic review by Giguère and colleagues, printed educational materials appeared to positively effect professional practice outcomes. However, it was not possible to measure the size of the effect in relation to patient outcomes . In another systematic review, there was a lack of evidence to assess the effectiveness of knowledge brokers . A Cochrane review reported that small but important changes to clinical practice can result from audit and feedback . A Cochrane systematic review by Forsetlund and colleagues found moderate quality evidence that for HCPs working in primary and secondary healthcare settings, higher attendance at educational meetings was effective at increasing compliance with a target practice. Interestingly, they found decreased effectiveness for outcomes with a lower level of severity and no evidence of effectiveness for complex behaviours. They recommended the use of strategies to increase attendance although they did not specify the necessary components of these strategies . While outcome evaluations tell us whether an implementation programme does or does not work, they can ignore confounding contextual factors and fail to tell us more about why, how or under what circumstances a programme does or does not work . In a given population, there needs to be an understanding of barriers and facilitators to evidence based practice . To address these issues, it is necessary to examine the process and context. Translation of knowledge is a context-dependent process, contingent on many factors and takes place in complex healthcare systems . While a number of definitions for the term dissemination have been suggested, in this paper we define it as “an active approach of spreading evidence-based interventions to the target audience via determined channels using planned strategies” . McCormack 2013 identified the broad goals of dissemination to clinicians as increasing the reach of the evidence b) increasing the motivation to utilise and apply evidence and c) increasing the ability to utilise and apply evidence . We utilised a multi-faceted KT strategy to actively disseminate evidence to healthcare professionals and promote evidence informed practice including implementation of evidence where appropriate . Our initiative called Evidence Rounds, took place over nine months from July 2016 to March 2017 and featured three core components: 1) six educational group sessions examining the evidence on clinical topics or questions chosen by our target audience, 2) support from a KT professional and 3) the use of multiple modes of delivery to communicate and disseminate information including a dedicated website. For each session, three HCPs presented the evidence on a single topic that was agreed upon by the larger group. It was not mandatory for staff to give presentations rather, they were invited to volunteer to present. In some cases individuals were recommended by their peers and invited by the implementation team to present. After the presentations a discussion forum would take place where the applicability of the evidence was explored and if appropriate, potential resulting actions were identified and discussed by attendees. For example, staff identified a gap in their knowledge relating to evidence around antenatal steroid use for preterm deliveries less than 37 weeks gestational age. So, this topic was chosen to be the focus of an Evidence Rounds educational session. As a result of the Evidence Rounds session, awareness of the evidence increased and it was deemed appropriate to implement the evidence. Further discussed at a multidisciplinary team meeting and other meetings contributed to the process of implementation. The local guideline on preterm premature rupture of the membranes (PPROM) was updated to recommend that antenatal steroids be considered by the consultant dealing with the patient when there is a risk of preterm birth at a gestational age of 23 weeks + 0 days to 23 weeks + 6 days (previously 24 weeks + 0 days). Therefore, this Evidence Rounds educational session led to a guideline update and a change in practice. Some of the core elements of Evidence Rounds were based on Evidence in Practice Groups established by Jacqui LeMay and run by the Clinical Evidence Based Information Service (CEBIS) at University Hospitals Coventry and Warwickshire NHS Trust. We used collaborative processes to design and develop the initiative and actively sought feedback from key stakeholders (HCPs) throughout these phases. By doing this, we could adjust components to better suit the local context and meet the needs and preferences of our target audience. A more comprehensive description of Evidence Rounds and its process of implementation is available in paper 1 of this two-part series . The objectives of this study were to use focus groups and interviews a) to identify HCP-reported barriers and facilitators to attending and presenting at educational group sessions b) to explore HCPs’ views of Evidence Rounds, particularly as a dissemination strategy, and c) to generate insights to improve the sustainability of future initiatives because evidence about the sustainability of KT interventions is still lacking .
Study design, setting and participants We utilised a qualitative study design which can provide valuable insights into contextual factors and intervention features which influence the success of KT interventions . We used total population, purposive sampling and invited all healthcare professionals working in the maternity unit of one urban hospital in Ireland who attended or presented at at least one Evidence Rounds educational session to participate. We excluded students on placement and other attendees who were not employed as health care staff at the hospital because the primary target audience of the initiative was HCPs who attended and presented at group sessions and we were specifically interested in learning more about their perceptions. We did not prespecify a target sample size before recruitment because we expected it to depend on attendance levels, availability and willingness to participate in the study as well as other potential factors. We decided that it was not appropriate to use other studies to provide the required estimates in our population. Nevertheless, focus groups were expected to consist of 4 to 8 participants each. No more than 10 individuals would be interviewed on a 1:1 format. If more than 10 individuals were to volunteer, selection would be prioritised using the following criteria: a) first priority would be given to any attendee type who is under-represented in the focus groups and b) second priority will be given to attendees who volunteered on a first come, first served basis. Procedure Focus groups and interviews We gave potential participants the choice to take part in either a focus group or an interview according to their individual preferences. We displayed posters in areas frequently accessed by our target population. To enhance recruitment, we entered each participant into a draw to win a voucher for a local restaurant. We developed an interview guide around the aims of the study (Additional file ). We asked participants about the determinants impacting their choice to attend or present at our group sessions and how our initiative performed in relation to the goals identified by McCormack (2013). We questioned them about the sustainability of Evidence Rounds and the factors that might increase the likelihood of sustainability for other initiatives. We asked participants questions about specific components and modes of delivery to find out what worked and did not work for them. Our study was granted ethical approval by the Galway University Hospitals Clinical Research Ethics Committee (CREC). During recruitment, we distributed informed consent packs incorporating a participant information leaflet and consent form (Additional file ), which all participants read and signed before taking part. We changed potential identifiers to protect the anonymity of our participants. Data collection and analysis We audio-recorded interviews and one author moderated all focus groups and interviews for consistency. Audio files were transcribed verbatim by a professional from a transcription service who had signed a confidentiality agreement. We chose to analyse the data using Richie and Spencer’s framework analysis which can be used in applied qualitative research . Our decision was based on its suitability for dealing with focus group and interview data and its focus on prospective actionable outcomes. We utilised an iterative rather than a linear process to complete the five components of this method of analysis: Familiarization AC who had been present at all recordings re-listened and where appropriate, made corrections and where possible, filled in sections of speech that were inaudible to the transcriber. Two authors (AC and MD) listened to the audio files while reading the corrected transcripts. AC reviewed the observational notes collected by the assistant moderator during the focus groups. Two authors (AC and MD) independently coded the transcripts and noted key points, repeated themes and issues considered important by participants. 2.) Identifying a thematic framework We began to create a thematic framework drawing from a list of 54 a priori key issues deemed relevant to our study aims, 21 additional emergent issues based from participant responses, and began to connect and look for patterns in participant responses to form analytical themes. The thematic framework took several iterations. 3.) Indexing We uploaded the transcripts to NVivo Version 11 and systematically applied the thematic framework by assigning nodes and sub-nodes to text within each transcript. As is common in framework analysis papers, some text was coded into multiple nodes , others were merged and throughout this stage, we made further refinements to the framework. 4.) Charting We reviewed the data and made a decision to chart by core themes rather than cases. We created five tables each with a unique domain and used themes, sub-themes and illustrative quotes that demonstrated the range of participant responses. All authors reviewed the tables and made revisions to improve the presentation of data. 5.) Mapping and interpretation We referred to the main aims of the study and reviewed the tables. We considered the nature and range of participant perspectives. Using this method, it was possible to extract key dimensions of the barriers and facilitators to attending and presenting at Evidence Rounds, their perspectives of our dissemination strategy, and suggestions to make future initiatives more sustainable.
We utilised a qualitative study design which can provide valuable insights into contextual factors and intervention features which influence the success of KT interventions . We used total population, purposive sampling and invited all healthcare professionals working in the maternity unit of one urban hospital in Ireland who attended or presented at at least one Evidence Rounds educational session to participate. We excluded students on placement and other attendees who were not employed as health care staff at the hospital because the primary target audience of the initiative was HCPs who attended and presented at group sessions and we were specifically interested in learning more about their perceptions. We did not prespecify a target sample size before recruitment because we expected it to depend on attendance levels, availability and willingness to participate in the study as well as other potential factors. We decided that it was not appropriate to use other studies to provide the required estimates in our population. Nevertheless, focus groups were expected to consist of 4 to 8 participants each. No more than 10 individuals would be interviewed on a 1:1 format. If more than 10 individuals were to volunteer, selection would be prioritised using the following criteria: a) first priority would be given to any attendee type who is under-represented in the focus groups and b) second priority will be given to attendees who volunteered on a first come, first served basis.
Focus groups and interviews We gave potential participants the choice to take part in either a focus group or an interview according to their individual preferences. We displayed posters in areas frequently accessed by our target population. To enhance recruitment, we entered each participant into a draw to win a voucher for a local restaurant. We developed an interview guide around the aims of the study (Additional file ). We asked participants about the determinants impacting their choice to attend or present at our group sessions and how our initiative performed in relation to the goals identified by McCormack (2013). We questioned them about the sustainability of Evidence Rounds and the factors that might increase the likelihood of sustainability for other initiatives. We asked participants questions about specific components and modes of delivery to find out what worked and did not work for them. Our study was granted ethical approval by the Galway University Hospitals Clinical Research Ethics Committee (CREC). During recruitment, we distributed informed consent packs incorporating a participant information leaflet and consent form (Additional file ), which all participants read and signed before taking part. We changed potential identifiers to protect the anonymity of our participants.
We gave potential participants the choice to take part in either a focus group or an interview according to their individual preferences. We displayed posters in areas frequently accessed by our target population. To enhance recruitment, we entered each participant into a draw to win a voucher for a local restaurant. We developed an interview guide around the aims of the study (Additional file ). We asked participants about the determinants impacting their choice to attend or present at our group sessions and how our initiative performed in relation to the goals identified by McCormack (2013). We questioned them about the sustainability of Evidence Rounds and the factors that might increase the likelihood of sustainability for other initiatives. We asked participants questions about specific components and modes of delivery to find out what worked and did not work for them. Our study was granted ethical approval by the Galway University Hospitals Clinical Research Ethics Committee (CREC). During recruitment, we distributed informed consent packs incorporating a participant information leaflet and consent form (Additional file ), which all participants read and signed before taking part. We changed potential identifiers to protect the anonymity of our participants.
We audio-recorded interviews and one author moderated all focus groups and interviews for consistency. Audio files were transcribed verbatim by a professional from a transcription service who had signed a confidentiality agreement. We chose to analyse the data using Richie and Spencer’s framework analysis which can be used in applied qualitative research . Our decision was based on its suitability for dealing with focus group and interview data and its focus on prospective actionable outcomes. We utilised an iterative rather than a linear process to complete the five components of this method of analysis: Familiarization AC who had been present at all recordings re-listened and where appropriate, made corrections and where possible, filled in sections of speech that were inaudible to the transcriber. Two authors (AC and MD) listened to the audio files while reading the corrected transcripts. AC reviewed the observational notes collected by the assistant moderator during the focus groups. Two authors (AC and MD) independently coded the transcripts and noted key points, repeated themes and issues considered important by participants. 2.) Identifying a thematic framework We began to create a thematic framework drawing from a list of 54 a priori key issues deemed relevant to our study aims, 21 additional emergent issues based from participant responses, and began to connect and look for patterns in participant responses to form analytical themes. The thematic framework took several iterations. 3.) Indexing We uploaded the transcripts to NVivo Version 11 and systematically applied the thematic framework by assigning nodes and sub-nodes to text within each transcript. As is common in framework analysis papers, some text was coded into multiple nodes , others were merged and throughout this stage, we made further refinements to the framework. 4.) Charting We reviewed the data and made a decision to chart by core themes rather than cases. We created five tables each with a unique domain and used themes, sub-themes and illustrative quotes that demonstrated the range of participant responses. All authors reviewed the tables and made revisions to improve the presentation of data. 5.) Mapping and interpretation We referred to the main aims of the study and reviewed the tables. We considered the nature and range of participant perspectives. Using this method, it was possible to extract key dimensions of the barriers and facilitators to attending and presenting at Evidence Rounds, their perspectives of our dissemination strategy, and suggestions to make future initiatives more sustainable.
Thirteen HCPs participated in three focus groups (of between two and four participants), and five in one-to-one interviews. Six medical doctors and seven nursing or midwifery staff participated, of which four were male and nine were female. Our data analysis revealed five core domains regarding HCPs perspectives of Evidence Rounds: (1) barriers and facilitators to attending; (2) barriers and facilitators to presenting; (3) organisational readiness for change; (4) communication and dissemination of information; and (5) sustainability. Barriers and facilitators to attendance This domain included three themes namely; departmental context and resources, social context and individual level factors. Our study demonstrated that attendance levels at Evidence Rounds were determined by the availability and workloads of staff, the organisational climate, the attendance of others (colleagues and senior-level staff), level of interest in the topic and extrinsic factors such as certificates of attendance and continuing education units from a professional body. HCPs who had control over the timing for their daily activities experienced less scheduling-related restrictions compared to those who were providing front-line care on hospital wards. Lunchtime was identified as the most likely time to suit the majority of people. The provision of food and beverages was a facilitator to attendance especially for HCPs who would not get another opportunity to eat during their work shift. Keeping sessions within the advertised timeframe was appreciated by busy HCPs. A number of staff came into work on their days off to attend Evidence Rounds. Some line managers agreed to allow time in lieu for these staff. However, this was not offered to all employees and in general, being off duty was a barrier to attendance. We also identified a previously unknown scheduling conflict with a lunchtime meeting for obstetric staff. This may contribute to the fact that there were fewer attendees from this department. Busy workloads and inadequate staffing levels were barriers to HCPs attending sessions. Understandably, clinical care took priority and staff reported that some colleagues had trouble attending even mandatory training sessions (attendance at Evidence Rounds was voluntary). All staff viewed the interprofessional and multiple disciplinary nature of Evidence Rounds as a facilitator to their attendance. Teamwork and the breaking down of professional silos were among the positive effects they saw from this approach. Consultant attendance and management support for Evidence Rounds was mentioned repeatedly as having a positive effect on non-consultant hospital doctor (NCHD), nursing and midwifery staff attendance. Senior staff acknowledged that their attendance set an example for junior staff. Some HCPs were motivated by a self-perceived benefit to attending e.g., obtaining professional credits for attendance, certificates of attendance or participation, claiming back time spent or enjoying a free lunch Table . Barriers and facilitators to presenting This domain included two themes of individual level factors, and departmental context and resources. The perceived benefit of taking part and having an interest in the topic or format facilitated presenting at Evidence Rounds. Presenting was considered as a more active way to engage with the literature. Some participants had a long-standing interest in their topic and viewed Evidence Rounds as a platform to promote discussion with colleagues. One participant took part because they wanted to experience giving a presentation in an alternative format to a journal club. Another participant shared that recruiting presenters was a continuing problem. Staffing issues also influenced decisions to present at Evidence Rounds. Even though evidence was presented by 3 HCPs per session, a lot of preparatory work was required from each individual. Another important finding was that some staff were motivated by a strong interest in the topic, a need to set an example for less experienced HCPs or the desire to experience presenting in this unique initiative. Our study found multi-dimensional factors that can be both barriers and enablers to different individuals, at different times and under different circumstances. For example, the level of self-confidence in presenting in front of others could either encourage or discourage potential presenters from taking part. Health care professionals who saw themselves or others as being deficient in knowledge, skills, or education or those without a research background, identified this as a barrier to presenting. For some participants, their taking part was done to motivate others and learn the process so that they could provide assistance to future presenters. Others presented because they were well-versed on the topic and felt confident to present. One participant mentioned their fear of being asked difficult questions by attendees but chose to present regardless. The structure of Evidence Rounds whereby three HCPs presented at each session was encouraging for some staff. Some topics can cause information overload if there is a lot of published evidence so sharing the literature and the workload with colleagues helped to minimise any negative impact on work-life balance. Nevertheless, some HCPs viewed their busy schedules and the extra work associated with presenting as barriers. The transience of junior medical staff was identified as a barrier because they were rotated to different hospital departments or hospitals every 6 months. They were perceived as being less willing to take part because they would be moved soon afterwards. Support from line managers i.e. protected time to prepare for their presentation, was identified as a determinant that would encourage staff to present Table . Organisational readiness for change This domain included two themes of acceptability and appropriateness, and pushing and changing slowly. All participants viewed Evidence Rounds as having a positive impact on their practice and education. It highlighted the need to improve their communication with colleagues in relation to approaches to care delivery. Evidence Rounds helped to ensure practice was based on research evidence as well as their own clinical experience and that of their colleagues. The initiative was acknowledged as having a wider scope, decreased risk of bias and more applicability to decision-making for clinical care than traditional journal clubs. Participants welcomed the opportunity for interprofessional collaboration across multiple professions and disciplines and saw this as a means to network and discuss key issues with colleagues they might work with infrequently. There was recognition that getting together for Evidence Rounds sessions helped to foster links between the midwifery, obstetric and neonatal departments. Most participants acknowledged that key research findings highlighted as actions from Evidence Rounds were slow to be implemented although some recommendations had been implemented in practice. Bridging the gap between research and practice is often contingent on additional steps. Evidence Rounds was seen as a platform to begin a conversation and start to plan the formal process of updating or creating new guidelines so that there could be a widespread change in practice. One participant noted that having the relevant guideline developer in attendance would increase the likelihood of getting the evidence into practice Table . Communication and dissemination of information This domain included two themes; modes of delivery and communication and dissemination strategy considerations. We asked participants questions to gain insight into their preferred modes of delivery when receiving communications and disseminated information. One important finding is that participant feedback did not identify a single mode of delivery of information that would have engaged all staff. Therefore, our decision to employ a multi-component strategy was appropriate for our target population despite a lack of evidence that this is the most effective approach . HCPs agreed that posters displayed in appropriate hospital areas were effective at drawing attention to upcoming sessions. The use of email to communicate information about Evidence Rounds elicited diverse responses from participants. For individuals who spent at least part of their working day with access to a computer or mobile phone and had a work email address, this was a convenient way to receive information. However, it was not an effective way to reach others such as staff midwives who were more clinically based and either were not issued with, or did not regularly access their professional email accounts. Not all participants used the Evidence Rounds website but those who did, found it accessible and an easy way to retrieve and refer others to past presentations. One participant found the critical appraisal tool links useful to prepare for their presentation. For one healthcare professional who limited their engagement with technology, the website was not a suitable medium. Participants had mixed opinions about the use of text messaging and other mobile messaging technologies such as WhatsApp. On one hand, they acknowledged that they were a means whereby information could be communicated to the intended receiver in an easy and direct manner. On the other hand, many staff voiced concerns that work-life boundaries might be violated or feared that they might be bombarded with messages particularly when they were not working. Many of the HCPs were involved in shift work, which compounded their concern regarding this issue. Word of mouth was a popular method among staff to encourage their colleagues to attend sessions. Multiple reminders and reminders on the day of the sessions were viewed as having a particularly positive impact on attendance Table . Sustainability Finally, we asked HCPs about their perceptions of the sustainability of Evidence Rounds and how they would make future initiatives more sustainable. Sustainability is difficult to measure so our qualitative approach allowed us to gain an understanding of context to help others select appropriate strategies during implementation to improve sustainability. This domain included two themes; staff engagement and collaboration and individual and departmental influences on sustainability. Perhaps the most striking finding is the influence of resources and particularly the HCPs themselves, on sustainability. Their availability, schedules and workloads, level of interest and motivation, the engagement of senior-level staff and their willingness to lead and become champions for initiatives were hugely important factors. These results corroborate suggestions that behaviour change theory may be useful to positively impact implementation processes. HCPs identified a number of factors key to the sustainability of Evidence Rounds and similar initiatives after the support of the KT professional would be terminated. Staff representatives from both the neonatal and obstetric units would need to take ownership and assume responsibility for administrative tasks such as planning and scheduling the meetings. Some participants viewed champions as essential for sustainability. Two participants believed that there needed to be a dedicated person whose job it was to oversee education and another thought their role should include developing clinical practice guidelines. All participants remarked positively on either or both of the interprofessional and multiple disciplinary aspects of the initiative. One individual believed that senior level staff from one discipline were more invested in keeping it going than those from the other discipline and worried about the impact of this. There was a sense that it was not always easy to come up with topics of simultaneous interest to midwifery, neonatal and obstetric departments. Evidence Rounds was just one of many educational opportunities open to staff during their working week. Taking into consideration the already busy workloads of the healthcare professionals, it was not easy to find staff to volunteer to take on the extra responsibility required to keep it going. Buy-in from senior level staff and having a consultant run the sessions were considered factors that might encourage staff to attend. Rotating presenters and dividing tasks between a team of three was a means of keeping the workload associated with presenting at a manageable level. Assigning a HCP to pre-schedule the sessions for the coming year was suggested by multiple participants. Participants mentioned the need to involve someone with experience in performing systematic literature searches and to provide additional support to upcoming presenters Table .
This domain included three themes namely; departmental context and resources, social context and individual level factors. Our study demonstrated that attendance levels at Evidence Rounds were determined by the availability and workloads of staff, the organisational climate, the attendance of others (colleagues and senior-level staff), level of interest in the topic and extrinsic factors such as certificates of attendance and continuing education units from a professional body. HCPs who had control over the timing for their daily activities experienced less scheduling-related restrictions compared to those who were providing front-line care on hospital wards. Lunchtime was identified as the most likely time to suit the majority of people. The provision of food and beverages was a facilitator to attendance especially for HCPs who would not get another opportunity to eat during their work shift. Keeping sessions within the advertised timeframe was appreciated by busy HCPs. A number of staff came into work on their days off to attend Evidence Rounds. Some line managers agreed to allow time in lieu for these staff. However, this was not offered to all employees and in general, being off duty was a barrier to attendance. We also identified a previously unknown scheduling conflict with a lunchtime meeting for obstetric staff. This may contribute to the fact that there were fewer attendees from this department. Busy workloads and inadequate staffing levels were barriers to HCPs attending sessions. Understandably, clinical care took priority and staff reported that some colleagues had trouble attending even mandatory training sessions (attendance at Evidence Rounds was voluntary). All staff viewed the interprofessional and multiple disciplinary nature of Evidence Rounds as a facilitator to their attendance. Teamwork and the breaking down of professional silos were among the positive effects they saw from this approach. Consultant attendance and management support for Evidence Rounds was mentioned repeatedly as having a positive effect on non-consultant hospital doctor (NCHD), nursing and midwifery staff attendance. Senior staff acknowledged that their attendance set an example for junior staff. Some HCPs were motivated by a self-perceived benefit to attending e.g., obtaining professional credits for attendance, certificates of attendance or participation, claiming back time spent or enjoying a free lunch Table .
This domain included two themes of individual level factors, and departmental context and resources. The perceived benefit of taking part and having an interest in the topic or format facilitated presenting at Evidence Rounds. Presenting was considered as a more active way to engage with the literature. Some participants had a long-standing interest in their topic and viewed Evidence Rounds as a platform to promote discussion with colleagues. One participant took part because they wanted to experience giving a presentation in an alternative format to a journal club. Another participant shared that recruiting presenters was a continuing problem. Staffing issues also influenced decisions to present at Evidence Rounds. Even though evidence was presented by 3 HCPs per session, a lot of preparatory work was required from each individual. Another important finding was that some staff were motivated by a strong interest in the topic, a need to set an example for less experienced HCPs or the desire to experience presenting in this unique initiative. Our study found multi-dimensional factors that can be both barriers and enablers to different individuals, at different times and under different circumstances. For example, the level of self-confidence in presenting in front of others could either encourage or discourage potential presenters from taking part. Health care professionals who saw themselves or others as being deficient in knowledge, skills, or education or those without a research background, identified this as a barrier to presenting. For some participants, their taking part was done to motivate others and learn the process so that they could provide assistance to future presenters. Others presented because they were well-versed on the topic and felt confident to present. One participant mentioned their fear of being asked difficult questions by attendees but chose to present regardless. The structure of Evidence Rounds whereby three HCPs presented at each session was encouraging for some staff. Some topics can cause information overload if there is a lot of published evidence so sharing the literature and the workload with colleagues helped to minimise any negative impact on work-life balance. Nevertheless, some HCPs viewed their busy schedules and the extra work associated with presenting as barriers. The transience of junior medical staff was identified as a barrier because they were rotated to different hospital departments or hospitals every 6 months. They were perceived as being less willing to take part because they would be moved soon afterwards. Support from line managers i.e. protected time to prepare for their presentation, was identified as a determinant that would encourage staff to present Table .
This domain included two themes of acceptability and appropriateness, and pushing and changing slowly. All participants viewed Evidence Rounds as having a positive impact on their practice and education. It highlighted the need to improve their communication with colleagues in relation to approaches to care delivery. Evidence Rounds helped to ensure practice was based on research evidence as well as their own clinical experience and that of their colleagues. The initiative was acknowledged as having a wider scope, decreased risk of bias and more applicability to decision-making for clinical care than traditional journal clubs. Participants welcomed the opportunity for interprofessional collaboration across multiple professions and disciplines and saw this as a means to network and discuss key issues with colleagues they might work with infrequently. There was recognition that getting together for Evidence Rounds sessions helped to foster links between the midwifery, obstetric and neonatal departments. Most participants acknowledged that key research findings highlighted as actions from Evidence Rounds were slow to be implemented although some recommendations had been implemented in practice. Bridging the gap between research and practice is often contingent on additional steps. Evidence Rounds was seen as a platform to begin a conversation and start to plan the formal process of updating or creating new guidelines so that there could be a widespread change in practice. One participant noted that having the relevant guideline developer in attendance would increase the likelihood of getting the evidence into practice Table .
This domain included two themes; modes of delivery and communication and dissemination strategy considerations. We asked participants questions to gain insight into their preferred modes of delivery when receiving communications and disseminated information. One important finding is that participant feedback did not identify a single mode of delivery of information that would have engaged all staff. Therefore, our decision to employ a multi-component strategy was appropriate for our target population despite a lack of evidence that this is the most effective approach . HCPs agreed that posters displayed in appropriate hospital areas were effective at drawing attention to upcoming sessions. The use of email to communicate information about Evidence Rounds elicited diverse responses from participants. For individuals who spent at least part of their working day with access to a computer or mobile phone and had a work email address, this was a convenient way to receive information. However, it was not an effective way to reach others such as staff midwives who were more clinically based and either were not issued with, or did not regularly access their professional email accounts. Not all participants used the Evidence Rounds website but those who did, found it accessible and an easy way to retrieve and refer others to past presentations. One participant found the critical appraisal tool links useful to prepare for their presentation. For one healthcare professional who limited their engagement with technology, the website was not a suitable medium. Participants had mixed opinions about the use of text messaging and other mobile messaging technologies such as WhatsApp. On one hand, they acknowledged that they were a means whereby information could be communicated to the intended receiver in an easy and direct manner. On the other hand, many staff voiced concerns that work-life boundaries might be violated or feared that they might be bombarded with messages particularly when they were not working. Many of the HCPs were involved in shift work, which compounded their concern regarding this issue. Word of mouth was a popular method among staff to encourage their colleagues to attend sessions. Multiple reminders and reminders on the day of the sessions were viewed as having a particularly positive impact on attendance Table .
Finally, we asked HCPs about their perceptions of the sustainability of Evidence Rounds and how they would make future initiatives more sustainable. Sustainability is difficult to measure so our qualitative approach allowed us to gain an understanding of context to help others select appropriate strategies during implementation to improve sustainability. This domain included two themes; staff engagement and collaboration and individual and departmental influences on sustainability. Perhaps the most striking finding is the influence of resources and particularly the HCPs themselves, on sustainability. Their availability, schedules and workloads, level of interest and motivation, the engagement of senior-level staff and their willingness to lead and become champions for initiatives were hugely important factors. These results corroborate suggestions that behaviour change theory may be useful to positively impact implementation processes. HCPs identified a number of factors key to the sustainability of Evidence Rounds and similar initiatives after the support of the KT professional would be terminated. Staff representatives from both the neonatal and obstetric units would need to take ownership and assume responsibility for administrative tasks such as planning and scheduling the meetings. Some participants viewed champions as essential for sustainability. Two participants believed that there needed to be a dedicated person whose job it was to oversee education and another thought their role should include developing clinical practice guidelines. All participants remarked positively on either or both of the interprofessional and multiple disciplinary aspects of the initiative. One individual believed that senior level staff from one discipline were more invested in keeping it going than those from the other discipline and worried about the impact of this. There was a sense that it was not always easy to come up with topics of simultaneous interest to midwifery, neonatal and obstetric departments. Evidence Rounds was just one of many educational opportunities open to staff during their working week. Taking into consideration the already busy workloads of the healthcare professionals, it was not easy to find staff to volunteer to take on the extra responsibility required to keep it going. Buy-in from senior level staff and having a consultant run the sessions were considered factors that might encourage staff to attend. Rotating presenters and dividing tasks between a team of three was a means of keeping the workload associated with presenting at a manageable level. Assigning a HCP to pre-schedule the sessions for the coming year was suggested by multiple participants. Participants mentioned the need to involve someone with experience in performing systematic literature searches and to provide additional support to upcoming presenters Table .
This study sought to identify the barriers and facilitators to attending and presenting at Evidence Rounds. Our findings agreed with evidence from other studies that the provision of refreshments may be associated with increased HCP attendance at educational events . We wanted to improve our understanding of HCPs’ perspectives of Evidence Rounds as a dissemination strategy. We asked multiple questions to gain insight into their preferred modes of delivery when receiving communication and disseminated information. Overall, our study findings were consistent with a mixed methods study also conducted in Ireland, to reach consensus on priorities for clinical learning environments for postgraduate medical education . Among the most important domains identified by participants in that study were: support for residents; opportunities to learn with senior doctors; engagement in clinical teams; organisational and working conditions. Strengths and limitations Evidence Rounds was an example of pragmatic, community-engaged dissemination and implementation research in which the community is the target population of HCPs. It came about because key stakeholders within our target audience approached staff at the National University of Ireland, Galway having identified a need for support in translating research evidence into practice. One of our authors (AC) was recruited as a PhD student to take on this project as a part of her PhD research, having had experience of implementing Evidence in Practice Groups with HCPs as part of CEBIS in the UK. The key strength of this study is the rich data from our focus groups and interviews, which provides context and contributes to the development of evidence about HCP perspectives on the implementation of KT strategies. Research has consistently shown that contextual factors in a given setting play a large role in the success or failure of these types of activities. We employed qualitative methods of research as a means to gain understanding of interactions between individuals, organisations and their unique contexts . The key finding of studies that have undertaken process evaluations is not only the significance of contextual factors but the fact that they can often have the most significant impact on the intervention . This information could be used to generate insights that decision-makers can use to plan, develop and implement their own initiatives. Notwithstanding, this study has some limitations. Despite our best efforts, recruitment of participants was low. Several factors could have attributed to this for example, the department where most staff worked was above capacity during the period when the focus groups were held. Nevertheless, one-to-one interviews were offered as an alternative. It is not clear whether our participants were a representative sample of the population. More than half had presented or were involved in the co-design or implementation of the initiative. Therefore, this group may be more invested in Evidence Rounds than other potential participants. We did not capture the perspectives of healthcare professionals who did not attend Evidence Rounds. The inclusion criteria for our study specified that participants must have attended at least one group session. Another limitation of the study is that the main researcher who implemented the initiative also moderated the focus groups and interviews and was involved in analysis and interpretation. Participants may have felt reluctant to share negative perceptions. To address this concern, at the start of each interview or focus group we emphasised that both positive and negative feedback was being sought to continue the initiative and make it more effective or to make recommendations for future initiatives. In one systematic literature review, the authors reported that a timeframe of two or more years is required to examine the sustainability of evidence based interventions . Tricco and colleagues (2016) reported that the KT interventions included in their scoping review focused on sustainability ranged from 61 to 522 weeks . Our initiative was implemented over 9 months so this timeframe may not be adequate for optimal conditions to ask participants questions about sustainability. Framework analysis uses an applied rather than a theoretical approach to research . Therefore, another potential limitation of our study is the lack of theory in our investigation of barriers. The use of a validated tool such as the Theoretical Domains Framework [ – ] would have allowed us to map our barriers to pre-specified behaviour change domains. Implications for research and practice Further research might explore how to leverage social media platforms to effectively communicate and disseminate evidence to a targeted population. Evidence Rounds was an initiative for HCPs in Ireland, which is classified as a high income country . Questions remain as to how the perspectives of health care professionals working in low and middle income countries might differ from those of our participants. Another important issue for future research is to determine how to integrate the values and preferences of patients, carers or the public, into initiatives like Evidence Rounds to inform and improve the decision-making process . Further, our findings may have implications for the understanding of how behaviour change theory might be used to optimise initiatives and strengthen capacity to improve the implementation of evidence. The findings of this study uncovered a number of important points to inform individuals planning, developing or implementing initiatives aimed at HCPs. We encourage others to consider interprofessional and multiple professional/disciplinary platforms for these types of initiatives as this approach was valued highly by staff. Those planning similar initiatives may consider multi-component strategies. Our HCPs found more benefit relating to the provision of patient care in group sessions focusing on the best available evidence than on previous events like journal club which critically appraised single articles. Effective communication and dissemination aimed at HCPs requires careful consideration of a number of factors including the mode of delivery, scheduling, frequency, and organisational, departmental and individual-level preferences. Feedback during implementation from the target population may guide decisions to maintain, remove or modify aspects of the strategy. Others implementing similar initiatives may consider factoring in the provision of support and training for presenters who need help with critical appraisal, data presentation, statistical inference etc. The development of a plan for presenters and attendees would be ideal to build organisational capacity. Our health service staff did not feel that they had the skills to perform adequate searches on clinical topics or questions. Like other authors, we recommend the involvement of information specialists, librarians or individuals with experience of designing and conducting search strategies . We also recommend involving and collaborating with guideline developers to increase the likelihood of implementation of research findings.
Evidence Rounds was an example of pragmatic, community-engaged dissemination and implementation research in which the community is the target population of HCPs. It came about because key stakeholders within our target audience approached staff at the National University of Ireland, Galway having identified a need for support in translating research evidence into practice. One of our authors (AC) was recruited as a PhD student to take on this project as a part of her PhD research, having had experience of implementing Evidence in Practice Groups with HCPs as part of CEBIS in the UK. The key strength of this study is the rich data from our focus groups and interviews, which provides context and contributes to the development of evidence about HCP perspectives on the implementation of KT strategies. Research has consistently shown that contextual factors in a given setting play a large role in the success or failure of these types of activities. We employed qualitative methods of research as a means to gain understanding of interactions between individuals, organisations and their unique contexts . The key finding of studies that have undertaken process evaluations is not only the significance of contextual factors but the fact that they can often have the most significant impact on the intervention . This information could be used to generate insights that decision-makers can use to plan, develop and implement their own initiatives. Notwithstanding, this study has some limitations. Despite our best efforts, recruitment of participants was low. Several factors could have attributed to this for example, the department where most staff worked was above capacity during the period when the focus groups were held. Nevertheless, one-to-one interviews were offered as an alternative. It is not clear whether our participants were a representative sample of the population. More than half had presented or were involved in the co-design or implementation of the initiative. Therefore, this group may be more invested in Evidence Rounds than other potential participants. We did not capture the perspectives of healthcare professionals who did not attend Evidence Rounds. The inclusion criteria for our study specified that participants must have attended at least one group session. Another limitation of the study is that the main researcher who implemented the initiative also moderated the focus groups and interviews and was involved in analysis and interpretation. Participants may have felt reluctant to share negative perceptions. To address this concern, at the start of each interview or focus group we emphasised that both positive and negative feedback was being sought to continue the initiative and make it more effective or to make recommendations for future initiatives. In one systematic literature review, the authors reported that a timeframe of two or more years is required to examine the sustainability of evidence based interventions . Tricco and colleagues (2016) reported that the KT interventions included in their scoping review focused on sustainability ranged from 61 to 522 weeks . Our initiative was implemented over 9 months so this timeframe may not be adequate for optimal conditions to ask participants questions about sustainability. Framework analysis uses an applied rather than a theoretical approach to research . Therefore, another potential limitation of our study is the lack of theory in our investigation of barriers. The use of a validated tool such as the Theoretical Domains Framework [ – ] would have allowed us to map our barriers to pre-specified behaviour change domains.
Further research might explore how to leverage social media platforms to effectively communicate and disseminate evidence to a targeted population. Evidence Rounds was an initiative for HCPs in Ireland, which is classified as a high income country . Questions remain as to how the perspectives of health care professionals working in low and middle income countries might differ from those of our participants. Another important issue for future research is to determine how to integrate the values and preferences of patients, carers or the public, into initiatives like Evidence Rounds to inform and improve the decision-making process . Further, our findings may have implications for the understanding of how behaviour change theory might be used to optimise initiatives and strengthen capacity to improve the implementation of evidence. The findings of this study uncovered a number of important points to inform individuals planning, developing or implementing initiatives aimed at HCPs. We encourage others to consider interprofessional and multiple professional/disciplinary platforms for these types of initiatives as this approach was valued highly by staff. Those planning similar initiatives may consider multi-component strategies. Our HCPs found more benefit relating to the provision of patient care in group sessions focusing on the best available evidence than on previous events like journal club which critically appraised single articles. Effective communication and dissemination aimed at HCPs requires careful consideration of a number of factors including the mode of delivery, scheduling, frequency, and organisational, departmental and individual-level preferences. Feedback during implementation from the target population may guide decisions to maintain, remove or modify aspects of the strategy. Others implementing similar initiatives may consider factoring in the provision of support and training for presenters who need help with critical appraisal, data presentation, statistical inference etc. The development of a plan for presenters and attendees would be ideal to build organisational capacity. Our health service staff did not feel that they had the skills to perform adequate searches on clinical topics or questions. Like other authors, we recommend the involvement of information specialists, librarians or individuals with experience of designing and conducting search strategies . We also recommend involving and collaborating with guideline developers to increase the likelihood of implementation of research findings.
We set out to identify barriers and facilitators to attending and presenting at group sessions from the perspectives of HCPs, to gain an understanding of their views of Evidence Rounds as a dissemination strategy and to generate insights to improve the sustainability of future initiatives. The results of this study and our analysis have extended our understanding and may be useful for guiding the development and implementation of future KT strategies for HCPs. Our focus groups and interviews highlighted the variability in preferences of mode of delivery in our target audience suggesting the multi-component approaches can be useful. They helped us gain insight into the influence of organisational and individual level factors (e.g. buy-in and support from senior staff, staffing levels and scheduling, self-confidence) on the willingness and ability of HCPs to attend, present at and sustain these types of initiatives. Although HCPs invariably work in complex systems with unique contexts, this paper may help others to understand factors that can impact the implementation of initiatives to disseminate key research findings and promote evidence informed practice.
Additional file 1: FGI Guide_BMC Med Ed. (PDF 261 kb) Additional file 2: Informed consent_BMC Med Ed. (PDF 140 kb)
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Effect of different incisions on dry eye symptoms after cataract surgery in diabetic patients | 4c7231ee-b7cb-4f58-9151-244342eb08e3 | 11827226 | Ophthalmologic Surgical Procedures[mh] | Cataract is a blinding disease that is common in the elderly population and is characterized by visual impairment due to clouding of the lens . With a growing elderly population, the prevalence of cataract is increasing over the years, and as of 2020, the number of adult cataract patients in China has reached 130 million, and it is expected that by 2050, it will exceed 240 million . In 2021, from IDF Diabetes Atlas data, there are more than 500 million people with diabetes in the world, and more than 90% of them are type 2 diabetes mellitus (T2DM) . It is well known that retinopathy is the most common complication of T2DM, but in recent years, the high incidence of cataracts in T2DM patients has gained more and more attention . Previous studies have shown that diabetic cataract is one of the major causes of vision loss in patients with T2DM, and the incidence of cataract in diabetic patients is about 3–5 times higher than that in non-diabetic patients, and the disease progresses more rapidly . Prevention and treatment of diabetic patients with complications of cataract is of great importance. Currently, the most common treatment for cataracts is phacoemulsification, which can significantly improve patients’ vision, but like other traditional cataract surgeries, it is prone to postoperative complications such as corneal damage and dry eye disease (DED) . DED, also known as corneal conjunctival dryness, can cause to symptoms such as dryness and redness of the eyes, which can seriously affect patients’ vision recovery. It has been reported that more than one-third of patients are afflicted with DED subsequent to cataract surgery. Additionally, in comparison with non-diabetic patients, patients suffering from T2DM are more inclined to develop tear film dysfunction and more severe DED after cataract surgery . Research findings have indicated that the incidence of DED after phacoemulsification is influenced by the size, type, and location of the surgical incision [ , , ]. Previous studies have shown that patients after phacoemulsification are less likely to develop DED and have less astigmatism in patients with smaller incisions compared to conventional cataract surgery, such as Manual small incision cataract surgery (MSICS) [ , , ]. In addition, clear corneal incisions of 2.2 mm have a lower incidence of infection compared to 2.8 mm in phacoemulsification . However, it is worth noting that there are various incision sizes for phacoemulsification, but fewer studies have been conducted to account for the differences in the incidence of DED in patients after phacoemulsification with different incision sizes . In this study, we retrospectively analyzed the difference in the incidence of DED after phacoemulsification in T2DM patients with two different-sized incisions (2.2 mm clear corneal incisions and 3.0 mm clear corneal incisions). We statistically analyzed the baseline characteristics of the patients and their Ocular surface disease index (OSDI), Dry eye symptom score, Schirmer I test (SIt), and Fluorescein breakup time (FBUT) data at preoperative, 7 days, 1 month, and 3 months postoperatively. In addition, given that impaired vision in older adults with cataract is strongly associated with increased depression and anxiety levels, we also assessed patients’ anxiety and depression levels at various time points in this study . This retrospective study aims to provide a new reference and solution idea for clinical improvement of postoperative DED after cataract surgery in patients with T2DM.
Clinical data In this study, we retrospectively analyzed the clinical data of 104 eyes of 104 patients who underwent phacoemulsification for cataract treatment in the Department of Ophthalmology of The People’s Hospital of Yingshang, from January 2022 to November 2023 (If the patient had surgery in both eyes, only the first eye was analyzed). Inclusion criteria: (1) diagnosed with T2DM; (2) no medications affecting tear secretion and tear film stability within 3 months; (3) no other diseases affecting tear secretion (rheumatoid arthritis, desiccation syndrome, thyroid disorders, etc.); (4) good adherence (5) absence of severe cognitive impairment; (6) intact clinical data. Following the recommendations of the Chinese guideline for cataract surgery in adults, these patients underwent a close and comprehensive follow-up examination preoperatively (Baseline), and at 7 days, 1 month, and 3 months postoperatively . We categorized the above patients into a 2.2 mm clear corneal incisions group (2.2 mm) and a 3.0 mm clear corneal incisions group (3.0 mm) based on the type of incision. There were 49 patients in the 2.2 mm group and 55 patients in the 3.0 mm group. Treatment program All patients were treated with Levofloxacin Eye Drops qid for 3 days before admission. Preoperatively, the patient’s pupils were dilated using Compound Tropicamide Eye Drops, and surface anesthesia was administered intraoperatively using Proparacaine Hydrochloride Eye Drops. All procedures were performed using the same model of ultrasonic emulsifier and balanced salt solution. Prior to March 2023, cataract surgery was performed in our department using a 3.0 mm clear corneal incision, which was standard practice at the time. Since March 2023, our department has been using the 2.2 mm clear corneal incision technique because of its advantages in reducing corneal damage and improving postoperative recovery. All surgeries were performed by the same experienced surgeon, and other medical staff involved in the surgeries were from the same team, with no intraoperative complications. Postoperatively, Tobramycin and Dexamethasone Eye Ointment were administered to the affected eyes. After discharge from the hospital, Tobramycin and Dexamethasone Eye Drops and Levofloxacin Eye Drops were administered qid for 2 weeks, followed by tid for 1 week. Observation indicators In the present study, we evaluated cataract grading and surgical duration in both groups. In addition, we evaluated OSDI, dry eye symptom score, SIt, FBUT, and anxiety and depression in both groups preoperatively and at 7 days, 1 month, and 3 months postoperatively. The lens opacities classification system III (LOCS III) is a commonly used clinical criterion for cataract classification. Nuclear color and nuclear opalescence are the two most commonly used standards in LOCS III . The OSDI consists of 12 questions that record the patient’s subjective ocular symptoms over the past week and is used clinically to screen and diagnose DED patients and to assess the severity of their dry eye . A dry eye symptom score is a rating of the severity of a patient’s subjective dry eye symptoms. 0 is asymptomatic, 0.5 is occasional, 1 is frequent and 2 is persistent. These symptoms include dry eyes, eye redness, burning sensation, foreign body sensation and eyelash adhesion discharge . SIt is a commonly used method for assessing tear secretion. SIt is tested as follows: the head end of a Schirmer test strip is folded inward and placed in the conjunctival sac at the junction of the outer middle third of the lower eyelid, and the length of the test strip that is soaked with tear fluid within 5 min is measured . FBUT is currently the most used method in clinical practice, and it must be conducted in an indoor environment with normal temperature, appropriate humidity, and away from direct sunlight. The standard examination procedure involves using a sterile dropper to instill 2 µL of 1% fluorescein sodium solution into the conjunctival sac, or using a fluorescein strip moistened with antibiotic eyedrops (ensuring no excess liquid remains on the strip to touch the lower eyelid margin). The patient is instructed to blink 3 to 4 times to evenly distribute the fluorescein on the ocular surface. With both eyes looking straight ahead, the time from the last blink to the appearance of the first dark spot on the cornea is recorded as the tear film breakup time. This measurement is repeated three times, and the average value is calculated . The Zung Self-Rating Anxiety Scale (SAS) serves as a tool for evaluating anxiety. It comprises 20 items, with each being scored on a four-point scale spanning from “none or occasionally present” to “mostly or always present”. This self-completed (or through question-asking) questionnaire can be utilized to gauge the intensity of anxiety symptoms . The Zung Self-Rating Depression Scale (SDS) is an instrument used to assess the severity of an individual’s depressive symptoms. Like the SAS, the SDS consists of 20 items, each of which is rated on a scale ranging from 1 to 4, with higher total scores indicating greater severity of depressive symptoms . Statistical analysis We used SPSS 26 to analyze the clinical data of the two groups of patients. We first tested the normality of the measurement data, if that fulfilled the normal distribution, they were presented as x̄ ± s . For comparison between the two groups, the independent sample t -test was utilized, and the paired sample t -test was used for comparison between different time points within the group and preoperative period. If measures did not fulfill normal distribution, they were presented as median, quartiles [M (P25, P75)]. For comparisons between independent samples in such situations, the Mann-Whitney U test was adopted, and for paired samples, the Wilcoxon matched-pairs signed rank test was used. Counting data were described as numbers and percentages and were analyzed using the χ 2 test. P < 0.05 indicates a statistically significant difference.
In this study, we retrospectively analyzed the clinical data of 104 eyes of 104 patients who underwent phacoemulsification for cataract treatment in the Department of Ophthalmology of The People’s Hospital of Yingshang, from January 2022 to November 2023 (If the patient had surgery in both eyes, only the first eye was analyzed). Inclusion criteria: (1) diagnosed with T2DM; (2) no medications affecting tear secretion and tear film stability within 3 months; (3) no other diseases affecting tear secretion (rheumatoid arthritis, desiccation syndrome, thyroid disorders, etc.); (4) good adherence (5) absence of severe cognitive impairment; (6) intact clinical data. Following the recommendations of the Chinese guideline for cataract surgery in adults, these patients underwent a close and comprehensive follow-up examination preoperatively (Baseline), and at 7 days, 1 month, and 3 months postoperatively . We categorized the above patients into a 2.2 mm clear corneal incisions group (2.2 mm) and a 3.0 mm clear corneal incisions group (3.0 mm) based on the type of incision. There were 49 patients in the 2.2 mm group and 55 patients in the 3.0 mm group.
All patients were treated with Levofloxacin Eye Drops qid for 3 days before admission. Preoperatively, the patient’s pupils were dilated using Compound Tropicamide Eye Drops, and surface anesthesia was administered intraoperatively using Proparacaine Hydrochloride Eye Drops. All procedures were performed using the same model of ultrasonic emulsifier and balanced salt solution. Prior to March 2023, cataract surgery was performed in our department using a 3.0 mm clear corneal incision, which was standard practice at the time. Since March 2023, our department has been using the 2.2 mm clear corneal incision technique because of its advantages in reducing corneal damage and improving postoperative recovery. All surgeries were performed by the same experienced surgeon, and other medical staff involved in the surgeries were from the same team, with no intraoperative complications. Postoperatively, Tobramycin and Dexamethasone Eye Ointment were administered to the affected eyes. After discharge from the hospital, Tobramycin and Dexamethasone Eye Drops and Levofloxacin Eye Drops were administered qid for 2 weeks, followed by tid for 1 week.
In the present study, we evaluated cataract grading and surgical duration in both groups. In addition, we evaluated OSDI, dry eye symptom score, SIt, FBUT, and anxiety and depression in both groups preoperatively and at 7 days, 1 month, and 3 months postoperatively. The lens opacities classification system III (LOCS III) is a commonly used clinical criterion for cataract classification. Nuclear color and nuclear opalescence are the two most commonly used standards in LOCS III . The OSDI consists of 12 questions that record the patient’s subjective ocular symptoms over the past week and is used clinically to screen and diagnose DED patients and to assess the severity of their dry eye . A dry eye symptom score is a rating of the severity of a patient’s subjective dry eye symptoms. 0 is asymptomatic, 0.5 is occasional, 1 is frequent and 2 is persistent. These symptoms include dry eyes, eye redness, burning sensation, foreign body sensation and eyelash adhesion discharge . SIt is a commonly used method for assessing tear secretion. SIt is tested as follows: the head end of a Schirmer test strip is folded inward and placed in the conjunctival sac at the junction of the outer middle third of the lower eyelid, and the length of the test strip that is soaked with tear fluid within 5 min is measured . FBUT is currently the most used method in clinical practice, and it must be conducted in an indoor environment with normal temperature, appropriate humidity, and away from direct sunlight. The standard examination procedure involves using a sterile dropper to instill 2 µL of 1% fluorescein sodium solution into the conjunctival sac, or using a fluorescein strip moistened with antibiotic eyedrops (ensuring no excess liquid remains on the strip to touch the lower eyelid margin). The patient is instructed to blink 3 to 4 times to evenly distribute the fluorescein on the ocular surface. With both eyes looking straight ahead, the time from the last blink to the appearance of the first dark spot on the cornea is recorded as the tear film breakup time. This measurement is repeated three times, and the average value is calculated . The Zung Self-Rating Anxiety Scale (SAS) serves as a tool for evaluating anxiety. It comprises 20 items, with each being scored on a four-point scale spanning from “none or occasionally present” to “mostly or always present”. This self-completed (or through question-asking) questionnaire can be utilized to gauge the intensity of anxiety symptoms . The Zung Self-Rating Depression Scale (SDS) is an instrument used to assess the severity of an individual’s depressive symptoms. Like the SAS, the SDS consists of 20 items, each of which is rated on a scale ranging from 1 to 4, with higher total scores indicating greater severity of depressive symptoms .
We used SPSS 26 to analyze the clinical data of the two groups of patients. We first tested the normality of the measurement data, if that fulfilled the normal distribution, they were presented as x̄ ± s . For comparison between the two groups, the independent sample t -test was utilized, and the paired sample t -test was used for comparison between different time points within the group and preoperative period. If measures did not fulfill normal distribution, they were presented as median, quartiles [M (P25, P75)]. For comparisons between independent samples in such situations, the Mann-Whitney U test was adopted, and for paired samples, the Wilcoxon matched-pairs signed rank test was used. Counting data were described as numbers and percentages and were analyzed using the χ 2 test. P < 0.05 indicates a statistically significant difference.
Baseline characteristics were similar between the two groups We divided 104 patients into 2.2 mm and 3.0 mm groups by distinguishing between different surgical incision sizes and subsequently statistically analyzed their demographic characteristics. As shown in Table , we found that there was no difference between the two groups in age, gender, education level, BMI, duration of diabetes and prevalence of other underlying diseases ( P > 0.05). This indicates that the two groups of patients have similar baseline data, which lays the foundation for further subsequent statistical analysis. Cataract grading and surgical duration were similar between the two groups Similarly, we analyzed the cataract grading and surgical duration of the above two groups of patients. As shown in Table , our results indicated that there was no significant difference in nuclear color, nuclear opalescence, and surgical duration between the two groups of patients ( P > 0.05). Our results in this section exclude the potential impact of differences in the extent of patients’ disease and differences in the duration of surgery on subsequent statistical analyses. Patients in the 2.2 mm group had milder dry eye symptoms After determining that the data were comparable between the two groups, we scored the dry eye symptoms and frequency at each time point in both groups. As shown in Table , we found that dry eye symptoms were mild in both groups preoperatively (most patients scored 0 or 0.5) and there was no significant difference between the two groups ( P = 0.517). In contrast, on postoperative day 7, an increase in the percentage of 1–2 scores was observed in both groups, and the increase was more significant in patients in the 3.0 mm group ( P = 0.014). At 1 month postoperatively, patients in the 3.0 mm group still had a significantly higher dry eye symptom score than those in the 2.2 mm incision group ( P = 0.045). At 3 months postoperatively, the percentage of patients with 0 and 0.5 scores increased significantly in both groups, and the difference between the two groups was no longer significant ( P = 0.463). While the OSDI and the dry eye symptom score are both subjective scores, the OSDI covers a broader range. Here, we also analyzed the OSDI of the two groups of patients. As shown in Table , we found that preoperatively, there was no significant difference in OSDI between the two groups of patients (9.35 ± 3.250 vs. 8.95 ± 2.850, P = 0.505). At postoperative day 7 and month 1, patients in the 2.2 incision group had significantly lower OSDI compared to the 3.0 mm incision group (26.55 ± 4.916 vs. 31.55 ± 5.750, 22.50 ± 5.499 vs. 25.05 ± 4.149, P < 0.001, P = 0.008). However, at month 3, there was no longer a significant difference in OSDI between the two groups (10.47 ± 3.802 vs. 10.10 ± 3.987, P = 0.635). Meanwhile, we found that OSDI was significantly higher in both groups compared to their preoperative period at postoperative day 7 and month 1 ( P < 0.001), but recovered at postoperative month 3 ( P = 0.130, P = 0.081). Our data in this section show that phacoemulsification causes significant dry eye symptoms in patients, which is consistent with previous findings, but compared to 3.0 mm, clear corneal incisions of 2.2 mm resulted in more mild dry eye symptoms. Patients in the 2.2 mm incision group had more tear secretion Given that decreased tear production is an important cause of DED. In this study, we evaluated tear production in both groups of patients using the SIt. As shown in Table , we found that both groups of patients had similar tear production preoperatively (11.75 ± 2.096 vs. 12.45 ± 2.850, P = 0.165). At postoperative day 7 and month 1, tear secretion was significantly greater in patients in the 2.2 mm incision group compared with patients in the 3.0 mm incision group (7.54 ± 2.449 vs. 6.38 ± 2.143, 8.25 ± 3.008 vs. 7.15 ± 2.349, P = 0.011, P = 0.039). However, at month 3, there was no longer a significant difference in tear secretion between the two groups (10.99 ± 3.280 vs. 11.40 ± 3.685, P = 0.547). At the same time, we found that SIt was significantly lower in both groups at postoperative day 7 and month 1 compared to baseline ( P < 0.001), but returned to preoperative levels at month 3 ( P = 0.191, P = 0.093). Our results showed that patients had significantly more tear secretion after a 2.2 mm incision compared to a conventional 3.0 mm incision. Patients in the 2.2 mm incision group had better tear film stability Imbalance in tear film stability is also an important cause of dry eye symptoms in patients, and the main manifestation of tear film stability imbalance is shortened tear film breakup time. In this study, we evaluated the tear film breakup time in both groups of patients using FBUT. As shown in Table , we found that the time to tear film breakup was similar between the two groups of patients preoperatively (10.45 ± 1.549 vs. 9.84 ± 2.090, P = 0.098). At postoperative day 7 and month 1, patients in the 2.2 mm incision group had significantly longer tear film breakup time compared to patients in the 3.0 mm group. (5.25 ± 1.199 vs. 4.44 ± 0.850, 7.25 ± 1.749 vs. 6.34 ± 1.250, P < 0.001, P = 0.003). However, at postoperative month 3, there was no longer a significant difference in FBUT between the two groups (10.82 ± 1.450 vs. 10.34 ± 2.097, P = 0.179). As mentioned earlier, we also compared the data of the two groups at each time point with their data at baseline. We found that at postoperative day 7 and month 1, tear film breakup time was significantly shorter in both groups compared to their baseline ( P < 0.001), but had returned to baseline levels by month 3 ( P = 0.230, P = 0.269). In the results of this section, we found that patients in the 3.0 mm group had a shorter time to tear film breakup compared to patients in the 2.2 mm incision group. Patients in the 2.2 mm incision group had better psychological status Vision impairment seriously interferes with the normal life of patients and negatively affects their psychological state. In this study as shown in Table , we assessed the levels of anxiety and depression at various time points in both groups of patients. Using the SAS scale, we found that patients in both groups were mildly depressed at baseline and postoperative day 7 and there was no significant difference (57.02 ± 4.380 vs. 58.34 ± 5.250, 55.73 ± 4.649 vs. 56.43 ± 4.713, P = 0.168, P = 0.447). At postoperative month 1, anxiety improved in both groups, but patients in the 2.2 mm group had significantly lower SAS scores (51.34 ± 3.854 vs. 53.83 ± 4.875, P = 0.005), although this difference was no longer significant at month 3 (9.75 ± 4.385 vs. 50.63 ± 4.142, P = 0.295). In addition, by comparing the data of the two groups of patients at each time point with their data at baseline, we found that there was no significant difference between the anxiety levels of the two groups and their anxiety levels at baseline at postoperative day 7 ( P = 0.161, P = 0.088), whereas, at postoperative month 1 and month 3, significant improvement in the anxiety levels of the patients in both groups was observed ( P < 0.001). Patients’ depression levels also showed similar results to anxiety levels. Using the SDS scale, we found that patients in both groups were mildly depressive preoperatively and at postoperative day 7 and there was no significant difference (56 (53, 60) vs. 58 (53, 63.5), 58 (53, 63) vs. 60 (54, 65.5), P = 0.123, P = 0.502). At postoperative month 1, depression scores improved in both groups, and SDS scores were significantly lower in the 2.2 mm group (50 (44, 52) vs. 55 (47.5, 60), P = 0.015), although this statistically significant difference was no longer evident after 3 months (49 (45, 53) vs. 52 (45, 56.5), P = 0.059). In addition, by comparing the data of the two groups at each time point with their data at baseline, we found that there was no significant difference between the depression levels of the two groups and their depression levels at baseline at postoperative day 7 ( P = 0.056, P = 0.446), whereas a significant improvement in the depression levels of both groups was observed at postoperative month 1 and month 3 ( P < 0.001). Our results suggest that phacoemulsification significantly enhances the psychological status of patients with T2DM cataracts and that a 2.2 mm incision has a more positive impact on the psychological status of patients compared to a 3.0 mm incision.
We divided 104 patients into 2.2 mm and 3.0 mm groups by distinguishing between different surgical incision sizes and subsequently statistically analyzed their demographic characteristics. As shown in Table , we found that there was no difference between the two groups in age, gender, education level, BMI, duration of diabetes and prevalence of other underlying diseases ( P > 0.05). This indicates that the two groups of patients have similar baseline data, which lays the foundation for further subsequent statistical analysis.
Similarly, we analyzed the cataract grading and surgical duration of the above two groups of patients. As shown in Table , our results indicated that there was no significant difference in nuclear color, nuclear opalescence, and surgical duration between the two groups of patients ( P > 0.05). Our results in this section exclude the potential impact of differences in the extent of patients’ disease and differences in the duration of surgery on subsequent statistical analyses.
After determining that the data were comparable between the two groups, we scored the dry eye symptoms and frequency at each time point in both groups. As shown in Table , we found that dry eye symptoms were mild in both groups preoperatively (most patients scored 0 or 0.5) and there was no significant difference between the two groups ( P = 0.517). In contrast, on postoperative day 7, an increase in the percentage of 1–2 scores was observed in both groups, and the increase was more significant in patients in the 3.0 mm group ( P = 0.014). At 1 month postoperatively, patients in the 3.0 mm group still had a significantly higher dry eye symptom score than those in the 2.2 mm incision group ( P = 0.045). At 3 months postoperatively, the percentage of patients with 0 and 0.5 scores increased significantly in both groups, and the difference between the two groups was no longer significant ( P = 0.463). While the OSDI and the dry eye symptom score are both subjective scores, the OSDI covers a broader range. Here, we also analyzed the OSDI of the two groups of patients. As shown in Table , we found that preoperatively, there was no significant difference in OSDI between the two groups of patients (9.35 ± 3.250 vs. 8.95 ± 2.850, P = 0.505). At postoperative day 7 and month 1, patients in the 2.2 incision group had significantly lower OSDI compared to the 3.0 mm incision group (26.55 ± 4.916 vs. 31.55 ± 5.750, 22.50 ± 5.499 vs. 25.05 ± 4.149, P < 0.001, P = 0.008). However, at month 3, there was no longer a significant difference in OSDI between the two groups (10.47 ± 3.802 vs. 10.10 ± 3.987, P = 0.635). Meanwhile, we found that OSDI was significantly higher in both groups compared to their preoperative period at postoperative day 7 and month 1 ( P < 0.001), but recovered at postoperative month 3 ( P = 0.130, P = 0.081). Our data in this section show that phacoemulsification causes significant dry eye symptoms in patients, which is consistent with previous findings, but compared to 3.0 mm, clear corneal incisions of 2.2 mm resulted in more mild dry eye symptoms.
Given that decreased tear production is an important cause of DED. In this study, we evaluated tear production in both groups of patients using the SIt. As shown in Table , we found that both groups of patients had similar tear production preoperatively (11.75 ± 2.096 vs. 12.45 ± 2.850, P = 0.165). At postoperative day 7 and month 1, tear secretion was significantly greater in patients in the 2.2 mm incision group compared with patients in the 3.0 mm incision group (7.54 ± 2.449 vs. 6.38 ± 2.143, 8.25 ± 3.008 vs. 7.15 ± 2.349, P = 0.011, P = 0.039). However, at month 3, there was no longer a significant difference in tear secretion between the two groups (10.99 ± 3.280 vs. 11.40 ± 3.685, P = 0.547). At the same time, we found that SIt was significantly lower in both groups at postoperative day 7 and month 1 compared to baseline ( P < 0.001), but returned to preoperative levels at month 3 ( P = 0.191, P = 0.093). Our results showed that patients had significantly more tear secretion after a 2.2 mm incision compared to a conventional 3.0 mm incision.
Imbalance in tear film stability is also an important cause of dry eye symptoms in patients, and the main manifestation of tear film stability imbalance is shortened tear film breakup time. In this study, we evaluated the tear film breakup time in both groups of patients using FBUT. As shown in Table , we found that the time to tear film breakup was similar between the two groups of patients preoperatively (10.45 ± 1.549 vs. 9.84 ± 2.090, P = 0.098). At postoperative day 7 and month 1, patients in the 2.2 mm incision group had significantly longer tear film breakup time compared to patients in the 3.0 mm group. (5.25 ± 1.199 vs. 4.44 ± 0.850, 7.25 ± 1.749 vs. 6.34 ± 1.250, P < 0.001, P = 0.003). However, at postoperative month 3, there was no longer a significant difference in FBUT between the two groups (10.82 ± 1.450 vs. 10.34 ± 2.097, P = 0.179). As mentioned earlier, we also compared the data of the two groups at each time point with their data at baseline. We found that at postoperative day 7 and month 1, tear film breakup time was significantly shorter in both groups compared to their baseline ( P < 0.001), but had returned to baseline levels by month 3 ( P = 0.230, P = 0.269). In the results of this section, we found that patients in the 3.0 mm group had a shorter time to tear film breakup compared to patients in the 2.2 mm incision group.
Vision impairment seriously interferes with the normal life of patients and negatively affects their psychological state. In this study as shown in Table , we assessed the levels of anxiety and depression at various time points in both groups of patients. Using the SAS scale, we found that patients in both groups were mildly depressed at baseline and postoperative day 7 and there was no significant difference (57.02 ± 4.380 vs. 58.34 ± 5.250, 55.73 ± 4.649 vs. 56.43 ± 4.713, P = 0.168, P = 0.447). At postoperative month 1, anxiety improved in both groups, but patients in the 2.2 mm group had significantly lower SAS scores (51.34 ± 3.854 vs. 53.83 ± 4.875, P = 0.005), although this difference was no longer significant at month 3 (9.75 ± 4.385 vs. 50.63 ± 4.142, P = 0.295). In addition, by comparing the data of the two groups of patients at each time point with their data at baseline, we found that there was no significant difference between the anxiety levels of the two groups and their anxiety levels at baseline at postoperative day 7 ( P = 0.161, P = 0.088), whereas, at postoperative month 1 and month 3, significant improvement in the anxiety levels of the patients in both groups was observed ( P < 0.001). Patients’ depression levels also showed similar results to anxiety levels. Using the SDS scale, we found that patients in both groups were mildly depressive preoperatively and at postoperative day 7 and there was no significant difference (56 (53, 60) vs. 58 (53, 63.5), 58 (53, 63) vs. 60 (54, 65.5), P = 0.123, P = 0.502). At postoperative month 1, depression scores improved in both groups, and SDS scores were significantly lower in the 2.2 mm group (50 (44, 52) vs. 55 (47.5, 60), P = 0.015), although this statistically significant difference was no longer evident after 3 months (49 (45, 53) vs. 52 (45, 56.5), P = 0.059). In addition, by comparing the data of the two groups at each time point with their data at baseline, we found that there was no significant difference between the depression levels of the two groups and their depression levels at baseline at postoperative day 7 ( P = 0.056, P = 0.446), whereas a significant improvement in the depression levels of both groups was observed at postoperative month 1 and month 3 ( P < 0.001). Our results suggest that phacoemulsification significantly enhances the psychological status of patients with T2DM cataracts and that a 2.2 mm incision has a more positive impact on the psychological status of patients compared to a 3.0 mm incision.
Previous studies showed that the occurrence rate of dry eye following cataract surgery stood at 37.4%, and these patients may cause irreversible damage if not treated in time . Notably, T2DM patients are more likely to develop complications including DED after cataract surgery compared to non-diabetic patients [ , , ]. In this study, we found that a 2.2 mm incision was more effective in improving patients’ dry eye symptoms compared to a 3.0 mm clear corneal incision. These improvements were primarily reflected in lower dry eye symptom scores and OSDI scores as well as higher SIt and FBUT results in patients of the 2.2 mm incision. Additionally, we noted that both incision sizes led to significant improvements in the patients’ adverse psychological status. However, the patients in the 2.2 mm group exhibited faster rates of recovery in this regard. Currently, commonly used cataract extraction surgeries include extracapsular cataract extraction (ECCE), MSICS, and phacoemulsification. ECCE and MSICS have the strongpoint of relatively simpler operation, lower cost, and faster recovery, but they also have disadvantages, including a larger incision, slower recovery of postoperative visual acuity, and more pronounced postoperative astigmatism . As cataract surgical techniques continue to evolve, these two traditional surgical modalities have been gradually replaced by phacoemulsification with fewer complications in more developed regions . The incidence of DED in patients after phacoemulsification has been reported to be about half that of MSICS with better visual recovery . Recent studies have found that reducing the size of the phacoemulsification incision reduces postoperative astigmatism and inflammation, as well as decreasing operative time and postoperative recovery time . In addition, a recent study has shown that longer surgical incisions are an independent risk factor for the development of dry eye in patients following cataract phacoemulsification . In the present study, we found that dry eye symptoms were milder after phacoemulsification with 2.2 mm clear corneal incisions in patients with T2DM compared to 3.0 mm clear corneal incisions, although this difference was no longer significant after 3 months postoperatively, while the anxiety and depression levels of patients in the group with a 2.2 mm incision showed remarkable improvement in comparison to those in the 3.0 mm group during this period. Our findings suggest that it is feasible to prevent postoperative DED in patients with T2DM by reducing the incision size for phacoemulsification. Cataract surgery can effectively improve patients’ vision, but it can cause damage to the corneal conjunctiva, leading to tear film instability, and many cataract patients develop DED after surgery . Previous studies have shown that before and after phacoemulsification surgery, diabetic patients have poorer tear film stability compared to non-diabetic patients . Compared to MSICS, patients after phacoemulsification have better tear film stability . Meanwhile, another study also showed that patients had longer FBUT from 1 to 12 weeks after phacoemulsification compared to conventional MSICS . During this research, we discovered that patients in the 2.2 mm incision group had longer tear film breakup time after phacoemulsification compared with the 3.0 mm incision. Our results suggest that decreasing the size of clear corneal incisions from 3.0 mm to 2.2 mm may be effective in improving the ocular environment after phacoemulsification. Another important cause of DED is inadequate tear production . Previous studies have shown that cataract patients produce more tears after phacoemulsification compared to MISUS, and this difference persists up to 3 months postoperatively . Consistent with the above study, we found in the present study that patients in the 2.2 mm incision group had more tear production postoperatively compared to the 3.0 mm incision group, and this difference persisted for up to one month. We speculate that smaller incisions may have less impact on corneal nerves, and local inflammation and therefore less impact on tear secretion and tear film stability, which may explain these results . Many studies have pointed out that diminished vision or even blindness due to cataracts is significantly linked to a heightened probability of suffering from anxiety and depression in the elderly [ , , ]. We found in the present study that preoperatively, patients in both groups were in a mild state of anxiety and depression (SAS and SDS scores greater than 50), which could be attributed to the patient’s fear of their vision problems. One month after phacoemulsification, both groups showed significant improvement in anxiety and depression scores, and the improvement was more pronounced in the 2.2 mm group. We believe that the improvement in anxiety and depression levels in both groups was mainly due to the improvement in vision from cataract surgery. Recent reports suggest that DED can lead to significant adverse psychological conditions in patients . In addition, refractive surgery patients experience significant dry eye symptoms, anxiety, and depression postoperatively, and that such poor psychological conditions may be related to the postoperative dry eye; whereas DED after refractive surgery has been attributed primarily to corneal damage from the surgery . Therefore, we hypothesized that the reason for the favorable psychological profile of patients in the 2.2 mm group over the 3.0 mm group was related to milder dry eye symptoms due to the smaller incision. In summary, we found in this retrospective study that compared to phacoemulsification with a 3.0 mm clear corneal incision, a 2.2 mm incision was effective in improving patients’ dry eye symptoms and patients’ adverse psychological status after surgery. In conclusion, decreasing the incision size has a positive impact on improving dry eye symptoms in cataract patients after surgery. Therefore, the use of smaller incision sizes should be emphasized in clinical practice. Although the results of this study are encouraging, some limitations remain. First, we were unable to fully assess the potential impact of topical eye drop use on dry eye symptoms. In the future, more rigorous research should be designed to clarify the specific effects of eye drops on dry eye symptoms. Second, patients’ behavioral status may have been a confounding factor during this study. Although we considered the baseline characteristics of the patients in our statistical analysis, there may have been other factors not included that influenced dry eye symptoms. Future studies should use more comprehensive behavioral assessment tools and control for these influences as much as possible. In addition, the sample size of this study was relatively small, and further studies in larger patient populations are warranted.
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